system

Abstract

Provide a system. [Solution] means for inputting the user's current location, destination, and departure time; A means for obtaining real-time operational status data of transportation facilities; A means of collecting disaster information; A means of calculating the optimal route that reflects current traffic conditions and disaster information, means for presenting the calculation results to a user; a means for proxy-obtaining a necessary reservation based on a user's selection; A means of continuously monitoring operational status and disaster information; The system includes a means to calculate the best alternative route and notify the user when conditions change.

Description

[Technical Field]

[0001] The technology of the present disclosure relates to a system. [Background technology]

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description of the chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] Traditionally, during disasters, transportation operation conditions change, making it extremely difficult for people to select the optimal route to reach their destination. Current navigation systems and traffic information systems are unable to adequately reflect real-time operation conditions and disaster information, often causing unnecessary delays and inconvenience to users. To resolve this situation, a smarter and more flexible system is needed. [Means for solving the problem]

[0005] The present invention provides a system that includes means for inputting a user's current location, destination, and departure time, means for acquiring real-time transportation operation status data, means for collecting disaster information, means for calculating an optimal route that reflects current operation status and disaster information, means for presenting the calculation results to the user, means for making necessary reservations on behalf of the user based on the user's selection, means for continuously monitoring operation status and disaster information, and means for calculating an optimal alternative route and notifying the user when the situation changes. This system enables users to reach their destination via the optimal route even in the event of a disaster. Furthermore, by using past data to predict future operation status and making reservations on behalf of the user, further convenience can be provided.

[0006] A "user" is a person or organization that uses the system to input their current location, destination, and departure time to receive optimized routing and reservation services.

[0007] "Current location" refers to the user's current location, and is information the system needs to calculate a route to the destination.

[0008] "Destination" refers to the location the user wants to reach, and is the finish point when the system calculates the optimal route.

[0009] "Departure time" means the time when the user plans to start traveling, and is information that serves as a basis for the system to calculate routes and perform reservation procedures.

[0010] "Transportation" refers to any public or private vehicle used by a user for transportation, such as a train, bus, or airline.

[0011] "Real-time operation status data" is data that shows the current operation status of transportation facilities and is basic information that the system uses to calculate the optimal route.

[0012] "Disaster information" refers to information about natural disasters such as typhoons, earthquakes, and floods, and is an element that affects the operation status of transportation and users' travel plans.

[0013] "Optimal route" refers to the route that allows the user to reach the destination most efficiently, taking into consideration the current traffic conditions and disaster information.

[0014] The "calculation result" refers to a series of route information obtained after the system calculates the optimal route, and is the content presented to the user.

[0015] "Reservation agency" refers to a service in which the system acts on the user's behalf to reserve transportation tickets and seats based on the user's selection.

[0016] "Monitoring" refers to the process by which the system continuously monitors transportation status and disaster information, which is necessary to provide users with optimal alternative routes as the situation changes.

[0017] An "alternate route" refers to an alternative route that is provided when the original route is unavailable, and is a secondary option for a user to reach a destination.

[0018] "Historical data" refers to data on the operation history of transportation systems in the past and the impact of disasters, and is information used to predict future operation conditions. [Brief explanation of the drawings]

[0019] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0020] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0021] First, the terms used in the following description will be explained.

[0022] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0023] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0024] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0025] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0026] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0027] [First embodiment]

[0028] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0029] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0030] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0031] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0032] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0033] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0034] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0035] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0036] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0037] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0038] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0039] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0040] The present invention relates to a system that inputs a user's current location, destination, and departure time, calculates the optimal route even in the event of a disaster, and even makes reservations on their behalf. This system can quickly respond to information about the operation status of public transportation and disaster information, and efficiently guide users to their destinations. Detailed embodiments of the system are described below.

[0041] System configuration

[0042] This system mainly consists of a user device, a server, and related APIs. The user device is a mobile device such as a smartphone or tablet, and the server is located on the cloud. It also works in conjunction with APIs that provide information on various transportation services and weather information.

[0043] Program processing

[0044] 1. Accepting user input

[0045] The user inputs his / her current location, destination, and departure time into the user terminal.

[0046] As a specific example, the user inputs "Tokyo Station", "Shin-Osaka Station", and "08:00".

[0047] 2. Data collection

[0048] The terminal transmits the input information to the server.

[0049] The server obtains real-time operation status data for transportation services from each transportation service's API.

[0050] The server also collects disaster information from the Japan Meteorological Agency and other sources.

[0051] 3. Route calculation

[0052] The optimal route is calculated based on the operation status and disaster information collected by the server.

[0053] As a specific example, if the Shinkansen train operation status is normal, the route "travel from Tokyo Station to Shin-Osaka Station by Shinkansen" is suggested.

[0054] 4. Presentation of results

[0055] The server sends the calculation results to the terminal.

[0056] The terminal presents the calculation results to the user, including the route, travel time, and fare.

[0057] As a concrete example, it states, "The Shinkansen from Tokyo Station to Shin-Osaka Station takes 2 hours and 30 minutes and costs 13,500 yen."

[0058] 5. Selection and Booking

[0059] The user selects a route from the options presented.

[0060] The terminal transmits the selected route information to the server.

[0061] The server connects with the transportation reservation system to reserve tickets.

[0062] 6. Real-time updates

[0063] The server continuously monitors transportation operation status and disaster information.

[0064] Each time the information is updated, the server calculates the optimal alternative route if necessary and notifies the terminal.

[0065] As a concrete example, if the Shinkansen from Tokyo Station to Shin-Osaka Station is delayed, the server will offer an alternative means of transportation (for example, a combination of bus and train).

[0066] The system allows users to reach their destinations efficiently even in times of disaster, and uses past data to predict future travel conditions, supporting more accurate and adaptive travel.

[0067] The processing flow will be explained below.

[0068] Step 1:

[0069] The user inputs his / her current location, destination, and departure time into the terminal.

[0070] Example: Enter "Current location: Tokyo Station, Destination: Shin-Osaka Station, Departure time: 08:00".

[0071] Step 2:

[0072] The terminal transmits the input information to the server.

[0073] Send data to the server in the form of an API request.

[0074] Step 3:

[0075] The server acquires real-time operational status data of transportation facilities.

[0076] Data is collected by calling the real-time operation status API of each transportation company.

[0077] Example: Obtaining Shinkansen train operation status from a railway company's API.

[0078] Step 4:

[0079] The server collects disaster information.

[0080] It calls the APIs of the Japan Meteorological Agency and disaster information services to obtain information on typhoons, earthquakes, floods, etc.

[0081] Step 5:

[0082] The server calculates the optimal route based on current traffic conditions and disaster information.

[0083] It uses an algorithm to generate the optimal route from the user's current location to their destination.

[0084] Example: If the Shinkansen is operating normally, select the route "Take the Shinkansen from Tokyo to Shin-Osaka."

[0085] Step 6:

[0086] The server sends the calculation results to the terminal.

[0087] Information such as the optimal route, travel time, and fare is sent to the terminal in JSON format.

[0088] Step 7:

[0089] The terminal presents the calculation results to the user.

[0090] Specific means of transportation, departure time, travel time, fare, etc. are displayed on the screen.

[0091] Example: "From Tokyo Station to Shin-Osaka Station by Shinkansen, travel time: 2 hours 30 minutes, fare: 13,500 yen."

[0092] Step 8:

[0093] The user selects a route from the options presented.

[0094] Tap or click to choose the best route from the multiple options presented.

[0095] Step 9:

[0096] The terminal transmits the user's selection information to the server.

[0097] The selected route information is sent to the server in the form of an API request.

[0098] Step 10:

[0099] The server connects with the reservation systems of each transportation facility to reserve tickets.

[0100] Example: Call the Shinkansen reservation system API to reserve a ticket for a specified flight.

[0101] Step 11:

[0102] The server continuously monitors transportation operation status and disaster information.

[0103] The API is called periodically to obtain the latest operational status and disaster information.

[0104] Step 12:

[0105] When the situation changes, the server calculates the optimal alternative route and notifies the device.

[0106] Calculate the new optimal route and push a notification to the user.

[0107] Example: "The Shinkansen is delayed. We recommend using a combination of bus and train as an alternative route."

[0108] Step 13:

[0109] The terminal presents the user with new information and prompts them to make another selection.

[0110] New route suggestions are displayed on the screen and the user is prompted to select one.

[0111] Example: "Take the bus from Tokyo Station to Shinagawa Station, then take the local train to Shin-Osaka Station."

[0112] This series of steps allows users to reach their destination efficiently even in the event of a disaster.

[0113] Example 1

[0114] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0115] There is a need to provide an efficient means of transportation that can respond quickly to disasters and changes in real-time transportation status, as well as calculate the optimal route for users and even make reservations on their behalf. This will reduce anxiety about delays and cancellations of transportation and enable smoother and more efficient travel.

[0116] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0117] In this invention, the server includes means for inputting the user's current location, destination, and departure time, means for transmitting input information from the user terminal to the server, means for acquiring real-time transportation operation status data, means for collecting weather and disaster information, means for calculating an optimal route reflecting current operation status and disaster information, means for transmitting the calculation results to the user terminal, means for presenting the calculation results to the user, means for making necessary reservations on behalf of the user based on their selection, means for reserving tickets in cooperation with the transportation reservation system, means for continuously monitoring operation status and disaster information, and means for calculating an optimal alternative route when information is updated and notifying the user. This enables efficient travel in the event of a disaster or when transportation delays or cancellations occur.

[0118] "Means for inputting user's current location, destination, and departure time" refers to the interface used by the user to input their current location, destination, and departure time.

[0119] "Means for transmitting input information from a user terminal to a server" refers to a communication means or protocol for transmitting information input from a user terminal to a server.

[0120] "Means for obtaining real-time transit status data" means means for accessing a transit agency's API or data source to obtain real-time transit status data.

[0121] "Means of collecting weather and disaster information" refers to means of accessing the APIs of the Japan Meteorological Agency and disaster response organizations in order to collect weather information and other emergency information during disasters.

[0122] "Means for calculating the optimal route that reflects current operational conditions and disaster information" refers to a means for calculating the optimal travel route using an algorithm, taking into account real-time operational conditions and disaster information.

[0123] "Means for transmitting the calculation results to the user terminal" refers to the communication means or protocol for transmitting the route information calculated by the server to the user terminal.

[0124] "Means for presenting calculation results to the user" refers to an interface for presenting the results displayed on the user terminal in a format that is easy for the user to understand.

[0125] "Means for obtaining the necessary reservations on behalf of the user based on their selection" refers to the procedures and protocols for making transportation reservations on behalf of the user based on the route selected by the user.

[0126] "Means for reserving tickets in cooperation with a transportation company's reservation system" refers to a means for reserving tickets by accessing a transportation company's ticket reservation system and inputting the necessary information.

[0127] "Means for continuously monitoring operation status and disaster information" refers to means for continuously monitoring the operation status of transportation facilities and disaster information in real time, and updating it whenever new information is obtained.

[0128] "Means for calculating the optimal alternative route when information is updated and notifying the user" refers to means for recalculating the optimal alternative route based on the new conditions when operation status or disaster information is updated and notifying the user.

[0129] MODE FOR CARRYING OUT THE INVENTION

[0130] This invention relates to a system that inputs a user's current location, destination, and departure time, calculates the optimal route even in the event of a disaster, and even makes reservations on their behalf. This system can quickly respond to information about the operation status of public transportation and disaster information, and efficiently guide users to their destinations.

[0131] System configuration

[0132] The system's main components are user devices, servers, and related APIs. User devices are mobile devices such as smartphones and tablets, and the servers are located in a cloud environment. The system also works in conjunction with APIs that provide information on various transportation services and weather information.

[0133] Hardware and software used

[0134] User devices: smartphones, tablets, etc.

[0135] Server: Server on a cloud environment

[0136] API: Transport API (e.g. transport information API), Japan Meteorological Agency API

[0137] Data processing and calculation

[0138] 1. Accepting user input

[0139] The user enters their current location, destination, and departure time into the user device. For example, the user opens the smartphone app, enters "Tokyo Station," "Shin-Osaka Station," and "08:00," and taps the send button.

[0140] 2. Data collection

[0141] The device sends the entered information to the server, where it is converted to JSON format and sent using an HTTPS request.

[0142] The server accesses the API of each transportation facility to obtain real-time operation status data of the transportation facility. For example, it sends a request to the transportation facility's API to obtain real-time operation information.

[0143] The server sends requests to the APIs of the Japan Meteorological Agency and disaster prevention organizations to collect real-time weather information and disaster information.

[0144] 3. Route calculation

[0145] The server calculates the optimal route based on the operational status and disaster information collected. It uses Dijkstra's algorithm and generative AI models to calculate the optimal route using real-time data as input. For example, if the Shinkansen operational status is normal, it will suggest the route "travel from Tokyo Station to Shin-Osaka Station by Shinkansen."

[0146] 4. Presentation of results

[0147] The server sends the calculation results to the terminal, where they are converted into JSON format and sent as an HTTPS response.

[0148] The terminal presents the calculation results to the user. The calculation results are displayed on the user interface, clearly indicating the route, travel time, fare, etc. For example, it may say, "From Tokyo Station to Shin-Osaka Station by Shinkansen, the travel time is 2 hours and 30 minutes, and the fare is 13,500 yen."

[0149] 5. Selection and Booking

[0150] The user selects a route from the options presented. The user taps on the desired route to select it.

[0151] The device sends the selected route information to the server, which converts the information into JSON format and sends it using an HTTPS request.

[0152] The server works with the transport company's reservation system to reserve a ticket. For example, the server accesses the transport company's reservation system API and sends the necessary information to reserve a ticket.

[0153] 6. Real-time updates

[0154] The server continuously monitors the status of public transport and disaster information, periodically checking the API endpoint to obtain new information.

[0155] Each time the information is updated, the server calculates the optimal alternative route as needed and notifies the device. For example, if the Shinkansen from Tokyo Station to Shin-Osaka Station is delayed, a notification will be sent offering an alternative route that combines buses and trains.

[0156] Prompt Sentence Examples

[0157] The following are some examples of prompts that can be input to a generative AI model:

[0158] "Calculate the optimal route if your current location is Tokyo Station, your destination is Shin-Osaka Station, and your departure time is 8:00."

[0159] "Please suggest the best way to get from Tokyo Station to Shin-Osaka Station in the event of a disaster."

[0160] "Please make a reservation for departure: Tokyo Station, destination: Shin-Osaka Station, departure time: 08:00."

[0161] This allows for optimal route and reservation suggestions based on real-time information.

[0162] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0163] Step 1:

[0164] The user inputs his / her current location, destination, and departure time into the user terminal.

[0165] Input: A user opens the app on their smartphone, enters "Tokyo Station," "Shin-Osaka Station," and "08:00," and taps the send button.

[0166] Output: The input data (current location, destination, departure time) is generated in JSON format.

[0167] Specific behavior: When you enter data into the input form and tap the submit button, the data is converted to JSON format within the app.

[0168] Step 2:

[0169] The terminal transmits the input information to the server.

[0170] Input: The JSON formatted data generated in step 1.

[0171] Output: Data sent to the server via an HTTP POST request.

[0172] Specific operation: The communication module in the device sends JSON formatted data as an HTTP POST request to the server's API endpoint.

[0173] Step 3:

[0174] The server acquires real-time operational status data of transportation facilities.

[0175] Input: API request (a request for transit status data).

[0176] Output: Response from the API (real-time transport status data).

[0177] Specific operation: The server sends a request to each transportation company's API and receives real-time operation status data. After receiving the data, it is analyzed.

[0178] Step 4:

[0179] The server collects disaster information from the Japan Meteorological Agency and disaster prevention agencies.

[0180] Input: API request (request for disaster information).

[0181] Output: Response from the API (disaster information data).

[0182] Specific operation: The server sends requests to the APIs of the Japan Meteorological Agency and disaster response organizations to receive real-time disaster information. After receiving the data, it is analyzed.

[0183] Step 5:

[0184] The optimal route is calculated based on the operation status data and disaster information collected by the server.

[0185] Input: Real-time transportation status data and disaster information.

[0186] Output: Optimal route data.

[0187] Specific operation: The server uses Dijkstra's algorithm and generative AI models to calculate the optimal route based on real-time data. The calculation results are then generated as specific route information.

[0188] Step 6:

[0189] The server sends the calculation results to the terminal.

[0190] Input: Optimal route data.

[0191] Output: Data is sent to the user's device via an HTTP response.

[0192] Specific operation: The calculation result is converted to JSON format and sent to the terminal as an HTTP response.

[0193] Step 7:

[0194] The terminal presents the calculation results to the user.

[0195] Input: Optimal route data sent from the server.

[0196] Output: Route information displayed on the user interface.

[0197] Specific operation: The received data is analyzed and displayed on the screen as the route, travel time, fare, etc. For example, it may display "From Tokyo Station to Shin-Osaka Station by Shinkansen, travel time is 2 hours and 30 minutes, fare is 13,500 yen."

[0198] Step 8:

[0199] The user selects a route from the options presented.

[0200] Input: The user taps the desired route from the options on the screen.

[0201] Output: Selected route information.

[0202] Specific behavior: The user taps on the desired route from the presented route options, and that information is selected.

[0203] Step 9:

[0204] The terminal transmits the selected route information to the server.

[0205] Input: Selected route information.

[0206] Output: Data sent to the server via an HTTP POST request.

[0207] Specific behavior: The selected information is converted to JSON format and sent to the server as an HTTP POST request.

[0208] Step 10:

[0209] The server connects with the transportation reservation system to reserve tickets.

[0210] Input: Selected route information and user information.

[0211] Output: Successful reservation information in the transport reservation system.

[0212] Specific operation: The server accesses the transport reservation system API, sends the necessary information and makes a ticket reservation.

[0213] Step 11:

[0214] The server continuously monitors transportation status and disaster information.

[0215] Input: A timer event that causes the server to periodically check the API endpoint.

[0216] Output: Updated operational status data and disaster information.

[0217] Specific operation: The server periodically accesses each API to obtain new information.

[0218] Step 12:

[0219] Each time the information is updated, the server calculates the optimal alternative route if necessary and notifies the terminal.

[0220] Input: Updated operational status data and disaster information.

[0221] Output: New best alternative route data and notification.

[0222] Specific operation: The server recalculates the route based on the newly acquired data, calculates the optimal alternative route, and notifies the user. For example, if the Shinkansen from Tokyo Station to Shin-Osaka Station is delayed, a notification will be sent offering a route that combines buses and trains.

[0223] (Application example 1)

[0224] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0225] Conventional autonomous vehicle route guidance systems have difficulty calculating routes that fully take into account real-time transportation status and disaster information, and there is no guarantee that users will arrive at their destination safely. Another issue is that autonomous vehicles cannot propose appropriate alternative routes in emergencies. Furthermore, they lack a reservation agent function to improve user convenience, forcing users to go through complicated procedures.

[0226] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0227] In this invention, the server includes means for inputting the user's current location, destination, and departure time, means for acquiring real-time transportation operation status data, means for collecting disaster information, means for calculating an optimal route reflecting the current operation status and disaster information, means for presenting the calculation results to the user, means for making necessary reservations on behalf of the user based on their selection, means for continuously monitoring operation status and disaster information, means for calculating an optimal alternative route when the situation changes and notifying the user, means installed in the autonomous vehicle for updating the vehicle's control system with route information, and means for suggesting alternative routes and stops for emergencies. This allows the user to receive optimal route guidance in real time, allowing for quick response in emergencies, and the reservation proxy function eliminates the need for complicated procedures.

[0228] "User's current location" refers to the location where a person using the system is currently located.

[0229] "Destination" refers to the final destination that the user is aiming for.

[0230] "Departure time" refers to the time set by the user as the planned departure time.

[0231] "Real-time transport status data" refers to up-to-date information about the current operating status of public transport such as buses, trains and planes.

[0232] "Disaster information" refers to information about natural disasters such as earthquakes, typhoons, and heavy rain provided by the Japan Meteorological Agency and other organizations.

[0233] "Optimal route" refers to the travel route that allows a user to reach their destination most efficiently and safely.

[0234] "Calculation results" refers to information on the optimal route or alternative route calculated by the system.

[0235] "Means of obtaining reservations on behalf of users" refers to a function that automatically obtains the necessary tickets and reservations through the transportation reservation system based on user operations.

[0236] "Means for continuously monitoring operation status and disaster information" refers to the system's ability to continuously monitor the operation status of transportation services and disaster information in real time.

[0237] "Means for calculating the optimal alternative route and notifying the user" refers to a function that calculates a new optimal route and notifies the user when the originally planned route is not available.

[0238] An "autonomous vehicle" refers to a vehicle that can drive and be controlled automatically using artificial intelligence and various sensors.

[0239] "Means for reflecting in the vehicle's control system" refers to the function of inputting the calculated route information into the control device of the autonomous vehicle and applying it as the vehicle's driving route.

[0240] "Means for suggesting alternative routes and stopping points in emergencies" refers to a function that suggests alternative travel routes and stopping points so that users can evacuate safely in the event of an emergency or disaster.

[0241] This invention is a system for providing optimal route guidance to autonomous vehicles. It inputs the user's current location, destination, and departure time, and calculates the optimal route in real time, reflecting the operation status of public transport and disaster information, and even handles necessary reservations. Furthermore, in emergencies, it can propose alternative routes and reflect them in the vehicle's control system.

[0242] The system consists of a user terminal, a server, related APIs, and an autonomous vehicle control system.

[0243] Hardware and software:

[0244] Hardware: On-board computers in autonomous vehicles, smartphones, and tablets

[0245] Software: Python, API (traffic information API, disaster information API), cloud server

[0246] System behavior:

[0247] 1. User Input

[0248] The user enters their current location, destination, and departure time into their smartphone or in-car tablet.

[0249] 2. Data collection

[0250] The terminal sends this information to a server, which then obtains real-time transportation status data and disaster information from various APIs.

[0251] 3. Route calculation

[0252] The server uses the acquired data to calculate the optimal route for the user, using algorithms such as generative AI models.

[0253] 4. Presentation of results

[0254] The server sends the calculation results to the terminal, which then presents them to the user, including route information, travel time, and fare information.

[0255] 5. Reservations and proxy acquisition

[0256] Once the user selects a route from the options presented, the terminal sends this information to the server, which then works with the transport company's reservation system to reserve a ticket on their behalf.

[0257] 6. Real-time updates

[0258] The server continuously monitors operational status and disaster information, calculates optimal alternative routes as needed, notifies users, and reflects the results in the vehicle's control system to support safe operation.

[0259] 7. Emergency Response

[0260] In an emergency, the server calculates alternative routes and stops and suggests them to the user via the terminal. For example, if Shinkansen service is suspended, the server will notify the user of alternative bus routes and nearby safe stops.

[0261] Examples:

[0262] For example, if a user wants to travel from Tokyo Station to Shin-Osaka Station, they can input their data and receive calculated Shinkansen route information (travel time, fare). If the Shinkansen is delayed, the system will suggest an alternative route that combines buses and trains, and will also make reservations for that route on their behalf.

