System

Abstract

To provide a user with smooth and comfortable movement.SOLUTION: A system comprising: means for a user to input a starting point and a destination; means for collecting transportation schedule and route information; means for calculating an optimal route and generating it as integrated data; means for presenting the generated integrated data to the user; means for monitoring traffic conditions during travel and providing delay information in real time; and means for recalculating and presenting an optimal alternative route to the user in case of a delay.SELECTED DRAWING: Figure 1

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] Conventionally, when a user travels from a departure point to a destination, they have to use multiple applications to search for transportation schedules, route information, and walking routes, which is extremely cumbersome. Furthermore, if a delay occurs during travel, it is difficult to immediately find the optimal alternative route, which can be stressful. The objective of the present invention is to solve these problems and provide users with smooth and comfortable travel. [Means for solving the problem]

[0005] The present invention provides a system that includes a means for a user to input a departure point and a destination, a means for collecting transportation schedules and route information, a means for calculating an optimal route and generating it as integrated data, a means for presenting the generated integrated data to the user, a means for monitoring traffic conditions during travel and providing delay information in real time, and a means for recalculating an optimal alternative route in the event of a delay and presenting it to the user. This eliminates the hassle of using multiple applications and reduces stress during travel. Furthermore, by including a means for calculating a walking route and presenting it to the user and a means for identifying the nearest transfer station or bus stop, the user can receive integrated travel support. As a result, the present invention provides the user with smooth and comfortable travel.

[0006] "User" means an individual or group that uses the system to input information about a starting point and a destination and receives travel guidance.

[0007] The "starting point" refers to the location where the user begins their journey.

[0008] The "destination" refers to a location set by the user as the final destination of the journey.

[0009] "Means" refers to a method, apparatus, or part of a program for performing a particular function or role.

[0010] "Transportation" refers to public and private transportation means such as trains, buses, and taxis used for user transportation.

[0011] "Schedule" refers to a planned time sequence, such as a transportation timetable.

[0012] "Route Information" means detailed information about the route from a starting point to a destination, including transfer points, boarding locations, and walking routes.

[0013] "Integrated data" refers to data that combines information collected from different sources into one format.

[0014] "User interface (UI)" refers to the design and arrangement of screens and controls that allow users to input and receive information.

[0015] An "alternate route" is a new, optimal route when the primary route is unavailable or delayed.

[0016] A "map API" is an application program interface that provides geographic information and refers to the technical means for using it to obtain detailed geographic information such as walking routes.

[0017] "Nearest station" refers to the railway station closest to the point of departure or destination.

[0018] "Bus stop" means a stop where a bus allows passengers to board or disembark.

[0019] "Real-time" refers to immediate response or processing at the current time. [Brief explanation of the drawings]

[0020] [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

[0021] 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.

[0022] First, the terms used in the following description will be explained.

[0023] 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).

[0024] 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.

[0025] 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.

[0026] 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.

[0027] 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."

[0028] [First embodiment]

[0029] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0030] 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.

[0031] 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).

[0032] 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.

[0033] 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.

[0034] 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.

[0035] 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.

[0036] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0037] 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.

[0038] 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.

[0039] 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.

[0040] 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."

[0041] This invention relates to a service that allows users to travel smoothly from their departure point to their destination. This system allows users to input their departure point and destination, and then collects public transport schedules and route information in one place, calculates the optimal route, and presents it to the user as integrated data. It also monitors traffic conditions in real time during travel, and recalculates and notifies the user of the optimal alternative route in the event of a delay, providing users with a smooth and comfortable journey.

[0042] Processing flow and specific operations

[0043] User Input

[0044] 1. The user enters their home address (e.g., "26-1 Sakuragaoka-cho, Shibuya-ku, Tokyo") and the address of their destination (e.g., "a cafe near Shinjuku Station") into their mobile device or PC.

[0045] 2. The device converts this input information into an appropriate format (such as JSON) and sends it to the server.

[0046] Route calculation and information acquisition

[0047] 1. The server analyzes the home and destination information received from the device and calls the geographic information API to identify the nearest train station or bus stop near the home.

[0048] 2. The server calculates the transportation method (walking, bus, etc.) from home to the nearest station or bus stop, and then obtains route information from the nearest station or bus stop to the station nearest to the destination using a transportation API (train or bus timetable).

[0049] 3. The server integrates this information and returns the generated integrated data to the user terminal.

[0050] Display to users

[0051] 1. The terminal analyzes the integrated data received from the server and displays it in an appropriate UI to make the information easy for the user to understand.

[0052] 2. The device will highlight particularly important information (e.g., platform numbers for transfers and walking routes).

[0053] Support on the move

[0054] 1. The server monitors traffic information (train and bus operation status) in real time and calculates a new optimal route if a delay occurs.

[0055] 2. The server notifies the user terminal of the new optimal route.

[0056] 3. The device analyzes the new route information, notifies the user, and, if necessary, uses the map API again to calculate and display a new walking route.

[0057] Specific examples

[0058] For example, if a user wants to go from 26-1 Sakuragaokacho, Shibuya-ku, Tokyo to a cafe near Shinjuku Station, the user enters the address of the starting point and destination into a smartphone app. The device sends this information to a server, which then calculates the optimal route. The resulting route is to board the Yamanote Line from Shibuya Station, get off at Shinjuku Station, and walk five minutes from the west exit. If the Yamanote Line is delayed during travel, the server calculates an alternative route using the Saikyo Line and notifies the user's device. The device then displays the new route information and recalculates the walking route to the cafe and presents it to the user. After arriving at Shinjuku Station, detailed walking route instructions are displayed, allowing the user to reach their destination without getting lost.

[0059] This allows users to travel more smoothly without having to use multiple applications, and by monitoring traffic conditions in real time and providing adaptive support, it also reduces the frustration of unexpected delays.

[0060] The processing flow will be explained below.

[0061] Step 1:

[0062] Using a mobile device or PC, the user enters their home address (e.g., "26-1 Sakuragaokacho, Shibuya-ku, Tokyo") and the address of their destination (e.g., "a cafe near Shinjuku Station").

[0063] Step 2:

[0064] The terminal converts the input information into an appropriate format, such as JSON, and sends it to the server.

[0065] Step 3:

[0066] The server analyzes the home and destination information received from the terminal.

[0067] Step 4:

[0068] The server accesses a geographic information API to identify the nearest train station or bus stop near the user's home.

[0069] Step 5:

[0070] The server calculates the transportation method (walking, bus, etc.) from home to the nearest station or bus stop.

[0071] Step 6:

[0072] The server calls the transportation API (train and bus timetables) and obtains route information from the nearest station or bus stop to the station nearest to the destination.

[0073] Step 7:

[0074] The server uses a map API to calculate the walking route from the nearest station to the destination.

[0075] Step 8:

[0076] The server generates all the information it has acquired (nearest station, bus stop, train and bus departure times, boarding location, detailed transfer routes, walking routes, etc.) as integrated data.

[0077] Step 9:

[0078] The server returns the generated integrated data to the user terminal.

[0079] Step 10:

[0080] The terminal analyzes the integrated data received from the server.

[0081] Step 11:

[0082] The terminal displays the analyzed information using an appropriate UI so that the information can be easily understood by the user.

[0083] Step 12:

[0084] The device highlights particularly important information (such as platform numbers for transfers and walking routes).

[0085] Step 13:

[0086] The server monitors traffic information (train and bus operation status) in real time.

[0087] Step 14:

[0088] If a delay occurs during the journey, the server recalculates a new optimal route.

[0089] Step 15:

[0090] The server notifies the user terminal of the new optimum route.

[0091] Step 16:

[0092] The terminal analyzes the new route information and notifies the user.

[0093] Step 17:

[0094] The device will again use the map API to calculate and display a new walking route if necessary.

[0095] Step 18:

[0096] Once the user arrives at the station nearest to their destination, the device will display detailed walking route instructions to help the user reach their destination without getting lost.

[0097] Example 1

[0098] 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."

[0099] Conventional mobility assistance systems require users to individually collect information on different modes of transport and combine it to find the optimal route, which is extremely time-consuming. Furthermore, they are unable to respond immediately to changes in traffic conditions (such as delays or service cancellations), making it difficult to respond quickly when unexpected problems occur.

[0100] 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.

[0101] In this invention, the server includes means for a user to input a departure point and a destination, means for collecting public transportation schedules and route information, means for identifying the nearest transfer station or bus stop, means for calculating routes from the departure point to the nearest station and from the nearest station to the destination and generating the resulting integrated data, means for presenting the generated integrated data to the user, means for monitoring traffic conditions in real time during travel and providing delay information, and means for recalculating a new optimal route in the event of a delay and presenting the new optimal route to the user. This not only allows the user to have the optimal route from the departure point to the destination automatically calculated in a single system, but also allows for immediate response to any problems that may arise during travel, enabling smooth and comfortable travel.

[0102] A "user" is an individual or organization that utilizes the system to input a starting point and a destination and obtain optimal route information.

[0103] The "starting point" is the location where the user begins their journey.

[0104] A "destination" is a location where a user ultimately wants to arrive.

[0105] "Public transportation" means transportation available to the general public (e.g., trains, buses, subways, etc.).

[0106] "Schedule" refers to the operating hours and timetables of public transportation.

[0107] "Route information" refers to detailed information about a specific route (e.g., which stations or bus stops to transfer at, travel time, etc.).

[0108] The "nearest station" refers to the train station closest to the user's starting point or destination.

[0109] A "bus stop" is a place where buses stop and passengers board and disembark.

[0110] "Integrated data" refers to data that centrally compiles information on multiple routes.

[0111] "Real-time" refers to reflecting the current situation immediately.

[0112] "Traffic conditions" refers to the current operational status of transportation (e.g., delays, cancellations, etc.).

[0113] "Delay information" refers to information about public transportation being delayed from its scheduled time.

[0114] An "optimal route" is the most efficient route from a starting point to a destination.

[0115] An "alternate route" is a different route that is set up when the optimal route is not available.

[0116] The present invention relates to a system that enables users to travel smoothly from their departure point to their destination. This system allows users to input their departure point and destination, and then collects public transportation schedules and route information in one go, calculates the optimal route, and presents it to the user as integrated data. It also monitors traffic conditions in real time during travel, and if a delay occurs, recalculates the optimal alternative route and presents it to the user, providing users with a smooth and comfortable journey.

[0117] User Input

[0118] 1. The user inputs the starting point and destination using a mobile device or computer. In this case, an example of the starting point is "26-1 Sakuragaokacho, Shibuya-ku, Tokyo," and an example of the destination is "a cafe near Shinjuku Station."

[0119] 2. The terminal converts the input data into JSON format and sends it to the server. This process can be done using a general-purpose programming language such as JavaScript (registered trademark) or Python.

[0120] Server processing

[0121] 1. The server analyzes the data received from the device. To do this, it uses the Google (registered trademark) Maps API to obtain the latitude and longitude of the departure point and destination, and identifies the nearest train station or bus stop.

[0122] 2. The server uses the Google Maps API and the train operation information API to calculate the route from the starting point to the nearest station and from the nearest station to the destination. Specific route information includes walking routes, train timetables, transfer information, etc.

[0123] Integrated data generation and presentation

[0124] 1. The server integrates the acquired information into a single integrated data set. This integrated data set provides a unified view of the user's travel plan.

[0125] 2. The server converts the generated integrated data back into JSON format and sends it back to the user's device.

[0126] 3. The device analyzes the received integrated data and displays it in a visually easy-to-understand format for the user, with important information (such as transfer platform numbers and walking routes) highlighted.

[0127] Real-time support on the go

[0128] 1. The server uses the NAVITIME API, for example, to monitor traffic conditions in real time, thereby constantly monitoring train and bus delay information.

[0129] 2. The server recalculates a new optimal route when a delay occurs and sends that information to the user's device. A generative AI model can be used for the calculation process.

[0130] 3. The device analyzes the new route information and notifies the user, and if necessary, calculates and displays a new walking route using the Google Maps API again.

[0131] Specific examples

[0132] For example, if a user wants to go from 26-1 Sakuragaokacho, Shibuya-ku, Tokyo to a cafe near Shinjuku Station, they input their starting point and destination into the smartphone app. The device sends this information to the server, which then calculates the optimal route. The resulting route is a train ride from Shibuya Station, alighting at Shinjuku Station, and a five-minute walk to the cafe.

[0133] Prompt Sentence Examples

[0134] Design a system that calculates the optimal route for a user to go from 26-1 Sakuragaokacho, Shibuya-ku, Tokyo to a cafe near Shinjuku Station, and suggests alternative routes if there are public transport delays. Explain each step in natural language.

[0135] This allows users to travel more smoothly without having to switch between multiple applications, and by monitoring traffic conditions in real time and providing adaptive support, it also reduces the frustration of unexpected delays.

[0136] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0137] Step 1:

[0138] The user uses a mobile device or PC to input the starting point (e.g., "26-1 Sakuragaoka-cho, Shibuya-ku, Tokyo") and the destination (e.g., "a cafe near Shinjuku Station").

[0139] Specific behavior: A user opens the application, manually enters the starting point and destination in the input form, and presses the submit button when the input is complete.

[0140] Input and Output: The input is the address information of the starting point and the destination, and the output is these addresses formatted as JSON.

[0141] Step 2:

[0142] The terminal converts the data entered by the user into JSON format and sends it to the server.

[0143] What happens: The device application collects the input information, converts it to JSON format using JavaScript or Python code, and then sends an HTTP request to the corresponding API endpoint.

[0144] Input and Output: The input is the address information of the starting point and the destination, and the output is the JSON format data sent to the server.

[0145] Step 3:

[0146] The server analyzes the JSON data received from the device and calls the geographic information API to obtain the geographic information (latitude and longitude) of the departure and destination points.

[0147] What happens: The server parses the received JSON data, extracts the address information, and then sends a request to the Google Maps API to convert the address information into latitude and longitude coordinates.

[0148] Input and Output: The input is address information in JSON format, and the output is latitude and longitude information.

[0149] Step 4:

[0150] The server calls a geographic information API to identify the nearest transfer station or bus stop based on the geographic information of the departure point and destination.

[0151] Specific operation: The server also uses the Google Maps API to search for the nearest train station or bus stop based on the acquired latitude and longitude information.

[0152] Input and output: The input is the latitude and longitude information of the departure point and destination, and the output is the name and location information of the nearest station or bus stop.

[0153] Step 5:

[0154] Based on the information on the nearest station and bus stop, the server obtains the walking route from the starting point to the nearest station or bus stop from the Google Maps API.

[0155] Specific operation: The server requests a route search from the Google Maps API using the latitude and longitude of the starting point and the latitude and longitude of the nearest station or bus stop.

[0156] Input and output: The input is the latitude and longitude information of the starting point and the nearest station, and the output is walking route information.

[0157] Step 6:

[0158] The server calls the public transport API to obtain route information for public transport from the nearest station to the station nearest to the destination.

[0159] Specific operation: Based on the information of the nearest station to the departure point and the nearest station to the destination, the server sends a request to the public transportation API to obtain operation schedules and route information.

[0160] Input and output: The input is the name information of the nearest station to the departure point and the nearest station to the destination, and the output is public transport route information.

[0161] Step 7:

[0162] The server obtains walking route information from the nearest station to the destination from the Google Maps API.

[0163] Specific operation: The server requests a route search from the Google Maps API using the latitude and longitude of the station nearest to the destination and the latitude and longitude of the destination.

[0164] Input and output: The input is the nearest station to the destination and the latitude and longitude information of the destination, and the output is walking route information.

[0165] Step 8:

[0166] The server integrates all this information and generates a comprehensive travel plan.

[0167] Specific operation: The server integrates the acquired walking routes, public transport routes and transfer information and converts them into a single integrated data in JSON format.

[0168] Input and Output: The input is the route information obtained at each stage, and the output is the integrated data.

[0169] Step 9:

[0170] The server returns the generated integrated data to the user terminal.

[0171] Specific operation: The server sends the generated integrated data in JSON format to the user's device as an HTTP response.

[0172] Input and Output: The input is the generated integrated data, and the output is the integrated data sent to the user terminal.

[0173] Step 10:

[0174] The terminal analyzes the integrated data received from the server and displays it on the UI in a format that is easy for the user to understand.

[0175] Specific behavior: The device parses the received JSON data, extracts the necessary information, and displays it in the UI component, highlighting particularly important elements (such as platform number and detailed walking route).

[0176] Input and Output: The input is the consolidated data received from the server, and the output is the visual route information displayed to the user.

[0177] Step 11:

[0178] The server monitors traffic conditions in real time while traveling and recalculates a new optimal route if delays occur.

[0179] How it works: The server continuously retrieves data from the real-time traffic information API and recalculates a new route in the event of delays or cancellations.

[0180] Input and Output: The input is real-time traffic situation information, and the output is new optimal route information.

[0181] Step 12:

[0182] The server notifies the user terminal of the new optimum route.

[0183] Specific operation: The server retransmits the newly calculated route information to the user terminal and notifies it as an HTTP response.

[0184] Input and Output: The input is the new optimal route information, and the output is the notification to the user terminal.

[0185] Step 13:

[0186] The device analyzes the received new route information and presents it to the user again, recalculating and displaying a new walking route if necessary.

[0187] Specific behavior: The device parses the newly received JSON data, extracts the necessary information, and displays it in the UI. If necessary, it calculates a new walking route using the Google Maps API and presents it to the user again.

[0188] Input and Output: The input is the new route information received from the server, and the output is the new route information displayed to the user.

[0189] (Application example 1)

[0190] 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."

[0191] When autonomous vehicles travel, they often encounter different traffic conditions and obstacles, which can make smooth travel difficult. In particular, when transportation delays or accidents occur, appropriate responses cannot be made, causing great inconvenience to users. In addition, autonomous vehicles often lack the information they need to determine the optimal route in real time. To solve these problems, a system is needed that can obtain traffic information in real time and adaptively provide the optimal route.

[0192] 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.

[0193] In this invention, the server includes means for a user to input a departure point and a destination, means for collecting transportation schedules and route information, means for calculating an optimal route and generating it as integrated data, means for presenting the generated integrated data to the user, means for monitoring traffic conditions during travel and providing delay information in real time, means for recalculating an optimal alternative route in the event of a delay and presenting it to the user, means for collecting route information specifically for autonomous vehicles, means for generating instructions for the autonomous vehicle to travel the optimal route, and means for detecting traffic obstructions while the autonomous vehicle is in operation and calculating an alternative route. This enables smooth travel using autonomous vehicles based on real-time traffic information.

[0194] "Means for a user to input a starting point and a destination" refers to a device or interface that allows a user to input information about their starting point and destination.

[0195] "Means for collecting transport schedule and route information" refers to software and hardware for obtaining information on public transport schedules and routes and storing it in the system.

[0196] "Means for calculating the optimal route and generating it as integrated data" is a function that analyzes multiple routes based on collected information, calculates the most efficient route among them, and generates it as a single integrated data.

[0197] The "means for presenting the generated integrated data to the user" refers to a device or system for providing the calculated optimum route information to the user visually or audibly.

[0198] "Means for monitoring traffic conditions while traveling and providing delay information in real time" refers to technology that monitors traffic conditions in real time, detects delays and obstacles, and immediately notifies users.

[0199] "Means for recalculating the optimal alternative route in the event of a delay and presenting it to the user" is a function that calculates a new alternative route and notifies the user when a delay occurs on the planned route due to changes in traffic conditions.

[0200] "Means for collecting route information specifically for autonomous vehicles" refers to technologies and devices for collecting route information specifically for the operation of autonomous vehicles.

[0201] The "means for generating instructions for an autonomous vehicle to travel along an optimal route" is a function for generating specific instructions for operating an autonomous vehicle along an optimal route.

[0202] "Means for detecting obstacles while an autonomous vehicle is in operation and calculating an alternative route" refers to technology that allows an autonomous vehicle to detect obstacles while in operation and calculate a safe and efficient alternative route.

[0203] This invention provides a system that calculates an optimal route in real time and adaptively responds to traffic conditions when a user travels to a destination using an autonomous vehicle. This system includes the following configuration and functions.

[0204] System Configuration

[0205] 1. User Device

[0206] Smartphones, tablets, and vehicle-mounted head-mounted displays (HMDs)

[0207] This allows the user to input a starting point and a destination.

[0208] 2. Server

[0209] High-performance computing facilities in cloud environments or data centers

[0210] A back-end system for collecting transport schedule and route information and calculating optimal routes.

[0211] 3. Self-driving vehicles

[0212] Equipped with sensors such as GPS, cameras, LiDAR, and radar, it acquires location information and traffic conditions in real time.

[0213] It receives instructions from the server and moves along the optimal route.

[0214] Program processing

[0215] Data Acquisition and Input

[0216] The user terminal provides an interface for the user to input the starting point and destination. The information entered by the user is converted into an appropriate format, such as JSON, and sent to the server.

[0217] Route calculation

[0218] Based on the received departure and destination information, the server calls the transportation schedule API and geographic information API to calculate the optimal route.

[0219] Data Integration

[0220] The calculated route information is generated as a single integrated data set and sent back to the user's device, which analyzes the data and displays it in an easy-to-understand UI.

[0221] Real-time monitoring

[0222] The server monitors traffic conditions in real time, detecting delays and accidents. If a delay occurs, the server immediately recalculates the optimal alternative route and notifies the user.

[0223] Operation of autonomous vehicles

[0224] The autonomous vehicle receives instructions from the server and moves along the optimal route. If an obstacle is detected, the autonomous vehicle will calculate an alternative route and control itself to move safely.

[0225] Specific examples

[0226] For example, a user inputs their starting point "Shibuya" and destination "Shinjuku" on their smartphone. The device sends this information to a server, which then uses a public transport API to calculate the optimal route. As a result, a train route from Shibuya to Shinjuku is suggested. If a train is delayed during travel, the server recalculates an alternative route and notifies the application. The same applies when traveling in an autonomous vehicle, where traffic conditions are monitored in real time and the optimal route is provided.

[0227] Prompt Sentence Examples

[0228] "Design an app system that suggests the best route for a self-driving vehicle from Shibuya to Shinjuku in Tokyo, and notifies the driver by recalculating the route based on real-time traffic conditions."

[0229] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0230] Step 1:

[0231] Input: The user inputs a starting point and a destination.

[0232] Operation: The user device receives the departure and destination information entered by the user (e.g., "Shibuya" and "Shinjuku"). The user device converts this information into JSON format and sends it to the server.

[0233] Output: The start and end points are sent to the server in JSON format.

[0234] Step 2:

[0235] Input: The departure and destination information received by the server from the device.

[0236] How it works: The server analyzes the received departure and destination information and uses a geographic information API to identify the nearest train station or bus stop near the user's home. Based on this data, the server calculates the optimal route.

[0237] Output: Information on the nearest station and bus stop, as well as the best route information.

[0238] Step 3:

[0239] Input: Information on the nearest station or bus stop, and optimal route information.

[0240] How it works: The server collects route information from the nearest station or bus stop to the station nearest to the destination using public transport APIs (train and bus timetables). The collected information is compiled into a single integrated data set.

[0241] Output: Overall route information as consolidated data.

[0242] Step 4:

[0243] Input: Integrated data.

[0244] Operation: The server returns the generated integrated data to the user terminal, which receives and analyzes the integrated data.

[0245] Output: Parsed route information.

[0246] Step 5:

[0247] Input: Parsed route information.

[0248] Operation: The user device presents the analyzed route information to the user in an easy-to-read format, highlighting particularly important information (such as transfer platform numbers and walking routes).

[0249] Output: Optimal route information presented to the user.

[0250] Step 6:

[0251] Input: Real-time traffic data.

[0252] How it works: During the journey, the server monitors traffic conditions in real time, obtaining information about delays and obstacles. If a delay occurs, it recalculates a new optimal route.

[0253] Output: Delay information and best alternative route.

[0254] Step 7:

[0255] Input: The new optimal route.

[0256] Operation: The server notifies the user device of the new, recalculated optimal route. The user device analyzes the new route information and notifies the user. If necessary, it uses the map API to calculate and display the new walking route.

[0257] Output: The new optimal route information presented to the user.

[0258] Step 8:

[0259] Input: Real-time sensor information from an autonomous vehicle.

[0260] How it works: Autonomous vehicles acquire real-time location information and traffic conditions through sensors such as GPS, cameras, LiDAR, and radar. Based on the acquired data, they receive instructions from a server to move along the optimal route, and if they detect an obstacle, they calculate an alternative route themselves.

[0261] Output: Safe and efficient route.

[0262] 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.

[0263] This invention relates to a service that enables users to travel smoothly from their departure point to their destination. The system collects public transport schedules and route information in one place when the user inputs their departure point and destination, calculates the optimal route, and presents the integrated data to the user. It also has a function to monitor traffic conditions in real time during travel and recalculate the optimal alternative route and notify the user in the event of a delay.

[0264] Furthermore, the present invention incorporates an emotion engine that recognizes the user's emotions, using the user's facial recognition system and voice analysis system to detect the user's emotions, and can adjust the way guidance information is presented based on the user's emotions, or provide a more comfortable alternative route depending on the user's stress level.

[0265] Processing flow and specific operations

[0266] User Input

[0267] 1. The user enters their home address (e.g., "26-1 Sakuragaoka-cho, Shibuya-ku, Tokyo") and the address of their destination (e.g., "a cafe near Shinjuku Station") into their mobile device or PC.

[0268] 2. The device converts this input information into an appropriate format (such as JSON) and sends it to the server.

[0269] Route calculation and information acquisition

[0270] 1. The server analyzes the home and destination information received from the device and accesses the geographic information API to identify the nearest train station or bus stop near the home.

[0271] 2. The server calculates the transportation method (walking, bus, etc.) from home to the nearest station or bus stop.

[0272] 3. The server calls the transportation API (train and bus timetables) and obtains route information from the nearest station or bus stop to the station nearest to the destination.

[0273] 4. The server uses a map API to calculate the walking route from the nearest station to the destination.

[0274] 5. The server generates all the acquired information (nearest station, bus stop, train and bus departure times, boarding location, detailed transfer routes, walking routes, etc.) as integrated data.

[0275] 6. The server returns the generated integrated data to the user terminal.

[0276] Display to users and operation of the emotion engine

[0277] 1. The terminal analyzes the integrated data received from the server and displays the information using an appropriate UI to make it easy for the user to understand.

[0278] 2. The device will highlight particularly important information (e.g., platform numbers for transfers and walking routes).

[0279] 3. The device uses a built-in emotion engine to recognize the user's face and analyze their voice to detect their current emotions.

[0280] 4. The emotion engine adjusts the display method based on the user's emotions. For example, if it determines that the user is under high stress, it displays more detailed and concise guidance information.

[0281] 5. If the emotion engine detects the user's stress level, it notifies the server to provide an alternative relaxing route (e.g., an avoidance route or a route through a park).

[0282] Support on the move

[0283] 1. The server monitors traffic information (train and bus operation status) in real time.

[0284] 2. If a delay occurs during the journey, the server recalculates a new optimal route.

[0285] 3. The server notifies the user terminal of the new optimal route.

[0286] 4. The device analyzes the new route information and notifies the user.

[0287] 5. The device will calculate and display a new walking route, again using the Maps API if necessary.

[0288] 6. After the user arrives at the station nearest to their destination, the device will display detailed walking route instructions to help the user reach their destination without getting lost.

[0289] Specific examples

[0290] For example, if a user wants to go from 26-1 Sakuragaokacho, Shibuya-ku, Tokyo to a cafe near Shinjuku Station, the user enters the address of the starting point and destination into a smartphone app. The device sends this information to a server, which then calculates the optimal route. The resulting route is to board the Yamanote Line from Shibuya Station, get off at Shinjuku Station, and walk five minutes from the west exit. If the Yamanote Line is delayed during travel, the server calculates an alternative route using the Saikyo Line and notifies the user's device. The device then displays the new route information and recalculates the walking route to the cafe and presents it to the user.

[0291] Furthermore, if the emotion engine detects that the user is becoming tense during their trip, it will support them by displaying more detailed and easy-to-understand guidance information and offering relaxing alternative routes. This way, users can avoid the hassle of switching between multiple applications and enjoy a smoother journey. Furthermore, by monitoring traffic conditions in real time and utilizing the emotion engine to provide adaptive support, stress caused by unexpected delays can also be reduced.

[0292] The processing flow will be explained below.

[0293] Step 1:

[0294] Using a mobile device or PC, the user inputs their home address (e.g., "26-1 Sakuragaokacho, Shibuya-ku, Tokyo") and the address of their destination (e.g., "a cafe near Shinjuku Station").

[0295] Step 2:

[0296] The terminal converts the input information into an appropriate format (such as JSON) and sends it to the server.

[0297] Step 3:

[0298] The server analyzes the home and destination information received from the terminal.

[0299] Step 4:

[0300] The server accesses a geographic information API to identify the nearest train station or bus stop near the user's home.

[0301] Step 5:

[0302] The server calculates the transportation method (walking, bus, etc.) to the nearest station or bus stop.

[0303] Step 6:

[0304] The server calls the transportation API (train and bus timetables) and obtains route information from the nearest station or bus stop to the station nearest to the destination.

[0305] Step 7:

[0306] The server uses a map API to calculate the walking route from the nearest station to the destination.

[0307] Step 8:

[0308] The server generates all the information it has acquired (nearest station, bus stop, train and bus departure times, boarding location, detailed transfer routes, walking routes, etc.) as integrated data.

[0309] Step 9:

[0310] The server returns the generated integrated data to the user terminal.

[0311] Step 10:

[0312] The terminal analyzes the integrated data received from the server.

[0313] Step 11:

[0314] The terminal displays information using an appropriate UI to make it easy for the user to understand.

[0315] Step 12:

[0316] The device highlights particularly important information (e.g., platform numbers for transfers and walking routes).

[0317] Step 13:

[0318] The device uses a built-in emotion engine to recognize the user's face and analyze their voice to detect their current emotions.

[0319] Step 14:

[0320] The emotion engine adjusts the display method based on the user's emotions. For example, if it determines that the user is nervous, it displays more detailed and concise guidance information.

[0321] Step 15:

[0322] The server monitors traffic information (train and bus operation status) in real time.

[0323] Step 16:

[0324] If a delay occurs during the journey, the server recalculates a new optimal route.

[0325] Step 17:

[0326] The server notifies the user terminal of the new optimum route.

[0327] Step 18:

[0328] If the emotion engine detects the user's stress level, it notifies the server to provide an alternative route to relaxation (e.g., a route that avoids crowds or a route through a park).

[0329] Step 19:

[0330] The terminal analyzes the new route information and notifies the user.

[0331] Step 20:

[0332] The device will again use the map API to calculate and display a new walking route if necessary.

[0333] Step 21:

[0334] Once the user arrives at the station nearest to their destination, the device will display detailed walking route instructions to help the user reach their destination without getting lost.

[0335] Specific examples

[0336] For example, if a user wants to go from 26-1 Sakuragaokacho, Shibuya-ku, Tokyo to a cafe near Shinjuku Station, the user enters the address of the starting point and destination into a smartphone app. The device sends this information to a server, which then calculates the optimal route. The resulting route is to board the Yamanote Line from Shibuya Station, get off at Shinjuku Station, and walk five minutes from the west exit. If the Yamanote Line is delayed during travel, the server calculates an alternative route using the Saikyo Line and notifies the user's device. The device then displays the new route information and recalculates the walking route to the cafe and presents it to the user.

[0337] Furthermore, if the emotion engine detects that the user is becoming tense during their trip, it will support them by displaying more detailed and easy-to-understand guidance information and offering relaxing alternative routes. This way, users can avoid the hassle of switching between multiple applications and enjoy a smoother journey. Furthermore, by monitoring traffic conditions in real time and utilizing the emotion engine to provide adaptive support, stress caused by unexpected delays can also be reduced.

[0338] Example 2

[0339] 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."

[0340] In modern transportation systems, users are required to efficiently plan the optimal route from their departure point to their destination. However, individually collecting information such as transportation schedules, route information, and real-time delay information is time-consuming and places a significant burden on users. Furthermore, users are prone to stress due to the lack of means to quickly respond when a delay occurs during travel. Furthermore, users' emotional state is not taken into consideration, which can increase stress during travel. These are important issues that need to be resolved.

[0341] 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.

[0342] In this invention, the server includes a means for collecting public transportation schedules and route information, a means for identifying the nearest station or bus stop and calculating the optimal route, and a means for detecting the user's emotions and providing guidance information in an adaptive manner. This allows the server to provide all the information the user needs in one place and quickly respond to delays during travel. Furthermore, providing guidance information according to the user's emotional state can reduce stress during travel.

[0343] "User" refers to an individual or organization that uses the system to obtain route information from a starting point to a destination.

[0344] The "starting point" indicates the location where the user starts moving.

[0345] A "destination" indicates the location where the user completes their journey.

[0346] "Public transportation" refers to public transportation means such as trains and buses.

[0347] "Schedule" refers to information about the operating hours and departure times of public transportation.

[0348] "Route information" refers to information about the route from the starting point to the destination.

[0349] "Nearest station" refers to the train station closest to the departure point or destination.

[0350] "Bus stop" refers to the bus stop closest to the departure point or destination.

[0351] The "optimal route" refers to the route that best satisfies conditions such as travel time and number of transfers.

[0352] "Integrated data" refers to data obtained from multiple sources that are combined into one.

[0353] "Traffic conditions" refers to the operation status of public transportation and road congestion.

[0354] "Delay information" refers to information when public transportation services are delayed from their scheduled times.

[0355] An "alternate route" is a different route used in the event of a delay or other problem.

[0356] "Emotion" refers to the user's state of mind.

[0357] "Emotion detection" refers to determining a user's emotional state from their facial expressions and voice.

[0358] "Adaptive method" refers to a method of changing the form and content of information provided depending on the emotional state of the user.

[0359] The present invention relates to a system that enables users to travel smoothly from their starting point to their destination. This system calculates the optimal route by inputting the user's starting point and destination, and presents the route to the user as integrated data. It also has the function of monitoring traffic conditions in real time during travel and recalculating the optimal alternative route in the event of a delay. Furthermore, the system incorporates an emotion engine that recognizes the user's emotions, and can adjust the way in which guidance information is presented based on the user's emotional state.

[0360] System Configuration

[0361] Hardware and Software Configuration

[0362] This system mainly consists of the following hardware and software:

[0363] 1. Terminal: A device such as a smartphone or PC that allows the user to input their starting point and destination. The terminal must be equipped with an internet connection, a camera, and a microphone.

[0364] 2. Server: A cloud-based system that analyzes data and calculates routes. The server has high-speed processing power and storage capacity to manage large amounts of data.

[0365] 3. API: An interface for obtaining route information, such as a geographical information API (e.g., Google Maps API) or a public transportation API (e.g., NAVITIME API).

[0366] 4. Emotion engine: Software that recognizes the user's face and analyzes their voice to detect their emotions.

[0367] Program processing flow and specific examples

[0368] User Input

[0369] The user enters their home address (e.g., "26-1 Sakuragaokacho, Shibuya-ku, Tokyo") and the address of their destination (e.g., "a cafe near Shinjuku Station") into their mobile device or PC. The device converts this input information into a format such as JSON and sends it to the server.

[0370] Route calculation and information integration

[0371] The server analyzes the home and destination information received from the device and identifies the nearest train station or bus stop near the home by accessing the Google Maps API. It then uses the NAVITIME API and other services to obtain public transportation schedules and route information and calculates the optimal route from the home to the destination. It then generates integrated data from all the information it has obtained and sends it back to the user's device.

[0372] Information presentation to users and operation of the emotion engine

[0373] The device analyzes the integrated data received from the server and displays the information in an easy-to-understand UI. It highlights particularly important information (e.g., platform numbers for transfers and walking routes). It also uses an emotion engine to analyze the user's face and voice and adjusts the display method based on the user's emotions. If the device determines that the user is under high stress, it displays more detailed and concise guidance information and offers relaxing alternative routes.

[0374] Support on the move

[0375] The server monitors traffic information in real time, and if a delay occurs during travel, it recalculates a new optimal route and notifies the user's device. The device then analyzes the new route information and notifies the user, allowing the user to continue traveling smoothly.

[0376] Specific examples

[0377] For example, if a user wants to go from 26-1 Sakuragaokacho, Shibuya-ku, Tokyo to a cafe near Shinjuku Station, the user enters the address of the starting point and destination into a smartphone app. The device sends this information to the server, which then uses the Google Maps API and NAVITIME API to calculate the optimal route. The resulting route is to board the Yamanote Line from Shibuya Station, get off at Shinjuku Station, and walk five minutes from the west exit. If the Yamanote Line is delayed during travel, the server calculates an alternative route using the Saikyo Line and notifies the user's device. The device then displays the new route information and recalculates the walking route to the cafe and presents it to the user.

[0378] Prompt Sentence Examples

[0379] "Please calculate the optimal route from the starting point '26-1 Sakuragaokacho, Shibuya-ku, Tokyo' to the destination 'a cafe near Shinjuku Station'. Please also include a detailed walking route to the destination. If possible, please also provide guidance on what to do if you become nervous during the trip."

[0380] The present invention provides users with all the traffic information they need in one place, allowing for quick responses to delays while traveling, and by providing information based on the user's emotional state, it is possible to reduce stress while traveling.

[0381] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0382] Step 1: User Input

[0383] The user enters their home address (e.g., "26-1 Sakuragaokacho, Shibuya-ku, Tokyo") and the address of their destination (e.g., "a cafe near Shinjuku Station") into a dedicated application on their smartphone or PC. The entered information is the user's starting point and destination data. When the user presses the "Search" button, the device receives this information and sends it to the next processing step.

[0384] input:

[0385] Address of departure point (e.g., "26-1 Sakuragaokacho, Shibuya-ku, Tokyo")

[0386] Destination address (e.g., "a cafe near Shinjuku Station")

[0387] output:

[0388] Origin and destination data converted to JSON format

[0389] Specific behavior:

[0390] The user enters address information into the application's input field and presses the "Search" button to complete the input.