[0263] Example prompt sentence:

[0264] "I'd like to travel from Tokyo Station to Shin-Osaka Station. My departure time is 8:00 AM. Please tell me the best route and an alternative route, taking into account the current traffic conditions and disaster information."

[0265] This system allows users to efficiently select the most suitable means of transportation and reach their destination safely and comfortably.

[0266] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0267] Step 1:

[0268] User input:

[0269] The user inputs their current location, destination, and departure time into their smartphone or in-car tablet. This input data becomes the initial input data for the system.

[0270] Step 2:

[0271] Sending data:

[0272] The device sends the current location, destination, and departure time data acquired from the user to the server, which then prepares the server for the next step of data collection.

[0273] Step 3:

[0274] Transportation data collection:

[0275] The server obtains real-time operational status data for transportation services. The latest operational information for each transportation service is collected via API and stored in a database. This data is used when calculating routes.

[0276] Step 4:

[0277] Disaster information collection:

[0278] The server acquires disaster information. It collects the latest disaster information from disaster information APIs such as those provided by the Japan Meteorological Agency and stores it in a database. This data affects route calculations.

[0279] Step 5:

[0280] Route calculation:

[0281] The server calculates the optimal route based on traffic status data and disaster information collected. Using generative AI models and route optimization algorithms, it determines the safest and most efficient route for users to reach their destination. This calculation takes into account the user's current location, destination, and departure time.

[0282] Step 6:

[0283] Presenting the results:

[0284] The server sends the calculation results to the terminal, which then presents them to the user. The calculation results include the optimal route, travel time, fare, etc., allowing the user to confirm the proposed route.

[0285] Step 7:

[0286] Booking and Acquisition:

[0287] When the user selects a route from the options presented, the device sends that information to the server. The server then works with the transportation company's reservation system to automatically obtain the necessary reservations on the user's behalf. Once the reservation is complete, the information is sent to the user's device.

[0288] Step 8:

[0289] Real-time updates:

[0290] The server continuously monitors transportation status and disaster information. If new information is confirmed, the server recalculates the optimal alternative route and sends the results to the device, ensuring that users always receive the latest route information.

[0291] Step 9:

[0292] Route information reflection:

[0293] The server then updates the autonomous vehicle's control system with the latest route information, allowing the autonomous vehicle to travel along the optimal route.

[0294] Step 10:

[0295] Emergency Response:

[0296] In the event of an emergency, the server calculates alternative routes and stops and suggests them to the user via their device, allowing the user to travel safely even in an emergency.

[0297] In this way, the system collects and processes data based on user input, providing optimal routes and alternative routes to help ensure efficient and safe travel.

[0298] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0299] This invention relates to a transportation route guidance system for use in emergencies that has been further improved by combining it with an emotion engine that recognizes the user's emotions. This system inputs the user's current location, destination, and departure time, and calculates and presents the optimal route based on real-time transportation conditions and disaster information, and makes reservations on behalf of the user if necessary. It also provides a more personalized service by recognizing the user's emotional state and suggesting optimal notification methods and routes based on that information.

[0300] System configuration

[0301] This system mainly consists of a user device, a server, an emotion engine, and a data acquisition API. The user device is a mobile device such as a smartphone or tablet, and the server is located on the cloud. The emotion engine is integrated into the device and recognizes emotions from the user's facial expressions, voice, text, etc. The data acquisition API provides transportation and weather information.

[0302] Program processing

[0303] 1. Accepting user input

[0304] The user inputs his / her current location, destination, and departure time into the user terminal.

[0305] For example, enter "Current location: Tokyo Station, Destination: Shin-Osaka Station, Departure time: 08:00".

[0306] 2. Data collection

[0307] The terminal transmits the input information to the server.

[0308] The server obtains real-time operation status data for transportation services from each transportation service's API.

[0309] The server also collects disaster information from the Japan Meteorological Agency and other sources.

[0310] 3. Emotional Recognition

[0311] The emotion engine recognizes the user's emotions, for example, by using facial recognition and voice analysis technology to determine whether the user is feeling stressed.

[0312] 4. Route calculation

[0313] The server calculates the optimal route based on the traffic status, disaster information, and user emotional information collected.

[0314] For example, if the Shinkansen train operation status is normal and the user is not feeling stressed, the route "from Tokyo to Shin-Osaka by Shinkansen" is suggested.

[0315] 5. Presentation of results

[0316] The server sends the calculation results to the terminal.

[0317] The terminal presents the calculation results to the user, including the route, travel time, and fare.

[0318] For example, it might say, "Take the Shinkansen from Tokyo Station to Shin-Osaka Station, travel time: 2 hours 30 minutes, fare: 13,500 yen."

[0319] 6. Selection and Reservation

[0320] The user selects a route from the options presented.

[0321] The terminal transmits the selected route information to the server.

[0322] The server connects with the transportation reservation system to reserve tickets.

[0323] For example, it can be linked to a Shinkansen reservation system to reserve tickets for a specified flight.

[0324] 7. Real-time updates

[0325] The server continuously monitors transportation operation status and disaster information.

[0326] Each time the information is updated, the server calculates the optimal alternative route if necessary and notifies the terminal.

[0327] For example, the notification could say, "The Shinkansen is delayed. We recommend using a combination of bus and train as an alternative route."

[0328] 8. Emotion-Based Regulation

[0329] The device adjusts the calculation results and notification method according to the user's emotions.

[0330] For example, if a user is feeling stressed, a notification that provides a sense of relief such as, "The Shinkansen is delayed, but we have found an alternative route that provides a comfortable space" can be displayed.

[0331] In this way, a system integrating an emotion engine allows users to reach their destination efficiently via the optimal route even in the event of a disaster, and complete their journey with a sense of security.

[0332] The processing flow will be explained below.

[0333] Step 1:

[0334] The user inputs his / her current location, destination, and departure time into the terminal.

[0335] Example: Enter "Current location: Tokyo Station, Destination: Shin-Osaka Station, Departure time: 08:00".

[0336] Step 2:

[0337] The terminal transmits the input information to the server.

[0338] Send data in the form of an API request.

[0339] Step 3:

[0340] The server obtains real-time operation status data for transportation services from each transportation service's API.

[0341] Example: Obtaining Shinkansen train operation status from a railway company's API.

[0342] Step 4:

[0343] The server collects disaster information from disaster information providers such as the Japan Meteorological Agency.

[0344] Example: Obtaining information about typhoons, earthquakes, and floods.

[0345] Step 5:

[0346] The terminal uses an emotion engine to recognize the user's emotion.

[0347] Example: Analyzing the user's facial expressions through the front camera to recognize stress levels.

[0348] Step 6:

[0349] The server calculates the optimal route based on the operation status, disaster information, and user emotional information collected.

[0350] Example: If the Shinkansen is running normally and the user is feeling stressed, suggest a route such as "Take the Shinkansen from Tokyo to Shin-Osaka," while also considering options that provide a comfortable space.

[0351] Step 7:

[0352] The server sends the calculation results to the terminal.

[0353] The obtained route information, travel time, fare, etc. are sent in JSON format.

[0354] Step 8:

[0355] The terminal presents the calculation results to the user.

[0356] Example: "Take the Shinkansen from Tokyo Station to Shin-Osaka Station, travel time: 2 hours 30 minutes, fare: 13,500 yen."

[0357] Step 9:

[0358] The user selects the best route from the options presented.

[0359] Example: Tap or click to select the best option from multiple options presented.

[0360] Step 10:

[0361] The terminal transmits the user's selection information to the server.

[0362] The selected route information is sent in the form of an API request.

[0363] Step 11:

[0364] The server connects with the transport company's reservation system to reserve tickets.

[0365] Example: Call the Shinkansen reservation system API to reserve a ticket for a specified flight.

[0366] Step 12:

[0367] The server continuously monitors transportation operation status and disaster information.

[0368] Continue to obtain real-time data on a regular basis.

[0369] Step 13:

[0370] When the situation changes, the server calculates the optimal alternative route and notifies the device.

[0371] Example: "The Shinkansen is delayed. We recommend using a combination of bus and train as an alternative route."

[0372] Step 14:

[0373] The terminal presents the user with new information and prompts them to make another selection.

[0374] Example: "Take the bus from Tokyo Station to Shinagawa Station, then take the local train to Shin-Osaka Station."

[0375] Step 15:

[0376] The device uses an emotion engine to adjust the notification method and content based on the user's emotions.

[0377] Example: If a user is feeling stressed, provide a reassuring notification such as, "The Shinkansen is delayed, but we have found an alternative route that provides a comfortable space."

[0378] In this way, users can reach their destination efficiently even in the event of a disaster, and the emotion engine allows them to complete their journey with an added sense of security.

[0379] Example 2

[0380] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0381] Conventional transportation route guidance systems do not take into account the user's psychological state, which often leaves users feeling anxious, especially during disasters. Furthermore, whenever the transportation status or disaster information changes, the recalculation and notification of optimal routes can be delayed, making it difficult for users to travel quickly and safely. Furthermore, the transportation reservation process is complicated, placing a burden on users in many situations.

[0382] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0383] In this invention, the server includes means for inputting the user's current location, destination, and departure time, means for acquiring real-time transportation operation status data, means for collecting disaster information, means for recognizing the user's emotions, means for calculating an optimal route reflecting the current operation status, disaster information, and the user's emotional information, means for presenting the calculation results to the user, means for making necessary reservations on behalf of the user based on their selection, means for continuously monitoring the operation status and disaster information, and means for calculating an optimal alternative route and notifying the user when the situation changes. This allows the user to receive optimal route guidance based on the latest information in real time, and by providing personalized notifications and guidance according to the user's emotional state, the server can travel with peace of mind.

[0384] "Current location of user" refers to geographical location information where the user is currently physically located.

[0385] A "destination" is the final geographic location that a user wishes to reach.

[0386] "Departure time" is information indicating the date and time when the user plans to start traveling.

[0387] "Real-time transportation status data" is the latest information on how transportation such as trains, buses, and planes are currently operating.

[0388] "Disaster information" refers to information about natural disasters and other emergencies that may affect users' travel.

[0389] "User's emotions" is information that indicates the user's psychological state and emotions, and includes states such as stress, relief, and excitement.

[0390] The "means for calculating the optimal route" refers to an algorithm or system that calculates the most efficient and safe travel route for the user based on collected information.

[0391] The "means for presenting the calculation results to the user" refers to a method or technology for displaying the results of the route calculation in a format that is easy for the user to view.

[0392] A "means for obtaining reservations on behalf of a user" is a system or process for automatically making reservations for transportation or other means selected by the user.

[0393] "Means for continuously monitoring operation status and disaster information" refers to technologies and methods for constantly monitoring the operation status of transportation and disaster information, and collecting the latest information.

[0394] "Means for calculating the optimal alternative route and notifying the user" refers to a system or method for recalculating the optimal route when the situation changes and notifying the user of the result.

[0395] MODE FOR CARRYING OUT THE INVENTION

[0396] The present invention relates to a traffic route guidance system for use in emergencies that has been further improved by combining it with an emotion engine that recognizes the user's emotions. This system aims to not only enable users to receive optimal route guidance based on the latest information in real time, but also to provide personalized notifications and suggestions according to the user's psychological state. Specific embodiments for implementing this invention are described below.

[0397] Hardware and software configuration

[0398] This system mainly consists of a user device, a server, an emotion engine, and a data acquisition API. The user device is a mobile device such as a smartphone or tablet, and the server is located on the cloud. The emotion engine is integrated into the device and recognizes emotions by analyzing the user's facial expressions, voice, text, etc. The data acquisition API is used to provide transportation and weather information.

[0399] Specific software names include OpenCV for face recognition and Google® Cloud Speech-to-Text for voice analysis. Transportation data is acquired through the transportation company's API (e.g., JR East's API). Weather information is acquired from the Japan Meteorological Agency's API.

[0400] Example of operation

[0401] The following describes an example in which the user inputs "current location: Shibuya Station, destination: Nagoya Station, departure time: 10:00".

[0402] 1. Accepting user input: The user starts the smartphone app and enters their current location, destination, and departure time. For example, they enter "Current location: Shibuya Station, Destination: Nagoya Station, Departure time: 10:00" and press the "Send" button.

[0403] 2. Data collection: The device sends the entered information to the server. The server uses APIs to obtain real-time traffic and disaster information, allowing users to check the operating status of bullet trains, buses, airplanes, and other services.

[0404] 3. Emotion Recognition: The emotion engine analyzes the user's facial expressions and voice to determine their emotional state, for example, whether they are stressed or calm.

[0405] 4. Route calculation: The server calculates the optimal route based on the collected data and emotion information. If there are no Shinkansen delays, it will suggest traveling by Shinkansen as usual, but if there are delays, it will consider alternative routes.

[0406] 5. Displaying the results: The server sends the calculation results to the terminal and displays them to the user. For example, it displays "From Shibuya Station to Nagoya Station by Shinkansen, travel time: 2 hours, fare: 10,000 yen."

[0407] 6. Selection and reservation: The user selects a route from the presented options. The selected route information is sent to the server, which then connects with the transportation reservation system to reserve a ticket. For example, it connects with the Shinkansen reservation system to reserve a ticket for the specified flight.

[0408] 7. Real-time updates: The server continuously monitors the status of public transport and disaster information, and when the situation changes, it recalculates the optimal route and notifies the user. For example, if the Shinkansen is delayed, the server will notify the user, "The Shinkansen is delayed. We recommend using a combination of bus and train as an alternative route."

[0409] 8. Emotion-based adjustment: The device adjusts the notification method according to the user's emotions. For example, if the user is feeling stressed, the device will send a reassuring notification such as, "We have found an alternative route that provides a comfortable space."

[0410] Prompt Sentence Examples

[0411] Here are some examples of prompts for generative AI models:

[0412] "If the current location is Shibuya Station and the destination is Nagoya Station, please tell me the optimal transportation route departing at 10:00. Please also take into consideration local public transportation APIs and real-time disaster information. Please also provide guidance that includes notification methods that will reassure the user even if they are feeling stressed."

[0413] In this way, a system that integrates an emotion engine will suggest optimal routes for users even in the event of a disaster, enabling them to reach their destination safely.

[0414] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0415] Step 1: Accepting User Input

[0416] The user launches the smartphone app and enters their current location, destination, and departure time. For example, they enter "Current location: Shibuya Station, Destination: Nagoya Station, Departure time: 10:00." Once the entry is complete, the device temporarily stores this information internally.

[0417] Input: current location, destination, departure time

[0418] Output: User input information stored in the device

[0419] Specific operation: When a user enters information and taps the "Send" button, the data is saved in temporary storage on the device.

[0420] Step 2: Collect data

[0421] The device sends the temporarily saved user-entered information to the server, which then uses an HTTP request to obtain real-time operation status data from the transport company's API and disaster information from the Japan Meteorological Agency's API.

[0422] Input: User-entered information

[0423] Output: Transportation status data, disaster information data

[0424] Specific operation: The device sends a request to the server, which then calls the API of each transportation company to obtain operation status and collects disaster information from the API of the Japan Meteorological Agency.

[0425] Step 3: Recognize emotions

[0426] The device's integrated emotion engine uses the camera and microphone to analyze the user's current emotional state, including facial expression recognition with OpenCV and voice analysis with Google Cloud Speech-to-Text.

[0427] Input: Camera video, audio data

[0428] Output: User's emotional information (stress, relief, etc.)

[0429] Specific operation: While the user is looking at the smartphone, the camera captures facial expressions, the microphone records the user's voice, and the emotion engine analyzes this data.

[0430] Step 4: Calculate the route

[0431] The server runs an algorithm that combines transportation status data, disaster information data, and user emotion information to calculate the optimal route.

[0432] Input: Operation status data, disaster information data, emotion information

[0433] Output: Optimal route information

[0434] How it works: The server integrates this data and the algorithm calculates the optimal travel route. For example, if the traffic conditions are normal and the user is not feeling stressed, the route using the Shinkansen will be selected.

[0435] Step 5: Presenting the results

[0436] The server sends the calculation results to the terminal, which then presents the results to the user, including route information, travel time, and fare information.

[0437] Input: Optimal route information

[0438] Output: Route information presented to the user (e.g., on-screen display)

[0439] Specific operation: Based on the data sent from the server, the terminal displays information such as "From Shibuya Station to Nagoya Station by Shinkansen, travel time: 2 hours, fare: 10,000 yen."

[0440] Step 6: Select and reserve

[0441] The user selects a route from the options presented, and the terminal sends the selected information to the server, which then connects with the transport company's reservation system to reserve a ticket.

[0442] Input: User-selected information

[0443] Output: Reservation completion notification

[0444] Specific operation: Based on the route information selected by the user, the server accesses the transportation reservation system and reserves a ticket for the specified flight.

[0445] Step 7: Real-time updates

[0446] The server continuously monitors transportation operation status and disaster information, and when the information is updated, it recalculates the optimal alternative route and notifies the device.

[0447] Input: Latest traffic status data and disaster information

[0448] Output: Updated route information

[0449] Specific operation: The server detects changes in train operation status and disaster information, and sends newly calculated route information to the terminal, notifying it, for example, "The Shinkansen is delayed. We recommend using a combination of bus and train as an alternative route."

[0450] Step 8: Emotional Adjustment

[0451] The device adjusts the calculation results and notification method based on the user's latest emotional information. For example, if it determines that the user is feeling stressed, it will send a notification that gives a sense of relief.

[0452] Input: Latest emotional information

[0453] Output: Personalized notification content

[0454] Specific operation: The device analyzes emotional information, and if the user is feeling stressed, it displays the message "We have found an alternative route that provides a comfortable space," giving the user a sense of security.

[0455] This series of processes enables users to reach their destination quickly and safely via the optimal route even in the event of a disaster.

[0456] (Application example 2)

[0457] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0458] Conventional traffic route guidance systems have the problem of being unable to adequately respond to complex situations and rapid route changes that arise during disasters. Furthermore, because they do not take into account the user's emotional state, they have difficulty responding to situations that are likely to cause stress or anxiety. Furthermore, there is a need for efficient route guidance when using autonomous vehicles.

[0459] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for inputting the user's current location, destination, and departure time, means for acquiring real-time operation status data of public transportation, means for collecting disaster information, means for calculating an optimal route reflecting the current operation status and disaster information, means for presenting the calculation results to the user, means for making necessary reservations on behalf of the user based on their selection, means for continuously monitoring operation status and disaster information, means for calculating an optimal alternative route when the situation changes and notifying the user, means for recognizing the user's emotions and adjusting the notification method and route suggestions based on the emotions, and means for providing route guidance and moving in cooperation with an autonomous vehicle. This makes it possible to provide the user with the optimal route even during a disaster and provide personalized services according to the user's emotional state.

[0460] "User" refers to any individual or organization that uses this system.

[0461] "Current location" indicates the location information of the user's current location.

[0462] The "destination" indicates the location the user is heading for.

[0463] "Departure time" indicates the time when the user starts traveling.

[0464] "Transportation" means any public or private means of transportation used by a User.

[0465] "Real-time operation status data" refers to data that indicates the current operation status of transportation facilities.

[0466] "Disaster information" refers to information about natural disasters such as earthquakes, typhoons, and fires, as well as sudden accidents.

[0467] An "optimal route" refers to the most efficient, safe, and quickest route from the user's current location to their destination.

[0468] "Route calculation" refers to the process of calculating the optimal route based on input data.

[0469] "Presenting" refers to the act of visually or audibly conveying the results of a calculation to a user.

[0470] "Reservation proxy acquisition" refers to the act of carrying out the necessary reservation procedures on behalf of the user.

[0471] "Monitoring" refers to the act of continuously watching traffic conditions and disaster information.

[0472] "Alternate Route" refers to a suggested alternative route if the planned route is unavailable.

[0473] "Emotion recognition" refers to the technology of determining a user's emotions from their facial expressions, voice, and text.

[0474] "Notification method" refers to the means by which information is conveyed to the user.

[0475] "Route suggestion" refers to the act of recommending the optimal travel route to the user.

[0476] An "autonomous vehicle" refers to a vehicle that can drive autonomously without human operation.

[0477] "Collaboration" refers to multiple systems and devices sharing information and working together.

[0478] This invention relates to a system for an autonomous vehicle that recognizes the user's emotions and provides optimal route guidance in the event of a disaster. Specific embodiments of this system will be described below.

[0479] Hardware Configuration

[0480] A user device (e.g., a smartphone) has the following capabilities:

[0481] Emotion recognition using a camera and microphone

[0482] Obtaining location information using GPS

[0483] Internet connection

[0484] Autonomous vehicles will have the following capabilities:

[0485] Route Navigation System

[0486] Internet connection

[0487] The server has the following features:

[0488] Data Processing Capacity

[0489] Cloud-based database

[0490] Various APIs (traffic information, weather information)

[0491] Software Configuration

[0492] It uses the EmotionRecognizer library for emotion recognition, the Requests library for real-time traffic and disaster information acquisition, and custom algorithms for navigation calculations.

[0493] System Operation

[0494] 1. The user enters their current location, destination, and departure time into the smartphone app. For example, they enter "Current location: Tokyo Station, Destination: Shin-Osaka Station, Departure time: 08:00."

[0495] 2. The terminal sends the entered information to the server.

[0496] 3. The server obtains real-time transportation status data and disaster information from each transportation company's API.

[0497] 4. The server recognizes the user's emotions through the smartphone's camera and microphone, using facial recognition and voice analysis technology to determine whether the user is feeling stressed.

[0498] 5. The server calculates the optimal route based on the collected traffic status and disaster information, as well as the user's emotional state. For example, if the user is feeling stressed, it will prioritize a relaxing route.

[0499] 6. The calculation results are sent to the user's device. The results include information such as the route, travel time, and fare. For example, the display might say, "From Tokyo Station to Shin-Osaka Station by Shinkansen, travel time: 2 hours 30 minutes, fare: 13,500 yen."

[0500] 7. The user selects a route from the presented options and sends the selection to the terminal.

[0501] 8. The server connects the selected route information to the transportation reservation system and reserves tickets if necessary.

[0502] 9. The server continuously monitors transportation status and disaster information, and whenever the information is updated, calculates the optimal alternative route as needed and notifies the device.

[0503] 10. The device adjusts the calculation results and notification method according to the user's emotions. For example, if the user is feeling stressed, the device will send a notification that provides a sense of relief, such as, "The Shinkansen is delayed, but we have found an alternative route that provides a comfortable space."

[0504] Examples of specific examples and prompts

[0505] As a specific example, if a Shinkansen train is delayed, the server can notify the terminal, "This Shinkansen train is currently delayed by 30 minutes. As an alternative route, we suggest a combination of bus and train, which is equally comfortable."

[0506] Example prompt sentence:

[0507] "Analyze the user's facial expressions to determine their stress level."

[0508] "Use current traffic and disaster information to calculate the best route from your origin to your destination."

[0509] This enables the system to support efficient and safe travel along optimal routes even in the event of a disaster.

[0510] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0511] Step 1:

[0512] A user inputs their current location, destination, and departure time into a smartphone app. This input data includes "Current location: Tokyo Station," "Destination: Shin-Osaka Station," and "Departure time: 08:00."

[0513] Step 2:

[0514] The terminal sends the entered information to the server. In this process, the entered data of current location, destination, and departure time is transferred to the server as is.

[0515] Step 3:

[0516] The server obtains real-time transportation status data and disaster information from each transportation agency's API. The data processing performed in this step involves analyzing the data obtained from the API and converting it into a specific format. The analyzed transportation data and disaster information are generated as output.

[0517] Step 4:

[0518] To recognize the user's emotions, the device acquires data from the camera or microphone and performs emotion analysis using the EmotionRecognizer library. In this step, raw data from the camera or microphone is input, and the user's emotional state (e.g., stress level) is output as an analysis result.

[0519] Step 5:

[0520] The server calculates the optimal route based on the collected traffic conditions, disaster information, and user sentiment information. This step also references map information and past traffic data stored in the database. The output is route guidance information that includes specific means of transportation and their details.

[0521] Step 6:

[0522] The server sends the calculation results to the terminal, and the terminal displays them to the user. The information displayed includes the route, travel time, fare, etc. For example, it displays "From Tokyo Station to Shin-Osaka Station by Shinkansen, travel time: 2 hours 30 minutes, fare: 13,500 yen."

[0523] Step 7:

[0524] The user selects a route from the presented options and transmits the selection to the terminal. The data operations performed in this step are recording and confirming the selection. The output is the route selected by the user.

[0525] Step 8:

[0526] The server connects the selected route information to the transport company's reservation system and reserves tickets if necessary. In this step, the server sends the necessary information to the ticket reservation API and receives a reservation confirmation. The output is a confirmation that the reservation has been completed.

[0527] Step 9:

[0528] The server continuously monitors the status of public transport and disaster information. Each time the information is updated, the server analyzes the new data and calculates an alternative route if there is an abnormality in the service status. The output is new route guidance information in the event of an abnormality.

[0529] Step 10:

[0530] The device adjusts the calculation results and notification method according to the user's emotions. For example, if the user is feeling stressed, the device will send a notification that provides a sense of relief, such as "The Shinkansen is delayed, but we have found an alternative route that provides a comfortable space." The output is a notification message that corresponds to the user's emotions.

[0531] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0532] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0533] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0534] [Second embodiment]

[0535] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0536] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0537] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0538] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0539] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0540] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0541] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0542] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0543] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0544] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0545] In the smart glasses 214, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0546] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0547] The present invention relates to a system that inputs a user's current location, destination, and departure time, calculates the optimal route even in the event of a disaster, and even makes reservations on their behalf. This system can quickly respond to information about the operation status of public transportation and disaster information, and efficiently guide users to their destinations. Detailed embodiments of the system are described below.

[0548] System configuration

[0549] This system mainly consists of a user device, a server, and related APIs. The user device is a mobile device such as a smartphone or tablet, and the server is located on the cloud. It also works in conjunction with APIs that provide information on various transportation services and weather information.

[0550] Program processing

[0551] 1. Accepting user input

[0552] The user inputs his / her current location, destination, and departure time into the user terminal.

[0553] As a specific example, the user inputs "Tokyo Station", "Shin-Osaka Station", and "08:00".

[0554] 2. Data collection

[0555] The terminal transmits the input information to the server.

[0556] The server obtains real-time operation status data for transportation services from each transportation service's API.

[0557] The server also collects disaster information from the Japan Meteorological Agency and other sources.

[0558] 3. Route calculation

[0559] The optimal route is calculated based on the operation status and disaster information collected by the server.

[0560] As a specific example, if the Shinkansen train operation status is normal, the route "travel from Tokyo Station to Shin-Osaka Station by Shinkansen" is suggested.

[0561] 4. Presentation of results

[0562] The server sends the calculation results to the terminal.

[0563] The terminal presents the calculation results to the user, including the route, travel time, and fare.

[0564] As a concrete example, it states, "The Shinkansen from Tokyo Station to Shin-Osaka Station takes 2 hours and 30 minutes and costs 13,500 yen."

[0565] 5. Selection and Booking

[0566] The user selects a route from the options presented.

[0567] The terminal transmits the selected route information to the server.

[0568] The server connects with the transportation reservation system to reserve tickets.

[0569] 6. Real-time updates

[0570] The server continuously monitors transportation operation status and disaster information.

[0571] Each time the information is updated, the server calculates the optimal alternative route if necessary and notifies the terminal.

[0572] As a concrete example, if the Shinkansen from Tokyo Station to Shin-Osaka Station is delayed, the server will offer an alternative means of transportation (for example, a combination of bus and train).

[0573] The system allows users to reach their destinations efficiently even in times of disaster, and uses past data to predict future travel conditions, supporting more accurate and adaptive travel.

[0574] The processing flow will be explained below.

[0575] Step 1:

[0576] The user inputs his / her current location, destination, and departure time into the terminal.

[0577] Example: Enter "Current location: Tokyo Station, Destination: Shin-Osaka Station, Departure time: 08:00".

[0578] Step 2:

[0579] The terminal transmits the input information to the server.

[0580] Send data to the server in the form of an API request.

[0581] Step 3:

[0582] The server acquires real-time operational status data of transportation facilities.

[0583] Data is collected by calling the real-time operation status API of each transportation company.

[0584] Example: Obtaining Shinkansen train operation status from a railway company's API.

[0585] Step 4:

[0586] The server collects disaster information.

[0587] It calls the APIs of the Japan Meteorological Agency and disaster information services to obtain information on typhoons, earthquakes, floods, etc.

[0588] Step 5:

[0589] The server calculates the optimal route based on current traffic conditions and disaster information.

[0590] It uses an algorithm to generate the optimal route from the user's current location to their destination.

[0591] Example: If the Shinkansen is operating normally, select the route "Take the Shinkansen from Tokyo to Shin-Osaka."

[0592] Step 6:

[0593] The server sends the calculation results to the terminal.

[0594] Information such as the optimal route, travel time, and fare is sent to the terminal in JSON format.

[0595] Step 7:

[0596] The terminal presents the calculation results to the user.

[0597] Specific means of transportation, departure time, travel time, fare, etc. are displayed on the screen.

[0598] Example: "From Tokyo Station to Shin-Osaka Station by Shinkansen, travel time: 2 hours 30 minutes, fare: 13,500 yen."

[0599] Step 8:

[0600] The user selects a route from the options presented.

[0601] Tap or click to choose the best route from the multiple options presented.

[0602] Step 9:

[0603] The terminal transmits the user's selection information to the server.

[0604] The selected route information is sent to the server in the form of an API request.

[0605] Step 10:

[0606] The server connects with the reservation systems of each transportation facility to reserve tickets.

[0607] Example: Call the Shinkansen reservation system API to reserve a ticket for a specified flight.

[0608] Step 11:

[0609] The server continuously monitors transportation operation status and disaster information.

[0610] The API is called periodically to obtain the latest operational status and disaster information.

[0611] Step 12:

[0612] When the situation changes, the server calculates the optimal alternative route and notifies the device.

[0613] Calculate the new optimal route and push a notification to the user.

[0614] Example: "The Shinkansen is delayed. We recommend using a combination of bus and train as an alternative route."

[0615] Step 13:

[0616] The terminal presents the user with new information and prompts them to make another selection.

[0617] New route suggestions are displayed on the screen and the user is prompted to select one.

[0618] Example: "Take the bus from Tokyo Station to Shinagawa Station, then take the local train to Shin-Osaka Station."

[0619] This series of steps allows users to reach their destination efficiently even in the event of a disaster.

[0620] Example 1

[0621] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0622] There is a need to provide an efficient means of transportation that can respond quickly to disasters and changes in real-time transportation status, as well as calculate the optimal route for users and even make reservations on their behalf. This will reduce anxiety about delays and cancellations of transportation and enable smoother and more efficient travel.

[0623] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0624] In this invention, the server includes means for inputting the user's current location, destination, and departure time, means for transmitting input information from the user terminal to the server, means for acquiring real-time transportation operation status data, means for collecting weather and disaster information, means for calculating an optimal route reflecting current operation status and disaster information, means for transmitting the calculation results to the user terminal, means for presenting the calculation results to the user, means for making necessary reservations on behalf of the user based on their selection, means for reserving tickets in cooperation with the transportation reservation system, means for continuously monitoring operation status and disaster information, and means for calculating an optimal alternative route when information is updated and notifying the user. This enables efficient travel in the event of a disaster or when transportation delays or cancellations occur.

[0625] "Means for inputting user's current location, destination, and departure time" refers to the interface used by the user to input their current location, destination, and departure time.

[0626] "Means for transmitting input information from a user terminal to a server" refers to a communication means or protocol for transmitting information input from a user terminal to a server.

[0627] "Means for obtaining real-time transit status data" means means for accessing a transit agency's API or data source to obtain real-time transit status data.

[0628] "Means of collecting weather and disaster information" refers to means of accessing the APIs of the Japan Meteorological Agency and disaster response organizations in order to collect weather information and other emergency information during disasters.

[0629] "Means for calculating the optimal route that reflects current operational conditions and disaster information" refers to a means for calculating the optimal travel route using an algorithm, taking into account real-time operational conditions and disaster information.

[0630] "Means for transmitting the calculation results to the user terminal" refers to the communication means or protocol for transmitting the route information calculated by the server to the user terminal.

[0631] "Means for presenting calculation results to the user" refers to an interface for presenting the results displayed on the user terminal in a format that is easy for the user to understand.

[0632] "Means for obtaining the necessary reservations on behalf of the user based on their selection" refers to the procedures and protocols for making transportation reservations on behalf of the user based on the route selected by the user.

[0633] "Means for reserving tickets in cooperation with a transportation company's reservation system" refers to a means for reserving tickets by accessing a transportation company's ticket reservation system and inputting the necessary information.

[0634] "Means for continuously monitoring operation status and disaster information" refers to means for continuously monitoring the operation status of transportation facilities and disaster information in real time, and updating it whenever new information is obtained.

[0635] "Means for calculating the optimal alternative route when information is updated and notifying the user" refers to means for recalculating the optimal alternative route based on the new conditions when operation status or disaster information is updated and notifying the user.

[0636] MODE FOR CARRYING OUT THE INVENTION

[0637] This invention relates to a system that inputs a user's current location, destination, and departure time, calculates the optimal route even in the event of a disaster, and even makes reservations on their behalf. This system can quickly respond to information about the operation status of public transportation and disaster information, and efficiently guide users to their destinations.

[0638] System configuration

[0639] The system's main components are user devices, servers, and related APIs. User devices are mobile devices such as smartphones and tablets, and the servers are located in a cloud environment. The system also works in conjunction with APIs that provide information on various transportation services and weather information.

[0640] Hardware and software used

[0641] User devices: smartphones, tablets, etc.

[0642] Server: Server on a cloud environment

[0643] API: Transport API (e.g. transport information API), Japan Meteorological Agency API

[0644] Data processing and calculation

[0645] 1. Accepting user input

[0646] The user enters their current location, destination, and departure time into the user device. For example, the user opens the smartphone app, enters "Tokyo Station," "Shin-Osaka Station," and "08:00," and taps the send button.

[0647] 2. Data collection

[0648] The device sends the entered information to the server, where it is converted to JSON format and sent using an HTTPS request.

[0649] The server accesses the API of each transportation facility to obtain real-time operation status data of the transportation facility. For example, it sends a request to the transportation facility's API to obtain real-time operation information.

[0650] The server sends requests to the APIs of the Japan Meteorological Agency and disaster prevention organizations to collect real-time weather information and disaster information.

[0651] 3. Route calculation

[0652] The server calculates the optimal route based on the operational status and disaster information collected. It uses Dijkstra's algorithm and generative AI models to calculate the optimal route using real-time data as input. For example, if the Shinkansen operational status is normal, it will suggest the route "travel from Tokyo Station to Shin-Osaka Station by Shinkansen."

[0653] 4. Presentation of results

[0654] The server sends the calculation results to the terminal, where they are converted into JSON format and sent as an HTTPS response.

[0655] The terminal presents the calculation results to the user. The calculation results are displayed on the user interface, clearly indicating the route, travel time, fare, etc. For example, it may say, "From Tokyo Station to Shin-Osaka Station by Shinkansen, the travel time is 2 hours and 30 minutes, and the fare is 13,500 yen."

[0656] 5. Selection and Booking

[0657] The user selects a route from the options presented. The user taps on the desired route to select it.

[0658] The device sends the selected route information to the server, which converts the information into JSON format and sends it using an HTTPS request.

[0659] The server works with the transport company's reservation system to reserve a ticket. For example, the server accesses the transport company's reservation system API and sends the necessary information to reserve a ticket.

[0660] 6. Real-time updates

[0661] The server continuously monitors the status of public transport and disaster information, periodically checking the API endpoint to obtain new information.

[0662] Each time the information is updated, the server calculates the optimal alternative route as needed and notifies the device. For example, if the Shinkansen from Tokyo Station to Shin-Osaka Station is delayed, a notification will be sent offering an alternative route that combines buses and trains.

[0663] Prompt Sentence Examples

[0664] The following are some examples of prompts that can be input to a generative AI model:

[0665] "Calculate the optimal route if your current location is Tokyo Station, your destination is Shin-Osaka Station, and your departure time is 8:00."

[0666] "Please suggest the best way to get from Tokyo Station to Shin-Osaka Station in the event of a disaster."

[0667] "Please make a reservation for departure: Tokyo Station, destination: Shin-Osaka Station, departure time: 08:00."

[0668] This allows for optimal route and reservation suggestions based on real-time information.

[0669] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0670] Step 1:

[0671] The user inputs his / her current location, destination, and departure time into the user terminal.

[0672] Input: A user opens the app on their smartphone, enters "Tokyo Station," "Shin-Osaka Station," and "08:00," and taps the send button.

[0673] Output: The input data (current location, destination, departure time) is generated in JSON format.

[0674] Specific behavior: When you enter data into the input form and tap the submit button, the data is converted to JSON format within the app.

[0675] Step 2:

[0676] The terminal transmits the input information to the server.

[0677] Input: The JSON formatted data generated in step 1.

[0678] Output: Data sent to the server via an HTTP POST request.

[0679] Specific operation: The communication module in the device sends JSON formatted data as an HTTP POST request to the server's API endpoint.

[0680] Step 3:

[0681] The server acquires real-time operational status data of transportation facilities.

[0682] Input: API request (a request for transit status data).

[0683] Output: Response from the API (real-time transport status data).

[0684] Specific operation: The server sends a request to each transportation company's API and receives real-time operation status data. After receiving the data, it is analyzed.

[0685] Step 4:

[0686] The server collects disaster information from the Japan Meteorological Agency and disaster prevention agencies.

[0687] Input: API request (request for disaster information).

[0688] Output: Response from the API (disaster information data).

[0689] Specific operation: The server sends requests to the APIs of the Japan Meteorological Agency and disaster response organizations to receive real-time disaster information. After receiving the data, it is analyzed.

[0690] Step 5:

[0691] The optimal route is calculated based on the operation status data and disaster information collected by the server.

[0692] Input: Real-time transportation status data and disaster information.

[0693] Output: Optimal route data.

[0694] Specific operation: The server uses Dijkstra's algorithm and generative AI models to calculate the optimal route based on real-time data. The calculation results are then generated as specific route information.

[0695] Step 6:

[0696] The server sends the calculation results to the terminal.

[0697] Input: Optimal route data.

[0698] Output: Data is sent to the user's device via an HTTP response.

[0699] Specific operation: The calculation result is converted to JSON format and sent to the terminal as an HTTP response.

[0700] Step 7:

[0701] The terminal presents the calculation results to the user.

[0702] Input: Optimal route data sent from the server.

[0703] Output: Route information displayed on the user interface.

[0704] Specific operation: The received data is analyzed and displayed on the screen as the route, travel time, fare, etc. For example, it may display "From Tokyo Station to Shin-Osaka Station by Shinkansen, travel time is 2 hours and 30 minutes, fare is 13,500 yen."

[0705] Step 8:

[0706] The user selects a route from the options presented.

[0707] Input: The user taps the desired route from the options on the screen.

[0708] Output: Selected route information.

[0709] Specific behavior: The user taps on the desired route from the presented route options, and that information is selected.

[0710] Step 9:

[0711] The terminal transmits the selected route information to the server.

[0712] Input: Selected route information.

[0713] Output: Data sent to the server via an HTTP POST request.

[0714] Specific behavior: The selected information is converted to JSON format and sent to the server as an HTTP POST request.

[0715] Step 10:

[0716] The server connects with the transportation reservation system to reserve tickets.

[0717] Input: Selected route information and user information.

[0718] Output: Successful reservation information in the transport reservation system.

[0719] Specific operation: The server accesses the transport reservation system API, sends the necessary information and makes a ticket reservation.

[0720] Step 11:

[0721] The server continuously monitors transportation status and disaster information.

[0722] Input: A timer event that causes the server to periodically check the API endpoint.

[0723] Output: Updated operational status data and disaster information.

[0724] Specific operation: The server periodically accesses each API to obtain new information.

[0725] Step 12:

[0726] Each time the information is updated, the server calculates the optimal alternative route if necessary and notifies the terminal.

[0727] Input: Updated operational status data and disaster information.

[0728] Output: New best alternative route data and notification.

[0729] Specific operation: The server recalculates the route based on the newly acquired data, calculates the optimal alternative route, and notifies the user. For example, if the Shinkansen from Tokyo Station to Shin-Osaka Station is delayed, a notification will be sent offering a route that combines buses and trains.

[0730] (Application example 1)

[0731] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0732] Conventional autonomous vehicle route guidance systems have difficulty calculating routes that fully take into account real-time transportation status and disaster information, and there is no guarantee that users will arrive at their destination safely. Another issue is that autonomous vehicles cannot propose appropriate alternative routes in emergencies. Furthermore, they lack a reservation agent function to improve user convenience, forcing users to go through complicated procedures.

[0733] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0734] In this invention, the server includes means for inputting the user's current location, destination, and departure time, means for acquiring real-time transportation operation status data, means for collecting disaster information, means for calculating an optimal route reflecting the current operation status and disaster information, means for presenting the calculation results to the user, means for making necessary reservations on behalf of the user based on their selection, means for continuously monitoring operation status and disaster information, means for calculating an optimal alternative route when the situation changes and notifying the user, means installed in the autonomous vehicle for updating the vehicle's control system with route information, and means for suggesting alternative routes and stops for emergencies. This allows the user to receive optimal route guidance in real time, allowing for quick response in emergencies, and the reservation proxy function eliminates the need for complicated procedures.

[0735] "User's current location" refers to the location where a person using the system is currently located.

[0736] "Destination" refers to the final destination that the user is aiming for.

[0737] "Departure time" refers to the time set by the user as the planned departure time.

[0738] "Real-time transport status data" refers to up-to-date information about the current operating status of public transport such as buses, trains and planes.

[0739] "Disaster information" refers to information about natural disasters such as earthquakes, typhoons, and heavy rain provided by the Japan Meteorological Agency and other organizations.

[0740] "Optimal route" refers to the travel route that allows a user to reach their destination most efficiently and safely.

[0741] "Calculation results" refers to information on the optimal route or alternative route calculated by the system.

[0742] "Means of obtaining reservations on behalf of users" refers to a function that automatically obtains the necessary tickets and reservations through the transportation reservation system based on user operations.

[0743] "Means for continuously monitoring operation status and disaster information" refers to the system's ability to continuously monitor the operation status of transportation services and disaster information in real time.

[0744] "Means for calculating the optimal alternative route and notifying the user" refers to a function that calculates a new optimal route and notifies the user when the originally planned route is not available.

[0745] An "autonomous vehicle" refers to a vehicle that can drive and be controlled automatically using artificial intelligence and various sensors.

[0746] "Means for reflecting in the vehicle's control system" refers to the function of inputting the calculated route information into the control device of the autonomous vehicle and applying it as the vehicle's driving route.

[0747] "Means for suggesting alternative routes and stopping points in emergencies" refers to a function that suggests alternative travel routes and stopping points so that users can evacuate safely in the event of an emergency or disaster.

[0748] This invention is a system for providing optimal route guidance to autonomous vehicles. It inputs the user's current location, destination, and departure time, and calculates the optimal route in real time, reflecting the operation status of public transport and disaster information, and even handles necessary reservations. Furthermore, in emergencies, it can propose alternative routes and reflect them in the vehicle's control system.

[0749] The system consists of a user terminal, a server, related APIs, and an autonomous vehicle control system.

[0750] Hardware and software:

[0751] Hardware: On-board computers in autonomous vehicles, smartphones, and tablets

[0752] Software: Python, API (traffic information API, disaster information API), cloud server

[0753] System behavior:

[0754] 1. User Input

[0755] The user enters their current location, destination, and departure time into their smartphone or in-car tablet.

[0756] 2. Data collection

[0757] The terminal sends this information to a server, which then obtains real-time transportation status data and disaster information from various APIs.

[0758] 3. Route calculation

[0759] The server uses the acquired data to calculate the optimal route for the user, using algorithms such as generative AI models.

[0760] 4. Presentation of results

[0761] The server sends the calculation results to the terminal, which then presents them to the user, including route information, travel time, and fare information.

[0762] 5. Reservations and proxy acquisition

[0763] Once the user selects a route from the options presented, the terminal sends this information to the server, which then works with the transport company's reservation system to reserve a ticket on their behalf.

[0764] 6. Real-time updates

[0765] The server continuously monitors operational status and disaster information, calculates optimal alternative routes as needed, notifies users, and reflects the results in the vehicle's control system to support safe operation.

[0766] 7. Emergency Response

[0767] In an emergency, the server calculates alternative routes and stops and suggests them to the user via the terminal. For example, if Shinkansen service is suspended, the server will notify the user of alternative bus routes and nearby safe stops.

[0768] Examples:

[0769] For example, if a user wants to travel from Tokyo Station to Shin-Osaka Station, they can input their data and receive calculated Shinkansen route information (travel time, fare). If the Shinkansen is delayed, the system will suggest an alternative route that combines buses and trains, and will also make reservations for that route on their behalf.

[0770] Example prompt sentence:

[0771] "I'd like to travel from Tokyo Station to Shin-Osaka Station. My departure time is 8:00 AM. Please tell me the best route and an alternative route, taking into account the current traffic conditions and disaster information."

[0772] This system allows users to efficiently select the most suitable means of transportation and reach their destination safely and comfortably.

[0773] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0774] Step 1:

[0775] User input:

[0776] The user inputs their current location, destination, and departure time into their smartphone or in-car tablet. This input data becomes the initial input data for the system.

[0777] Step 2:

[0778] Sending data:

[0779] The device sends the current location, destination, and departure time data acquired from the user to the server, which then prepares the server for the next step of data collection.

[0780] Step 3:

[0781] Transportation data collection:

[0782] The server obtains real-time operational status data for transportation services. The latest operational information for each transportation service is collected via API and stored in a database. This data is used when calculating routes.

[0783] Step 4:

[0784] Disaster information collection:

[0785] The server acquires disaster information. It collects the latest disaster information from disaster information APIs such as those provided by the Japan Meteorological Agency and stores it in a database. This data affects route calculations.