[0391] Step 2: Send device data

[0392] The terminal converts the address data entered by the user into JSON format and sends it to the server. This conversion is for the purpose of improving data consistency and transmission efficiency. The terminal then sends this data to the server as an HTTP POST request.

[0393] input:

[0394] Origin and destination data converted to JSON format

[0395] output:

[0396] The HTTP POST request sent to the server

[0397] Specific behavior:

[0398] The terminal converts the data entered by the user into JSON format and sends it as an HTTP POST request to the server.

[0399] Step 3: Data analysis and route calculation on the server

[0400] 1. Data analysis: The server analyzes the address information received from the terminal to identify the starting point and destination.

[0401] 2. Identifying the nearest station or bus stop: The server uses the geographic information API to identify the nearest station or bus stop near the departure point.

[0402] 3. Calculating transportation: The server calculates the appropriate transportation method (walking, bus, etc.) from home to the nearest station or bus stop.

[0403] 4. Obtain route information: The server uses the public transport API to obtain public transport schedule and route information.

[0404] 5. Calculating walking route: The server calculates the walking route from the nearest station to the destination to the destination.

[0405] 6. Generation of integrated data: All acquired information is integrated to generate comprehensive route data.

[0406] input:

[0407] HTTP POST request sent to the server

[0408] Origin and destination information based on geographical API

[0409] Schedule and route information obtained from public transport APIs

[0410] output:

[0411] Integrated Route Data

[0412] Specific behavior:

[0413] The server uses a programming language such as Python to send requests to the Google Maps API or NAVITIME API, obtain the necessary data, and generate integrated data.

[0414] Step 4: Sending route information from the server to the device

[0415] The server then sends the generated integrated data back to the device, which includes the nearest stations, departure times, transfer details, walking routes, etc.

[0416] input:

[0417] Integrated Route Data

[0418] output:

[0419] Route data sent to the device as an HTTP response

[0420] Specific behavior:

[0421] The server sends the integrated data to the terminal as an HTTP response.

[0422] Step 5: Displaying consolidated data on the terminal

[0423] The device analyzes the integrated data received from the server and displays the information on the UI of a dedicated application, highlighting particularly important information (e.g., platform numbers for transfers and walking routes).

[0424] input:

[0425] Aggregated data received from the server

[0426] output:

[0427] Route information displayed to users

[0428] Specific behavior:

[0429] The terminal analyzes the data received from the server and displays it in the format best suited to the application.

[0430] Step 6: Detect and adjust user emotions with the emotion engine

[0431] 1. Facial recognition and voice analysis: The device's built-in emotion engine performs facial recognition and voice analysis of the user.

[0432] 2. Display content adjustment: The emotion engine adjusts the display content based on the detected emotions. If stress is detected to be high, the guidance information will be displayed in more detail and concisely.

[0433] 3. Providing alternative routes: The emotion engine sends a notification to the server to provide alternative routes to relax depending on the user's stress level.

[0434] input:

[0435] User's facial image and voice data

[0436] output:

[0437] Adjusted guidance information

[0438] Notifying the server

[0439] Specific behavior:

[0440] The device's camera and microphone collect the user's face and voice, and the emotion engine analyzes them to determine the user's emotions. The system adjusts the display content to take appropriate action and sends notifications to the server as necessary.

[0441] Step 7: Real-time traffic monitoring and route updates

[0442] 1. Traffic information monitoring: The server monitors the train and bus operation status in real time.

[0443] 2. Recalculation on Delay: If a delay occurs during travel, the server recalculates a new optimal route.

[0444] 3. Notification to the terminal: The server notifies the terminal of the new route information.

[0445] 4. Displaying the new route: The device analyzes the new route information and notifies the user. If necessary, it calculates and displays a new walking route using the map API.

[0446] input:

[0447] Real-time traffic information

[0448] output:

[0449] New route information

[0450] Specific behavior:

[0451] The server periodically calls the traffic information API to obtain the current operating conditions, and if a delay occurs, calculates a new optimal route and notifies the device. The device then displays the new route to the user.

[0452] Through the above process, users can obtain optimal route information and receive real-time support while traveling. This system is expected to make users' travels smoother and stress-free.

[0453] (Application example 2)

[0454] 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."

[0455] The present invention relates to a system that enables users to travel smoothly and comfortably. Conventional mobility assistance systems have limitations in optimizing routes and providing delay information, and are unable to consider the user's emotional state. Furthermore, the control of autonomous vehicles is limited, making it difficult to provide an optimal travel experience. Therefore, there is a need for systems that can present guidance information according to the user's emotional state and enable smooth travel using autonomous vehicles.

[0456] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0457] In this invention, the server includes: means for a user to input a departure point and a destination; means for collecting transportation schedules and route information; means for calculating an optimal route and generating it as integrated data; means for presenting the generated integrated data to the user; means for monitoring traffic conditions during travel and providing delay information in real time; means for recalculating an optimal alternative route in the event of a delay and presenting it to the user; means for adjusting the presentation method of guidance information based on the user's emotions, which includes an emotion engine that recognizes the user's emotions; means for sending instructions about the optimal route to an autonomous vehicle and means for controlling the autonomous vehicle. This enables smooth and comfortable travel by utilizing an autonomous vehicle that adapts to the user's emotional state.

[0458] The "means by which a user inputs their starting point and destination" refers to the interface that a user uses to set a route to their destination, and is provided through a device such as a smartphone, tablet, or PC.

[0459] "Means for collecting transport schedule and route information" refers to a system or module for obtaining timetables and route information for transport such as trains and buses, and collects information using APIs and databases.

[0460] The "means for calculating the optimal route and generating it as integrated data" refers to an algorithm and calculation system for calculating the optimal travel route based on the starting point and destination entered by the user and generating the result as integrated data.

[0461] The "means for presenting the generated integrated data to the user" refers to an interface that visually or audibly presents the calculated optimal route to the user, and displays the information through a display such as a smartphone or smart glasses.

[0462] "Means for monitoring traffic conditions while traveling and providing delay information in real time" refers to a system for monitoring the real-time conditions of roads and transportation facilities while traveling and providing delay information to users immediately.

[0463] "Means for recalculating the optimal alternative route in the event of a delay and presenting it to the user" refers to an algorithm and interface for recalculating the optimal route when a delay occurs in a transportation service or route and presenting that information to the user.

[0464] An "emotion engine that recognizes the user's emotions" is software or hardware that can analyze the user's facial expressions and voice data and detect their current emotional state.

[0465] The "means for adjusting the method of presenting guidance information" is a system that dynamically changes the method and timing of displaying guidance information based on the detected emotional state of the user.

[0466] The "means for transmitting optimal route instructions to an autonomous vehicle" is a system for communicating information about the calculated optimal route to an autonomous vehicle and transmitting the instructions to the vehicle.

[0467] The "means for controlling an autonomous vehicle" refers to hardware and software for appropriately controlling the autonomous vehicle in accordance with the received optimal route.

[0468] The present invention is a support system for users to travel smoothly from their starting point to their destination. This system realizes comfortable travel by providing real-time information on transportation and the optimal route according to the user's emotional state. Furthermore, the invention supports travel using autonomous vehicles.

[0469] System configuration

[0470] The system consists of the following main components:

[0471] 1. User Input Method

[0472] The user inputs the starting point and destination using a device such as a smartphone, smart glasses, or tablet.

[0473] 2. Means of collecting transportation information

[0474] The server utilizes an API (e.g., Google Maps API) to collect transportation schedule and route information.

[0475] 3. Route calculation method

[0476] The server calculates the optimal route based on the collected information and generates the results as integrated data.

[0477] 4. Integrated Data Presentation Method

[0478] The generated integrated data is presented on the user terminal, and guidance information is provided visually and audibly.

[0479] 5. Traffic monitoring means

[0480] The server monitors traffic conditions in real time and provides delay information to users.

[0481] 6. Alternative Route Calculation Methods

[0482] If a delay occurs, the server recalculates a new optimal route and presents it to the user.

[0483] 7. Emotion Engine

[0484] It uses the camera and microphone built into the user's device to incorporate an emotion engine that recognizes emotions (e.g., Affectiva SDK).

[0485] The emotion engine adjusts how the guidance information is displayed based on the user's emotional state.

[0486] 8. Autonomous Vehicle Control Methods

[0487] The server instructs the autonomous vehicle on the optimal route and controls the vehicle appropriately.

[0488] Specific examples of processing

[0489] The user uses the smart glasses to voice-input their home address and destination address. The device then sends this information to the server, which then uses a public transport API to calculate the optimal route. The calculation results are displayed on the smart glasses' display. If a public transport delay occurs during travel, the server automatically calculates a new route and provides that information to the user.

[0490] The smart glasses' camera and microphone are also used to analyze the user's facial and voice data with an emotion engine to recognize their emotional state. For example, if the system determines that the user is nervous, it will display more detailed and easy-to-understand guidance information and suggest a relaxing route. In this way, providing guidance information that adapts to the user's emotional state can reduce stress during travel.

[0491] Furthermore, when using an autonomous vehicle, the server sends instructions for the optimal route to the vehicle, which then performs autonomous driving according to those instructions, allowing the user to travel smoothly and safely from their starting point to their destination.

[0492] Prompt Sentence Examples

[0493] Below is an example of a prompt sentence to input to the generative AI model.

[0494] Enter the user's starting point and destination. Write a program to calculate the route and display it on the smart glasses. It should also analyze the user's emotional state and suggest a relaxing route. Write the program in Python and explain how to use any necessary libraries and APIs. Below is an example of input data.

[0495] The present invention enables smooth and comfortable travel using autonomous vehicles that adapt to the user's emotional state.

[0496] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0497] Step 1:

[0498] The user inputs a starting point and a destination.

[0499] Input: The user puts on the smart glasses and enters the starting point and destination by voice.

[0500] How it works: The device recognizes the input as text data and converts it into a format (e.g., JSON).

[0501] Output: Formatted text data is generated.

[0502] Step 2:

[0503] The terminal sends the input data to the server.

[0504] Input: Text data of the starting point and destination entered by the user.

[0505] How it works: The device uses a communication protocol (e.g. HTTP) to send this data to the server.

[0506] Output: The server receives the request.

[0507] Step 3:

[0508] A server collects transportation schedule and route information.

[0509] Input: The origin and destination data sent to the server.

[0510] How it works: The server calls a transit API (e.g., Google Maps API) to get the necessary schedule and route information.

[0511] Output: Transit schedules and route information.

[0512] Step 4:

[0513] The server calculates the optimal route and generates it as integrated data.

[0514] Input: Transit schedule and route information.

[0515] How it works: The server uses the collected information to run algorithms and calculate the optimal route. The results are then compiled into a consolidated data set.

[0516] Output: Consolidated data of optimal routes.

[0517] Step 5:

[0518] The server transmits the integrated data to the terminal.

[0519] Input: Optimal route synthesis data.

[0520] Operation: The server sends the generated integrated data to the terminal.

[0521] Output: The terminal receives the consolidated data.

[0522] Step 6:

[0523] The terminal presents the integrated data to the user.

[0524] Input: The aggregate data received from the server.

[0525] Operation: The device analyzes the integrated data and displays guidance information visually or audibly on the display.

[0526] Output: The user is presented with a guide.

[0527] Step 7:

[0528] The server monitors traffic conditions in real time while on the move.

[0529] Input: Real-time traffic data.

[0530] Operation: The server periodically calls the transport API to monitor real-time traffic conditions.

[0531] Output: Traffic updates.

[0532] Step 8:

[0533] The terminal provides delay information to the user.

[0534] Input: Traffic updates.

[0535] Operation: If a delay occurs, the server recalculates a new optimal route and sends that information to the terminal, which then receives it and notifies the user.

[0536] Output: The latest guidance information is presented to the user.

[0537] Step 9:

[0538] The terminal recognizes the user's emotional state.

[0539] Input: User's facial expression data and voice data.

[0540] How it works: The device uses its built-in camera and microphone to collect data, which is then analyzed by an emotion engine.

[0541] Output: User's emotional state (e.g. stress level).

[0542] Step 10:

[0543] The server adjusts how the guidance information is presented.

[0544] Input: The user's emotional state.

[0545] Operation: The server dynamically adjusts the display method and content of the guidance information based on the output of the emotion engine.

[0546] Output: Adjusted guidance information.

[0547] Step 11:

[0548] The server sends optimal route instructions to the autonomous vehicle.

[0549] Input: The final calculated or recalculated optimal route.

[0550] Operation: The server communicates with the autonomous vehicle and sends it the optimal route.

[0551] Output: The autonomous vehicle receives and executes the optimal route.

[0552] Step 12:

[0553] An autonomous vehicle transports the user to their destination.

[0554] Input: Optimal route instructions sent by the server.

[0555] Action: The autonomous driving system starts driving according to the optimal route and takes the user to their destination.

[0556] Output: The user reaches the destination.

[0557] 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.

[0558] 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.

[0559] 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.

[0560] [Second embodiment]

[0561] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0562] 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.

[0563] 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).

[0564] 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.

[0565] 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.

[0566] 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).

[0567] 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. 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.

[0568] 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.

[0569] 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.

[0570] 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.

[0571] In the smart glasses 214, the 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.

[0572] 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."

[0573] This invention relates to a service that allows users to travel smoothly from their departure point to their destination. This system allows users to input their departure point and destination, and then collects public transport schedules and route information in one place, calculates the optimal route, and presents it to the user as integrated data. It also monitors traffic conditions in real time during travel, and recalculates and notifies the user of the optimal alternative route in the event of a delay, providing users with a smooth and comfortable journey.

[0574] Processing flow and specific operations

[0575] User Input

[0576] 1. The user enters their home address (e.g., "26-1 Sakuragaoka-cho, Shibuya-ku, Tokyo") and the address of their destination (e.g., "a cafe near Shinjuku Station") into their mobile device or PC.

[0577] 2. The device converts this input information into an appropriate format (such as JSON) and sends it to the server.

[0578] Route calculation and information acquisition

[0579] 1. The server analyzes the home and destination information received from the device and calls the geographic information API to identify the nearest train station or bus stop near the home.

[0580] 2. The server calculates the transportation method (walking, bus, etc.) from home to the nearest station or bus stop, and then obtains route information from the nearest station or bus stop to the station nearest to the destination using a transportation API (train or bus timetable).

[0581] 3. The server integrates this information and returns the generated integrated data to the user terminal.

[0582] Display to users

[0583] 1. The terminal analyzes the integrated data received from the server and displays it in an appropriate UI to make the information easy for the user to understand.

[0584] 2. The device will highlight particularly important information (e.g., platform numbers for transfers and walking routes).

[0585] Support on the move

[0586] 1. The server monitors traffic information (train and bus operation status) in real time and calculates a new optimal route if a delay occurs.

[0587] 2. The server notifies the user terminal of the new optimal route.

[0588] 3. The device analyzes the new route information, notifies the user, and, if necessary, uses the map API again to calculate and display a new walking route.

[0589] Specific examples

[0590] For example, if a user wants to go from 26-1 Sakuragaokacho, Shibuya-ku, Tokyo to a cafe near Shinjuku Station, the user enters the address of the starting point and destination into a smartphone app. The device sends this information to a server, which then calculates the optimal route. The resulting route is to board the Yamanote Line from Shibuya Station, get off at Shinjuku Station, and walk five minutes from the west exit. If the Yamanote Line is delayed during travel, the server calculates an alternative route using the Saikyo Line and notifies the user's device. The device then displays the new route information and recalculates the walking route to the cafe and presents it to the user. After arriving at Shinjuku Station, detailed walking route instructions are displayed, allowing the user to reach their destination without getting lost.

[0591] This allows users to travel more smoothly without having to use multiple applications, and by monitoring traffic conditions in real time and providing adaptive support, it also reduces the frustration of unexpected delays.

[0592] The processing flow will be explained below.

[0593] Step 1:

[0594] Using a mobile device or PC, the user enters their home address (e.g., "26-1 Sakuragaokacho, Shibuya-ku, Tokyo") and the address of their destination (e.g., "a cafe near Shinjuku Station").

[0595] Step 2:

[0596] The terminal converts the input information into an appropriate format, such as JSON, and sends it to the server.

[0597] Step 3:

[0598] The server analyzes the home and destination information received from the terminal.

[0599] Step 4:

[0600] The server accesses a geographic information API to identify the nearest train station or bus stop near the user's home.

[0601] Step 5:

[0602] The server calculates the transportation method (walking, bus, etc.) from home to the nearest station or bus stop.

[0603] Step 6:

[0604] The server calls the transportation API (train and bus timetables) and obtains route information from the nearest station or bus stop to the station nearest to the destination.

[0605] Step 7:

[0606] The server uses a map API to calculate the walking route from the nearest station to the destination.

[0607] Step 8:

[0608] The server generates all the information it has acquired (nearest station, bus stop, train and bus departure times, boarding location, detailed transfer routes, walking routes, etc.) as integrated data.

[0609] Step 9:

[0610] The server returns the generated integrated data to the user terminal.

[0611] Step 10:

[0612] The terminal analyzes the integrated data received from the server.

[0613] Step 11:

[0614] The terminal displays the analyzed information using an appropriate UI so that the information can be easily understood by the user.

[0615] Step 12:

[0616] The device highlights particularly important information (such as platform numbers for transfers and walking routes).

[0617] Step 13:

[0618] The server monitors traffic information (train and bus operation status) in real time.

[0619] Step 14:

[0620] If a delay occurs during the journey, the server recalculates a new optimal route.

[0621] Step 15:

[0622] The server notifies the user terminal of the new optimum route.

[0623] Step 16:

[0624] The terminal analyzes the new route information and notifies the user.

[0625] Step 17:

[0626] The device will again use the map API to calculate and display a new walking route if necessary.

[0627] Step 18:

[0628] Once the user arrives at the station nearest to their destination, the device will display detailed walking route instructions to help the user reach their destination without getting lost.

[0629] Example 1

[0630] 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."

[0631] Conventional mobility assistance systems require users to individually collect information on different modes of transport and combine it to find the optimal route, which is extremely time-consuming. Furthermore, they are unable to respond immediately to changes in traffic conditions (such as delays or service cancellations), making it difficult to respond quickly when unexpected problems occur.

[0632] 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.

[0633] In this invention, the server includes means for a user to input a departure point and a destination, means for collecting public transportation schedules and route information, means for identifying the nearest transfer station or bus stop, means for calculating routes from the departure point to the nearest station and from the nearest station to the destination and generating the resulting integrated data, means for presenting the generated integrated data to the user, means for monitoring traffic conditions in real time during travel and providing delay information, and means for recalculating a new optimal route in the event of a delay and presenting the new optimal route to the user. This not only allows the user to have the optimal route from the departure point to the destination automatically calculated in a single system, but also allows for immediate response to any problems that may arise during travel, enabling smooth and comfortable travel.

[0634] A "user" is an individual or organization that utilizes the system to input a starting point and a destination and obtain optimal route information.

[0635] The "starting point" is the location where the user begins their journey.

[0636] A "destination" is a location where a user ultimately wants to arrive.