[0786] Step 5:

[0787] Route calculation:

[0788] The server calculates the optimal route based on traffic status data and disaster information collected. Using generative AI models and route optimization algorithms, it determines the safest and most efficient route for users to reach their destination. This calculation takes into account the user's current location, destination, and departure time.

[0789] Step 6:

[0790] Presenting the results:

[0791] The server sends the calculation results to the terminal, which then presents them to the user. The calculation results include the optimal route, travel time, fare, etc., allowing the user to confirm the proposed route.

[0792] Step 7:

[0793] Booking and Acquisition:

[0794] When the user selects a route from the options presented, the device sends that information to the server. The server then works with the transportation company's reservation system to automatically obtain the necessary reservations on the user's behalf. Once the reservation is complete, the information is sent to the user's device.

[0795] Step 8:

[0796] Real-time updates:

[0797] The server continuously monitors transportation status and disaster information. If new information is confirmed, the server recalculates the optimal alternative route and sends the results to the device, ensuring that users always receive the latest route information.

[0798] Step 9:

[0799] Route information reflection:

[0800] The server then updates the autonomous vehicle's control system with the latest route information, allowing the autonomous vehicle to travel along the optimal route.

[0801] Step 10:

[0802] Emergency Response:

[0803] In the event of an emergency, the server calculates alternative routes and stops and suggests them to the user via their device, allowing the user to travel safely even in an emergency.

[0804] In this way, the system collects and processes data based on user input, providing optimal routes and alternative routes to help ensure efficient and safe travel.

[0805] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0806] This invention relates to a transportation route guidance system for use in emergencies that has been further improved by combining it with an emotion engine that recognizes the user's emotions. This system inputs the user's current location, destination, and departure time, and calculates and presents the optimal route based on real-time transportation conditions and disaster information, and makes reservations on behalf of the user if necessary. It also provides a more personalized service by recognizing the user's emotional state and suggesting optimal notification methods and routes based on that information.

[0807] System configuration

[0808] This system mainly consists of a user device, a server, an emotion engine, and a data acquisition API. The user device is a mobile device such as a smartphone or tablet, and the server is located on the cloud. The emotion engine is integrated into the device and recognizes emotions from the user's facial expressions, voice, text, etc. The data acquisition API provides transportation and weather information.

[0809] Program processing

[0810] 1. Accepting user input

[0811] The user inputs his / her current location, destination, and departure time into the user terminal.

[0812] For example, enter "Current location: Tokyo Station, Destination: Shin-Osaka Station, Departure time: 08:00".

[0813] 2. Data collection

[0814] The terminal transmits the input information to the server.

[0815] The server obtains real-time operation status data for transportation services from each transportation service's API.

[0816] The server also collects disaster information from the Japan Meteorological Agency and other sources.

[0817] 3. Emotional Recognition

[0818] The emotion engine recognizes the user's emotions, for example, by using facial recognition and voice analysis technology to determine whether the user is feeling stressed.

[0819] 4. Route calculation

[0820] The server calculates the optimal route based on the traffic status, disaster information, and user emotional information collected.

[0821] For example, if the Shinkansen train operation status is normal and the user is not feeling stressed, the route "from Tokyo to Shin-Osaka by Shinkansen" is suggested.

[0822] 5. Presentation of results

[0823] The server sends the calculation results to the terminal.

[0824] The terminal presents the calculation results to the user, including the route, travel time, and fare.

[0825] For example, it might say, "Take the Shinkansen from Tokyo Station to Shin-Osaka Station, travel time: 2 hours 30 minutes, fare: 13,500 yen."

[0826] 6. Selection and Reservation

[0827] The user selects a route from the options presented.

[0828] The terminal transmits the selected route information to the server.

[0829] The server connects with the transportation reservation system to reserve tickets.

[0830] For example, it can be linked to a Shinkansen reservation system to reserve tickets for a specified flight.

[0831] 7. Real-time updates

[0832] The server continuously monitors transportation operation status and disaster information.

[0833] Each time the information is updated, the server calculates the optimal alternative route if necessary and notifies the terminal.

[0834] For example, the notification could say, "The Shinkansen is delayed. We recommend using a combination of bus and train as an alternative route."

[0835] 8. Emotion-Based Regulation

[0836] The device adjusts the calculation results and notification method according to the user's emotions.

[0837] For example, if a user is feeling stressed, a notification that provides a sense of relief such as, "The Shinkansen is delayed, but we have found an alternative route that provides a comfortable space" can be displayed.

[0838] In this way, a system integrating an emotion engine allows users to reach their destination efficiently via the optimal route even in the event of a disaster, and complete their journey with a sense of security.

[0839] The processing flow will be explained below.

[0840] Step 1:

[0841] The user inputs his / her current location, destination, and departure time into the terminal.

[0842] Example: Enter "Current location: Tokyo Station, Destination: Shin-Osaka Station, Departure time: 08:00".

[0843] Step 2:

[0844] The terminal transmits the input information to the server.

[0845] Send data in the form of an API request.

[0846] Step 3:

[0847] The server obtains real-time operation status data for transportation services from each transportation service's API.

[0848] Example: Obtaining Shinkansen train operation status from a railway company's API.

[0849] Step 4:

[0850] The server collects disaster information from disaster information providers such as the Japan Meteorological Agency.

[0851] Example: Obtaining information about typhoons, earthquakes, and floods.

[0852] Step 5:

[0853] The terminal uses an emotion engine to recognize the user's emotion.

[0854] Example: Analyzing the user's facial expressions through the front camera to recognize stress levels.

[0855] Step 6:

[0856] The server calculates the optimal route based on the operation status, disaster information, and user emotional information collected.

[0857] Example: If the Shinkansen is running normally and the user is feeling stressed, suggest a route such as "Take the Shinkansen from Tokyo to Shin-Osaka," while also considering options that provide a comfortable space.

[0858] Step 7:

[0859] The server sends the calculation results to the terminal.

[0860] The obtained route information, travel time, fare, etc. are sent in JSON format.

[0861] Step 8:

[0862] The terminal presents the calculation results to the user.

[0863] Example: "Take the Shinkansen from Tokyo Station to Shin-Osaka Station, travel time: 2 hours 30 minutes, fare: 13,500 yen."

[0864] Step 9:

[0865] The user selects the best route from the options presented.

[0866] Example: Tap or click to select the best option from multiple options presented.

[0867] Step 10:

[0868] The terminal transmits the user's selection information to the server.

[0869] The selected route information is sent in the form of an API request.

[0870] Step 11:

[0871] The server connects with the transport company's reservation system to reserve tickets.

[0872] Example: Call the Shinkansen reservation system API to reserve a ticket for a specified flight.

[0873] Step 12:

[0874] The server continuously monitors transportation operation status and disaster information.

[0875] Continue to obtain real-time data on a regular basis.

[0876] Step 13:

[0877] When the situation changes, the server calculates the optimal alternative route and notifies the device.

[0878] Example: "The Shinkansen is delayed. We recommend using a combination of bus and train as an alternative route."

[0879] Step 14:

[0880] The terminal presents the user with new information and prompts them to make another selection.

[0881] Example: "Take the bus from Tokyo Station to Shinagawa Station, then take the local train to Shin-Osaka Station."

[0882] Step 15:

[0883] The device uses an emotion engine to adjust the notification method and content based on the user's emotions.

[0884] Example: If a user is feeling stressed, provide a reassuring notification such as, "The Shinkansen is delayed, but we have found an alternative route that provides a comfortable space."

[0885] In this way, users can reach their destination efficiently even in the event of a disaster, and the emotion engine allows them to complete their journey with an added sense of security.

[0886] Example 2

[0887] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0888] Conventional transportation route guidance systems do not take into account the user's psychological state, which often leaves users feeling anxious, especially during disasters. Furthermore, whenever the transportation status or disaster information changes, the recalculation and notification of optimal routes can be delayed, making it difficult for users to travel quickly and safely. Furthermore, the transportation reservation process is complicated, placing a burden on users in many situations.

[0889] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0890] In this invention, the server includes means for inputting the user's current location, destination, and departure time, means for acquiring real-time transportation operation status data, means for collecting disaster information, means for recognizing the user's emotions, means for calculating an optimal route reflecting the current operation status, disaster information, and the user's emotional information, means for presenting the calculation results to the user, means for making necessary reservations on behalf of the user based on their selection, means for continuously monitoring the operation status and disaster information, and means for calculating an optimal alternative route and notifying the user when the situation changes. This allows the user to receive optimal route guidance based on the latest information in real time, and by providing personalized notifications and guidance according to the user's emotional state, the server can travel with peace of mind.

[0891] "Current location of user" refers to geographical location information where the user is currently physically located.

[0892] A "destination" is the final geographic location that a user wishes to reach.

[0893] "Departure time" is information indicating the date and time when the user plans to start traveling.

[0894] "Real-time transportation status data" is the latest information on how transportation such as trains, buses, and planes are currently operating.

[0895] "Disaster information" refers to information about natural disasters and other emergencies that may affect users' travel.

[0896] "User's emotions" is information that indicates the user's psychological state and emotions, and includes states such as stress, relief, and excitement.

[0897] The "means for calculating the optimal route" refers to an algorithm or system that calculates the most efficient and safe travel route for the user based on collected information.

[0898] The "means for presenting the calculation results to the user" refers to a method or technology for displaying the results of the route calculation in a format that is easy for the user to view.

[0899] A "means for obtaining reservations on behalf of a user" is a system or process for automatically making reservations for transportation or other means selected by the user.

[0900] "Means for continuously monitoring operation status and disaster information" refers to technologies and methods for constantly monitoring the operation status of transportation and disaster information, and collecting the latest information.

[0901] "Means for calculating the optimal alternative route and notifying the user" refers to a system or method for recalculating the optimal route when the situation changes and notifying the user of the result.

[0902] MODE FOR CARRYING OUT THE INVENTION

[0903] The present invention relates to a traffic route guidance system for use in emergencies that has been further improved by combining it with an emotion engine that recognizes the user's emotions. This system aims to not only enable users to receive optimal route guidance based on the latest information in real time, but also to provide personalized notifications and suggestions according to the user's psychological state. Specific embodiments for implementing this invention are described below.

[0904] Hardware and software configuration

[0905] This system mainly consists of a user device, a server, an emotion engine, and a data acquisition API. The user device is a mobile device such as a smartphone or tablet, and the server is located on the cloud. The emotion engine is integrated into the device and recognizes emotions by analyzing the user's facial expressions, voice, text, etc. The data acquisition API is used to provide transportation and weather information.

[0906] Specifically, OpenCV is used for facial recognition, Google Cloud Speech-to-Text for voice analysis, and the APIs of transportation agencies (e.g., JR East's API) are used to obtain transportation data. Weather information is obtained from the API of the Japan Meteorological Agency.

[0907] Example of operation

[0908] The following describes an example in which the user inputs "current location: Shibuya Station, destination: Nagoya Station, departure time: 10:00".

[0909] 1. Accepting user input: The user starts the smartphone app and enters their current location, destination, and departure time. For example, they enter "Current location: Shibuya Station, Destination: Nagoya Station, Departure time: 10:00" and press the "Send" button.

[0910] 2. Data collection: The device sends the entered information to the server. The server uses APIs to obtain real-time traffic and disaster information, allowing users to check the operating status of bullet trains, buses, airplanes, and other services.

[0911] 3. Emotion Recognition: The emotion engine analyzes the user's facial expressions and voice to determine their emotional state, for example, whether they are stressed or calm.

[0912] 4. Route calculation: The server calculates the optimal route based on the collected data and emotion information. If there are no Shinkansen delays, it will suggest traveling by Shinkansen as usual, but if there are delays, it will consider alternative routes.

[0913] 5. Displaying the results: The server sends the calculation results to the terminal and displays them to the user. For example, it displays "From Shibuya Station to Nagoya Station by Shinkansen, travel time: 2 hours, fare: 10,000 yen."

[0914] 6. Selection and reservation: The user selects a route from the presented options. The selected route information is sent to the server, which then connects with the transportation reservation system to reserve a ticket. For example, it connects with the Shinkansen reservation system to reserve a ticket for the specified flight.

[0915] 7. Real-time updates: The server continuously monitors the status of public transport and disaster information, and when the situation changes, it recalculates the optimal route and notifies the user. For example, if the Shinkansen is delayed, the server will notify the user, "The Shinkansen is delayed. We recommend using a combination of bus and train as an alternative route."

[0916] 8. Emotion-based adjustment: The device adjusts the notification method according to the user's emotions. For example, if the user is feeling stressed, the device will send a reassuring notification such as, "We have found an alternative route that provides a comfortable space."

[0917] Prompt Sentence Examples

[0918] Here are some examples of prompts for generative AI models:

[0919] "If the current location is Shibuya Station and the destination is Nagoya Station, please tell me the optimal transportation route departing at 10:00. Please also take into consideration local public transportation APIs and real-time disaster information. Please also provide guidance that includes notification methods that will reassure the user even if they are feeling stressed."

[0920] In this way, a system that integrates an emotion engine will suggest optimal routes for users even in the event of a disaster, enabling them to reach their destination safely.

[0921] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0922] Step 1: Accepting User Input

[0923] The user launches the smartphone app and enters their current location, destination, and departure time. For example, they enter "Current location: Shibuya Station, Destination: Nagoya Station, Departure time: 10:00." Once the entry is complete, the device temporarily stores this information internally.

[0924] Input: current location, destination, departure time

[0925] Output: User input information stored in the device

[0926] Specific operation: When a user enters information and taps the "Send" button, the data is saved in temporary storage on the device.

[0927] Step 2: Collect data

[0928] The device sends the temporarily saved user-entered information to the server, which then uses an HTTP request to obtain real-time operation status data from the transport company's API and disaster information from the Japan Meteorological Agency's API.

[0929] Input: User-entered information

[0930] Output: Transportation status data, disaster information data

[0931] Specific operation: The device sends a request to the server, which then calls the API of each transportation company to obtain operation status and collects disaster information from the API of the Japan Meteorological Agency.

[0932] Step 3: Recognize emotions

[0933] The device's integrated emotion engine uses the camera and microphone to analyze the user's current emotional state, including facial expression recognition with OpenCV and voice analysis with Google Cloud Speech-to-Text.

[0934] Input: Camera video, audio data

[0935] Output: User's emotional information (stress, relief, etc.)

[0936] Specific operation: While the user is looking at the smartphone, the camera captures facial expressions, the microphone records the user's voice, and the emotion engine analyzes this data.

[0937] Step 4: Calculate the route

[0938] The server runs an algorithm that combines transportation status data, disaster information data, and user emotion information to calculate the optimal route.

[0939] Input: Operation status data, disaster information data, emotion information

[0940] Output: Optimal route information

[0941] How it works: The server integrates this data and the algorithm calculates the optimal travel route. For example, if the traffic conditions are normal and the user is not feeling stressed, the route using the Shinkansen will be selected.

[0942] Step 5: Presenting the results

[0943] The server sends the calculation results to the terminal, which then presents the results to the user, including route information, travel time, and fare information.

[0944] Input: Optimal route information

[0945] Output: Route information presented to the user (e.g., on-screen display)

[0946] Specific operation: Based on the data sent from the server, the terminal displays information such as "From Shibuya Station to Nagoya Station by Shinkansen, travel time: 2 hours, fare: 10,000 yen."

[0947] Step 6: Select and reserve

[0948] The user selects a route from the options presented, and the terminal sends the selected information to the server, which then connects with the transport company's reservation system to reserve a ticket.

[0949] Input: User-selected information

[0950] Output: Reservation completion notification

[0951] Specific operation: Based on the route information selected by the user, the server accesses the transportation reservation system and reserves a ticket for the specified flight.

[0952] Step 7: Real-time updates

[0953] The server continuously monitors transportation operation status and disaster information, and when the information is updated, it recalculates the optimal alternative route and notifies the device.

[0954] Input: Latest traffic status data and disaster information

[0955] Output: Updated route information

[0956] Specific operation: The server detects changes in train operation status and disaster information, and sends newly calculated route information to the terminal, notifying it, for example, "The Shinkansen is delayed. We recommend using a combination of bus and train as an alternative route."

[0957] Step 8: Emotional Adjustment

[0958] The device adjusts the calculation results and notification method based on the user's latest emotional information. For example, if it determines that the user is feeling stressed, it will send a notification that gives a sense of relief.

[0959] Input: Latest emotional information

[0960] Output: Personalized notification content

[0961] Specific operation: The device analyzes emotional information, and if the user is feeling stressed, it displays the message "We have found an alternative route that provides a comfortable space," giving the user a sense of security.

[0962] This series of processes enables users to reach their destination quickly and safely via the optimal route even in the event of a disaster.

[0963] (Application example 2)

[0964] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0965] Conventional traffic route guidance systems have the problem of being unable to adequately respond to complex situations and rapid route changes that arise during disasters. Furthermore, because they do not take into account the user's emotional state, they have difficulty responding to situations that are likely to cause stress or anxiety. Furthermore, there is a need for efficient route guidance when using autonomous vehicles.

[0966] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for inputting the user's current location, destination, and departure time, means for acquiring real-time operation status data of public transportation, means for collecting disaster information, means for calculating an optimal route reflecting the current operation status and disaster information, means for presenting the calculation results to the user, means for making necessary reservations on behalf of the user based on their selection, means for continuously monitoring operation status and disaster information, means for calculating an optimal alternative route when the situation changes and notifying the user, means for recognizing the user's emotions and adjusting the notification method and route suggestions based on the emotions, and means for providing route guidance and moving in cooperation with an autonomous vehicle. This makes it possible to provide the user with the optimal route even during a disaster and provide personalized services according to the user's emotional state.

[0967] "User" refers to any individual or organization that uses this system.

[0968] "Current location" indicates the location information of the user's current location.

[0969] The "destination" indicates the location the user is heading for.

[0970] "Departure time" indicates the time when the user starts traveling.

[0971] "Transportation" means any public or private means of transportation used by a User.

[0972] "Real-time operation status data" refers to data that indicates the current operation status of transportation facilities.

[0973] "Disaster information" refers to information about natural disasters such as earthquakes, typhoons, and fires, as well as sudden accidents.

[0974] An "optimal route" refers to the most efficient, safe, and quickest route from the user's current location to their destination.

[0975] "Route calculation" refers to the process of calculating the optimal route based on input data.

[0976] "Presenting" refers to the act of visually or audibly conveying the results of a calculation to a user.

[0977] "Reservation proxy acquisition" refers to the act of carrying out the necessary reservation procedures on behalf of the user.

[0978] "Monitoring" refers to the act of continuously watching traffic conditions and disaster information.

[0979] "Alternate Route" refers to a suggested alternative route if the planned route is unavailable.

[0980] "Emotion recognition" refers to the technology of determining a user's emotions from their facial expressions, voice, and text.

[0981] "Notification method" refers to the means by which information is conveyed to the user.

[0982] "Route suggestion" refers to the act of recommending the optimal travel route to the user.

[0983] An "autonomous vehicle" refers to a vehicle that can drive autonomously without human operation.

[0984] "Collaboration" refers to multiple systems and devices sharing information and working together.

[0985] This invention relates to a system for an autonomous vehicle that recognizes the user's emotions and provides optimal route guidance in the event of a disaster. Specific embodiments of this system will be described below.

[0986] Hardware Configuration

[0987] A user device (e.g., a smartphone) has the following capabilities:

[0988] Emotion recognition using a camera and microphone

[0989] Obtaining location information using GPS

[0990] Internet connection

[0991] Autonomous vehicles will have the following capabilities:

[0992] Route Navigation System

[0993] Internet connection

[0994] The server has the following features:

[0995] Data Processing Capacity

[0996] Cloud-based database

[0997] Various APIs (traffic information, weather information)

[0998] Software Configuration

[0999] It uses the EmotionRecognizer library for emotion recognition, the Requests library for real-time traffic and disaster information acquisition, and custom algorithms for navigation calculations.

[1000] System Operation

[1001] 1. The user enters their current location, destination, and departure time into the smartphone app. For example, they enter "Current location: Tokyo Station, Destination: Shin-Osaka Station, Departure time: 08:00."

[1002] 2. The terminal sends the entered information to the server.

[1003] 3. The server obtains real-time transportation status data and disaster information from each transportation company's API.

[1004] 4. The server recognizes the user's emotions through the smartphone's camera and microphone, using facial recognition and voice analysis technology to determine whether the user is feeling stressed.

[1005] 5. The server calculates the optimal route based on the collected traffic status and disaster information, as well as the user's emotional state. For example, if the user is feeling stressed, it will prioritize a relaxing route.

[1006] 6. The calculation results are sent to the user's device. The results include information such as the route, travel time, and fare. For example, the display might say, "From Tokyo Station to Shin-Osaka Station by Shinkansen, travel time: 2 hours 30 minutes, fare: 13,500 yen."

[1007] 7. The user selects a route from the presented options and sends the selection to the terminal.

[1008] 8. The server connects the selected route information to the transportation reservation system and reserves tickets if necessary.

[1009] 9. The server continuously monitors transportation status and disaster information, and whenever the information is updated, calculates the optimal alternative route as needed and notifies the device.

[1010] 10. The device adjusts the calculation results and notification method according to the user's emotions. For example, if the user is feeling stressed, the device will send a notification that provides a sense of relief, such as, "The Shinkansen is delayed, but we have found an alternative route that provides a comfortable space."

[1011] Examples of specific examples and prompts

[1012] As a specific example, if a Shinkansen train is delayed, the server can notify the terminal, "This Shinkansen train is currently delayed by 30 minutes. As an alternative route, we suggest a combination of bus and train, which is equally comfortable."

[1013] Example prompt sentence:

[1014] "Analyze the user's facial expressions to determine their stress level."

[1015] "Use current traffic and disaster information to calculate the best route from your origin to your destination."

[1016] This enables the system to support efficient and safe travel along optimal routes even in the event of a disaster.

[1017] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1018] Step 1:

[1019] A user inputs their current location, destination, and departure time into a smartphone app. This input data includes "Current location: Tokyo Station," "Destination: Shin-Osaka Station," and "Departure time: 08:00."

[1020] Step 2:

[1021] The terminal sends the entered information to the server. In this process, the entered data of current location, destination, and departure time is transferred to the server as is.

[1022] Step 3:

[1023] The server obtains real-time transportation status data and disaster information from each transportation agency's API. The data processing performed in this step involves analyzing the data obtained from the API and converting it into a specific format. The analyzed transportation data and disaster information are generated as output.

[1024] Step 4:

[1025] To recognize the user's emotions, the device acquires data from the camera or microphone and performs emotion analysis using the EmotionRecognizer library. In this step, raw data from the camera or microphone is input, and the user's emotional state (e.g., stress level) is output as an analysis result.

[1026] Step 5:

[1027] The server calculates the optimal route based on the collected traffic conditions, disaster information, and user sentiment information. This step also references map information and past traffic data stored in the database. The output is route guidance information that includes specific means of transportation and their details.