[0637] "Public transportation" means transportation available to the general public (e.g., trains, buses, subways, etc.).

[0638] "Schedule" refers to the operating hours and timetables of public transportation.

[0639] "Route information" refers to detailed information about a specific route (e.g., which stations or bus stops to transfer at, travel time, etc.).

[0640] The "nearest station" refers to the train station closest to the user's starting point or destination.

[0641] A "bus stop" is a place where buses stop and passengers board and disembark.

[0642] "Integrated data" refers to data that centrally compiles information on multiple routes.

[0643] "Real-time" refers to reflecting the current situation immediately.

[0644] "Traffic conditions" refers to the current operational status of transportation (e.g., delays, cancellations, etc.).

[0645] "Delay information" refers to information about public transportation being delayed from its scheduled time.

[0646] An "optimal route" is the most efficient route from a starting point to a destination.

[0647] An "alternate route" is a different route that is set up when the optimal route is not available.

[0648] The present invention relates to a system that enables users to travel smoothly from their departure point to their destination. This system allows users to input their departure point and destination, and then collects public transportation schedules and route information in one go, calculates the optimal route, and presents it to the user as integrated data. It also monitors traffic conditions in real time during travel, and if a delay occurs, recalculates the optimal alternative route and presents it to the user, providing users with a smooth and comfortable journey.

[0649] User Input

[0650] 1. The user inputs the starting point and destination using a mobile device or computer. In this case, an example of the starting point is "26-1 Sakuragaokacho, Shibuya-ku, Tokyo," and an example of the destination is "a cafe near Shinjuku Station."

[0651] 2. The terminal converts the input data into JSON format and sends it to the server. This process can be done using general-purpose programming languages ​​such as JavaScript and Python.

[0652] Server processing

[0653] 1. The server analyzes the data received from the device. To do this, it uses the Google Maps API to obtain the latitude and longitude of the departure and destination points and identifies the nearest train station or bus stop.

[0654] 2. The server uses the Google Maps API and the train operation information API to calculate the route from the starting point to the nearest station and from the nearest station to the destination. Specific route information includes walking routes, train timetables, transfer information, etc.

[0655] Integrated data generation and presentation

[0656] 1. The server integrates the acquired information into a single integrated data set. This integrated data set provides a unified view of the user's travel plan.

[0657] 2. The server converts the generated integrated data back into JSON format and sends it back to the user's device.

[0658] 3. The device analyzes the received integrated data and displays it in a visually easy-to-understand format for the user, with important information (such as transfer platform numbers and walking routes) highlighted.

[0659] Real-time support on the go

[0660] 1. The server uses the NAVITIME API, for example, to monitor traffic conditions in real time, thereby constantly monitoring train and bus delay information.

[0661] 2. The server recalculates a new optimal route when a delay occurs and sends that information to the user's device. A generative AI model can be used for the calculation process.

[0662] 3. The device analyzes the new route information and notifies the user, and if necessary, calculates and displays a new walking route using the Google Maps API again.

[0663] Specific examples

[0664] For example, if a user wants to go from 26-1 Sakuragaokacho, Shibuya-ku, Tokyo to a cafe near Shinjuku Station, they input their starting point and destination into the smartphone app. The device sends this information to the server, which then calculates the optimal route. The resulting route is a train ride from Shibuya Station, alighting at Shinjuku Station, and a five-minute walk to the cafe.

[0665] Prompt Sentence Examples

[0666] Design a system that calculates the optimal route for a user to go from 26-1 Sakuragaokacho, Shibuya-ku, Tokyo to a cafe near Shinjuku Station, and suggests alternative routes if there are public transport delays. Explain each step in natural language.

[0667] This allows users to travel more smoothly without having to switch between multiple applications, and by monitoring traffic conditions in real time and providing adaptive support, it also reduces the frustration of unexpected delays.

[0668] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0669] Step 1:

[0670] The user uses a mobile device or PC to input the starting point (e.g., "26-1 Sakuragaoka-cho, Shibuya-ku, Tokyo") and the destination (e.g., "a cafe near Shinjuku Station").

[0671] Specific behavior: A user opens the application, manually enters the starting point and destination in the input form, and presses the submit button when the input is complete.

[0672] Input and Output: The input is the address information of the starting point and the destination, and the output is these addresses formatted as JSON.

[0673] Step 2:

[0674] The terminal converts the data entered by the user into JSON format and sends it to the server.

[0675] What happens: The device application collects the input information, converts it to JSON format using JavaScript or Python code, and then sends an HTTP request to the corresponding API endpoint.

[0676] Input and Output: The input is the address information of the starting point and the destination, and the output is the JSON format data sent to the server.

[0677] Step 3:

[0678] The server analyzes the JSON data received from the device and calls the geographic information API to obtain the geographic information (latitude and longitude) of the departure and destination points.

[0679] What happens: The server parses the received JSON data, extracts the address information, and then sends a request to the Google Maps API to convert the address information into latitude and longitude coordinates.

[0680] Input and Output: The input is address information in JSON format, and the output is latitude and longitude information.

[0681] Step 4:

[0682] The server calls a geographic information API to identify the nearest transfer station or bus stop based on the geographic information of the departure point and destination.

[0683] Specific operation: The server also uses the Google Maps API to search for the nearest train station or bus stop based on the acquired latitude and longitude information.

[0684] Input and output: The input is the latitude and longitude information of the departure point and destination, and the output is the name and location information of the nearest station or bus stop.

[0685] Step 5:

[0686] Based on the information on the nearest station and bus stop, the server obtains the walking route from the starting point to the nearest station or bus stop from the Google Maps API.

[0687] Specific operation: The server requests a route search from the Google Maps API using the latitude and longitude of the starting point and the latitude and longitude of the nearest station or bus stop.

[0688] Input and output: The input is the latitude and longitude information of the starting point and the nearest station, and the output is walking route information.

[0689] Step 6:

[0690] The server calls the public transport API to obtain route information for public transport from the nearest station to the station nearest to the destination.

[0691] Specific operation: Based on the information of the nearest station to the departure point and the nearest station to the destination, the server sends a request to the public transportation API to obtain operation schedules and route information.

[0692] Input and output: The input is the name information of the nearest station to the departure point and the nearest station to the destination, and the output is public transport route information.

[0693] Step 7:

[0694] The server obtains walking route information from the nearest station to the destination from the Google Maps API.

[0695] Specific operation: The server requests a route search from the Google Maps API using the latitude and longitude of the station nearest to the destination and the latitude and longitude of the destination.

[0696] Input and output: The input is the nearest station to the destination and the latitude and longitude information of the destination, and the output is walking route information.

[0697] Step 8:

[0698] The server integrates all this information and generates a comprehensive travel plan.

[0699] Specific operation: The server integrates the acquired walking routes, public transport routes and transfer information and converts them into a single integrated data in JSON format.

[0700] Input and Output: The input is the route information obtained at each stage, and the output is the integrated data.

[0701] Step 9:

[0702] The server returns the generated integrated data to the user terminal.

[0703] Specific operation: The server sends the generated integrated data in JSON format to the user's device as an HTTP response.

[0704] Input and Output: The input is the generated integrated data, and the output is the integrated data sent to the user terminal.

[0705] Step 10:

[0706] The terminal analyzes the integrated data received from the server and displays it on the UI in a format that is easy for the user to understand.

[0707] Specific behavior: The device parses the received JSON data, extracts the necessary information, and displays it in the UI component, highlighting particularly important elements (such as platform number and detailed walking route).

[0708] Input and Output: The input is the consolidated data received from the server, and the output is the visual route information displayed to the user.

[0709] Step 11:

[0710] The server monitors traffic conditions in real time while traveling and recalculates a new optimal route if delays occur.

[0711] How it works: The server continuously retrieves data from the real-time traffic information API and recalculates a new route in the event of delays or cancellations.

[0712] Input and Output: The input is real-time traffic situation information, and the output is new optimal route information.

[0713] Step 12:

[0714] The server notifies the user terminal of the new optimum route.

[0715] Specific operation: The server retransmits the newly calculated route information to the user terminal and notifies it as an HTTP response.

[0716] Input and Output: The input is the new optimal route information, and the output is the notification to the user terminal.

[0717] Step 13:

[0718] The device analyzes the received new route information and presents it to the user again, recalculating and displaying a new walking route if necessary.

[0719] Specific behavior: The device parses the newly received JSON data, extracts the necessary information, and displays it in the UI. If necessary, it calculates a new walking route using the Google Maps API and presents it to the user again.

[0720] Input and Output: The input is the new route information received from the server, and the output is the new route information displayed to the user.

[0721] (Application example 1)

[0722] 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."

[0723] When autonomous vehicles travel, they often encounter different traffic conditions and obstacles, which can make smooth travel difficult. In particular, when transportation delays or accidents occur, appropriate responses cannot be made, causing great inconvenience to users. In addition, autonomous vehicles often lack the information they need to determine the optimal route in real time. To solve these problems, a system is needed that can obtain traffic information in real time and adaptively provide the optimal route.

[0724] 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.

[0725] In this invention, the server includes means for a user to input a departure point and a destination, means for collecting transportation schedules and route information, means for calculating an optimal route and generating it as integrated data, means for presenting the generated integrated data to the user, means for monitoring traffic conditions during travel and providing delay information in real time, means for recalculating an optimal alternative route in the event of a delay and presenting it to the user, means for collecting route information specifically for autonomous vehicles, means for generating instructions for the autonomous vehicle to travel the optimal route, and means for detecting traffic obstructions while the autonomous vehicle is in operation and calculating an alternative route. This enables smooth travel using autonomous vehicles based on real-time traffic information.

[0726] "Means for a user to input a starting point and a destination" refers to a device or interface that allows a user to input information about their starting point and destination.

[0727] "Means for collecting transport schedule and route information" refers to software and hardware for obtaining information on public transport schedules and routes and storing it in the system.

[0728] "Means for calculating the optimal route and generating it as integrated data" is a function that analyzes multiple routes based on collected information, calculates the most efficient route among them, and generates it as a single integrated data.

[0729] The "means for presenting the generated integrated data to the user" refers to a device or system for providing the calculated optimum route information to the user visually or audibly.

[0730] "Means for monitoring traffic conditions while traveling and providing delay information in real time" refers to technology that monitors traffic conditions in real time, detects delays and obstacles, and immediately notifies users.

[0731] "Means for recalculating the optimal alternative route in the event of a delay and presenting it to the user" is a function that calculates a new alternative route and notifies the user when a delay occurs on the planned route due to changes in traffic conditions.

[0732] "Means for collecting route information specifically for autonomous vehicles" refers to technologies and devices for collecting route information specifically for the operation of autonomous vehicles.

[0733] The "means for generating instructions for an autonomous vehicle to travel along an optimal route" is a function for generating specific instructions for operating an autonomous vehicle along an optimal route.

[0734] "Means for detecting obstacles while an autonomous vehicle is in operation and calculating an alternative route" refers to technology that allows an autonomous vehicle to detect obstacles while in operation and calculate a safe and efficient alternative route.

[0735] This invention provides a system that calculates an optimal route in real time and adaptively responds to traffic conditions when a user travels to a destination using an autonomous vehicle. This system includes the following configuration and functions.

[0736] System Configuration

[0737] 1. User Device

[0738] Smartphones, tablets, and vehicle-mounted head-mounted displays (HMDs)

[0739] This allows the user to input a starting point and a destination.

[0740] 2. Server

[0741] High-performance computing facilities in cloud environments or data centers

[0742] A back-end system for collecting transport schedule and route information and calculating optimal routes.

[0743] 3. Self-driving vehicles

[0744] Equipped with sensors such as GPS, cameras, LiDAR, and radar, it acquires location information and traffic conditions in real time.

[0745] It receives instructions from the server and moves along the optimal route.

[0746] Program processing

[0747] Data Acquisition and Input

[0748] The user terminal provides an interface for the user to input the starting point and destination. The information entered by the user is converted into an appropriate format, such as JSON, and sent to the server.

[0749] Route calculation

[0750] Based on the received departure and destination information, the server calls the transportation schedule API and geographic information API to calculate the optimal route.

[0751] Data Integration

[0752] The calculated route information is generated as a single integrated data set and sent back to the user's device, which analyzes the data and displays it in an easy-to-understand UI.

[0753] Real-time monitoring

[0754] The server monitors traffic conditions in real time, detecting delays and accidents. If a delay occurs, the server immediately recalculates the optimal alternative route and notifies the user.

[0755] Operation of autonomous vehicles

[0756] The autonomous vehicle receives instructions from the server and moves along the optimal route. If an obstacle is detected, the autonomous vehicle will calculate an alternative route and control itself to move safely.

[0757] Specific examples

[0758] For example, a user inputs their starting point "Shibuya" and destination "Shinjuku" on their smartphone. The device sends this information to a server, which then uses a public transport API to calculate the optimal route. As a result, a train route from Shibuya to Shinjuku is suggested. If a train is delayed during travel, the server recalculates an alternative route and notifies the application. The same applies when traveling in an autonomous vehicle, where traffic conditions are monitored in real time and the optimal route is provided.

[0759] Prompt Sentence Examples

[0760] "Design an app system that suggests the best route for a self-driving vehicle from Shibuya to Shinjuku in Tokyo, and notifies the driver by recalculating the route based on real-time traffic conditions."

[0761] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0762] Step 1:

[0763] Input: The user inputs a starting point and a destination.

[0764] Operation: The user device receives the departure and destination information entered by the user (e.g., "Shibuya" and "Shinjuku"). The user device converts this information into JSON format and sends it to the server.

[0765] Output: The start and end points are sent to the server in JSON format.

[0766] Step 2:

[0767] Input: The departure and destination information received by the server from the device.

[0768] How it works: The server analyzes the received departure and destination information and uses a geographic information API to identify the nearest train station or bus stop near the user's home. Based on this data, the server calculates the optimal route.

[0769] Output: Information on the nearest station and bus stop, as well as the best route information.

[0770] Step 3:

[0771] Input: Information on the nearest station or bus stop, and optimal route information.

[0772] How it works: The server collects route information from the nearest station or bus stop to the station nearest to the destination using public transport APIs (train and bus timetables). The collected information is compiled into a single integrated data set.

[0773] Output: Overall route information as consolidated data.

[0774] Step 4:

[0775] Input: Integrated data.

[0776] Operation: The server returns the generated integrated data to the user terminal, which receives and analyzes the integrated data.

[0777] Output: Parsed route information.

[0778] Step 5:

[0779] Input: Parsed route information.

[0780] Operation: The user device presents the analyzed route information to the user in an easy-to-read format, highlighting particularly important information (such as transfer platform numbers and walking routes).

[0781] Output: Optimal route information presented to the user.

[0782] Step 6:

[0783] Input: Real-time traffic data.

[0784] How it works: During the journey, the server monitors traffic conditions in real time, obtaining information about delays and obstacles. If a delay occurs, it recalculates a new optimal route.

[0785] Output: Delay information and best alternative route.

[0786] Step 7:

[0787] Input: The new optimal route.

[0788] Operation: The server notifies the user device of the new, recalculated optimal route. The user device analyzes the new route information and notifies the user. If necessary, it uses the map API to calculate and display the new walking route.

[0789] Output: The new optimal route information presented to the user.

[0790] Step 8:

[0791] Input: Real-time sensor information from an autonomous vehicle.

[0792] How it works: Autonomous vehicles acquire real-time location information and traffic conditions through sensors such as GPS, cameras, LiDAR, and radar. Based on the acquired data, they receive instructions from a server to move along the optimal route, and if they detect an obstacle, they calculate an alternative route themselves.

[0793] Output: Safe and efficient route.

[0794] 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.

[0795] This invention relates to a service that enables users to travel smoothly from their departure point to their destination. The system collects public transport schedules and route information in one place when the user inputs their departure point and destination, calculates the optimal route, and presents the integrated data to the user. It also has a function to monitor traffic conditions in real time during travel and recalculate the optimal alternative route and notify the user in the event of a delay.

[0796] Furthermore, the present invention incorporates an emotion engine that recognizes the user's emotions, using the user's facial recognition system and voice analysis system to detect the user's emotions, and can adjust the way guidance information is presented based on the user's emotions, or provide a more comfortable alternative route depending on the user's stress level.

[0797] Processing flow and specific operations

[0798] User Input

[0799] 1. The user enters their home address (e.g., "26-1 Sakuragaoka-cho, Shibuya-ku, Tokyo") and the address of their destination (e.g., "a cafe near Shinjuku Station") into their mobile device or PC.

[0800] 2. The device converts this input information into an appropriate format (such as JSON) and sends it to the server.

[0801] Route calculation and information acquisition

[0802] 1. The server analyzes the home and destination information received from the device and accesses the geographic information API to identify the nearest train station or bus stop near the home.

[0803] 2. The server calculates the transportation method (walking, bus, etc.) from home to the nearest station or bus stop.

[0804] 3. The server calls the transportation API (train and bus timetables) and obtains route information from the nearest station or bus stop to the station nearest to the destination.

[0805] 4. The server uses a map API to calculate the walking route from the nearest station to the destination.

[0806] 5. The server generates all the acquired information (nearest station, bus stop, train and bus departure times, boarding location, detailed transfer routes, walking routes, etc.) as integrated data.

[0807] 6. The server returns the generated integrated data to the user terminal.

[0808] Display to users and operation of the emotion engine

[0809] 1. The terminal analyzes the integrated data received from the server and displays the information using an appropriate UI to make it easy for the user to understand.

[0810] 2. The device will highlight particularly important information (e.g., platform numbers for transfers and walking routes).

[0811] 3. The device uses a built-in emotion engine to recognize the user's face and analyze their voice to detect their current emotions.

[0812] 4. The emotion engine adjusts the display method based on the user's emotions. For example, if it determines that the user is under high stress, it displays more detailed and concise guidance information.

[0813] 5. If the emotion engine detects the user's stress level, it notifies the server to provide an alternative relaxing route (e.g., an avoidance route or a route through a park).

[0814] Support on the move

[0815] 1. The server monitors traffic information (train and bus operation status) in real time.

[0816] 2. If a delay occurs during the journey, the server recalculates a new optimal route.

[0817] 3. The server notifies the user terminal of the new optimal route.

[0818] 4. The device analyzes the new route information and notifies the user.

[0819] 5. The device will calculate and display a new walking route, again using the Maps API if necessary.

[0820] 6. After the user arrives at the station nearest to their destination, the device will display detailed walking route instructions to help the user reach their destination without getting lost.

[0821] Specific examples

[0822] For example, if a user wants to go from 26-1 Sakuragaokacho, Shibuya-ku, Tokyo to a cafe near Shinjuku Station, the user enters the address of the starting point and destination into a smartphone app. The device sends this information to a server, which then calculates the optimal route. The resulting route is to board the Yamanote Line from Shibuya Station, get off at Shinjuku Station, and walk five minutes from the west exit. If the Yamanote Line is delayed during travel, the server calculates an alternative route using the Saikyo Line and notifies the user's device. The device then displays the new route information and recalculates the walking route to the cafe and presents it to the user.