[1028] Step 6:

[1029] The server sends the calculation results to the terminal, and the terminal displays them to the user. The information displayed includes the route, travel time, fare, etc. For example, it displays "From Tokyo Station to Shin-Osaka Station by Shinkansen, travel time: 2 hours 30 minutes, fare: 13,500 yen."

[1030] Step 7:

[1031] The user selects a route from the presented options and transmits the selection to the terminal. The data operations performed in this step are recording and confirming the selection. The output is the route selected by the user.

[1032] Step 8:

[1033] The server connects the selected route information to the transport company's reservation system and reserves tickets if necessary. In this step, the server sends the necessary information to the ticket reservation API and receives a reservation confirmation. The output is a confirmation that the reservation has been completed.

[1034] Step 9:

[1035] The server continuously monitors the status of public transport and disaster information. Each time the information is updated, the server analyzes the new data and calculates an alternative route if there is an abnormality in the service status. The output is new route guidance information in the event of an abnormality.

[1036] Step 10:

[1037] The device adjusts the calculation results and notification method according to the user's emotions. For example, if the user is feeling stressed, the device will send a notification that provides a sense of relief, such as "The Shinkansen is delayed, but we have found an alternative route that provides a comfortable space." The output is a notification message that corresponds to the user's emotions.

[1038] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1039] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1040] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1041] [Third embodiment]

[1042] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1043] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1044] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1045] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[1046] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1047] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1048] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1049] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1050] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1051] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1052] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1053] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[1054] The present invention relates to a system that inputs a user's current location, destination, and departure time, calculates the optimal route even in the event of a disaster, and even makes reservations on their behalf. This system can quickly respond to information about the operation status of public transportation and disaster information, and efficiently guide users to their destinations. Detailed embodiments of the system are described below.

[1055] System configuration

[1056] This system mainly consists of a user device, a server, and related APIs. The user device is a mobile device such as a smartphone or tablet, and the server is located on the cloud. It also works in conjunction with APIs that provide information on various transportation services and weather information.

[1057] Program processing

[1058] 1. Accepting user input

[1059] The user inputs his / her current location, destination, and departure time into the user terminal.

[1060] As a specific example, the user inputs "Tokyo Station", "Shin-Osaka Station", and "08:00".

[1061] 2. Data collection

[1062] The terminal transmits the input information to the server.

[1063] The server obtains real-time operation status data for transportation services from each transportation service's API.

[1064] The server also collects disaster information from the Japan Meteorological Agency and other sources.

[1065] 3. Route calculation

[1066] The optimal route is calculated based on the operation status and disaster information collected by the server.

[1067] As a specific example, if the Shinkansen train operation status is normal, the route "travel from Tokyo Station to Shin-Osaka Station by Shinkansen" is suggested.

[1068] 4. Presentation of results

[1069] The server sends the calculation results to the terminal.

[1070] The terminal presents the calculation results to the user, including the route, travel time, and fare.

[1071] As a concrete example, it states, "The Shinkansen from Tokyo Station to Shin-Osaka Station takes 2 hours and 30 minutes and costs 13,500 yen."

[1072] 5. Selection and Booking

[1073] The user selects a route from the options presented.

[1074] The terminal transmits the selected route information to the server.

[1075] The server connects with the transportation reservation system to reserve tickets.

[1076] 6. Real-time updates

[1077] The server continuously monitors transportation operation status and disaster information.

[1078] Each time the information is updated, the server calculates the optimal alternative route if necessary and notifies the terminal.

[1079] As a concrete example, if the Shinkansen from Tokyo Station to Shin-Osaka Station is delayed, the server will offer an alternative means of transportation (for example, a combination of bus and train).

[1080] The system allows users to reach their destinations efficiently even in times of disaster, and uses past data to predict future travel conditions, supporting more accurate and adaptive travel.

[1081] The processing flow will be explained below.

[1082] Step 1:

[1083] The user inputs his / her current location, destination, and departure time into the terminal.

[1084] Example: Enter "Current location: Tokyo Station, Destination: Shin-Osaka Station, Departure time: 08:00".

[1085] Step 2:

[1086] The terminal transmits the input information to the server.

[1087] Send data to the server in the form of an API request.

[1088] Step 3:

[1089] The server acquires real-time operational status data of transportation facilities.

[1090] Data is collected by calling the real-time operation status API of each transportation company.

[1091] Example: Obtaining Shinkansen train operation status from a railway company's API.

[1092] Step 4:

[1093] The server collects disaster information.

[1094] It calls the APIs of the Japan Meteorological Agency and disaster information services to obtain information on typhoons, earthquakes, floods, etc.

[1095] Step 5:

[1096] The server calculates the optimal route based on current traffic conditions and disaster information.

[1097] It uses an algorithm to generate the optimal route from the user's current location to their destination.

[1098] Example: If the Shinkansen is operating normally, select the route "Take the Shinkansen from Tokyo to Shin-Osaka."

[1099] Step 6:

[1100] The server sends the calculation results to the terminal.

[1101] Information such as the optimal route, travel time, and fare is sent to the terminal in JSON format.

[1102] Step 7:

[1103] The terminal presents the calculation results to the user.

[1104] Specific means of transportation, departure time, travel time, fare, etc. are displayed on the screen.

[1105] Example: "From Tokyo Station to Shin-Osaka Station by Shinkansen, travel time: 2 hours 30 minutes, fare: 13,500 yen."

[1106] Step 8:

[1107] The user selects a route from the options presented.

[1108] Tap or click to choose the best route from the multiple options presented.

[1109] Step 9:

[1110] The terminal transmits the user's selection information to the server.

[1111] The selected route information is sent to the server in the form of an API request.

[1112] Step 10:

[1113] The server connects with the reservation systems of each transportation facility to reserve tickets.

[1114] Example: Call the Shinkansen reservation system API to reserve a ticket for a specified flight.

[1115] Step 11:

[1116] The server continuously monitors transportation operation status and disaster information.

[1117] The API is called periodically to obtain the latest operational status and disaster information.

[1118] Step 12:

[1119] When the situation changes, the server calculates the optimal alternative route and notifies the device.

[1120] Calculate the new optimal route and push a notification to the user.

[1121] Example: "The Shinkansen is delayed. We recommend using a combination of bus and train as an alternative route."

[1122] Step 13:

[1123] The terminal presents the user with new information and prompts them to make another selection.

[1124] New route suggestions are displayed on the screen and the user is prompted to select one.

[1125] Example: "Take the bus from Tokyo Station to Shinagawa Station, then take the local train to Shin-Osaka Station."

[1126] This series of steps allows users to reach their destination efficiently even in the event of a disaster.

[1127] Example 1

[1128] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1129] There is a need to provide an efficient means of transportation that can respond quickly to disasters and changes in real-time transportation status, as well as calculate the optimal route for users and even make reservations on their behalf. This will reduce anxiety about delays and cancellations of transportation and enable smoother and more efficient travel.

[1130] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1131] In this invention, the server includes means for inputting the user's current location, destination, and departure time, means for transmitting input information from the user terminal to the server, means for acquiring real-time transportation operation status data, means for collecting weather and disaster information, means for calculating an optimal route reflecting current operation status and disaster information, means for transmitting the calculation results to the user terminal, means for presenting the calculation results to the user, means for making necessary reservations on behalf of the user based on their selection, means for reserving tickets in cooperation with the transportation reservation system, means for continuously monitoring operation status and disaster information, and means for calculating an optimal alternative route when information is updated and notifying the user. This enables efficient travel in the event of a disaster or when transportation delays or cancellations occur.

[1132] "Means for inputting user's current location, destination, and departure time" refers to the interface used by the user to input their current location, destination, and departure time.

[1133] "Means for transmitting input information from a user terminal to a server" refers to a communication means or protocol for transmitting information input from a user terminal to a server.

[1134] "Means for obtaining real-time transit status data" means means for accessing a transit agency's API or data source to obtain real-time transit status data.

[1135] "Means of collecting weather and disaster information" refers to means of accessing the APIs of the Japan Meteorological Agency and disaster response organizations in order to collect weather information and other emergency information during disasters.

[1136] "Means for calculating the optimal route that reflects current operational conditions and disaster information" refers to a means for calculating the optimal travel route using an algorithm, taking into account real-time operational conditions and disaster information.

[1137] "Means for transmitting the calculation results to the user terminal" refers to the communication means or protocol for transmitting the route information calculated by the server to the user terminal.

[1138] "Means for presenting calculation results to the user" refers to an interface for presenting the results displayed on the user terminal in a format that is easy for the user to understand.

[1139] "Means for obtaining the necessary reservations on behalf of the user based on their selection" refers to the procedures and protocols for making transportation reservations on behalf of the user based on the route selected by the user.

[1140] "Means for reserving tickets in cooperation with a transportation company's reservation system" refers to a means for reserving tickets by accessing a transportation company's ticket reservation system and inputting the necessary information.

[1141] "Means for continuously monitoring operation status and disaster information" refers to means for continuously monitoring the operation status of transportation facilities and disaster information in real time, and updating it whenever new information is obtained.

[1142] "Means for calculating the optimal alternative route when information is updated and notifying the user" refers to means for recalculating the optimal alternative route based on the new conditions when operation status or disaster information is updated and notifying the user.

[1143] MODE FOR CARRYING OUT THE INVENTION

[1144] This invention relates to a system that inputs a user's current location, destination, and departure time, calculates the optimal route even in the event of a disaster, and even makes reservations on their behalf. This system can quickly respond to information about the operation status of public transportation and disaster information, and efficiently guide users to their destinations.

[1145] System configuration

[1146] The system's main components are user devices, servers, and related APIs. User devices are mobile devices such as smartphones and tablets, and the servers are located in a cloud environment. The system also works in conjunction with APIs that provide information on various transportation services and weather information.

[1147] Hardware and software used

[1148] User devices: smartphones, tablets, etc.

[1149] Server: Server on a cloud environment

[1150] API: Transport API (e.g. transport information API), Japan Meteorological Agency API

[1151] Data processing and calculation

[1152] 1. Accepting user input

[1153] The user enters their current location, destination, and departure time into the user device. For example, the user opens the smartphone app, enters "Tokyo Station," "Shin-Osaka Station," and "08:00," and taps the send button.

[1154] 2. Data collection

[1155] The device sends the entered information to the server, where it is converted to JSON format and sent using an HTTPS request.

[1156] The server accesses the API of each transportation facility to obtain real-time operation status data of the transportation facility. For example, it sends a request to the transportation facility's API to obtain real-time operation information.

[1157] The server sends requests to the APIs of the Japan Meteorological Agency and disaster prevention organizations to collect real-time weather information and disaster information.

[1158] 3. Route calculation

[1159] The server calculates the optimal route based on the operational status and disaster information collected. It uses Dijkstra's algorithm and generative AI models to calculate the optimal route using real-time data as input. For example, if the Shinkansen operational status is normal, it will suggest the route "travel from Tokyo Station to Shin-Osaka Station by Shinkansen."

[1160] 4. Presentation of results

[1161] The server sends the calculation results to the terminal, where they are converted into JSON format and sent as an HTTPS response.

[1162] The terminal presents the calculation results to the user. The calculation results are displayed on the user interface, clearly indicating the route, travel time, fare, etc. For example, it may say, "From Tokyo Station to Shin-Osaka Station by Shinkansen, the travel time is 2 hours and 30 minutes, and the fare is 13,500 yen."

[1163] 5. Selection and Booking

[1164] The user selects a route from the options presented. The user taps on the desired route to select it.

[1165] The device sends the selected route information to the server, which converts the information into JSON format and sends it using an HTTPS request.

[1166] The server works with the transport company's reservation system to reserve a ticket. For example, the server accesses the transport company's reservation system API and sends the necessary information to reserve a ticket.

[1167] 6. Real-time updates

[1168] The server continuously monitors the status of public transport and disaster information, periodically checking the API endpoint to obtain new information.

[1169] Each time the information is updated, the server calculates the optimal alternative route as needed and notifies the device. For example, if the Shinkansen from Tokyo Station to Shin-Osaka Station is delayed, a notification will be sent offering an alternative route that combines buses and trains.

[1170] Prompt Sentence Examples

[1171] The following are some examples of prompts that can be input to a generative AI model:

[1172] "Calculate the optimal route if your current location is Tokyo Station, your destination is Shin-Osaka Station, and your departure time is 8:00."

[1173] "Please suggest the best way to get from Tokyo Station to Shin-Osaka Station in the event of a disaster."

[1174] "Please make a reservation for departure: Tokyo Station, destination: Shin-Osaka Station, departure time: 08:00."

[1175] This allows for optimal route and reservation suggestions based on real-time information.

[1176] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1177] Step 1:

[1178] The user inputs his / her current location, destination, and departure time into the user terminal.

[1179] Input: A user opens the app on their smartphone, enters "Tokyo Station," "Shin-Osaka Station," and "08:00," and taps the send button.

[1180] Output: The input data (current location, destination, departure time) is generated in JSON format.

[1181] Specific behavior: When you enter data into the input form and tap the submit button, the data is converted to JSON format within the app.

[1182] Step 2:

[1183] The terminal transmits the input information to the server.

[1184] Input: The JSON formatted data generated in step 1.

[1185] Output: Data sent to the server via an HTTP POST request.

[1186] Specific operation: The communication module in the device sends JSON formatted data as an HTTP POST request to the server's API endpoint.

[1187] Step 3:

[1188] The server acquires real-time operational status data of transportation facilities.

[1189] Input: API request (a request for transit status data).

[1190] Output: Response from the API (real-time transport status data).

[1191] Specific operation: The server sends a request to each transportation company's API and receives real-time operation status data. After receiving the data, it is analyzed.

[1192] Step 4:

[1193] The server collects disaster information from the Japan Meteorological Agency and disaster prevention agencies.

[1194] Input: API request (request for disaster information).

[1195] Output: Response from the API (disaster information data).

[1196] Specific operation: The server sends requests to the APIs of the Japan Meteorological Agency and disaster response organizations to receive real-time disaster information. After receiving the data, it is analyzed.

[1197] Step 5:

[1198] The optimal route is calculated based on the operation status data and disaster information collected by the server.

[1199] Input: Real-time transportation status data and disaster information.

[1200] Output: Optimal route data.

[1201] Specific operation: The server uses Dijkstra's algorithm and generative AI models to calculate the optimal route based on real-time data. The calculation results are then generated as specific route information.

[1202] Step 6:

[1203] The server sends the calculation results to the terminal.

[1204] Input: Optimal route data.

[1205] Output: Data is sent to the user's device via an HTTP response.

[1206] Specific operation: The calculation result is converted to JSON format and sent to the terminal as an HTTP response.

[1207] Step 7:

[1208] The terminal presents the calculation results to the user.

[1209] Input: Optimal route data sent from the server.

[1210] Output: Route information displayed on the user interface.

[1211] Specific operation: The received data is analyzed and displayed on the screen as the route, travel time, fare, etc. For example, it may display "From Tokyo Station to Shin-Osaka Station by Shinkansen, travel time is 2 hours and 30 minutes, fare is 13,500 yen."

[1212] Step 8:

[1213] The user selects a route from the options presented.

[1214] Input: The user taps the desired route from the options on the screen.

[1215] Output: Selected route information.

[1216] Specific behavior: The user taps on the desired route from the presented route options, and that information is selected.

[1217] Step 9:

[1218] The terminal transmits the selected route information to the server.

[1219] Input: Selected route information.

[1220] Output: Data sent to the server via an HTTP POST request.

[1221] Specific behavior: The selected information is converted to JSON format and sent to the server as an HTTP POST request.

[1222] Step 10:

[1223] The server connects with the transportation reservation system to reserve tickets.

[1224] Input: Selected route information and user information.

[1225] Output: Successful reservation information in the transport reservation system.

[1226] Specific operation: The server accesses the transport reservation system API, sends the necessary information and makes a ticket reservation.

[1227] Step 11:

[1228] The server continuously monitors transportation status and disaster information.

[1229] Input: A timer event that causes the server to periodically check the API endpoint.

[1230] Output: Updated operational status data and disaster information.

[1231] Specific operation: The server periodically accesses each API to obtain new information.

[1232] Step 12:

[1233] Each time the information is updated, the server calculates the optimal alternative route if necessary and notifies the terminal.

[1234] Input: Updated operational status data and disaster information.

[1235] Output: New best alternative route data and notification.

[1236] Specific operation: The server recalculates the route based on the newly acquired data, calculates the optimal alternative route, and notifies the user. For example, if the Shinkansen from Tokyo Station to Shin-Osaka Station is delayed, a notification will be sent offering a route that combines buses and trains.

[1237] (Application example 1)

[1238] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1239] Conventional autonomous vehicle route guidance systems have difficulty calculating routes that fully take into account real-time transportation status and disaster information, and there is no guarantee that users will arrive at their destination safely. Another issue is that autonomous vehicles cannot propose appropriate alternative routes in emergencies. Furthermore, they lack a reservation agent function to improve user convenience, forcing users to go through complicated procedures.

[1240] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1241] In this invention, the server includes means for inputting the user's current location, destination, and departure time, means for acquiring real-time transportation operation status data, means for collecting disaster information, means for calculating an optimal route reflecting the current operation status and disaster information, means for presenting the calculation results to the user, means for making necessary reservations on behalf of the user based on their selection, means for continuously monitoring operation status and disaster information, means for calculating an optimal alternative route when the situation changes and notifying the user, means installed in the autonomous vehicle for updating the vehicle's control system with route information, and means for suggesting alternative routes and stops for emergencies. This allows the user to receive optimal route guidance in real time, allowing for quick response in emergencies, and the reservation proxy function eliminates the need for complicated procedures.

[1242] "User's current location" refers to the location where a person using the system is currently located.

[1243] "Destination" refers to the final destination that the user is aiming for.

[1244] "Departure time" refers to the time set by the user as the planned departure time.

[1245] "Real-time transport status data" refers to up-to-date information about the current operating status of public transport such as buses, trains and planes.

[1246] "Disaster information" refers to information about natural disasters such as earthquakes, typhoons, and heavy rain provided by the Japan Meteorological Agency and other organizations.

[1247] "Optimal route" refers to the travel route that allows a user to reach their destination most efficiently and safely.

[1248] "Calculation results" refers to information on the optimal route or alternative route calculated by the system.

[1249] "Means of obtaining reservations on behalf of users" refers to a function that automatically obtains the necessary tickets and reservations through the transportation reservation system based on user operations.

[1250] "Means for continuously monitoring operation status and disaster information" refers to the system's ability to continuously monitor the operation status of transportation services and disaster information in real time.

[1251] "Means for calculating the optimal alternative route and notifying the user" refers to a function that calculates a new optimal route and notifies the user when the originally planned route is not available.

[1252] An "autonomous vehicle" refers to a vehicle that can drive and be controlled automatically using artificial intelligence and various sensors.

[1253] "Means for reflecting in the vehicle's control system" refers to the function of inputting the calculated route information into the control device of the autonomous vehicle and applying it as the vehicle's driving route.

[1254] "Means for suggesting alternative routes and stopping points in emergencies" refers to a function that suggests alternative travel routes and stopping points so that users can evacuate safely in the event of an emergency or disaster.

[1255] This invention is a system for providing optimal route guidance to autonomous vehicles. It inputs the user's current location, destination, and departure time, and calculates the optimal route in real time, reflecting the operation status of public transport and disaster information, and even handles necessary reservations. Furthermore, in emergencies, it can propose alternative routes and reflect them in the vehicle's control system.

[1256] The system consists of a user terminal, a server, related APIs, and an autonomous vehicle control system.

[1257] Hardware and software:

[1258] Hardware: On-board computers in autonomous vehicles, smartphones, and tablets

[1259] Software: Python, API (traffic information API, disaster information API), cloud server

[1260] System behavior:

[1261] 1. User Input

[1262] The user enters their current location, destination, and departure time into their smartphone or in-car tablet.

[1263] 2. Data collection

[1264] The terminal sends this information to a server, which then obtains real-time transportation status data and disaster information from various APIs.

[1265] 3. Route calculation

[1266] The server uses the acquired data to calculate the optimal route for the user, using algorithms such as generative AI models.

[1267] 4. Presentation of results

[1268] The server sends the calculation results to the terminal, which then presents them to the user, including route information, travel time, and fare information.

[1269] 5. Reservations and proxy acquisition

[1270] Once the user selects a route from the options presented, the terminal sends this information to the server, which then works with the transport company's reservation system to reserve a ticket on their behalf.

[1271] 6. Real-time updates

[1272] The server continuously monitors operational status and disaster information, calculates optimal alternative routes as needed, notifies users, and reflects the results in the vehicle's control system to support safe operation.

[1273] 7. Emergency Response

[1274] In an emergency, the server calculates alternative routes and stops and suggests them to the user via the terminal. For example, if Shinkansen service is suspended, the server will notify the user of alternative bus routes and nearby safe stops.

[1275] Examples:

[1276] For example, if a user wants to travel from Tokyo Station to Shin-Osaka Station, they can input their data and receive calculated Shinkansen route information (travel time, fare). If the Shinkansen is delayed, the system will suggest an alternative route that combines buses and trains, and will also make reservations for that route on their behalf.

[1277] Example prompt sentence:

[1278] "I'd like to travel from Tokyo Station to Shin-Osaka Station. My departure time is 8:00 AM. Please tell me the best route and an alternative route, taking into account the current traffic conditions and disaster information."

[1279] This system allows users to efficiently select the most suitable means of transportation and reach their destination safely and comfortably.

[1280] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1281] Step 1:

[1282] User input:

[1283] The user inputs their current location, destination, and departure time into their smartphone or in-car tablet. This input data becomes the initial input data for the system.

[1284] Step 2:

[1285] Sending data:

[1286] The device sends the current location, destination, and departure time data acquired from the user to the server, which then prepares the server for the next step of data collection.

[1287] Step 3:

[1288] Transportation data collection:

[1289] The server obtains real-time operational status data for transportation services. The latest operational information for each transportation service is collected via API and stored in a database. This data is used when calculating routes.

[1290] Step 4:

[1291] Disaster information collection:

[1292] The server acquires disaster information. It collects the latest disaster information from disaster information APIs such as those provided by the Japan Meteorological Agency and stores it in a database. This data affects route calculations.

[1293] Step 5:

[1294] Route calculation:

[1295] The server calculates the optimal route based on traffic status data and disaster information collected. Using generative AI models and route optimization algorithms, it determines the safest and most efficient route for users to reach their destination. This calculation takes into account the user's current location, destination, and departure time.

[1296] Step 6:

[1297] Presenting the results:

[1298] The server sends the calculation results to the terminal, which then presents them to the user. The calculation results include the optimal route, travel time, fare, etc., allowing the user to confirm the proposed route.

[1299] Step 7:

[1300] Booking and Acquisition:

[1301] When the user selects a route from the options presented, the device sends that information to the server. The server then works with the transportation company's reservation system to automatically obtain the necessary reservations on the user's behalf. Once the reservation is complete, the information is sent to the user's device.

[1302] Step 8:

[1303] Real-time updates:

[1304] The server continuously monitors transportation status and disaster information. If new information is confirmed, the server recalculates the optimal alternative route and sends the results to the device, ensuring that users always receive the latest route information.