[0823] Furthermore, if the emotion engine detects that the user is becoming tense during their trip, it will support them by displaying more detailed and easy-to-understand guidance information and offering relaxing alternative routes. This way, users can avoid the hassle of switching between multiple applications and enjoy a smoother journey. Furthermore, by monitoring traffic conditions in real time and utilizing the emotion engine to provide adaptive support, stress caused by unexpected delays can also be reduced.

[0824] The processing flow will be explained below.

[0825] Step 1:

[0826] Using a mobile device or PC, the user inputs their home address (e.g., "26-1 Sakuragaokacho, Shibuya-ku, Tokyo") and the address of their destination (e.g., "a cafe near Shinjuku Station").

[0827] Step 2:

[0828] The terminal converts the input information into an appropriate format (such as JSON) and sends it to the server.

[0829] Step 3:

[0830] The server analyzes the home and destination information received from the terminal.

[0831] Step 4:

[0832] The server accesses a geographic information API to identify the nearest train station or bus stop near the user's home.

[0833] Step 5:

[0834] The server calculates the transportation method (walking, bus, etc.) to the nearest station or bus stop.

[0835] Step 6:

[0836] The server calls the transportation API (train and bus timetables) and obtains route information from the nearest station or bus stop to the station nearest to the destination.

[0837] Step 7:

[0838] The server uses a map API to calculate the walking route from the nearest station to the destination.

[0839] Step 8:

[0840] The server generates all the information it has acquired (nearest station, bus stop, train and bus departure times, boarding location, detailed transfer routes, walking routes, etc.) as integrated data.

[0841] Step 9:

[0842] The server returns the generated integrated data to the user terminal.

[0843] Step 10:

[0844] The terminal analyzes the integrated data received from the server.

[0845] Step 11:

[0846] The terminal displays information using an appropriate UI to make it easy for the user to understand.

[0847] Step 12:

[0848] The device highlights particularly important information (e.g., platform numbers for transfers and walking routes).

[0849] Step 13:

[0850] The device uses a built-in emotion engine to recognize the user's face and analyze their voice to detect their current emotions.

[0851] Step 14:

[0852] The emotion engine adjusts the display method based on the user's emotions. For example, if it determines that the user is nervous, it displays more detailed and concise guidance information.

[0853] Step 15:

[0854] The server monitors traffic information (train and bus operation status) in real time.

[0855] Step 16:

[0856] If a delay occurs during the journey, the server recalculates a new optimal route.

[0857] Step 17:

[0858] The server notifies the user terminal of the new optimum route.

[0859] Step 18:

[0860] If the emotion engine detects the user's stress level, it notifies the server to provide an alternative route to relaxation (e.g., a route that avoids crowds or a route through a park).

[0861] Step 19:

[0862] The terminal analyzes the new route information and notifies the user.

[0863] Step 20:

[0864] The device will again use the map API to calculate and display a new walking route if necessary.

[0865] Step 21:

[0866] Once the user arrives at the station nearest to their destination, the device will display detailed walking route instructions to help the user reach their destination without getting lost.

[0867] Specific examples

[0868] For example, if a user wants to go from 26-1 Sakuragaokacho, Shibuya-ku, Tokyo to a cafe near Shinjuku Station, the user enters the address of the starting point and destination into a smartphone app. The device sends this information to a server, which then calculates the optimal route. The resulting route is to board the Yamanote Line from Shibuya Station, get off at Shinjuku Station, and walk five minutes from the west exit. If the Yamanote Line is delayed during travel, the server calculates an alternative route using the Saikyo Line and notifies the user's device. The device then displays the new route information and recalculates the walking route to the cafe and presents it to the user.

[0869] Furthermore, if the emotion engine detects that the user is becoming tense during their trip, it will support them by displaying more detailed and easy-to-understand guidance information and offering relaxing alternative routes. This way, users can avoid the hassle of switching between multiple applications and enjoy a smoother journey. Furthermore, by monitoring traffic conditions in real time and utilizing the emotion engine to provide adaptive support, stress caused by unexpected delays can also be reduced.

[0870] Example 2

[0871] 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."

[0872] In modern transportation systems, users are required to efficiently plan the optimal route from their departure point to their destination. However, individually collecting information such as transportation schedules, route information, and real-time delay information is time-consuming and places a significant burden on users. Furthermore, users are prone to stress due to the lack of means to quickly respond when a delay occurs during travel. Furthermore, users' emotional state is not taken into consideration, which can increase stress during travel. These are important issues that need to be resolved.

[0873] 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.

[0874] In this invention, the server includes a means for collecting public transportation schedules and route information, a means for identifying the nearest station or bus stop and calculating the optimal route, and a means for detecting the user's emotions and providing guidance information in an adaptive manner. This allows the server to provide all the information the user needs in one place and quickly respond to delays during travel. Furthermore, providing guidance information according to the user's emotional state can reduce stress during travel.

[0875] "User" refers to an individual or organization that uses the system to obtain route information from a starting point to a destination.

[0876] The "starting point" indicates the location where the user starts moving.

[0877] A "destination" indicates the location where the user completes their journey.

[0878] "Public transportation" refers to public transportation means such as trains and buses.

[0879] "Schedule" refers to information about the operating hours and departure times of public transportation.

[0880] "Route information" refers to information about the route from the starting point to the destination.

[0881] "Nearest station" refers to the train station closest to the departure point or destination.

[0882] "Bus stop" refers to the bus stop closest to the departure point or destination.

[0883] The "optimal route" refers to the route that best satisfies conditions such as travel time and number of transfers.

[0884] "Integrated data" refers to data obtained from multiple sources that are combined into one.

[0885] "Traffic conditions" refers to the operation status of public transportation and road congestion.

[0886] "Delay information" refers to information when public transportation services are delayed from their scheduled times.

[0887] An "alternate route" is a different route used in the event of a delay or other problem.

[0888] "Emotion" refers to the user's state of mind.

[0889] "Emotion detection" refers to determining a user's emotional state from their facial expressions and voice.

[0890] "Adaptive method" refers to a method of changing the form and content of information provided depending on the emotional state of the user.

[0891] The present invention relates to a system that enables users to travel smoothly from their starting point to their destination. This system calculates the optimal route by having the user input their starting point and destination, and presents the route to the user as integrated data. It also has the function of monitoring traffic conditions in real time during travel and recalculating the optimal alternative route in the event of a delay, and notifying the user. Furthermore, the system incorporates an emotion engine that recognizes the user's emotions, and can adjust the way in which guidance information is presented based on the user's emotional state.

[0892] System Configuration

[0893] Hardware and Software Configuration

[0894] This system mainly consists of the following hardware and software:

[0895] 1. Terminal: A device such as a smartphone or PC that allows the user to input their starting point and destination. The terminal must be equipped with an internet connection, a camera, and a microphone.

[0896] 2. Server: A cloud-based system that analyzes data and calculates routes. The server has high-speed processing power and storage capacity to manage large amounts of data.

[0897] 3. API: An interface for obtaining route information, such as a geographical information API (e.g., Google Maps API) or a public transportation API (e.g., NAVITIME API).

[0898] 4. Emotion engine: Software that recognizes the user's face and analyzes their voice to detect their emotions.

[0899] Program processing flow and specific examples

[0900] User Input

[0901] The user enters their home address (e.g., "26-1 Sakuragaokacho, Shibuya-ku, Tokyo") and the address of their destination (e.g., "a cafe near Shinjuku Station") into their mobile device or PC. The device converts this input information into a format such as JSON and sends it to the server.

[0902] Route calculation and information integration

[0903] The server analyzes the home and destination information received from the device and identifies the nearest train station or bus stop near the home by accessing the Google Maps API. It then uses the NAVITIME API and other services to obtain public transportation schedules and route information and calculates the optimal route from the home to the destination. It then generates integrated data from all the information it has obtained and sends it back to the user's device.

[0904] Information presentation to users and operation of the emotion engine

[0905] The device analyzes the integrated data received from the server and displays the information in an easy-to-understand UI. It highlights particularly important information (e.g., platform numbers for transfers and walking routes). It also uses an emotion engine to analyze the user's face and voice and adjusts the display method based on the user's emotions. If the device determines that the user is under high stress, it displays more detailed and concise guidance information and offers relaxing alternative routes.

[0906] Support on the move

[0907] The server monitors traffic information in real time, and if a delay occurs during travel, it recalculates a new optimal route and notifies the user's device. The device then analyzes the new route information and notifies the user, allowing the user to continue traveling smoothly.

[0908] Specific examples

[0909] For example, if a user wants to go from 26-1 Sakuragaokacho, Shibuya-ku, Tokyo to a cafe near Shinjuku Station, the user enters the address of the starting point and destination into a smartphone app. The device sends this information to the server, which then uses the Google Maps API and NAVITIME API to calculate the optimal route. The resulting route is to board the Yamanote Line from Shibuya Station, get off at Shinjuku Station, and walk five minutes from the west exit. If the Yamanote Line is delayed during travel, the server calculates an alternative route using the Saikyo Line and notifies the user's device. The device then displays the new route information and recalculates the walking route to the cafe and presents it to the user.

[0910] Prompt Sentence Examples

[0911] "Please calculate the optimal route from the starting point '26-1 Sakuragaokacho, Shibuya-ku, Tokyo' to the destination 'a cafe near Shinjuku Station'. Please also include a detailed walking route to the destination. If possible, please also provide guidance on what to do if you become nervous during the trip."

[0912] The present invention provides users with all the traffic information they need in one place, allowing for quick responses to delays while traveling, and by providing information based on the user's emotional state, it is possible to reduce stress while traveling.

[0913] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0914] Step 1: User Input

[0915] The user enters their home address (e.g., "26-1 Sakuragaokacho, Shibuya-ku, Tokyo") and the address of their destination (e.g., "a cafe near Shinjuku Station") into a dedicated application on their smartphone or PC. The entered information is the user's starting point and destination data. When the user presses the "Search" button, the device receives this information and sends it to the next processing step.

[0916] input:

[0917] Address of departure point (e.g., "26-1 Sakuragaokacho, Shibuya-ku, Tokyo")

[0918] Destination address (e.g., "a cafe near Shinjuku Station")

[0919] output:

[0920] Origin and destination data converted to JSON format

[0921] Specific behavior:

[0922] The user enters address information into the application's input field and presses the "Search" button to complete the input.

[0923] Step 2: Send device data

[0924] The terminal converts the address data entered by the user into JSON format and sends it to the server. This conversion is for the purpose of improving data consistency and transmission efficiency. The terminal then sends this data to the server as an HTTP POST request.

[0925] input:

[0926] Origin and destination data converted to JSON format

[0927] output:

[0928] The HTTP POST request sent to the server

[0929] Specific behavior:

[0930] The terminal converts the data entered by the user into JSON format and sends it as an HTTP POST request to the server.

[0931] Step 3: Data analysis and route calculation on the server

[0932] 1. Data analysis: The server analyzes the address information received from the terminal to identify the starting point and destination.

[0933] 2. Identifying the nearest station or bus stop: The server uses the geographic information API to identify the nearest station or bus stop near the departure point.

[0934] 3. Calculating transportation: The server calculates the appropriate transportation method (walking, bus, etc.) from home to the nearest station or bus stop.

[0935] 4. Obtain route information: The server uses the public transport API to obtain public transport schedule and route information.

[0936] 5. Calculating walking route: The server calculates the walking route from the nearest station to the destination to the destination.

[0937] 6. Generation of integrated data: All acquired information is integrated to generate comprehensive route data.

[0938] input:

[0939] HTTP POST request sent to the server

[0940] Origin and destination information based on geographical API

[0941] Schedule and route information obtained from public transport APIs

[0942] output:

[0943] Integrated Route Data

[0944] Specific behavior:

[0945] The server uses a programming language such as Python to send requests to the Google Maps API or NAVITIME API, obtain the necessary data, and generate integrated data.

[0946] Step 4: Sending route information from the server to the device

[0947] The server then sends the generated integrated data back to the device, which includes the nearest stations, departure times, transfer details, walking routes, etc.

[0948] input:

[0949] Integrated Route Data

[0950] output:

[0951] Route data sent to the device as an HTTP response

[0952] Specific behavior:

[0953] The server sends the integrated data to the terminal as an HTTP response.

[0954] Step 5: Displaying consolidated data on the terminal

[0955] The device analyzes the integrated data received from the server and displays the information on the UI of a dedicated application, highlighting particularly important information (e.g., platform numbers for transfers and walking routes).

[0956] input:

[0957] Aggregated data received from the server

[0958] output:

[0959] Route information displayed to users

[0960] Specific behavior:

[0961] The terminal analyzes the data received from the server and displays it in the format best suited to the application.

[0962] Step 6: Detect and adjust user emotions with the emotion engine

[0963] 1. Facial recognition and voice analysis: The device's built-in emotion engine performs facial recognition and voice analysis of the user.

[0964] 2. Display content adjustment: The emotion engine adjusts the display content based on the detected emotions. If stress is detected to be high, the guidance information will be displayed in more detail and concisely.

[0965] 3. Providing alternative routes: The emotion engine sends a notification to the server to provide alternative routes to relax depending on the user's stress level.

[0966] input:

[0967] User's facial image and voice data

[0968] output:

[0969] Adjusted guidance information

[0970] Notifying the server

[0971] Specific behavior:

[0972] The device's camera and microphone collect the user's face and voice, and the emotion engine analyzes them to determine the user's emotions. The system adjusts the display content to take appropriate action and sends notifications to the server as necessary.

[0973] Step 7: Real-time traffic monitoring and route updates

[0974] 1. Traffic information monitoring: The server monitors the train and bus operation status in real time.

[0975] 2. Recalculation on Delay: If a delay occurs during travel, the server recalculates a new optimal route.

[0976] 3. Notification to the terminal: The server notifies the terminal of the new route information.

[0977] 4. Displaying the new route: The device analyzes the new route information and notifies the user. If necessary, it calculates and displays a new walking route using the map API.

[0978] input:

[0979] Real-time traffic information

[0980] output:

[0981] New route information

[0982] Specific behavior:

[0983] The server periodically calls the traffic information API to obtain the current operating conditions, and if a delay occurs, calculates a new optimal route and notifies the device. The device then displays the new route to the user.

[0984] Through the above process, users can obtain optimal route information and receive real-time support while traveling. This system is expected to make users' travels smoother and stress-free.

[0985] (Application example 2)

[0986] 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."

[0987] The present invention relates to a system that enables users to travel smoothly and comfortably. Conventional mobility assistance systems have limitations in optimizing routes and providing delay information, and are unable to consider the user's emotional state. Furthermore, the control of autonomous vehicles is limited, making it difficult to provide an optimal travel experience. Therefore, there is a need for systems that can present guidance information according to the user's emotional state and enable smooth travel using autonomous vehicles.

[0988] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0989] In this invention, the server includes: means for a user to input a departure point and a destination; means for collecting transportation schedules and route information; means for calculating an optimal route and generating it as integrated data; means for presenting the generated integrated data to the user; means for monitoring traffic conditions during travel and providing delay information in real time; means for recalculating an optimal alternative route in the event of a delay and presenting it to the user; means for adjusting the presentation method of guidance information based on the user's emotions, which includes an emotion engine that recognizes the user's emotions; means for sending instructions about the optimal route to an autonomous vehicle and means for controlling the autonomous vehicle. This enables smooth and comfortable travel by utilizing an autonomous vehicle that adapts to the user's emotional state.

[0990] The "means by which a user inputs their starting point and destination" refers to the interface that a user uses to set a route to their destination, and is provided through a device such as a smartphone, tablet, or PC.

[0991] "Means for collecting transport schedule and route information" refers to a system or module for obtaining timetables and route information for transport such as trains and buses, and collects information using APIs and databases.

[0992] The "means for calculating the optimal route and generating it as integrated data" refers to an algorithm and calculation system for calculating the optimal travel route based on the starting point and destination entered by the user and generating the result as integrated data.

[0993] The "means for presenting the generated integrated data to the user" refers to an interface that visually or audibly presents the calculated optimal route to the user, and displays the information through a display such as a smartphone or smart glasses.

[0994] "Means for monitoring traffic conditions while traveling and providing delay information in real time" refers to a system for monitoring the real-time conditions of roads and transportation facilities while traveling and providing delay information to users immediately.

[0995] "Means for recalculating the optimal alternative route in the event of a delay and presenting it to the user" refers to an algorithm and interface for recalculating the optimal route when a delay occurs in a transportation service or route and presenting that information to the user.

[0996] An "emotion engine that recognizes the user's emotions" is software or hardware that can analyze the user's facial expressions and voice data and detect their current emotional state.

[0997] The "means for adjusting the method of presenting guidance information" is a system that dynamically changes the method and timing of displaying guidance information based on the detected emotional state of the user.

[0998] The "means for transmitting optimal route instructions to an autonomous vehicle" is a system for communicating information about the calculated optimal route to an autonomous vehicle and transmitting the instructions to the vehicle.

[0999] The "means for controlling an autonomous vehicle" refers to hardware and software for appropriately controlling the autonomous vehicle in accordance with the received optimal route.

[1000] The present invention is a support system for users to travel smoothly from their starting point to their destination. This system realizes comfortable travel by providing real-time information on transportation and the optimal route according to the user's emotional state. Furthermore, the invention supports travel using autonomous vehicles.

[1001] System configuration

[1002] The system consists of the following main components:

[1003] 1. User Input Method

[1004] The user inputs the starting point and destination using a device such as a smartphone, smart glasses, or tablet.

[1005] 2. Means of collecting transportation information

[1006] The server utilizes an API (e.g., Google Maps API) to collect transportation schedule and route information.

[1007] 3. Route calculation method

[1008] The server calculates the optimal route based on the collected information and generates the results as integrated data.

[1009] 4. Integrated Data Presentation Method

[1010] The generated integrated data is presented on the user terminal, and guidance information is provided visually and audibly.

[1011] 5. Traffic monitoring means

[1012] The server monitors traffic conditions in real time and provides delay information to users.

[1013] 6. Alternative Route Calculation Methods

[1014] If a delay occurs, the server recalculates a new optimal route and presents it to the user.

[1015] 7. Emotion Engine

[1016] It uses the camera and microphone built into the user's device to incorporate an emotion engine that recognizes emotions (e.g., Affectiva SDK).

[1017] The emotion engine adjusts how the guidance information is displayed based on the user's emotional state.

[1018] 8. Autonomous Vehicle Control Methods

[1019] The server instructs the autonomous vehicle on the optimal route and controls the vehicle appropriately.

[1020] Specific examples of processing

[1021] The user uses the smart glasses to voice-input their home address and destination address. The device then sends this information to the server, which then uses a public transport API to calculate the optimal route. The calculation results are displayed on the smart glasses' display. If a public transport delay occurs during travel, the server automatically calculates a new route and provides that information to the user.

[1022] The smart glasses' camera and microphone are also used to analyze the user's facial and voice data with an emotion engine to recognize their emotional state. For example, if the system determines that the user is nervous, it will display more detailed and easy-to-understand guidance information and suggest a relaxing route. In this way, providing guidance information that adapts to the user's emotional state can reduce stress during travel.