[1305] Step 9:

[1306] Route information reflection:

[1307] The server then updates the autonomous vehicle's control system with the latest route information, allowing the autonomous vehicle to travel along the optimal route.

[1308] Step 10:

[1309] Emergency Response:

[1310] In the event of an emergency, the server calculates alternative routes and stops and suggests them to the user via their device, allowing the user to travel safely even in an emergency.

[1311] In this way, the system collects and processes data based on user input, providing optimal routes and alternative routes to help ensure efficient and safe travel.

[1312] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1313] This invention relates to a transportation route guidance system for use in emergencies that has been further improved by combining it with an emotion engine that recognizes the user's emotions. This system inputs the user's current location, destination, and departure time, and calculates and presents the optimal route based on real-time transportation conditions and disaster information, and makes reservations on behalf of the user if necessary. It also provides a more personalized service by recognizing the user's emotional state and suggesting optimal notification methods and routes based on that information.

[1314] System configuration

[1315] This system mainly consists of a user device, a server, an emotion engine, and a data acquisition API. The user device is a mobile device such as a smartphone or tablet, and the server is located on the cloud. The emotion engine is integrated into the device and recognizes emotions from the user's facial expressions, voice, text, etc. The data acquisition API provides transportation and weather information.

[1316] Program processing

[1317] 1. Accepting user input

[1318] The user inputs his / her current location, destination, and departure time into the user terminal.

[1319] For example, enter "Current location: Tokyo Station, Destination: Shin-Osaka Station, Departure time: 08:00".

[1320] 2. Data collection

[1321] The terminal transmits the input information to the server.

[1322] The server obtains real-time operation status data for transportation services from each transportation service's API.

[1323] The server also collects disaster information from the Japan Meteorological Agency and other sources.

[1324] 3. Emotional Recognition

[1325] The emotion engine recognizes the user's emotions, for example, by using facial recognition and voice analysis technology to determine whether the user is feeling stressed.

[1326] 4. Route calculation

[1327] The server calculates the optimal route based on the traffic status, disaster information, and user emotional information collected.

[1328] For example, if the Shinkansen train operation status is normal and the user is not feeling stressed, the route "from Tokyo to Shin-Osaka by Shinkansen" is suggested.

[1329] 5. Presentation of results

[1330] The server sends the calculation results to the terminal.

[1331] The terminal presents the calculation results to the user, including the route, travel time, and fare.

[1332] For example, it might say, "Take the Shinkansen from Tokyo Station to Shin-Osaka Station, travel time: 2 hours 30 minutes, fare: 13,500 yen."

[1333] 6. Selection and Reservation

[1334] The user selects a route from the options presented.

[1335] The terminal transmits the selected route information to the server.

[1336] The server connects with the transportation reservation system to reserve tickets.

[1337] For example, it can be linked to a Shinkansen reservation system to reserve tickets for a specified flight.

[1338] 7. Real-time updates

[1339] The server continuously monitors transportation operation status and disaster information.

[1340] Each time the information is updated, the server calculates the optimal alternative route if necessary and notifies the terminal.

[1341] For example, the notification could say, "The Shinkansen is delayed. We recommend using a combination of bus and train as an alternative route."

[1342] 8. Emotion-Based Regulation

[1343] The device adjusts the calculation results and notification method according to the user's emotions.

[1344] For example, if a user is feeling stressed, a notification that provides a sense of relief such as, "The Shinkansen is delayed, but we have found an alternative route that provides a comfortable space" can be displayed.

[1345] In this way, a system integrating an emotion engine allows users to reach their destination efficiently via the optimal route even in the event of a disaster, and complete their journey with a sense of security.

[1346] The processing flow will be explained below.

[1347] Step 1:

[1348] The user inputs his / her current location, destination, and departure time into the terminal.

[1349] Example: Enter "Current location: Tokyo Station, Destination: Shin-Osaka Station, Departure time: 08:00".

[1350] Step 2:

[1351] The terminal transmits the input information to the server.

[1352] Send data in the form of an API request.

[1353] Step 3:

[1354] The server obtains real-time operation status data for transportation services from each transportation service's API.

[1355] Example: Obtaining Shinkansen train operation status from a railway company's API.

[1356] Step 4:

[1357] The server collects disaster information from disaster information providers such as the Japan Meteorological Agency.

[1358] Example: Obtaining information about typhoons, earthquakes, and floods.

[1359] Step 5:

[1360] The terminal uses an emotion engine to recognize the user's emotion.

[1361] Example: Analyzing the user's facial expressions through the front camera to recognize stress levels.

[1362] Step 6:

[1363] The server calculates the optimal route based on the operation status, disaster information, and user emotional information collected.

[1364] Example: If the Shinkansen is running normally and the user is feeling stressed, suggest a route such as "Take the Shinkansen from Tokyo to Shin-Osaka," while also considering options that provide a comfortable space.

[1365] Step 7:

[1366] The server sends the calculation results to the terminal.

[1367] The obtained route information, travel time, fare, etc. are sent in JSON format.

[1368] Step 8:

[1369] The terminal presents the calculation results to the user.

[1370] Example: "Take the Shinkansen from Tokyo Station to Shin-Osaka Station, travel time: 2 hours 30 minutes, fare: 13,500 yen."

[1371] Step 9:

[1372] The user selects the best route from the options presented.

[1373] Example: Tap or click to select the best option from multiple options presented.

[1374] Step 10:

[1375] The terminal transmits the user's selection information to the server.

[1376] The selected route information is sent in the form of an API request.

[1377] Step 11:

[1378] The server connects with the transport company's reservation system to reserve tickets.

[1379] Example: Call the Shinkansen reservation system API to reserve a ticket for a specified flight.

[1380] Step 12:

[1381] The server continuously monitors transportation operation status and disaster information.

[1382] Continue to obtain real-time data on a regular basis.

[1383] Step 13:

[1384] When the situation changes, the server calculates the optimal alternative route and notifies the device.

[1385] Example: "The Shinkansen is delayed. We recommend using a combination of bus and train as an alternative route."

[1386] Step 14:

[1387] The terminal presents the user with new information and prompts them to make another selection.

[1388] Example: "Take the bus from Tokyo Station to Shinagawa Station, then take the local train to Shin-Osaka Station."

[1389] Step 15:

[1390] The device uses an emotion engine to adjust the notification method and content based on the user's emotions.

[1391] Example: If a user is feeling stressed, provide a reassuring notification such as, "The Shinkansen is delayed, but we have found an alternative route that provides a comfortable space."

[1392] In this way, users can reach their destination efficiently even in the event of a disaster, and the emotion engine allows them to complete their journey with an added sense of security.

[1393] Example 2

[1394] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1395] Conventional transportation route guidance systems do not take into account the user's psychological state, which often leaves users feeling anxious, especially during disasters. Furthermore, whenever the transportation status or disaster information changes, the recalculation and notification of optimal routes can be delayed, making it difficult for users to travel quickly and safely. Furthermore, the transportation reservation process is complicated, placing a burden on users in many situations.

[1396] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1397] In this invention, the server includes means for inputting the user's current location, destination, and departure time, means for acquiring real-time transportation operation status data, means for collecting disaster information, means for recognizing the user's emotions, means for calculating an optimal route reflecting the current operation status, disaster information, and the user's emotional information, means for presenting the calculation results to the user, means for making necessary reservations on behalf of the user based on their selection, means for continuously monitoring the operation status and disaster information, and means for calculating an optimal alternative route and notifying the user when the situation changes. This allows the user to receive optimal route guidance based on the latest information in real time, and by providing personalized notifications and guidance according to the user's emotional state, the server can travel with peace of mind.

[1398] "Current location of user" refers to geographical location information where the user is currently physically located.

[1399] A "destination" is the final geographic location that a user wishes to reach.

[1400] "Departure time" is information indicating the date and time when the user plans to start traveling.

[1401] "Real-time transportation status data" is the latest information on how transportation such as trains, buses, and planes are currently operating.

[1402] "Disaster information" refers to information about natural disasters and other emergencies that may affect users' travel.

[1403] "User's emotions" is information that indicates the user's psychological state and emotions, and includes states such as stress, relief, and excitement.

[1404] The "means for calculating the optimal route" refers to an algorithm or system that calculates the most efficient and safe travel route for the user based on collected information.

[1405] The "means for presenting the calculation results to the user" refers to a method or technology for displaying the results of the route calculation in a format that is easy for the user to view.

[1406] A "means for obtaining reservations on behalf of a user" is a system or process for automatically making reservations for transportation or other means selected by the user.

[1407] "Means for continuously monitoring operation status and disaster information" refers to technologies and methods for constantly monitoring the operation status of transportation and disaster information, and collecting the latest information.

[1408] "Means for calculating the optimal alternative route and notifying the user" refers to a system or method for recalculating the optimal route when the situation changes and notifying the user of the result.

[1409] MODE FOR CARRYING OUT THE INVENTION

[1410] The present invention relates to a traffic route guidance system for use in emergencies that has been further improved by combining it with an emotion engine that recognizes the user's emotions. This system aims to not only enable users to receive optimal route guidance based on the latest information in real time, but also to provide personalized notifications and suggestions according to the user's psychological state. Specific embodiments for implementing this invention are described below.

[1411] Hardware and software configuration

[1412] This system mainly consists of a user device, a server, an emotion engine, and a data acquisition API. The user device is a mobile device such as a smartphone or tablet, and the server is located on the cloud. The emotion engine is integrated into the device and recognizes emotions by analyzing the user's facial expressions, voice, text, etc. The data acquisition API is used to provide transportation and weather information.

[1413] Specifically, OpenCV is used for facial recognition, Google Cloud Speech-to-Text for voice analysis, and the APIs of transportation agencies (e.g., JR East's API) are used to obtain transportation data. Weather information is obtained from the API of the Japan Meteorological Agency.

[1414] Example of operation

[1415] The following describes an example in which the user inputs "current location: Shibuya Station, destination: Nagoya Station, departure time: 10:00".

[1416] 1. Accepting user input: The user starts the smartphone app and enters their current location, destination, and departure time. For example, they enter "Current location: Shibuya Station, Destination: Nagoya Station, Departure time: 10:00" and press the "Send" button.

[1417] 2. Data collection: The device sends the entered information to the server. The server uses APIs to obtain real-time traffic and disaster information, allowing users to check the operating status of bullet trains, buses, airplanes, and other services.

[1418] 3. Emotion Recognition: The emotion engine analyzes the user's facial expressions and voice to determine their emotional state, for example, whether they are stressed or calm.

[1419] 4. Route calculation: The server calculates the optimal route based on the collected data and emotion information. If there are no Shinkansen delays, it will suggest traveling by Shinkansen as usual, but if there are delays, it will consider alternative routes.

[1420] 5. Displaying the results: The server sends the calculation results to the terminal and displays them to the user. For example, it displays "From Shibuya Station to Nagoya Station by Shinkansen, travel time: 2 hours, fare: 10,000 yen."

[1421] 6. Selection and reservation: The user selects a route from the presented options. The selected route information is sent to the server, which then connects with the transportation reservation system to reserve a ticket. For example, it connects with the Shinkansen reservation system to reserve a ticket for the specified flight.

[1422] 7. Real-time updates: The server continuously monitors the status of public transport and disaster information, and when the situation changes, it recalculates the optimal route and notifies the user. For example, if the Shinkansen is delayed, the server will notify the user, "The Shinkansen is delayed. We recommend using a combination of bus and train as an alternative route."

[1423] 8. Emotion-based adjustment: The device adjusts the notification method according to the user's emotions. For example, if the user is feeling stressed, the device will send a reassuring notification such as, "We have found an alternative route that provides a comfortable space."

[1424] Prompt Sentence Examples

[1425] Here are some examples of prompts for generative AI models:

[1426] "If the current location is Shibuya Station and the destination is Nagoya Station, please tell me the optimal transportation route departing at 10:00. Please also take into consideration local public transportation APIs and real-time disaster information. Please also provide guidance that includes notification methods that will reassure the user even if they are feeling stressed."

[1427] In this way, a system that integrates an emotion engine will suggest optimal routes for users even in the event of a disaster, enabling them to reach their destination safely.

[1428] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1429] Step 1: Accepting User Input

[1430] The user launches the smartphone app and enters their current location, destination, and departure time. For example, they enter "Current location: Shibuya Station, Destination: Nagoya Station, Departure time: 10:00." Once the entry is complete, the device temporarily stores this information internally.

[1431] Input: current location, destination, departure time

[1432] Output: User input information stored in the device

[1433] Specific operation: When a user enters information and taps the "Send" button, the data is saved in temporary storage on the device.

[1434] Step 2: Collect data

[1435] The device sends the temporarily saved user-entered information to the server, which then uses an HTTP request to obtain real-time operation status data from the transport company's API and disaster information from the Japan Meteorological Agency's API.

[1436] Input: User-entered information

[1437] Output: Transportation status data, disaster information data

[1438] Specific operation: The device sends a request to the server, which then calls the API of each transportation company to obtain operation status and collects disaster information from the API of the Japan Meteorological Agency.

[1439] Step 3: Recognize emotions

[1440] The device's integrated emotion engine uses the camera and microphone to analyze the user's current emotional state, including facial expression recognition with OpenCV and voice analysis with Google Cloud Speech-to-Text.

[1441] Input: Camera video, audio data

[1442] Output: User's emotional information (stress, relief, etc.)

[1443] Specific operation: While the user is looking at the smartphone, the camera captures facial expressions, the microphone records the user's voice, and the emotion engine analyzes this data.

[1444] Step 4: Calculate the route

[1445] The server runs an algorithm that combines transportation status data, disaster information data, and user emotion information to calculate the optimal route.

[1446] Input: Operation status data, disaster information data, emotion information

[1447] Output: Optimal route information

[1448] How it works: The server integrates this data and the algorithm calculates the optimal travel route. For example, if the traffic conditions are normal and the user is not feeling stressed, the route using the Shinkansen will be selected.

[1449] Step 5: Presenting the results

[1450] The server sends the calculation results to the terminal, which then presents the results to the user, including route information, travel time, and fare information.

[1451] Input: Optimal route information

[1452] Output: Route information presented to the user (e.g., on-screen display)

[1453] Specific operation: Based on the data sent from the server, the terminal displays information such as "From Shibuya Station to Nagoya Station by Shinkansen, travel time: 2 hours, fare: 10,000 yen."

[1454] Step 6: Select and reserve

[1455] The user selects a route from the options presented, and the terminal sends the selected information to the server, which then connects with the transport company's reservation system to reserve a ticket.

[1456] Input: User-selected information

[1457] Output: Reservation completion notification

[1458] Specific operation: Based on the route information selected by the user, the server accesses the transportation reservation system and reserves a ticket for the specified flight.

[1459] Step 7: Real-time updates

[1460] The server continuously monitors transportation operation status and disaster information, and when the information is updated, it recalculates the optimal alternative route and notifies the device.

[1461] Input: Latest traffic status data and disaster information

[1462] Output: Updated route information

[1463] Specific operation: The server detects changes in train operation status and disaster information, and sends newly calculated route information to the terminal, notifying it, for example, "The Shinkansen is delayed. We recommend using a combination of bus and train as an alternative route."

[1464] Step 8: Emotional Adjustment

[1465] The device adjusts the calculation results and notification method based on the user's latest emotional information. For example, if it determines that the user is feeling stressed, it will send a notification that gives a sense of relief.

[1466] Input: Latest emotional information

[1467] Output: Personalized notification content

[1468] Specific operation: The device analyzes emotional information, and if the user is feeling stressed, it displays the message "We have found an alternative route that provides a comfortable space," giving the user a sense of security.

[1469] This series of processes enables users to reach their destination quickly and safely via the optimal route even in the event of a disaster.

[1470] (Application example 2)

[1471] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1472] Conventional traffic route guidance systems have the problem of being unable to adequately respond to complex situations and rapid route changes that arise during disasters. Furthermore, because they do not take into account the user's emotional state, they have difficulty responding to situations that are likely to cause stress or anxiety. Furthermore, there is a need for efficient route guidance when using autonomous vehicles.

[1473] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for inputting the user's current location, destination, and departure time, means for acquiring real-time operation status data of public transportation, means for collecting disaster information, means for calculating an optimal route reflecting the current operation status and disaster information, means for presenting the calculation results to the user, means for making necessary reservations on behalf of the user based on their selection, means for continuously monitoring operation status and disaster information, means for calculating an optimal alternative route when the situation changes and notifying the user, means for recognizing the user's emotions and adjusting the notification method and route suggestions based on the emotions, and means for providing route guidance and moving in cooperation with an autonomous vehicle. This makes it possible to provide the user with the optimal route even during a disaster and provide personalized services according to the user's emotional state.

[1474] "User" refers to any individual or organization that uses this system.

[1475] "Current location" indicates the location information of the user's current location.

[1476] The "destination" indicates the location the user is heading for.

[1477] "Departure time" indicates the time when the user starts traveling.

[1478] "Transportation" means any public or private means of transportation used by a User.

[1479] "Real-time operation status data" refers to data that indicates the current operation status of transportation facilities.

[1480] "Disaster information" refers to information about natural disasters such as earthquakes, typhoons, and fires, as well as sudden accidents.

[1481] An "optimal route" refers to the most efficient, safe, and quickest route from the user's current location to their destination.

[1482] "Route calculation" refers to the process of calculating the optimal route based on input data.

[1483] "Presenting" refers to the act of visually or audibly conveying the results of a calculation to a user.

[1484] "Reservation proxy acquisition" refers to the act of carrying out the necessary reservation procedures on behalf of the user.

[1485] "Monitoring" refers to the act of continuously watching traffic conditions and disaster information.

[1486] "Alternate Route" refers to a suggested alternative route if the planned route is unavailable.

[1487] "Emotion recognition" refers to the technology of determining a user's emotions from their facial expressions, voice, and text.

[1488] "Notification method" refers to the means by which information is conveyed to the user.

[1489] "Route suggestion" refers to the act of recommending the optimal travel route to the user.

[1490] An "autonomous vehicle" refers to a vehicle that can drive autonomously without human operation.

[1491] "Collaboration" refers to multiple systems and devices sharing information and working together.

[1492] This invention relates to a system for an autonomous vehicle that recognizes the user's emotions and provides optimal route guidance in the event of a disaster. Specific embodiments of this system will be described below.

[1493] Hardware Configuration

[1494] A user device (e.g., a smartphone) has the following capabilities:

[1495] Emotion recognition using a camera and microphone

[1496] Obtaining location information using GPS

[1497] Internet connection

[1498] Autonomous vehicles will have the following capabilities:

[1499] Route Navigation System

[1500] Internet connection

[1501] The server has the following features:

[1502] Data Processing Capacity

[1503] Cloud-based database

[1504] Various APIs (traffic information, weather information)

[1505] Software Configuration

[1506] It uses the EmotionRecognizer library for emotion recognition, the Requests library for real-time traffic and disaster information acquisition, and custom algorithms for navigation calculations.

[1507] System Operation

[1508] 1. The user enters their current location, destination, and departure time into the smartphone app. For example, they enter "Current location: Tokyo Station, Destination: Shin-Osaka Station, Departure time: 08:00."

[1509] 2. The terminal sends the entered information to the server.

[1510] 3. The server obtains real-time transportation status data and disaster information from each transportation company's API.

[1511] 4. The server recognizes the user's emotions through the smartphone's camera and microphone, using facial recognition and voice analysis technology to determine whether the user is feeling stressed.

[1512] 5. The server calculates the optimal route based on the collected traffic status and disaster information, as well as the user's emotional state. For example, if the user is feeling stressed, it will prioritize a relaxing route.

[1513] 6. The calculation results are sent to the user's device. The results include information such as the route, travel time, and fare. For example, the display might say, "From Tokyo Station to Shin-Osaka Station by Shinkansen, travel time: 2 hours 30 minutes, fare: 13,500 yen."

[1514] 7. The user selects a route from the presented options and sends the selection to the terminal.

[1515] 8. The server connects the selected route information to the transportation reservation system and reserves tickets if necessary.

[1516] 9. The server continuously monitors transportation status and disaster information, and whenever the information is updated, calculates the optimal alternative route as needed and notifies the device.

[1517] 10. The device adjusts the calculation results and notification method according to the user's emotions. For example, if the user is feeling stressed, the device will send a notification that provides a sense of relief, such as, "The Shinkansen is delayed, but we have found an alternative route that provides a comfortable space."

[1518] Examples of specific examples and prompts

[1519] As a specific example, if a Shinkansen train is delayed, the server can notify the terminal, "This Shinkansen train is currently delayed by 30 minutes. As an alternative route, we suggest a combination of bus and train, which is equally comfortable."

[1520] Example prompt sentence:

[1521] "Analyze the user's facial expressions to determine their stress level."

[1522] "Use current traffic and disaster information to calculate the best route from your origin to your destination."

[1523] This enables the system to support efficient and safe travel along optimal routes even in the event of a disaster.

[1524] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1525] Step 1:

[1526] A user inputs their current location, destination, and departure time into a smartphone app. This input data includes "Current location: Tokyo Station," "Destination: Shin-Osaka Station," and "Departure time: 08:00."

[1527] Step 2:

[1528] The terminal sends the entered information to the server. In this process, the entered data of current location, destination, and departure time is transferred to the server as is.

[1529] Step 3:

[1530] The server obtains real-time transportation status data and disaster information from each transportation agency's API. The data processing performed in this step involves analyzing the data obtained from the API and converting it into a specific format. The analyzed transportation data and disaster information are generated as output.

[1531] Step 4:

[1532] To recognize the user's emotions, the device acquires data from the camera or microphone and performs emotion analysis using the EmotionRecognizer library. In this step, raw data from the camera or microphone is input, and the user's emotional state (e.g., stress level) is output as an analysis result.

[1533] Step 5:

[1534] The server calculates the optimal route based on the collected traffic conditions, disaster information, and user sentiment information. This step also references map information and past traffic data stored in the database. The output is route guidance information that includes specific means of transportation and their details.

[1535] Step 6:

[1536] The server sends the calculation results to the terminal, and the terminal displays them to the user. The information displayed includes the route, travel time, fare, etc. For example, it displays "From Tokyo Station to Shin-Osaka Station by Shinkansen, travel time: 2 hours 30 minutes, fare: 13,500 yen."

[1537] Step 7:

[1538] The user selects a route from the presented options and transmits the selection to the terminal. The data operations performed in this step are recording and confirming the selection. The output is the route selected by the user.

[1539] Step 8:

[1540] The server connects the selected route information to the transport company's reservation system and reserves tickets if necessary. In this step, the server sends the necessary information to the ticket reservation API and receives a reservation confirmation. The output is a confirmation that the reservation has been completed.

[1541] Step 9:

[1542] The server continuously monitors the status of public transport and disaster information. Each time the information is updated, the server analyzes the new data and calculates an alternative route if there is an abnormality in the service status. The output is new route guidance information in the event of an abnormality.