[1023] Furthermore, when using an autonomous vehicle, the server sends instructions for the optimal route to the vehicle, which then performs autonomous driving according to those instructions, allowing the user to travel smoothly and safely from their starting point to their destination.

[1024] Prompt Sentence Examples

[1025] Below is an example of a prompt sentence to input to the generative AI model.

[1026] Enter the user's starting point and destination. Write a program to calculate the route and display it on the smart glasses. It should also analyze the user's emotional state and suggest a relaxing route. Write the program in Python and explain how to use any necessary libraries and APIs. Below is an example of input data.

[1027] The present invention enables smooth and comfortable travel using autonomous vehicles that adapt to the user's emotional state.

[1028] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1029] Step 1:

[1030] The user inputs a starting point and a destination.

[1031] Input: The user puts on the smart glasses and enters the starting point and destination by voice.

[1032] How it works: The device recognizes the input as text data and converts it into a format (e.g., JSON).

[1033] Output: Formatted text data is generated.

[1034] Step 2:

[1035] The terminal sends the input data to the server.

[1036] Input: Text data of the starting point and destination entered by the user.

[1037] How it works: The device uses a communication protocol (e.g. HTTP) to send this data to the server.

[1038] Output: The server receives the request.

[1039] Step 3:

[1040] A server collects transportation schedule and route information.

[1041] Input: The origin and destination data sent to the server.

[1042] How it works: The server calls a transit API (e.g., Google Maps API) to get the necessary schedule and route information.

[1043] Output: Transit schedules and route information.

[1044] Step 4:

[1045] The server calculates the optimal route and generates it as integrated data.

[1046] Input: Transit schedule and route information.

[1047] How it works: The server uses the collected information to run algorithms and calculate the optimal route. The results are then compiled into a consolidated data set.

[1048] Output: Consolidated data of optimal routes.

[1049] Step 5:

[1050] The server transmits the integrated data to the terminal.

[1051] Input: Optimal route synthesis data.

[1052] Operation: The server sends the generated integrated data to the terminal.

[1053] Output: The terminal receives the consolidated data.

[1054] Step 6:

[1055] The terminal presents the integrated data to the user.

[1056] Input: The aggregate data received from the server.

[1057] Operation: The device analyzes the integrated data and displays guidance information visually or audibly on the display.

[1058] Output: The user is presented with a guide.

[1059] Step 7:

[1060] The server monitors traffic conditions in real time while on the move.

[1061] Input: Real-time traffic data.

[1062] Operation: The server periodically calls the transport API to monitor real-time traffic conditions.

[1063] Output: Traffic updates.

[1064] Step 8:

[1065] The terminal provides delay information to the user.

[1066] Input: Traffic updates.

[1067] Operation: If a delay occurs, the server recalculates a new optimal route and sends that information to the terminal, which then receives it and notifies the user.

[1068] Output: The latest guidance information is presented to the user.

[1069] Step 9:

[1070] The terminal recognizes the user's emotional state.

[1071] Input: User's facial expression data and voice data.

[1072] How it works: The device uses its built-in camera and microphone to collect data, which is then analyzed by an emotion engine.

[1073] Output: User's emotional state (e.g. stress level).

[1074] Step 10:

[1075] The server adjusts how the guidance information is presented.

[1076] Input: The user's emotional state.

[1077] Operation: The server dynamically adjusts the display method and content of the guidance information based on the output of the emotion engine.

[1078] Output: Adjusted guidance information.

[1079] Step 11:

[1080] The server sends optimal route instructions to the autonomous vehicle.

[1081] Input: The final calculated or recalculated optimal route.

[1082] Operation: The server communicates with the autonomous vehicle and sends it the optimal route.

[1083] Output: The autonomous vehicle receives and executes the optimal route.

[1084] Step 12:

[1085] An autonomous vehicle transports the user to their destination.

[1086] Input: Optimal route instructions sent by the server.

[1087] Action: The autonomous driving system starts driving according to the optimal route and takes the user to their destination.

[1088] Output: The user reaches the destination.

[1089] 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.

[1090] 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.

[1091] 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.

[1092] [Third embodiment]

[1093] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1094] 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.

[1095] 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).

[1096] 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.

[1097] 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.

[1098] 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).

[1099] 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. 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.

[1100] 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.

[1101] 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.

[1102] 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.

[1103] 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.

[1104] 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."

[1105] This invention relates to a service that allows users to travel smoothly from their departure point to their destination. This system allows users to input their departure point and destination, and then collects public transport schedules and route information in one place, calculates the optimal route, and presents it to the user as integrated data. It also monitors traffic conditions in real time during travel, and recalculates and notifies the user of the optimal alternative route in the event of a delay, providing users with a smooth and comfortable journey.

[1106] Processing flow and specific operations

[1107] User Input

[1108] 1. The user enters their home address (e.g., "26-1 Sakuragaoka-cho, Shibuya-ku, Tokyo") and the address of their destination (e.g., "a cafe near Shinjuku Station") into their mobile device or PC.

[1109] 2. The device converts this input information into an appropriate format (such as JSON) and sends it to the server.

[1110] Route calculation and information acquisition

[1111] 1. The server analyzes the home and destination information received from the device and calls the geographic information API to identify the nearest train station or bus stop near the home.

[1112] 2. The server calculates the transportation method (walking, bus, etc.) from home to the nearest station or bus stop, and then obtains route information from the nearest station or bus stop to the station nearest to the destination using a transportation API (train or bus timetable).

[1113] 3. The server integrates this information and returns the generated integrated data to the user terminal.

[1114] Display to users

[1115] 1. The terminal analyzes the integrated data received from the server and displays it in an appropriate UI to make the information easy for the user to understand.

[1116] 2. The device will highlight particularly important information (e.g., platform numbers for transfers and walking routes).

[1117] Support on the move

[1118] 1. The server monitors traffic information (train and bus operation status) in real time and calculates a new optimal route if a delay occurs.

[1119] 2. The server notifies the user terminal of the new optimal route.

[1120] 3. The device analyzes the new route information, notifies the user, and, if necessary, uses the map API again to calculate and display a new walking route.

[1121] Specific examples

[1122] For example, if a user wants to go from 26-1 Sakuragaokacho, Shibuya-ku, Tokyo to a cafe near Shinjuku Station, the user enters the address of the starting point and destination into a smartphone app. The device sends this information to a server, which then calculates the optimal route. The resulting route is to board the Yamanote Line from Shibuya Station, get off at Shinjuku Station, and walk five minutes from the west exit. If the Yamanote Line is delayed during travel, the server calculates an alternative route using the Saikyo Line and notifies the user's device. The device then displays the new route information and recalculates the walking route to the cafe and presents it to the user. After arriving at Shinjuku Station, detailed walking route instructions are displayed, allowing the user to reach their destination without getting lost.

[1123] This allows users to travel more smoothly without having to use multiple applications, and by monitoring traffic conditions in real time and providing adaptive support, it also reduces the frustration of unexpected delays.

[1124] The processing flow will be explained below.

[1125] Step 1:

[1126] Using a mobile device or PC, the user enters their home address (e.g., "26-1 Sakuragaokacho, Shibuya-ku, Tokyo") and the address of their destination (e.g., "a cafe near Shinjuku Station").

[1127] Step 2:

[1128] The terminal converts the input information into an appropriate format, such as JSON, and sends it to the server.

[1129] Step 3:

[1130] The server analyzes the home and destination information received from the terminal.

[1131] Step 4:

[1132] The server accesses a geographic information API to identify the nearest train station or bus stop near the user's home.

[1133] Step 5:

[1134] The server calculates the transportation method (walking, bus, etc.) from home to the nearest station or bus stop.

[1135] Step 6:

[1136] The server calls the transportation API (train and bus timetables) and obtains route information from the nearest station or bus stop to the station nearest to the destination.

[1137] Step 7:

[1138] The server uses a map API to calculate the walking route from the nearest station to the destination.

[1139] Step 8:

[1140] The server generates all the information it has acquired (nearest station, bus stop, train and bus departure times, boarding location, detailed transfer routes, walking routes, etc.) as integrated data.

[1141] Step 9:

[1142] The server returns the generated integrated data to the user terminal.

[1143] Step 10:

[1144] The terminal analyzes the integrated data received from the server.

[1145] Step 11:

[1146] The terminal displays the analyzed information using an appropriate UI so that the information can be easily understood by the user.

[1147] Step 12:

[1148] The device highlights particularly important information (such as platform numbers for transfers and walking routes).

[1149] Step 13:

[1150] The server monitors traffic information (train and bus operation status) in real time.

[1151] Step 14:

[1152] If a delay occurs during the journey, the server recalculates a new optimal route.

[1153] Step 15:

[1154] The server notifies the user terminal of the new optimum route.

[1155] Step 16:

[1156] The terminal analyzes the new route information and notifies the user.

[1157] Step 17:

[1158] The device will again use the map API to calculate and display a new walking route if necessary.

[1159] Step 18:

[1160] Once the user arrives at the station nearest to their destination, the device will display detailed walking route instructions to help the user reach their destination without getting lost.

[1161] Example 1

[1162] 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."

[1163] Conventional mobility assistance systems require users to individually collect information on different modes of transport and combine it to find the optimal route, which is extremely time-consuming. Furthermore, they are unable to respond immediately to changes in traffic conditions (such as delays or service cancellations), making it difficult to respond quickly when unexpected problems occur.

[1164] 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.

[1165] In this invention, the server includes means for a user to input a departure point and a destination, means for collecting public transportation schedules and route information, means for identifying the nearest transfer station or bus stop, means for calculating routes from the departure point to the nearest station and from the nearest station to the destination and generating the resulting integrated data, means for presenting the generated integrated data to the user, means for monitoring traffic conditions in real time during travel and providing delay information, and means for recalculating a new optimal route in the event of a delay and presenting the new optimal route to the user. This not only allows the user to have the optimal route from the departure point to the destination automatically calculated in a single system, but also allows for immediate response to any problems that may arise during travel, enabling smooth and comfortable travel.

[1166] A "user" is an individual or organization that utilizes the system to input a starting point and a destination and obtain optimal route information.

[1167] The "starting point" is the location where the user begins their journey.

[1168] A "destination" is a location where a user ultimately wants to arrive.

[1169] "Public transportation" means transportation available to the general public (e.g., trains, buses, subways, etc.).

[1170] "Schedule" refers to the operating hours and timetables of public transportation.

[1171] "Route information" refers to detailed information about a specific route (e.g., which stations or bus stops to transfer at, travel time, etc.).

[1172] The "nearest station" refers to the train station closest to the user's starting point or destination.

[1173] A "bus stop" is a place where buses stop and passengers board and disembark.

[1174] "Integrated data" refers to data that centrally compiles information on multiple routes.

[1175] "Real-time" refers to reflecting the current situation immediately.

[1176] "Traffic conditions" refers to the current operational status of transportation (e.g., delays, cancellations, etc.).

[1177] "Delay information" refers to information about public transportation being delayed from its scheduled time.

[1178] An "optimal route" is the most efficient route from a starting point to a destination.

[1179] An "alternate route" is a different route that is set up when the optimal route is not available.

[1180] The present invention relates to a system that enables users to travel smoothly from their departure point to their destination. This system allows users to input their departure point and destination, and then collects public transportation schedules and route information in one go, calculates the optimal route, and presents it to the user as integrated data. It also monitors traffic conditions in real time during travel, and if a delay occurs, recalculates the optimal alternative route and presents it to the user, providing users with a smooth and comfortable journey.

[1181] User Input

[1182] 1. The user inputs the starting point and destination using a mobile device or computer. In this case, an example of the starting point is "26-1 Sakuragaokacho, Shibuya-ku, Tokyo," and an example of the destination is "a cafe near Shinjuku Station."

[1183] 2. The terminal converts the input data into JSON format and sends it to the server. This process can be done using general-purpose programming languages ​​such as JavaScript and Python.

[1184] Server processing

[1185] 1. The server analyzes the data received from the device. To do this, it uses the Google Maps API to obtain the latitude and longitude of the departure and destination points and identifies the nearest train station or bus stop.

[1186] 2. The server uses the Google Maps API and the train operation information API to calculate the route from the starting point to the nearest station and from the nearest station to the destination. Specific route information includes walking routes, train timetables, transfer information, etc.

[1187] Integrated data generation and presentation

[1188] 1. The server integrates the acquired information into a single integrated data set. This integrated data set provides a unified view of the user's travel plan.

[1189] 2. The server converts the generated integrated data back into JSON format and sends it back to the user's device.

[1190] 3. The device analyzes the received integrated data and displays it in a visually easy-to-understand format for the user, with important information (such as transfer platform numbers and walking routes) highlighted.

[1191] Real-time support on the go

[1192] 1. The server uses the NAVITIME API, for example, to monitor traffic conditions in real time, thereby constantly monitoring train and bus delay information.

[1193] 2. The server recalculates a new optimal route when a delay occurs and sends that information to the user's device. A generative AI model can be used for the calculation process.

[1194] 3. The device analyzes the new route information and notifies the user, and if necessary, calculates and displays a new walking route using the Google Maps API again.

[1195] Specific examples

[1196] For example, if a user wants to go from 26-1 Sakuragaokacho, Shibuya-ku, Tokyo to a cafe near Shinjuku Station, they input their starting point and destination into the smartphone app. The device sends this information to the server, which then calculates the optimal route. The resulting route is a train ride from Shibuya Station, alighting at Shinjuku Station, and a five-minute walk to the cafe.

[1197] Prompt Sentence Examples

[1198] Design a system that calculates the optimal route for a user to go from 26-1 Sakuragaokacho, Shibuya-ku, Tokyo to a cafe near Shinjuku Station, and suggests alternative routes if there are public transport delays. Explain each step in natural language.

[1199] This allows users to travel more smoothly without having to switch between multiple applications, and by monitoring traffic conditions in real time and providing adaptive support, it also reduces the frustration of unexpected delays.

[1200] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1201] Step 1:

[1202] The user uses a mobile device or PC to input the starting point (e.g., "26-1 Sakuragaoka-cho, Shibuya-ku, Tokyo") and the destination (e.g., "a cafe near Shinjuku Station").

[1203] Specific behavior: A user opens the application, manually enters the starting point and destination in the input form, and presses the submit button when the input is complete.

[1204] Input and Output: The input is the address information of the starting point and the destination, and the output is these addresses formatted as JSON.

[1205] Step 2:

[1206] The terminal converts the data entered by the user into JSON format and sends it to the server.

[1207] What happens: The device application collects the input information, converts it to JSON format using JavaScript or Python code, and then sends an HTTP request to the corresponding API endpoint.

[1208] Input and Output: The input is the address information of the starting point and the destination, and the output is the JSON format data sent to the server.

[1209] Step 3:

[1210] The server analyzes the JSON data received from the device and calls the geographic information API to obtain the geographic information (latitude and longitude) of the departure and destination points.

[1211] What happens: The server parses the received JSON data, extracts the address information, and then sends a request to the Google Maps API to convert the address information into latitude and longitude coordinates.

[1212] Input and Output: The input is address information in JSON format, and the output is latitude and longitude information.

[1213] Step 4:

[1214] The server calls a geographic information API to identify the nearest transfer station or bus stop based on the geographic information of the departure point and destination.

[1215] Specific operation: The server also uses the Google Maps API to search for the nearest train station or bus stop based on the acquired latitude and longitude information.

[1216] Input and output: The input is the latitude and longitude information of the departure point and destination, and the output is the name and location information of the nearest station or bus stop.

[1217] Step 5:

[1218] Based on the information on the nearest station and bus stop, the server obtains the walking route from the starting point to the nearest station or bus stop from the Google Maps API.

[1219] Specific operation: The server requests a route search from the Google Maps API using the latitude and longitude of the starting point and the latitude and longitude of the nearest station or bus stop.

[1220] Input and output: The input is the latitude and longitude information of the starting point and the nearest station, and the output is walking route information.

[1221] Step 6:

[1222] The server calls the public transport API to obtain route information for public transport from the nearest station to the station nearest to the destination.

[1223] Specific operation: Based on the information of the nearest station to the departure point and the nearest station to the destination, the server sends a request to the public transportation API to obtain operation schedules and route information.

[1224] Input and output: The input is the name information of the nearest station to the departure point and the nearest station to the destination, and the output is public transport route information.

[1225] Step 7:

[1226] The server obtains walking route information from the nearest station to the destination from the Google Maps API.

[1227] Specific operation: The server requests a route search from the Google Maps API using the latitude and longitude of the station nearest to the destination and the latitude and longitude of the destination.

[1228] Input and output: The input is the nearest station to the destination and the latitude and longitude information of the destination, and the output is walking route information.

[1229] Step 8:

[1230] The server integrates all this information and generates a comprehensive travel plan.

[1231] Specific operation: The server integrates the acquired walking routes, public transport routes and transfer information and converts them into a single integrated data in JSON format.

[1232] Input and Output: The input is the route information obtained at each stage, and the output is the integrated data.

[1233] Step 9:

[1234] The server returns the generated integrated data to the user terminal.

[1235] Specific operation: The server sends the generated integrated data in JSON format to the user's device as an HTTP response.

[1236] Input and Output: The input is the generated integrated data, and the output is the integrated data sent to the user terminal.

[1237] Step 10:

[1238] The terminal analyzes the integrated data received from the server and displays it on the UI in a format that is easy for the user to understand.

[1239] Specific behavior: The device parses the received JSON data, extracts the necessary information, and displays it in the UI component, highlighting particularly important elements (such as platform number and detailed walking route).

[1240] Input and Output: The input is the consolidated data received from the server, and the output is the visual route information displayed to the user.

[1241] Step 11:

[1242] The server monitors traffic conditions in real time while traveling and recalculates a new optimal route if delays occur.

[1243] How it works: The server continuously retrieves data from the real-time traffic information API and recalculates a new route in the event of delays or cancellations.

[1244] Input and Output: The input is real-time traffic situation information, and the output is new optimal route information.

[1245] Step 12:

[1246] The server notifies the user terminal of the new optimum route.

[1247] Specific operation: The server retransmits the newly calculated route information to the user terminal and notifies it as an HTTP response.

[1248] Input and Output: The input is the new optimal route information, and the output is the notification to the user terminal.

[1249] Step 13:

[1250] The device analyzes the received new route information and presents it to the user again, recalculating and displaying a new walking route if necessary.

[1251] Specific behavior: The device parses the newly received JSON data, extracts the necessary information, and displays it in the UI. If necessary, it calculates a new walking route using the Google Maps API and presents it to the user again.

[1252] Input and Output: The input is the new route information received from the server, and the output is the new route information displayed to the user.

[1253] (Application example 1)

[1254] 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."

[1255] When autonomous vehicles travel, they often encounter different traffic conditions and obstacles, which can make smooth travel difficult. In particular, when transportation delays or accidents occur, appropriate responses cannot be made, causing great inconvenience to users. In addition, autonomous vehicles often lack the information they need to determine the optimal route in real time. To solve these problems, a system is needed that can obtain traffic information in real time and adaptively provide the optimal route.

[1256] 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.