[1543] Step 10:

[1544] The device adjusts the calculation results and notification method according to the user's emotions. For example, if the user is feeling stressed, the device will send a notification that provides a sense of relief, such as "The Shinkansen is delayed, but we have found an alternative route that provides a comfortable space." The output is a notification message that corresponds to the user's emotions.

[1545] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1546] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1547] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1548] [Fourth embodiment]

[1549] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1550] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1551] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1552] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1553] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1554] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1555] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1556] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1557] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1558] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1559] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1560] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1561] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1562] The present invention relates to a system that inputs a user's current location, destination, and departure time, calculates the optimal route even in the event of a disaster, and even makes reservations on their behalf. This system can quickly respond to information about the operation status of public transportation and disaster information, and efficiently guide users to their destinations. Detailed embodiments of the system are described below.

[1563] System configuration

[1564] This system mainly consists of a user device, a server, and related APIs. The user device is a mobile device such as a smartphone or tablet, and the server is located on the cloud. It also works in conjunction with APIs that provide information on various transportation services and weather information.

[1565] Program processing

[1566] 1. Accepting user input

[1567] The user inputs his / her current location, destination, and departure time into the user terminal.

[1568] As a specific example, the user inputs "Tokyo Station", "Shin-Osaka Station", and "08:00".

[1569] 2. Data collection

[1570] The terminal transmits the input information to the server.

[1571] The server obtains real-time operation status data for transportation services from each transportation service's API.

[1572] The server also collects disaster information from the Japan Meteorological Agency and other sources.

[1573] 3. Route calculation

[1574] The optimal route is calculated based on the operation status and disaster information collected by the server.

[1575] As a specific example, if the Shinkansen train operation status is normal, the route "travel from Tokyo Station to Shin-Osaka Station by Shinkansen" is suggested.

[1576] 4. Presentation of results

[1577] The server sends the calculation results to the terminal.

[1578] The terminal presents the calculation results to the user, including the route, travel time, and fare.

[1579] As a concrete example, it states, "The Shinkansen from Tokyo Station to Shin-Osaka Station takes 2 hours and 30 minutes and costs 13,500 yen."

[1580] 5. Selection and Booking

[1581] The user selects a route from the options presented.

[1582] The terminal transmits the selected route information to the server.

[1583] The server connects with the transportation reservation system to reserve tickets.

[1584] 6. Real-time updates

[1585] The server continuously monitors transportation operation status and disaster information.

[1586] Each time the information is updated, the server calculates the optimal alternative route if necessary and notifies the terminal.

[1587] As a concrete example, if the Shinkansen from Tokyo Station to Shin-Osaka Station is delayed, the server will offer an alternative means of transportation (for example, a combination of bus and train).

[1588] The system allows users to reach their destinations efficiently even in times of disaster, and uses past data to predict future travel conditions, supporting more accurate and adaptive travel.

[1589] The processing flow will be explained below.

[1590] Step 1:

[1591] The user inputs his / her current location, destination, and departure time into the terminal.

[1592] Example: Enter "Current location: Tokyo Station, Destination: Shin-Osaka Station, Departure time: 08:00".

[1593] Step 2:

[1594] The terminal transmits the input information to the server.

[1595] Send data to the server in the form of an API request.

[1596] Step 3:

[1597] The server acquires real-time operational status data of transportation facilities.

[1598] Data is collected by calling the real-time operation status API of each transportation company.

[1599] Example: Obtaining Shinkansen train operation status from a railway company's API.

[1600] Step 4:

[1601] The server collects disaster information.

[1602] It calls the APIs of the Japan Meteorological Agency and disaster information services to obtain information on typhoons, earthquakes, floods, etc.

[1603] Step 5:

[1604] The server calculates the optimal route based on current traffic conditions and disaster information.

[1605] It uses an algorithm to generate the optimal route from the user's current location to their destination.

[1606] Example: If the Shinkansen is operating normally, select the route "Take the Shinkansen from Tokyo to Shin-Osaka."

[1607] Step 6:

[1608] The server sends the calculation results to the terminal.

[1609] Information such as the optimal route, travel time, and fare is sent to the terminal in JSON format.

[1610] Step 7:

[1611] The terminal presents the calculation results to the user.

[1612] Specific means of transportation, departure time, travel time, fare, etc. are displayed on the screen.

[1613] Example: "From Tokyo Station to Shin-Osaka Station by Shinkansen, travel time: 2 hours 30 minutes, fare: 13,500 yen."

[1614] Step 8:

[1615] The user selects a route from the options presented.

[1616] Tap or click to choose the best route from the multiple options presented.

[1617] Step 9:

[1618] The terminal transmits the user's selection information to the server.

[1619] The selected route information is sent to the server in the form of an API request.

[1620] Step 10:

[1621] The server connects with the reservation systems of each transportation facility to reserve tickets.

[1622] Example: Call the Shinkansen reservation system API to reserve a ticket for a specified flight.

[1623] Step 11:

[1624] The server continuously monitors transportation operation status and disaster information.

[1625] The API is called periodically to obtain the latest operational status and disaster information.

[1626] Step 12:

[1627] When the situation changes, the server calculates the optimal alternative route and notifies the device.

[1628] Calculate the new optimal route and push a notification to the user.

[1629] Example: "The Shinkansen is delayed. We recommend using a combination of bus and train as an alternative route."

[1630] Step 13:

[1631] The terminal presents the user with new information and prompts them to make another selection.

[1632] New route suggestions are displayed on the screen and the user is prompted to select one.

[1633] Example: "Take the bus from Tokyo Station to Shinagawa Station, then take the local train to Shin-Osaka Station."

[1634] This series of steps allows users to reach their destination efficiently even in the event of a disaster.

[1635] Example 1

[1636] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1637] There is a need to provide an efficient means of transportation that can respond quickly to disasters and changes in real-time transportation status, as well as calculate the optimal route for users and even make reservations on their behalf. This will reduce anxiety about delays and cancellations of transportation and enable smoother and more efficient travel.

[1638] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1639] In this invention, the server includes means for inputting the user's current location, destination, and departure time, means for transmitting input information from the user terminal to the server, means for acquiring real-time transportation operation status data, means for collecting weather and disaster information, means for calculating an optimal route reflecting current operation status and disaster information, means for transmitting the calculation results to the user terminal, means for presenting the calculation results to the user, means for making necessary reservations on behalf of the user based on their selection, means for reserving tickets in cooperation with the transportation reservation system, means for continuously monitoring operation status and disaster information, and means for calculating an optimal alternative route when information is updated and notifying the user. This enables efficient travel in the event of a disaster or when transportation delays or cancellations occur.

[1640] "Means for inputting user's current location, destination, and departure time" refers to the interface used by the user to input their current location, destination, and departure time.

[1641] "Means for transmitting input information from a user terminal to a server" refers to a communication means or protocol for transmitting information input from a user terminal to a server.

[1642] "Means for obtaining real-time transit status data" means means for accessing a transit agency's API or data source to obtain real-time transit status data.

[1643] "Means of collecting weather and disaster information" refers to means of accessing the APIs of the Japan Meteorological Agency and disaster response organizations in order to collect weather information and other emergency information during disasters.

[1644] "Means for calculating the optimal route that reflects current operational conditions and disaster information" refers to a means for calculating the optimal travel route using an algorithm, taking into account real-time operational conditions and disaster information.

[1645] "Means for transmitting the calculation results to the user terminal" refers to the communication means or protocol for transmitting the route information calculated by the server to the user terminal.

[1646] "Means for presenting calculation results to the user" refers to an interface for presenting the results displayed on the user terminal in a format that is easy for the user to understand.

[1647] "Means for obtaining the necessary reservations on behalf of the user based on their selection" refers to the procedures and protocols for making transportation reservations on behalf of the user based on the route selected by the user.

[1648] "Means for reserving tickets in cooperation with a transportation company's reservation system" refers to a means for reserving tickets by accessing a transportation company's ticket reservation system and inputting the necessary information.

[1649] "Means for continuously monitoring operation status and disaster information" refers to means for continuously monitoring the operation status of transportation facilities and disaster information in real time, and updating it whenever new information is obtained.

[1650] "Means for calculating the optimal alternative route when information is updated and notifying the user" refers to means for recalculating the optimal alternative route based on the new conditions when operation status or disaster information is updated and notifying the user.

[1651] MODE FOR CARRYING OUT THE INVENTION

[1652] This invention relates to a system that inputs a user's current location, destination, and departure time, calculates the optimal route even in the event of a disaster, and even makes reservations on their behalf. This system can quickly respond to information about the operation status of public transportation and disaster information, and efficiently guide users to their destinations.

[1653] System configuration

[1654] The system's main components are user devices, servers, and related APIs. User devices are mobile devices such as smartphones and tablets, and the servers are located in a cloud environment. The system also works in conjunction with APIs that provide information on various transportation services and weather information.

[1655] Hardware and software used

[1656] User devices: smartphones, tablets, etc.

[1657] Server: Server on a cloud environment

[1658] API: Transport API (e.g. transport information API), Japan Meteorological Agency API

[1659] Data processing and calculation

[1660] 1. Accepting user input

[1661] The user enters their current location, destination, and departure time into the user device. For example, the user opens the smartphone app, enters "Tokyo Station," "Shin-Osaka Station," and "08:00," and taps the send button.

[1662] 2. Data collection

[1663] The device sends the entered information to the server, where it is converted to JSON format and sent using an HTTPS request.

[1664] The server accesses the API of each transportation facility to obtain real-time operation status data of the transportation facility. For example, it sends a request to the transportation facility's API to obtain real-time operation information.

[1665] The server sends requests to the APIs of the Japan Meteorological Agency and disaster prevention organizations to collect real-time weather information and disaster information.

[1666] 3. Route calculation

[1667] The server calculates the optimal route based on the operational status and disaster information collected. It uses Dijkstra's algorithm and generative AI models to calculate the optimal route using real-time data as input. For example, if the Shinkansen operational status is normal, it will suggest the route "travel from Tokyo Station to Shin-Osaka Station by Shinkansen."

[1668] 4. Presentation of results

[1669] The server sends the calculation results to the terminal, where they are converted into JSON format and sent as an HTTPS response.

[1670] The terminal presents the calculation results to the user. The calculation results are displayed on the user interface, clearly indicating the route, travel time, fare, etc. For example, it may say, "From Tokyo Station to Shin-Osaka Station by Shinkansen, the travel time is 2 hours and 30 minutes, and the fare is 13,500 yen."

[1671] 5. Selection and Booking

[1672] The user selects a route from the options presented. The user taps on the desired route to select it.

[1673] The device sends the selected route information to the server, which converts the information into JSON format and sends it using an HTTPS request.

[1674] The server works with the transport company's reservation system to reserve a ticket. For example, the server accesses the transport company's reservation system API and sends the necessary information to reserve a ticket.

[1675] 6. Real-time updates

[1676] The server continuously monitors the status of public transport and disaster information, periodically checking the API endpoint to obtain new information.

[1677] Each time the information is updated, the server calculates the optimal alternative route as needed and notifies the device. For example, if the Shinkansen from Tokyo Station to Shin-Osaka Station is delayed, a notification will be sent offering an alternative route that combines buses and trains.

[1678] Prompt Sentence Examples

[1679] The following are some examples of prompts that can be input to a generative AI model:

[1680] "Calculate the optimal route if your current location is Tokyo Station, your destination is Shin-Osaka Station, and your departure time is 8:00."

[1681] "Please suggest the best way to get from Tokyo Station to Shin-Osaka Station in the event of a disaster."

[1682] "Please make a reservation for departure: Tokyo Station, destination: Shin-Osaka Station, departure time: 08:00."

[1683] This allows for optimal route and reservation suggestions based on real-time information.

[1684] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1685] Step 1:

[1686] The user inputs his / her current location, destination, and departure time into the user terminal.

[1687] Input: A user opens the app on their smartphone, enters "Tokyo Station," "Shin-Osaka Station," and "08:00," and taps the send button.

[1688] Output: The input data (current location, destination, departure time) is generated in JSON format.

[1689] Specific behavior: When you enter data into the input form and tap the submit button, the data is converted to JSON format within the app.

[1690] Step 2:

[1691] The terminal transmits the input information to the server.

[1692] Input: The JSON formatted data generated in step 1.

[1693] Output: Data sent to the server via an HTTP POST request.

[1694] Specific operation: The communication module in the device sends JSON formatted data as an HTTP POST request to the server's API endpoint.

[1695] Step 3:

[1696] The server acquires real-time operational status data of transportation facilities.

[1697] Input: API request (a request for transit status data).

[1698] Output: Response from the API (real-time transport status data).

[1699] Specific operation: The server sends a request to each transportation company's API and receives real-time operation status data. After receiving the data, it is analyzed.

[1700] Step 4:

[1701] The server collects disaster information from the Japan Meteorological Agency and disaster prevention agencies.

[1702] Input: API request (request for disaster information).

[1703] Output: Response from the API (disaster information data).

[1704] Specific operation: The server sends requests to the APIs of the Japan Meteorological Agency and disaster response organizations to receive real-time disaster information. After receiving the data, it is analyzed.

[1705] Step 5:

[1706] The optimal route is calculated based on the operation status data and disaster information collected by the server.

[1707] Input: Real-time transportation status data and disaster information.

[1708] Output: Optimal route data.

[1709] Specific operation: The server uses Dijkstra's algorithm and generative AI models to calculate the optimal route based on real-time data. The calculation results are then generated as specific route information.

[1710] Step 6:

[1711] The server sends the calculation results to the terminal.

[1712] Input: Optimal route data.

[1713] Output: Data is sent to the user's device via an HTTP response.

[1714] Specific operation: The calculation result is converted to JSON format and sent to the terminal as an HTTP response.

[1715] Step 7:

[1716] The terminal presents the calculation results to the user.

[1717] Input: Optimal route data sent from the server.

[1718] Output: Route information displayed on the user interface.

[1719] Specific operation: The received data is analyzed and displayed on the screen as the route, travel time, fare, etc. For example, it may display "From Tokyo Station to Shin-Osaka Station by Shinkansen, travel time is 2 hours and 30 minutes, fare is 13,500 yen."

[1720] Step 8:

[1721] The user selects a route from the options presented.

[1722] Input: The user taps the desired route from the options on the screen.

[1723] Output: Selected route information.

[1724] Specific behavior: The user taps on the desired route from the presented route options, and that information is selected.

[1725] Step 9:

[1726] The terminal transmits the selected route information to the server.

[1727] Input: Selected route information.

[1728] Output: Data sent to the server via an HTTP POST request.

[1729] Specific behavior: The selected information is converted to JSON format and sent to the server as an HTTP POST request.

[1730] Step 10:

[1731] The server connects with the transportation reservation system to reserve tickets.

[1732] Input: Selected route information and user information.

[1733] Output: Successful reservation information in the transport reservation system.

[1734] Specific operation: The server accesses the transport reservation system API, sends the necessary information and makes a ticket reservation.

[1735] Step 11:

[1736] The server continuously monitors transportation status and disaster information.

[1737] Input: A timer event that causes the server to periodically check the API endpoint.

[1738] Output: Updated operational status data and disaster information.

[1739] Specific operation: The server periodically accesses each API to obtain new information.

[1740] Step 12:

[1741] Each time the information is updated, the server calculates the optimal alternative route if necessary and notifies the terminal.

[1742] Input: Updated operational status data and disaster information.

[1743] Output: New best alternative route data and notification.

[1744] Specific operation: The server recalculates the route based on the newly acquired data, calculates the optimal alternative route, and notifies the user. For example, if the Shinkansen from Tokyo Station to Shin-Osaka Station is delayed, a notification will be sent offering a route that combines buses and trains.

[1745] (Application example 1)

[1746] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1747] Conventional autonomous vehicle route guidance systems have difficulty calculating routes that fully take into account real-time transportation status and disaster information, and there is no guarantee that users will arrive at their destination safely. Another issue is that autonomous vehicles cannot propose appropriate alternative routes in emergencies. Furthermore, they lack a reservation agent function to improve user convenience, forcing users to go through complicated procedures.

[1748] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1749] In this invention, the server includes means for inputting the user's current location, destination, and departure time, means for acquiring real-time transportation operation status data, means for collecting disaster information, means for calculating an optimal route reflecting the current operation status and disaster information, means for presenting the calculation results to the user, means for making necessary reservations on behalf of the user based on their selection, means for continuously monitoring operation status and disaster information, means for calculating an optimal alternative route when the situation changes and notifying the user, means installed in the autonomous vehicle for updating the vehicle's control system with route information, and means for suggesting alternative routes and stops for emergencies. This allows the user to receive optimal route guidance in real time, allowing for quick response in emergencies, and the reservation proxy function eliminates the need for complicated procedures.

[1750] "User's current location" refers to the location where a person using the system is currently located.

[1751] "Destination" refers to the final destination that the user is aiming for.

[1752] "Departure time" refers to the time set by the user as the planned departure time.

[1753] "Real-time transport status data" refers to up-to-date information about the current operating status of public transport such as buses, trains and planes.

[1754] "Disaster information" refers to information about natural disasters such as earthquakes, typhoons, and heavy rain provided by the Japan Meteorological Agency and other organizations.

[1755] "Optimal route" refers to the travel route that allows a user to reach their destination most efficiently and safely.

[1756] "Calculation results" refers to information on the optimal route or alternative route calculated by the system.

[1757] "Means of obtaining reservations on behalf of users" refers to a function that automatically obtains the necessary tickets and reservations through the transportation reservation system based on user operations.

[1758] "Means for continuously monitoring operation status and disaster information" refers to the system's ability to continuously monitor the operation status of transportation services and disaster information in real time.

[1759] "Means for calculating the optimal alternative route and notifying the user" refers to a function that calculates a new optimal route and notifies the user when the originally planned route is not available.

[1760] An "autonomous vehicle" refers to a vehicle that can drive and be controlled automatically using artificial intelligence and various sensors.

[1761] "Means for reflecting in the vehicle's control system" refers to the function of inputting the calculated route information into the control device of the autonomous vehicle and applying it as the vehicle's driving route.

[1762] "Means for suggesting alternative routes and stopping points in emergencies" refers to a function that suggests alternative travel routes and stopping points so that users can evacuate safely in the event of an emergency or disaster.

[1763] This invention is a system for providing optimal route guidance to autonomous vehicles. It inputs the user's current location, destination, and departure time, and calculates the optimal route in real time, reflecting the operation status of public transport and disaster information, and even handles necessary reservations. Furthermore, in emergencies, it can propose alternative routes and reflect them in the vehicle's control system.

[1764] The system consists of a user terminal, a server, related APIs, and an autonomous vehicle control system.

[1765] Hardware and software:

[1766] Hardware: On-board computers in autonomous vehicles, smartphones, and tablets

[1767] Software: Python, API (traffic information API, disaster information API), cloud server

[1768] System behavior:

[1769] 1. User Input

[1770] The user enters their current location, destination, and departure time into their smartphone or in-car tablet.

[1771] 2. Data collection

[1772] The terminal sends this information to a server, which then obtains real-time transportation status data and disaster information from various APIs.

[1773] 3. Route calculation

[1774] The server uses the acquired data to calculate the optimal route for the user, using algorithms such as generative AI models.

[1775] 4. Presentation of results

[1776] The server sends the calculation results to the terminal, which then presents them to the user, including route information, travel time, and fare information.

[1777] 5. Reservations and proxy acquisition

[1778] Once the user selects a route from the options presented, the terminal sends this information to the server, which then works with the transport company's reservation system to reserve a ticket on their behalf.

[1779] 6. Real-time updates

[1780] The server continuously monitors operational status and disaster information, calculates optimal alternative routes as needed, notifies users, and reflects the results in the vehicle's control system to support safe operation.

[1781] 7. Emergency Response

[1782] In an emergency, the server calculates alternative routes and stops and suggests them to the user via the terminal. For example, if Shinkansen service is suspended, the server will notify the user of alternative bus routes and nearby safe stops.

[1783] Examples:

[1784] For example, if a user wants to travel from Tokyo Station to Shin-Osaka Station, they can input their data and receive calculated Shinkansen route information (travel time, fare). If the Shinkansen is delayed, the system will suggest an alternative route that combines buses and trains, and will also make reservations for that route on their behalf.

[1785] Example prompt sentence:

[1786] "I'd like to travel from Tokyo Station to Shin-Osaka Station. My departure time is 8:00 AM. Please tell me the best route and an alternative route, taking into account the current traffic conditions and disaster information."

[1787] This system allows users to efficiently select the most suitable means of transportation and reach their destination safely and comfortably.

[1788] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1789] Step 1:

[1790] User input:

[1791] The user inputs their current location, destination, and departure time into their smartphone or in-car tablet. This input data becomes the initial input data for the system.

[1792] Step 2:

[1793] Sending data:

[1794] The device sends the current location, destination, and departure time data acquired from the user to the server, which then prepares the server for the next step of data collection.

[1795] Step 3:

[1796] Transportation data collection:

[1797] The server obtains real-time operational status data for transportation services. The latest operational information for each transportation service is collected via API and stored in a database. This data is used when calculating routes.

[1798] Step 4:

[1799] Disaster information collection:

[1800] The server acquires disaster information. It collects the latest disaster information from disaster information APIs such as those provided by the Japan Meteorological Agency and stores it in a database. This data affects route calculations.

[1801] Step 5:

[1802] Route calculation:

[1803] The server calculates the optimal route based on traffic status data and disaster information collected. Using generative AI models and route optimization algorithms, it determines the safest and most efficient route for users to reach their destination. This calculation takes into account the user's current location, destination, and departure time.

[1804] Step 6:

[1805] Presenting the results:

[1806] The server sends the calculation results to the terminal, which then presents them to the user. The calculation results include the optimal route, travel time, fare, etc., allowing the user to confirm the proposed route.

[1807] Step 7:

[1808] Booking and Acquisition:

[1809] When the user selects a route from the options presented, the device sends that information to the server. The server then works with the transportation company's reservation system to automatically obtain the necessary reservations on the user's behalf. Once the reservation is complete, the information is sent to the user's device.

[1810] Step 8:

[1811] Real-time updates:

[1812] The server continuously monitors transportation status and disaster information. If new information is confirmed, the server recalculates the optimal alternative route and sends the results to the device, ensuring that users always receive the latest route information.

[1813] Step 9:

[1814] Route information reflection:

[1815] The server then updates the autonomous vehicle's control system with the latest route information, allowing the autonomous vehicle to travel along the optimal route.

[1816] Step 10:

[1817] Emergency Response:

[1818] In the event of an emergency, the server calculates alternative routes and stops and suggests them to the user via their device, allowing the user to travel safely even in an emergency.

[1819] In this way, the system collects and processes data based on user input, providing optimal routes and alternative routes to help ensure efficient and safe travel.

[1820] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1821] This invention relates to a transportation route guidance system for use in emergencies that has been further improved by combining it with an emotion engine that recognizes the user's emotions. This system inputs the user's current location, destination, and departure time, and calculates and presents the optimal route based on real-time transportation conditions and disaster information, and makes reservations on behalf of the user if necessary. It also provides a more personalized service by recognizing the user's emotional state and suggesting optimal notification methods and routes based on that information.