[1257] In this invention, the server includes means for a user to input a departure point and a destination, means for collecting transportation schedules and route information, means for calculating an optimal route and generating it as integrated data, means for presenting the generated integrated data to the user, means for monitoring traffic conditions during travel and providing delay information in real time, means for recalculating an optimal alternative route in the event of a delay and presenting it to the user, means for collecting route information specifically for autonomous vehicles, means for generating instructions for the autonomous vehicle to travel the optimal route, and means for detecting traffic obstructions while the autonomous vehicle is in operation and calculating an alternative route. This enables smooth travel using autonomous vehicles based on real-time traffic information.

[1258] "Means for a user to input a starting point and a destination" refers to a device or interface that allows a user to input information about their starting point and destination.

[1259] "Means for collecting transport schedule and route information" refers to software and hardware for obtaining information on public transport schedules and routes and storing it in the system.

[1260] "Means for calculating the optimal route and generating it as integrated data" is a function that analyzes multiple routes based on collected information, calculates the most efficient route among them, and generates it as a single integrated data.

[1261] The "means for presenting the generated integrated data to the user" refers to a device or system for providing the calculated optimum route information to the user visually or audibly.

[1262] "Means for monitoring traffic conditions while traveling and providing delay information in real time" refers to technology that monitors traffic conditions in real time, detects delays and obstacles, and immediately notifies users.

[1263] "Means for recalculating the optimal alternative route in the event of a delay and presenting it to the user" is a function that calculates a new alternative route and notifies the user when a delay occurs on the planned route due to changes in traffic conditions.

[1264] "Means for collecting route information specifically for autonomous vehicles" refers to technologies and devices for collecting route information specifically for the operation of autonomous vehicles.

[1265] The "means for generating instructions for an autonomous vehicle to travel along an optimal route" is a function for generating specific instructions for operating an autonomous vehicle along an optimal route.

[1266] "Means for detecting obstacles while an autonomous vehicle is in operation and calculating an alternative route" refers to technology that allows an autonomous vehicle to detect obstacles while in operation and calculate a safe and efficient alternative route.

[1267] This invention provides a system that calculates an optimal route in real time and adaptively responds to traffic conditions when a user travels to a destination using an autonomous vehicle. This system includes the following configuration and functions.

[1268] System Configuration

[1269] 1. User Device

[1270] Smartphones, tablets, and vehicle-mounted head-mounted displays (HMDs)

[1271] This allows the user to input a starting point and a destination.

[1272] 2. Server

[1273] High-performance computing facilities in cloud environments or data centers

[1274] A back-end system for collecting transport schedule and route information and calculating optimal routes.

[1275] 3. Self-driving vehicles

[1276] Equipped with sensors such as GPS, cameras, LiDAR, and radar, it acquires location information and traffic conditions in real time.

[1277] It receives instructions from the server and moves along the optimal route.

[1278] Program processing

[1279] Data Acquisition and Input

[1280] The user terminal provides an interface for the user to input the starting point and destination. The information entered by the user is converted into an appropriate format, such as JSON, and sent to the server.

[1281] Route calculation

[1282] Based on the received departure and destination information, the server calls the transportation schedule API and geographic information API to calculate the optimal route.

[1283] Data Integration

[1284] The calculated route information is generated as a single integrated data set and sent back to the user's device, which analyzes the data and displays it in an easy-to-understand UI.

[1285] Real-time monitoring

[1286] The server monitors traffic conditions in real time, detecting delays and accidents. If a delay occurs, the server immediately recalculates the optimal alternative route and notifies the user.

[1287] Operation of autonomous vehicles

[1288] The autonomous vehicle receives instructions from the server and moves along the optimal route. If an obstacle is detected, the autonomous vehicle will calculate an alternative route and control itself to move safely.

[1289] Specific examples

[1290] For example, a user inputs their starting point "Shibuya" and destination "Shinjuku" on their smartphone. The device sends this information to a server, which then uses a public transport API to calculate the optimal route. As a result, a train route from Shibuya to Shinjuku is suggested. If a train is delayed during travel, the server recalculates an alternative route and notifies the application. The same applies when traveling in an autonomous vehicle, where traffic conditions are monitored in real time and the optimal route is provided.

[1291] Prompt Sentence Examples

[1292] "Design an app system that suggests the best route for a self-driving vehicle from Shibuya to Shinjuku in Tokyo, and notifies the driver by recalculating the route based on real-time traffic conditions."

[1293] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1294] Step 1:

[1295] Input: The user inputs a starting point and a destination.

[1296] Operation: The user device receives the departure and destination information entered by the user (e.g., "Shibuya" and "Shinjuku"). The user device converts this information into JSON format and sends it to the server.

[1297] Output: The start and end points are sent to the server in JSON format.

[1298] Step 2:

[1299] Input: The departure and destination information received by the server from the device.

[1300] How it works: The server analyzes the received departure and destination information and uses a geographic information API to identify the nearest train station or bus stop near the user's home. Based on this data, the server calculates the optimal route.

[1301] Output: Information on the nearest station and bus stop, as well as the best route information.

[1302] Step 3:

[1303] Input: Information on the nearest station or bus stop, and optimal route information.

[1304] How it works: The server collects route information from the nearest station or bus stop to the station nearest to the destination using public transport APIs (train and bus timetables). The collected information is compiled into a single integrated data set.

[1305] Output: Overall route information as consolidated data.

[1306] Step 4:

[1307] Input: Integrated data.

[1308] Operation: The server returns the generated integrated data to the user terminal, which receives and analyzes the integrated data.

[1309] Output: Parsed route information.

[1310] Step 5:

[1311] Input: Parsed route information.

[1312] Operation: The user device presents the analyzed route information to the user in an easy-to-read format, highlighting particularly important information (such as transfer platform numbers and walking routes).

[1313] Output: Optimal route information presented to the user.

[1314] Step 6:

[1315] Input: Real-time traffic data.

[1316] How it works: During the journey, the server monitors traffic conditions in real time, obtaining information about delays and obstacles. If a delay occurs, it recalculates a new optimal route.

[1317] Output: Delay information and best alternative route.

[1318] Step 7:

[1319] Input: The new optimal route.

[1320] Operation: The server notifies the user device of the new, recalculated optimal route. The user device analyzes the new route information and notifies the user. If necessary, it uses the map API to calculate and display the new walking route.

[1321] Output: The new optimal route information presented to the user.

[1322] Step 8:

[1323] Input: Real-time sensor information from an autonomous vehicle.

[1324] How it works: Autonomous vehicles acquire real-time location information and traffic conditions through sensors such as GPS, cameras, LiDAR, and radar. Based on the acquired data, they receive instructions from a server to move along the optimal route, and if they detect an obstacle, they calculate an alternative route themselves.

[1325] Output: Safe and efficient route.

[1326] 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.

[1327] This invention relates to a service that enables users to travel smoothly from their departure point to their destination. The system collects public transport schedules and route information in one place when the user inputs their departure point and destination, calculates the optimal route, and presents the integrated data to the user. It also has a function to monitor traffic conditions in real time during travel and recalculate the optimal alternative route and notify the user in the event of a delay.

[1328] Furthermore, the present invention incorporates an emotion engine that recognizes the user's emotions, using the user's facial recognition system and voice analysis system to detect the user's emotions, and can adjust the way guidance information is presented based on the user's emotions, or provide a more comfortable alternative route depending on the user's stress level.

[1329] Processing flow and specific operations

[1330] User Input

[1331] 1. The user enters their home address (e.g., "26-1 Sakuragaoka-cho, Shibuya-ku, Tokyo") and the address of their destination (e.g., "a cafe near Shinjuku Station") into their mobile device or PC.

[1332] 2. The device converts this input information into an appropriate format (such as JSON) and sends it to the server.

[1333] Route calculation and information acquisition

[1334] 1. The server analyzes the home and destination information received from the device and accesses the geographic information API to identify the nearest train station or bus stop near the home.

[1335] 2. The server calculates the transportation method (walking, bus, etc.) from home to the nearest station or bus stop.

[1336] 3. The server calls the transportation API (train and bus timetables) and obtains route information from the nearest station or bus stop to the station nearest to the destination.

[1337] 4. The server uses a map API to calculate the walking route from the nearest station to the destination.

[1338] 5. The server generates all the acquired information (nearest station, bus stop, train and bus departure times, boarding location, detailed transfer routes, walking routes, etc.) as integrated data.

[1339] 6. The server returns the generated integrated data to the user terminal.

[1340] Display to users and operation of the emotion engine

[1341] 1. The terminal analyzes the integrated data received from the server and displays the information using an appropriate UI to make it easy for the user to understand.

[1342] 2. The device will highlight particularly important information (e.g., platform numbers for transfers and walking routes).

[1343] 3. The device uses a built-in emotion engine to recognize the user's face and analyze their voice to detect their current emotions.

[1344] 4. The emotion engine adjusts the display method based on the user's emotions. For example, if it determines that the user is under high stress, it displays more detailed and concise guidance information.

[1345] 5. If the emotion engine detects the user's stress level, it notifies the server to provide an alternative relaxing route (e.g., an avoidance route or a route through a park).

[1346] Support on the move

[1347] 1. The server monitors traffic information (train and bus operation status) in real time.

[1348] 2. If a delay occurs during the journey, the server recalculates a new optimal route.

[1349] 3. The server notifies the user terminal of the new optimal route.

[1350] 4. The device analyzes the new route information and notifies the user.

[1351] 5. The device will calculate and display a new walking route, again using the Maps API if necessary.

[1352] 6. After the user arrives at the station nearest to their destination, the device will display detailed walking route instructions to help the user reach their destination without getting lost.

[1353] Specific examples

[1354] For example, if a user wants to go from 26-1 Sakuragaokacho, Shibuya-ku, Tokyo to a cafe near Shinjuku Station, the user enters the address of the starting point and destination into a smartphone app. The device sends this information to a server, which then calculates the optimal route. The resulting route is to board the Yamanote Line from Shibuya Station, get off at Shinjuku Station, and walk five minutes from the west exit. If the Yamanote Line is delayed during travel, the server calculates an alternative route using the Saikyo Line and notifies the user's device. The device then displays the new route information and recalculates the walking route to the cafe and presents it to the user.

[1355] Furthermore, if the emotion engine detects that the user is becoming tense during their trip, it will support them by displaying more detailed and easy-to-understand guidance information and offering relaxing alternative routes. This way, users can avoid the hassle of switching between multiple applications and enjoy a smoother journey. Furthermore, by monitoring traffic conditions in real time and utilizing the emotion engine to provide adaptive support, stress caused by unexpected delays can also be reduced.

[1356] The processing flow will be explained below.

[1357] Step 1:

[1358] Using a mobile device or PC, the user inputs their home address (e.g., "26-1 Sakuragaokacho, Shibuya-ku, Tokyo") and the address of their destination (e.g., "a cafe near Shinjuku Station").

[1359] Step 2:

[1360] The terminal converts the input information into an appropriate format (such as JSON) and sends it to the server.

[1361] Step 3:

[1362] The server analyzes the home and destination information received from the terminal.

[1363] Step 4:

[1364] The server accesses a geographic information API to identify the nearest train station or bus stop near the user's home.

[1365] Step 5:

[1366] The server calculates the transportation method (walking, bus, etc.) to the nearest station or bus stop.

[1367] Step 6:

[1368] The server calls the transportation API (train and bus timetables) and obtains route information from the nearest station or bus stop to the station nearest to the destination.

[1369] Step 7:

[1370] The server uses a map API to calculate the walking route from the nearest station to the destination.

[1371] Step 8:

[1372] The server generates all the information it has acquired (nearest station, bus stop, train and bus departure times, boarding location, detailed transfer routes, walking routes, etc.) as integrated data.

[1373] Step 9:

[1374] The server returns the generated integrated data to the user terminal.

[1375] Step 10:

[1376] The terminal analyzes the integrated data received from the server.

[1377] Step 11:

[1378] The terminal displays information using an appropriate UI to make it easy for the user to understand.

[1379] Step 12:

[1380] The device highlights particularly important information (e.g., platform numbers for transfers and walking routes).

[1381] Step 13:

[1382] The device uses a built-in emotion engine to recognize the user's face and analyze their voice to detect their current emotions.

[1383] Step 14:

[1384] The emotion engine adjusts the display method based on the user's emotions. For example, if it determines that the user is nervous, it displays more detailed and concise guidance information.

[1385] Step 15:

[1386] The server monitors traffic information (train and bus operation status) in real time.

[1387] Step 16:

[1388] If a delay occurs during the journey, the server recalculates a new optimal route.

[1389] Step 17:

[1390] The server notifies the user terminal of the new optimum route.

[1391] Step 18:

[1392] If the emotion engine detects the user's stress level, it notifies the server to provide an alternative route to relaxation (e.g., a route that avoids crowds or a route through a park).

[1393] Step 19:

[1394] The terminal analyzes the new route information and notifies the user.

[1395] Step 20:

[1396] The device will again use the map API to calculate and display a new walking route if necessary.

[1397] Step 21:

[1398] Once the user arrives at the station nearest to their destination, the device will display detailed walking route instructions to help the user reach their destination without getting lost.

[1399] Specific examples

[1400] For example, if a user wants to go from 26-1 Sakuragaokacho, Shibuya-ku, Tokyo to a cafe near Shinjuku Station, the user enters the address of the starting point and destination into a smartphone app. The device sends this information to a server, which then calculates the optimal route. The resulting route is to board the Yamanote Line from Shibuya Station, get off at Shinjuku Station, and walk five minutes from the west exit. If the Yamanote Line is delayed during travel, the server calculates an alternative route using the Saikyo Line and notifies the user's device. The device then displays the new route information and recalculates the walking route to the cafe and presents it to the user.

[1401] Furthermore, if the emotion engine detects that the user is becoming tense during their trip, it will support them by displaying more detailed and easy-to-understand guidance information and offering relaxing alternative routes. This way, users can avoid the hassle of switching between multiple applications and enjoy a smoother journey. Furthermore, by monitoring traffic conditions in real time and utilizing the emotion engine to provide adaptive support, stress caused by unexpected delays can also be reduced.

[1402] Example 2

[1403] 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."

[1404] In modern transportation systems, users are required to efficiently plan the optimal route from their departure point to their destination. However, individually collecting information such as transportation schedules, route information, and real-time delay information is time-consuming and places a significant burden on users. Furthermore, users are prone to stress due to the lack of means to quickly respond when a delay occurs during travel. Furthermore, users' emotional state is not taken into consideration, which can increase stress during travel. These are important issues that need to be resolved.

[1405] 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.

[1406] In this invention, the server includes a means for collecting public transportation schedules and route information, a means for identifying the nearest station or bus stop and calculating the optimal route, and a means for detecting the user's emotions and providing guidance information in an adaptive manner. This allows the server to provide all the information the user needs in one place and quickly respond to delays during travel. Furthermore, providing guidance information according to the user's emotional state can reduce stress during travel.

[1407] "User" refers to an individual or organization that uses the system to obtain route information from a starting point to a destination.

[1408] The "starting point" indicates the location where the user starts moving.

[1409] A "destination" indicates the location where the user completes their journey.

[1410] "Public transportation" refers to public transportation means such as trains and buses.

[1411] "Schedule" refers to information about the operating hours and departure times of public transportation.

[1412] "Route information" refers to information about the route from the starting point to the destination.

[1413] "Nearest station" refers to the train station closest to the departure point or destination.

[1414] "Bus stop" refers to the bus stop closest to the departure point or destination.

[1415] The "optimal route" refers to the route that best satisfies conditions such as travel time and number of transfers.

[1416] "Integrated data" refers to data obtained from multiple sources that are combined into one.

[1417] "Traffic conditions" refers to the operation status of public transportation and road congestion.

[1418] "Delay information" refers to information when public transportation services are delayed from their scheduled times.

[1419] An "alternate route" is a different route used in the event of a delay or other problem.

[1420] "Emotion" refers to the user's state of mind.

[1421] "Emotion detection" refers to determining a user's emotional state from their facial expressions and voice.

[1422] "Adaptive method" refers to a method of changing the form and content of information provided depending on the emotional state of the user.

[1423] The present invention relates to a system that enables users to travel smoothly from their starting point to their destination. This system calculates the optimal route by having the user input their starting point and destination, and presents the route to the user as integrated data. It also has the function of monitoring traffic conditions in real time during travel and recalculating the optimal alternative route in the event of a delay, and notifying the user. Furthermore, the system incorporates an emotion engine that recognizes the user's emotions, and can adjust the way in which guidance information is presented based on the user's emotional state.

[1424] System Configuration

[1425] Hardware and Software Configuration

[1426] This system mainly consists of the following hardware and software:

[1427] 1. Terminal: A device such as a smartphone or PC that allows the user to input their starting point and destination. The terminal must be equipped with an internet connection, a camera, and a microphone.

[1428] 2. Server: A cloud-based system that analyzes data and calculates routes. The server has high-speed processing power and storage capacity to manage large amounts of data.

[1429] 3. API: An interface for obtaining route information, such as a geographical information API (e.g., Google Maps API) or a public transportation API (e.g., NAVITIME API).

[1430] 4. Emotion engine: Software that recognizes the user's face and analyzes their voice to detect their emotions.

[1431] Program processing flow and specific examples

[1432] User Input

[1433] The user enters their home address (e.g., "26-1 Sakuragaokacho, Shibuya-ku, Tokyo") and the address of their destination (e.g., "a cafe near Shinjuku Station") into their mobile device or PC. The device converts this input information into a format such as JSON and sends it to the server.

[1434] Route calculation and information integration

[1435] The server analyzes the home and destination information received from the device and identifies the nearest train station or bus stop near the home by accessing the Google Maps API. It then uses the NAVITIME API and other services to obtain public transportation schedules and route information and calculates the optimal route from the home to the destination. It then generates integrated data from all the information it has obtained and sends it back to the user's device.

[1436] Information presentation to users and operation of the emotion engine

[1437] The device analyzes the integrated data received from the server and displays the information in an easy-to-understand UI. It highlights particularly important information (e.g., platform numbers for transfers and walking routes). It also uses an emotion engine to analyze the user's face and voice and adjusts the display method based on the user's emotions. If the device determines that the user is under high stress, it displays more detailed and concise guidance information and offers relaxing alternative routes.

[1438] Support on the move

[1439] The server monitors traffic information in real time, and if a delay occurs during travel, it recalculates a new optimal route and notifies the user's device. The device then analyzes the new route information and notifies the user, allowing the user to continue traveling smoothly.

[1440] Specific examples

[1441] For example, if a user wants to go from 26-1 Sakuragaokacho, Shibuya-ku, Tokyo to a cafe near Shinjuku Station, the user enters the address of the starting point and destination into a smartphone app. The device sends this information to the server, which then uses the Google Maps API and NAVITIME API to calculate the optimal route. The resulting route is to board the Yamanote Line from Shibuya Station, get off at Shinjuku Station, and walk five minutes from the west exit. If the Yamanote Line is delayed during travel, the server calculates an alternative route using the Saikyo Line and notifies the user's device. The device then displays the new route information and recalculates the walking route to the cafe and presents it to the user.