[1822] System configuration

[1823] This system mainly consists of a user device, a server, an emotion engine, and a data acquisition API. The user device is a mobile device such as a smartphone or tablet, and the server is located on the cloud. The emotion engine is integrated into the device and recognizes emotions from the user's facial expressions, voice, text, etc. The data acquisition API provides transportation and weather information.

[1824] Program processing

[1825] 1. Accepting user input

[1826] The user inputs his / her current location, destination, and departure time into the user terminal.

[1827] For example, enter "Current location: Tokyo Station, Destination: Shin-Osaka Station, Departure time: 08:00".

[1828] 2. Data collection

[1829] The terminal transmits the input information to the server.

[1830] The server obtains real-time operation status data for transportation services from each transportation service's API.

[1831] The server also collects disaster information from the Japan Meteorological Agency and other sources.

[1832] 3. Emotional Recognition

[1833] The emotion engine recognizes the user's emotions, for example, by using facial recognition and voice analysis technology to determine whether the user is feeling stressed.

[1834] 4. Route calculation

[1835] The server calculates the optimal route based on the traffic status, disaster information, and user emotional information collected.

[1836] For example, if the Shinkansen train operation status is normal and the user is not feeling stressed, the route "from Tokyo to Shin-Osaka by Shinkansen" is suggested.

[1837] 5. Presentation of results

[1838] The server sends the calculation results to the terminal.

[1839] The terminal presents the calculation results to the user, including the route, travel time, and fare.

[1840] For example, it might say, "Take the Shinkansen from Tokyo Station to Shin-Osaka Station, travel time: 2 hours 30 minutes, fare: 13,500 yen."

[1841] 6. Selection and Reservation

[1842] The user selects a route from the options presented.

[1843] The terminal transmits the selected route information to the server.

[1844] The server connects with the transportation reservation system to reserve tickets.

[1845] For example, it can be linked to a Shinkansen reservation system to reserve tickets for a specified flight.

[1846] 7. Real-time updates

[1847] The server continuously monitors transportation operation status and disaster information.

[1848] Each time the information is updated, the server calculates the optimal alternative route if necessary and notifies the terminal.

[1849] For example, the notification could say, "The Shinkansen is delayed. We recommend using a combination of bus and train as an alternative route."

[1850] 8. Emotion-Based Regulation

[1851] The device adjusts the calculation results and notification method according to the user's emotions.

[1852] For example, if a user is feeling stressed, a notification that provides a sense of relief such as, "The Shinkansen is delayed, but we have found an alternative route that provides a comfortable space" can be displayed.

[1853] In this way, a system that integrates an emotion engine allows users to reach their destination efficiently via the optimal route even during a disaster, and complete their journey with a sense of security.

[1854] The processing flow will be explained below.

[1855] Step 1:

[1856] The user inputs his / her current location, destination, and departure time into the terminal.

[1857] Example: Enter "Current location: Tokyo Station, Destination: Shin-Osaka Station, Departure time: 08:00".

[1858] Step 2:

[1859] The terminal transmits the input information to the server.

[1860] Send data in the form of an API request.

[1861] Step 3:

[1862] The server obtains real-time operation status data for transportation services from each transportation service's API.

[1863] Example: Obtaining Shinkansen train operation status from a railway company's API.

[1864] Step 4:

[1865] The server collects disaster information from disaster information providers such as the Japan Meteorological Agency.

[1866] Example: Obtaining information about typhoons, earthquakes, and floods.

[1867] Step 5:

[1868] The terminal uses an emotion engine to recognize the user's emotion.

[1869] Example: Analyzing the user's facial expressions through the front camera to recognize stress levels.

[1870] Step 6:

[1871] The server calculates the optimal route based on the operation status, disaster information, and user emotional information collected.

[1872] Example: If the Shinkansen is running normally and the user is feeling stressed, suggest a route such as "Take the Shinkansen from Tokyo to Shin-Osaka," while also considering options that provide a comfortable space.

[1873] Step 7:

[1874] The server sends the calculation results to the terminal.

[1875] The obtained route information, travel time, fare, etc. are sent in JSON format.

[1876] Step 8:

[1877] The terminal presents the calculation results to the user.

[1878] Example: "Take the Shinkansen from Tokyo Station to Shin-Osaka Station, travel time: 2 hours 30 minutes, fare: 13,500 yen."

[1879] Step 9:

[1880] The user selects the best route from the options presented.

[1881] Example: Tap or click to select the best option from multiple options presented.

[1882] Step 10:

[1883] The terminal transmits the user's selection information to the server.

[1884] The selected route information is sent in the form of an API request.

[1885] Step 11:

[1886] The server connects with the transport company's reservation system to reserve tickets.

[1887] Example: Call the Shinkansen reservation system API to reserve a ticket for a specified flight.

[1888] Step 12:

[1889] The server continuously monitors transportation operation status and disaster information.

[1890] Continue to obtain real-time data on a regular basis.

[1891] Step 13:

[1892] When the situation changes, the server calculates the optimal alternative route and notifies the device.

[1893] Example: "The Shinkansen is delayed. We recommend using a combination of bus and train as an alternative route."

[1894] Step 14:

[1895] The terminal presents the user with new information and prompts them to make another selection.

[1896] Example: "Take the bus from Tokyo Station to Shinagawa Station, then take the local train to Shin-Osaka Station."

[1897] Step 15:

[1898] The device uses an emotion engine to adjust the notification method and content based on the user's emotions.

[1899] Example: If a user is feeling stressed, provide a reassuring notification such as, "The Shinkansen is delayed, but we have found an alternative route that provides a comfortable space."

[1900] In this way, users can reach their destination efficiently even in the event of a disaster, and the emotion engine allows them to complete their journey with an added sense of security.

[1901] Example 2

[1902] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1903] Conventional transportation route guidance systems do not take into account the user's psychological state, which often leaves users feeling anxious, especially during disasters. Furthermore, whenever the transportation status or disaster information changes, the recalculation and notification of optimal routes can be delayed, making it difficult for users to travel quickly and safely. Furthermore, the transportation reservation process is complicated, placing a burden on users in many situations.

[1904] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1905] In this invention, the server includes means for inputting the user's current location, destination, and departure time, means for acquiring real-time transportation operation status data, means for collecting disaster information, means for recognizing the user's emotions, means for calculating an optimal route reflecting the current operation status, disaster information, and the user's emotional information, means for presenting the calculation results to the user, means for making necessary reservations on behalf of the user based on their selection, means for continuously monitoring the operation status and disaster information, and means for calculating an optimal alternative route and notifying the user when the situation changes. This allows the user to receive optimal route guidance based on the latest information in real time, and by providing personalized notifications and guidance according to the user's emotional state, the server can travel with peace of mind.

[1906] "Current location of user" refers to geographical location information where the user is currently physically located.

[1907] A "destination" is the final geographic location that a user wishes to reach.

[1908] "Departure time" is information indicating the date and time when the user plans to start traveling.

[1909] "Real-time transportation status data" is the latest information on how transportation such as trains, buses, and planes are currently operating.

[1910] "Disaster information" refers to information about natural disasters and other emergencies that may affect users' travel.

[1911] "User's emotions" is information that indicates the user's psychological state and emotions, and includes states such as stress, relief, and excitement.

[1912] The "means for calculating the optimal route" refers to an algorithm or system that calculates the most efficient and safe travel route for the user based on collected information.

[1913] The "means for presenting the calculation results to the user" refers to a method or technology for displaying the results of the route calculation in a format that is easy for the user to view.

[1914] A "means for obtaining reservations on behalf of a user" is a system or process for automatically making reservations for transportation or other means selected by the user.

[1915] "Means for continuously monitoring operation status and disaster information" refers to technologies and methods for constantly monitoring the operation status of transportation and disaster information, and collecting the latest information.

[1916] "Means for calculating the optimal alternative route and notifying the user" refers to a system or method for recalculating the optimal route when the situation changes and notifying the user of the result.

[1917] MODE FOR CARRYING OUT THE INVENTION

[1918] The present invention relates to a traffic route guidance system for use in emergencies that has been further improved by combining it with an emotion engine that recognizes the user's emotions. This system aims to not only enable users to receive optimal route guidance based on the latest information in real time, but also to provide personalized notifications and suggestions according to the user's psychological state. Specific embodiments for implementing this invention are described below.

[1919] Hardware and software configuration

[1920] This system mainly consists of a user device, a server, an emotion engine, and a data acquisition API. The user device is a mobile device such as a smartphone or tablet, and the server is located on the cloud. The emotion engine is integrated into the device and recognizes emotions by analyzing the user's facial expressions, voice, text, etc. The data acquisition API is used to provide transportation and weather information.

[1921] Specifically, OpenCV is used for facial recognition, Google Cloud Speech-to-Text for voice analysis, and the APIs of transportation agencies (e.g., JR East's API) are used to obtain transportation data. Weather information is obtained from the API of the Japan Meteorological Agency.

[1922] Example of operation

[1923] The following describes an example in which the user inputs "current location: Shibuya Station, destination: Nagoya Station, departure time: 10:00".

[1924] 1. Accepting user input: The user starts the smartphone app and enters their current location, destination, and departure time. For example, they enter "Current location: Shibuya Station, Destination: Nagoya Station, Departure time: 10:00" and press the "Send" button.

[1925] 2. Data collection: The device sends the entered information to the server. The server uses APIs to obtain real-time traffic and disaster information, allowing users to check the operating status of bullet trains, buses, airplanes, and other services.

[1926] 3. Emotion Recognition: The emotion engine analyzes the user's facial expressions and voice to determine their emotional state, for example, whether they are stressed or calm.

[1927] 4. Route calculation: The server calculates the optimal route based on the collected data and emotion information. If there are no Shinkansen delays, it will suggest traveling by Shinkansen as usual, but if there are delays, it will consider alternative routes.

[1928] 5. Displaying the results: The server sends the calculation results to the terminal and displays them to the user. For example, it displays "From Shibuya Station to Nagoya Station by Shinkansen, travel time: 2 hours, fare: 10,000 yen."

[1929] 6. Selection and reservation: The user selects a route from the presented options. The selected route information is sent to the server, which then connects with the transportation reservation system to reserve a ticket. For example, it connects with the Shinkansen reservation system to reserve a ticket for the specified flight.

[1930] 7. Real-time updates: The server continuously monitors the status of public transport and disaster information, and when the situation changes, it recalculates the optimal route and notifies the user. For example, if the Shinkansen is delayed, the server will notify the user, "The Shinkansen is delayed. We recommend using a combination of bus and train as an alternative route."

[1931] 8. Emotion-based adjustment: The device adjusts the notification method according to the user's emotions. For example, if the user is feeling stressed, the device will send a reassuring notification such as, "We have found an alternative route that provides a comfortable space."

[1932] Prompt Sentence Examples

[1933] Here are some examples of prompts for generative AI models:

[1934] "If the current location is Shibuya Station and the destination is Nagoya Station, please tell me the optimal transportation route departing at 10:00. Please also take into consideration local public transportation APIs and real-time disaster information. Please also provide guidance that includes notification methods that will reassure the user even if they are feeling stressed."

[1935] In this way, a system that integrates an emotion engine will suggest optimal routes for users even in the event of a disaster, enabling them to reach their destination safely.

[1936] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1937] Step 1: Accepting User Input

[1938] The user launches the smartphone app and enters their current location, destination, and departure time. For example, they enter "Current location: Shibuya Station, Destination: Nagoya Station, Departure time: 10:00." Once the entry is complete, the device temporarily stores this information internally.

[1939] Input: current location, destination, departure time

[1940] Output: User input information stored in the device

[1941] Specific operation: When a user enters information and taps the "Send" button, the data is saved in temporary storage on the device.

[1942] Step 2: Collect data

[1943] The device sends the temporarily saved user-entered information to the server, which then uses an HTTP request to obtain real-time operation status data from the transport company's API and disaster information from the Japan Meteorological Agency's API.

[1944] Input: User-entered information

[1945] Output: Transportation status data, disaster information data

[1946] Specific operation: The device sends a request to the server, which then calls the API of each transportation company to obtain operation status and collects disaster information from the API of the Japan Meteorological Agency.

[1947] Step 3: Recognize emotions

[1948] The device's integrated emotion engine uses the camera and microphone to analyze the user's current emotional state, including facial expression recognition with OpenCV and voice analysis with Google Cloud Speech-to-Text.

[1949] Input: Camera video, audio data

[1950] Output: User's emotional information (stress, relief, etc.)

[1951] Specific operation: While the user is looking at the smartphone, the camera captures facial expressions, the microphone records the user's voice, and the emotion engine analyzes this data.

[1952] Step 4: Calculate the route

[1953] The server runs an algorithm that combines transportation status data, disaster information data, and user emotion information to calculate the optimal route.

[1954] Input: Operation status data, disaster information data, emotion information

[1955] Output: Optimal route information

[1956] How it works: The server integrates this data and the algorithm calculates the optimal travel route. For example, if the traffic conditions are normal and the user is not feeling stressed, the route using the Shinkansen will be selected.

[1957] Step 5: Presenting the results

[1958] The server sends the calculation results to the terminal, which then presents the results to the user, including route information, travel time, and fare information.

[1959] Input: Optimal route information

[1960] Output: Route information presented to the user (e.g., on-screen display)

[1961] Specific operation: Based on the data sent from the server, the terminal displays information such as "From Shibuya Station to Nagoya Station by Shinkansen, travel time: 2 hours, fare: 10,000 yen."

[1962] Step 6: Select and reserve

[1963] The user selects a route from the options presented, and the terminal sends the selected information to the server, which then connects with the transport company's reservation system to reserve a ticket.

[1964] Input: User-selected information

[1965] Output: Reservation completion notification

[1966] Specific operation: Based on the route information selected by the user, the server accesses the transportation reservation system and reserves a ticket for the specified flight.

[1967] Step 7: Real-time updates

[1968] The server continuously monitors transportation operation status and disaster information, and when the information is updated, it recalculates the optimal alternative route and notifies the device.

[1969] Input: Latest traffic status data and disaster information

[1970] Output: Updated route information

[1971] Specific operation: The server detects changes in train operation status and disaster information, and sends newly calculated route information to the terminal, notifying it, for example, "The Shinkansen is delayed. We recommend using a combination of bus and train as an alternative route."

[1972] Step 8: Emotional Adjustment

[1973] The device adjusts the calculation results and notification method based on the user's latest emotional information. For example, if it determines that the user is feeling stressed, it will send a notification that gives a sense of relief.

[1974] Input: Latest emotional information

[1975] Output: Personalized notification content

[1976] Specific operation: The device analyzes emotional information, and if the user is feeling stressed, it displays the message "We have found an alternative route that provides a comfortable space," giving the user a sense of security.

[1977] This series of processes enables users to reach their destination quickly and safely via the optimal route even in the event of a disaster.

[1978] (Application example 2)

[1979] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1980] Conventional traffic route guidance systems have the problem of being unable to adequately respond to complex situations and rapid route changes that arise during disasters. Furthermore, because they do not take into account the user's emotional state, they have difficulty responding to situations that are likely to cause stress or anxiety. Furthermore, there is a need for efficient route guidance when using autonomous vehicles.

[1981] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for inputting the user's current location, destination, and departure time, means for acquiring real-time operation status data of public transportation, means for collecting disaster information, means for calculating an optimal route reflecting the current operation status and disaster information, means for presenting the calculation results to the user, means for making necessary reservations on behalf of the user based on their selection, means for continuously monitoring operation status and disaster information, means for calculating an optimal alternative route when the situation changes and notifying the user, means for recognizing the user's emotions and adjusting the notification method and route suggestions based on the emotions, and means for providing route guidance and moving in cooperation with an autonomous vehicle. This makes it possible to provide the user with the optimal route even during a disaster and provide personalized services according to the user's emotional state.

[1982] "User" refers to any individual or organization that uses this system.

[1983] "Current location" indicates the location information of the user's current location.

[1984] The "destination" indicates the location the user is heading for.

[1985] "Departure time" indicates the time when the user starts traveling.

[1986] "Transportation" means any public or private means of transportation used by a User.

[1987] "Real-time operation status data" refers to data that indicates the current operation status of transportation facilities.

[1988] "Disaster information" refers to information about natural disasters such as earthquakes, typhoons, and fires, as well as sudden accidents.

[1989] An "optimal route" refers to the most efficient, safe, and quickest route from the user's current location to their destination.

[1990] "Route calculation" refers to the process of calculating the optimal route based on input data.

[1991] "Presenting" refers to the act of visually or audibly conveying the results of a calculation to a user.

[1992] "Reservation proxy acquisition" refers to the act of carrying out the necessary reservation procedures on behalf of the user.

[1993] "Monitoring" refers to the act of continuously watching traffic conditions and disaster information.

[1994] "Alternate Route" refers to a suggested alternative route if the planned route is unavailable.

[1995] "Emotion recognition" refers to the technology of determining a user's emotions from their facial expressions, voice, and text.

[1996] "Notification method" refers to the means by which information is conveyed to the user.

[1997] "Route suggestion" refers to the act of recommending the optimal travel route to the user.

[1998] An "autonomous vehicle" refers to a vehicle that can drive autonomously without human operation.

[1999] "Collaboration" refers to multiple systems and devices sharing information and working together.

[2000] This invention relates to a system for an autonomous vehicle that recognizes the user's emotions and provides optimal route guidance in the event of a disaster. Specific embodiments of this system will be described below.

[2001] Hardware Configuration

[2002] A user device (e.g., a smartphone) has the following capabilities:

[2003] Emotion recognition using a camera and microphone

[2004] Obtaining location information using GPS

[2005] Internet connection

[2006] Autonomous vehicles will have the following capabilities:

[2007] Route Navigation System

[2008] Internet connection

[2009] The server has the following features:

[2010] Data Processing Capacity

[2011] Cloud-based database

[2012] Various APIs (traffic information, weather information)

[2013] Software Configuration

[2014] It uses the EmotionRecognizer library for emotion recognition, the Requests library for real-time traffic and disaster information acquisition, and custom algorithms for navigation calculations.

[2015] System Operation

[2016] 1. The user enters their current location, destination, and departure time into the smartphone app. For example, they enter "Current location: Tokyo Station, Destination: Shin-Osaka Station, Departure time: 08:00."

[2017] 2. The terminal sends the entered information to the server.

[2018] 3. The server obtains real-time transportation status data and disaster information from each transportation company's API.

[2019] 4. The server recognizes the user's emotions through the smartphone's camera and microphone, using facial recognition and voice analysis technology to determine whether the user is feeling stressed.

[2020] 5. The server calculates the optimal route based on the collected traffic status and disaster information, as well as the user's emotional state. For example, if the user is feeling stressed, it will prioritize a relaxing route.

[2021] 6. The calculation results are sent to the user's device. The results include information such as the route, travel time, and fare. For example, the display might say, "From Tokyo Station to Shin-Osaka Station by Shinkansen, travel time: 2 hours 30 minutes, fare: 13,500 yen."

[2022] 7. The user selects a route from the presented options and sends the selection to the terminal.

[2023] 8. The server connects the selected route information to the transportation reservation system and reserves tickets if necessary.

[2024] 9. The server continuously monitors transportation status and disaster information, and whenever the information is updated, calculates the optimal alternative route as needed and notifies the device.

[2025] 10. The device adjusts the calculation results and notification method according to the user's emotions. For example, if the user is feeling stressed, the device will send a notification that provides a sense of relief, such as, "The Shinkansen is delayed, but we have found an alternative route that provides a comfortable space."

[2026] Examples of specific examples and prompts

[2027] As a specific example, if a Shinkansen train is delayed, the server can notify the terminal, "This Shinkansen train is currently delayed by 30 minutes. As an alternative route, we suggest a combination of bus and train, which is equally comfortable."

[2028] Example prompt sentence:

[2029] "Analyze the user's facial expressions to determine their stress level."

[2030] "Use current traffic and disaster information to calculate the best route from your origin to your destination."

[2031] This enables the system to support efficient and safe travel along optimal routes even in the event of a disaster.

[2032] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2033] Step 1:

[2034] A user inputs their current location, destination, and departure time into a smartphone app. This input data includes "Current location: Tokyo Station," "Destination: Shin-Osaka Station," and "Departure time: 08:00."

[2035] Step 2:

[2036] The terminal sends the entered information to the server. In this process, the entered data of current location, destination, and departure time is transferred to the server as is.

[2037] Step 3:

[2038] The server obtains real-time transportation status data and disaster information from each transportation agency's API. The data processing performed in this step involves analyzing the data obtained from the API and converting it into a specific format. The analyzed transportation data and disaster information are generated as output.

[2039] Step 4:

[2040] To recognize the user's emotions, the device acquires data from the camera or microphone and performs emotion analysis using the EmotionRecognizer library. In this step, raw data from the camera or microphone is input, and the user's emotional state (e.g., stress level) is output as an analysis result.

[2041] Step 5:

[2042] The server calculates the optimal route based on the collected traffic conditions, disaster information, and user sentiment information. This step also references map information and past traffic data stored in the database. The output is route guidance information that includes specific means of transportation and their details.

[2043] Step 6:

[2044] The server sends the calculation results to the terminal, and the terminal displays them to the user. The information displayed includes the route, travel time, fare, etc. For example, it displays "From Tokyo Station to Shin-Osaka Station by Shinkansen, travel time: 2 hours 30 minutes, fare: 13,500 yen."

[2045] Step 7:

[2046] The user selects a route from the presented options and transmits the selection to the terminal. The data operations performed in this step are recording and confirming the selection. The output is the route selected by the user.

[2047] Step 8:

[2048] The server connects the selected route information to the transport company's reservation system and reserves tickets if necessary. In this step, the server sends the necessary information to the ticket reservation API and receives a reservation confirmation. The output is a confirmation that the reservation has been completed.

[2049] Step 9:

[2050] The server continuously monitors the status of public transport and disaster information. Each time the information is updated, the server analyzes the new data and calculates an alternative route if there is an abnormality in the service status. The output is new route guidance information in the event of an abnormality.

[2051] Step 10:

[2052] The device adjusts the calculation results and notification method according to the user's emotions. For example, if the user is feeling stressed, the device will send a notification that provides a sense of relief, such as "The Shinkansen is delayed, but we have found an alternative route that provides a comfortable space." The output is a notification message that corresponds to the user's emotions.

[2053] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[2054] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[2055] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[2056] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[2057] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[2058] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[2059] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[2060] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, bas...

Claims

1. means for inputting the user's current location, destination, and departure time; A means for obtaining real-time operational status data of transportation facilities; A means of collecting disaster information; A means of calculating the optimal route that reflects current traffic conditions and disaster information, means for presenting the calculation results to a user; a means for proxy-obtaining a necessary reservation based on a user's selection; A means of continuously monitoring operational status and disaster information; The system includes a means to calculate the best alternative route and notify the user when conditions change.

2. 10. The system of claim 1, further comprising means for predicting future operating conditions using historical data.

3. 2. The system according to claim 1, wherein the means for obtaining reservations on behalf of the user includes means for purchasing tickets in cooperation with a reservation system of the means of transport.

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