[1442] Prompt Sentence Examples

[1443] "Please calculate the optimal route from the starting point '26-1 Sakuragaokacho, Shibuya-ku, Tokyo' to the destination 'a cafe near Shinjuku Station'. Please also include a detailed walking route to the destination. If possible, please also provide guidance on what to do if you become nervous during the trip."

[1444] The present invention provides users with all the traffic information they need in one place, allowing for quick responses to delays while traveling, and by providing information based on the user's emotional state, it is possible to reduce stress while traveling.

[1445] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1446] Step 1: User Input

[1447] The user enters their home address (e.g., "26-1 Sakuragaokacho, Shibuya-ku, Tokyo") and the address of their destination (e.g., "a cafe near Shinjuku Station") into a dedicated application on their smartphone or PC. The entered information is the user's starting point and destination data. When the user presses the "Search" button, the device receives this information and sends it to the next processing step.

[1448] input:

[1449] Address of departure point (e.g., "26-1 Sakuragaokacho, Shibuya-ku, Tokyo")

[1450] Destination address (e.g., "a cafe near Shinjuku Station")

[1451] output:

[1452] Origin and destination data converted to JSON format

[1453] Specific behavior:

[1454] The user enters address information into the application's input field and presses the "Search" button to complete the input.

[1455] Step 2: Send device data

[1456] The terminal converts the address data entered by the user into JSON format and sends it to the server. This conversion is for the purpose of improving data consistency and transmission efficiency. The terminal then sends this data to the server as an HTTP POST request.

[1457] input:

[1458] Origin and destination data converted to JSON format

[1459] output:

[1460] The HTTP POST request sent to the server

[1461] Specific behavior:

[1462] The terminal converts the data entered by the user into JSON format and sends it as an HTTP POST request to the server.

[1463] Step 3: Data analysis and route calculation on the server

[1464] 1. Data analysis: The server analyzes the address information received from the terminal to identify the starting point and destination.

[1465] 2. Identifying the nearest station or bus stop: The server uses the geographic information API to identify the nearest station or bus stop near the departure point.

[1466] 3. Calculating transportation: The server calculates the appropriate transportation method (walking, bus, etc.) from home to the nearest station or bus stop.

[1467] 4. Obtain route information: The server uses the public transport API to obtain public transport schedule and route information.

[1468] 5. Calculating walking route: The server calculates the walking route from the nearest station to the destination to the destination.

[1469] 6. Generation of integrated data: All acquired information is integrated to generate comprehensive route data.

[1470] input:

[1471] HTTP POST request sent to the server

[1472] Origin and destination information based on geographical API

[1473] Schedule and route information obtained from public transport APIs

[1474] output:

[1475] Integrated Route Data

[1476] Specific behavior:

[1477] The server uses a programming language such as Python to send requests to the Google Maps API or NAVITIME API, obtain the necessary data, and generate integrated data.

[1478] Step 4: Sending route information from the server to the device

[1479] The server then sends the generated integrated data back to the device, which includes the nearest stations, departure times, transfer details, walking routes, etc.

[1480] input:

[1481] Integrated Route Data

[1482] output:

[1483] Route data sent to the device as an HTTP response

[1484] Specific behavior:

[1485] The server sends the integrated data to the terminal as an HTTP response.

[1486] Step 5: Displaying consolidated data on the terminal

[1487] The device analyzes the integrated data received from the server and displays the information on the UI of a dedicated application, highlighting particularly important information (e.g., platform numbers for transfers and walking routes).

[1488] input:

[1489] Aggregated data received from the server

[1490] output:

[1491] Route information displayed to users

[1492] Specific behavior:

[1493] The terminal analyzes the data received from the server and displays it in the format best suited to the application.

[1494] Step 6: Detect and adjust user emotions with the emotion engine

[1495] 1. Facial recognition and voice analysis: The device's built-in emotion engine performs facial recognition and voice analysis of the user.

[1496] 2. Display content adjustment: The emotion engine adjusts the display content based on the detected emotions. If stress is detected to be high, the guidance information will be displayed in more detail and concisely.

[1497] 3. Providing alternative routes: The emotion engine sends a notification to the server to provide alternative routes to relax depending on the user's stress level.

[1498] input:

[1499] User's facial image and voice data

[1500] output:

[1501] Adjusted guidance information

[1502] Notifying the server

[1503] Specific behavior:

[1504] The device's camera and microphone collect the user's face and voice, and the emotion engine analyzes them to determine the user's emotions. The system adjusts the display content to take appropriate action and sends notifications to the server as necessary.

[1505] Step 7: Real-time traffic monitoring and route updates

[1506] 1. Traffic information monitoring: The server monitors the train and bus operation status in real time.

[1507] 2. Recalculation on Delay: If a delay occurs during travel, the server recalculates a new optimal route.

[1508] 3. Notification to the terminal: The server notifies the terminal of the new route information.

[1509] 4. Displaying the new route: The device analyzes the new route information and notifies the user. If necessary, it calculates and displays a new walking route using the map API.

[1510] input:

[1511] Real-time traffic information

[1512] output:

[1513] New route information

[1514] Specific behavior:

[1515] The server periodically calls the traffic information API to obtain the current operating conditions, and if a delay occurs, calculates a new optimal route and notifies the device. The device then displays the new route to the user.

[1516] Through the above process, users can obtain optimal route information and receive real-time support while traveling. This system is expected to make users' travels smoother and stress-free.

[1517] (Application example 2)

[1518] 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."

[1519] The present invention relates to a system that enables users to travel smoothly and comfortably. Conventional mobility assistance systems have limitations in optimizing routes and providing delay information, and are unable to consider the user's emotional state. Furthermore, the control of autonomous vehicles is limited, making it difficult to provide an optimal travel experience. Therefore, there is a need for systems that can present guidance information according to the user's emotional state and enable smooth travel using autonomous vehicles.

[1520] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1521] In this invention, the server includes: means for a user to input a departure point and a destination; means for collecting transportation schedules and route information; means for calculating an optimal route and generating it as integrated data; means for presenting the generated integrated data to the user; means for monitoring traffic conditions during travel and providing delay information in real time; means for recalculating an optimal alternative route in the event of a delay and presenting it to the user; means for adjusting the presentation method of guidance information based on the user's emotions, which includes an emotion engine that recognizes the user's emotions; means for sending instructions about the optimal route to an autonomous vehicle and means for controlling the autonomous vehicle. This enables smooth and comfortable travel by utilizing an autonomous vehicle that adapts to the user's emotional state.

[1522] The "means by which a user inputs their starting point and destination" refers to the interface that a user uses to set a route to their destination, and is provided through a device such as a smartphone, tablet, or PC.

[1523] "Means for collecting transport schedule and route information" refers to a system or module for obtaining timetables and route information for transport such as trains and buses, and collects information using APIs and databases.

[1524] The "means for calculating the optimal route and generating it as integrated data" refers to an algorithm and calculation system for calculating the optimal travel route based on the starting point and destination entered by the user and generating the result as integrated data.

[1525] The "means for presenting the generated integrated data to the user" refers to an interface that visually or audibly presents the calculated optimal route to the user, and displays the information through a display such as a smartphone or smart glasses.

[1526] "Means for monitoring traffic conditions while traveling and providing delay information in real time" refers to a system for monitoring the real-time conditions of roads and transportation facilities while traveling and providing delay information to users immediately.

[1527] "Means for recalculating the optimal alternative route in the event of a delay and presenting it to the user" refers to an algorithm and interface for recalculating the optimal route when a delay occurs in a transportation service or route and presenting that information to the user.

[1528] An "emotion engine that recognizes the user's emotions" is software or hardware that can analyze the user's facial expressions and voice data and detect their current emotional state.

[1529] The "means for adjusting the method of presenting guidance information" is a system that dynamically changes the method and timing of displaying guidance information based on the detected emotional state of the user.

[1530] The "means for transmitting optimal route instructions to an autonomous vehicle" is a system for communicating information about the calculated optimal route to an autonomous vehicle and transmitting the instructions to the vehicle.

[1531] The "means for controlling an autonomous vehicle" refers to hardware and software for appropriately controlling the autonomous vehicle in accordance with the received optimal route.

[1532] The present invention is a support system for users to travel smoothly from their starting point to their destination. This system realizes comfortable travel by providing real-time information on transportation and the optimal route according to the user's emotional state. Furthermore, the invention supports travel using autonomous vehicles.

[1533] System configuration

[1534] The system consists of the following main components:

[1535] 1. User Input Method

[1536] The user inputs the starting point and destination using a device such as a smartphone, smart glasses, or tablet.

[1537] 2. Means of collecting transportation information

[1538] The server utilizes an API (e.g., Google Maps API) to collect transportation schedule and route information.

[1539] 3. Route calculation method

[1540] The server calculates the optimal route based on the collected information and generates the results as integrated data.

[1541] 4. Integrated Data Presentation Method

[1542] The generated integrated data is presented on the user terminal, and guidance information is provided visually and audibly.

[1543] 5. Traffic monitoring means

[1544] The server monitors traffic conditions in real time and provides delay information to users.

[1545] 6. Alternative Route Calculation Methods

[1546] If a delay occurs, the server recalculates a new optimal route and presents it to the user.

[1547] 7. Emotion Engine

[1548] It uses the camera and microphone built into the user's device to incorporate an emotion engine that recognizes emotions (e.g., Affectiva SDK).

[1549] The emotion engine adjusts how the guidance information is displayed based on the user's emotional state.

[1550] 8. Autonomous Vehicle Control Methods

[1551] The server instructs the autonomous vehicle on the optimal route and controls the vehicle appropriately.

[1552] Specific examples of processing

[1553] The user uses the smart glasses to voice-input their home address and destination address. The device then sends this information to the server, which then uses a public transport API to calculate the optimal route. The calculation results are displayed on the smart glasses' display. If a public transport delay occurs during travel, the server automatically calculates a new route and provides that information to the user.

[1554] The smart glasses' camera and microphone are also used to analyze the user's facial and voice data with an emotion engine to recognize their emotional state. For example, if the system determines that the user is nervous, it will display more detailed and easy-to-understand guidance information and suggest a relaxing route. In this way, providing guidance information that adapts to the user's emotional state can reduce stress during travel.

[1555] Furthermore, when using an autonomous vehicle, the server sends instructions for the optimal route to the vehicle, which then performs autonomous driving according to those instructions, allowing the user to travel smoothly and safely from their starting point to their destination.

[1556] Prompt Sentence Examples

[1557] Below is an example of a prompt sentence to input to the generative AI model.

[1558] Enter the user's starting point and destination. Write a program to calculate the route and display it on the smart glasses. It should also analyze the user's emotional state and suggest a relaxing route. Write the program in Python and explain how to use any necessary libraries and APIs. Below is an example of input data.

[1559] The present invention enables smooth and comfortable travel using autonomous vehicles that adapt to the user's emotional state.

[1560] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1561] Step 1:

[1562] The user inputs a starting point and a destination.

[1563] Input: The user puts on the smart glasses and enters the starting point and destination by voice.

[1564] How it works: The device recognizes the input as text data and converts it into a format (e.g., JSON).

[1565] Output: Formatted text data is generated.

[1566] Step 2:

[1567] The terminal sends the input data to the server.

[1568] Input: Text data of the starting point and destination entered by the user.

[1569] How it works: The device uses a communication protocol (e.g. HTTP) to send this data to the server.

[1570] Output: The server receives the request.

[1571] Step 3:

[1572] A server collects transportation schedule and route information.

[1573] Input: The origin and destination data sent to the server.

[1574] How it works: The server calls a transit API (e.g., Google Maps API) to get the necessary schedule and route information.

[1575] Output: Transit schedules and route information.

[1576] Step 4:

[1577] The server calculates the optimal route and generates it as integrated data.

[1578] Input: Transit schedule and route information.

[1579] How it works: The server uses the collected information to run algorithms and calculate the optimal route. The results are then compiled into a consolidated data set.

[1580] Output: Consolidated data of optimal routes.

[1581] Step 5:

[1582] The server transmits the integrated data to the terminal.

[1583] Input: Optimal route synthesis data.

[1584] Operation: The server sends the generated integrated data to the terminal.

[1585] Output: The terminal receives the consolidated data.

[1586] Step 6:

[1587] The terminal presents the integrated data to the user.

[1588] Input: The aggregate data received from the server.

[1589] Operation: The device analyzes the integrated data and displays guidance information visually or audibly on the display.

[1590] Output: The user is presented with a guide.

[1591] Step 7:

[1592] The server monitors traffic conditions in real time while on the move.

[1593] Input: Real-time traffic data.

[1594] Operation: The server periodically calls the transport API to monitor real-time traffic conditions.

[1595] Output: Traffic updates.

[1596] Step 8:

[1597] The terminal provides delay information to the user.

[1598] Input: Traffic updates.

[1599] Operation: If a delay occurs, the server recalculates a new optimal route and sends that information to the terminal, which then receives it and notifies the user.

[1600] Output: The latest guidance information is presented to the user.

[1601] Step 9:

[1602] The terminal recognizes the user's emotional state.

[1603] Input: User's facial expression data and voice data.

[1604] How it works: The device uses its built-in camera and microphone to collect data, which is then analyzed by an emotion engine.

[1605] Output: User's emotional state (e.g. stress level).

[1606] Step 10:

[1607] The server adjusts how the guidance information is presented.

[1608] Input: The user's emotional state.

[1609] Operation: The server dynamically adjusts the display method and content of the guidance information based on the output of the emotion engine.

[1610] Output: Adjusted guidance information.

[1611] Step 11:

[1612] The server sends optimal route instructions to the autonomous vehicle.

[1613] Input: The final calculated or recalculated optimal route.

[1614] Operation: The server communicates with the autonomous vehicle and sends it the optimal route.

[1615] Output: The autonomous vehicle receives and executes the optimal route.

[1616] Step 12:

[1617] An autonomous vehicle transports the user to their destination.

[1618] Input: Optimal route instructions sent by the server.

[1619] Action: The autonomous driving system starts driving according to the optimal route and takes the user to their destination.

[1620] Output: The user reaches the destination.

[1621] 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.

[1622] 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.

[1623] 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.

[1624] [Fourth embodiment]

[1625] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1626] 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.

[1627] 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).

[1628] 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.

[1629] 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.

[1630] 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).

[1631] 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. 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.

[1632] 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.

[1633] 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.

[1634] 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.

[1635] 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.

[1636] 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.

[1637] 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."

[1638] This invention relates to a service that allows users to travel smoothly from their departure point to their destination. This system allows users to input their departure point and destination, and then collects public transport schedules and route information in one place, calculates the optimal route, and presents it to the user as integrated data. It also monitors traffic conditions in real time during travel, and recalculates and notifies the user of the optimal alternative route in the event of a delay, providing users with a smooth and comfortable journey.

[1639] Processing flow and specific operations

[1640] User Input

[1641] 1. The user enters their home address (e.g., "26-1 Sakuragaoka-cho, Shibuya-ku, Tokyo") and the address of their destination (e.g., "a cafe near Shinjuku Station") into their mobile device or PC.

[1642] 2. The device converts this input information into an appropriate format (such as JSON) and sends it to the server.

[1643] Route calculation and information acquisition

[1644] 1. The server analyzes the home and destination information received from the device and calls the geographic information API to identify the nearest train station or bus stop near the home.

[1645] 2. The server calculates the transportation method (walking, bus, etc.) from home to the nearest station or bus stop, and then obtains route information from the nearest station or bus stop to the station nearest to the destination using a transportation API (train or bus timetable).

[1646] 3. The server integrates this information and returns the generated integrated data to the user terminal.

[1647] Display to users

[1648] 1. The terminal analyzes the integrated data received from the server and displays it in an appropriate UI to make the information easy for the user to understand.

[1649] 2. The device will highlight particularly important information (e.g., platform numbers for transfers and walking routes).

[1650] Support on the move

[1651] 1. The server monitors traffic information (train and bus operation status) in real time and calculates a new optimal route if a delay occurs.

[1652] 2. The server notifies the user terminal of the new optimal route.

[1653] 3. The device analyzes the new route information, notifies the user, and, if necessary, uses the map API again to calculate and display a new walking route.

[1654] Specific examples

[1655] For example, if a user wants to go from 26-1 Sakuragaokacho, Shibuya-ku, Tokyo to a cafe near Shinjuku Station, the user enters the address of the starting point and destination into a smartphone app. The device sends this information to a server, which then calculates the optimal route. The resulting route is to board the Yamanote Line from Shibuya Station, get off at Shinjuku Station, and walk five minutes from the west exit. If the Yamanote Line is delayed during travel, the server calculates an alternative route using the Saikyo Line and notifies the user's device. The device then displays the new route information and recalculates the walking route to the cafe and presents it to the user. After arriving at Shinjuku Station, detailed walking route instructions are displayed, allowing the user to reach their destination without getting lost.

[1656] This allows users to travel more smoothly without having to use multiple applications, and by monitoring traffic conditions in real time and providing adaptive support, it also reduces the frustration of unexpected delays.

[1657] The processing flow will be explained below.

[1658] Step 1:

[1659] Using a mobile device or PC, the user enters their home address (e.g., "26-1 Sakuragaokacho, Shibuya-ku, Tokyo") and the address of their destination (e.g., "a cafe near Shinjuku Station").

[1660] Step 2:

[1661] The terminal converts the input information into an appropriate format, such as JSON, and sends it to the server.

[1662] Step 3:

[1663] The server analyzes the home and destination information received from the terminal.

[1664] Step 4:

[1665] The server accesses a geographic information API to identify the nearest train station or bus stop near the user's home.

[1666] Step 5:

[1667] The server calculates the transportation method (walking, bus, etc.) from home to the nearest station or bus stop.

[1668] Step 6:

[1669] The server calls the transportation API (train and bus timetables) and obtains route information from the nearest station or bus stop to the station nearest to the destination.

[1670] Step 7:

[1671] The server uses a map API to calculate the walking route from the nearest station to the destination.

[1672] Step 8:

[1673] The server generates all the information it has acquired (nearest station, bus stop, train and bus departure times, boarding location, detailed transfer routes, walking routes, etc.) as integrated data.

[1674] Step 9:

[1675] The server returns the generated integrated data to the user terminal.

[1676] Step 10:

[1677] The terminal analyzes the integrated data received from the server.

[1678] Step 11:

[1679] The terminal displays the analyzed information using an appropriate UI so that the information can be easily understood by the user.

[1680] Step 12:

[1681] The device highlights particularly important information (such as platform numbers for transfers and walking routes).

[1682] Step 13:

[1683] The server monitors traffic information (train and bus operation status) in real time.

[1684] Step 14:

[1685] If a delay occurs during the journey, the server recalculates a new optimal route.

[1686] Step 15:

[1687] The server notifies the user terminal of the new optimum route.

[1688] Step 16:

[1689] The terminal analyzes the new route information and notifies the user.

[1690] Step 17:

[1691] The device will again use the map API to calculate and display a new walking route if necessary.

[1692] Step 18:

[1693] Once the user arrives at the station nearest to their destination, the device will display detailed walking route instructions to help the user reach their destination without getting lost.

[1694] Example 1

[1695] 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."

[1696] Conventional mobility assistance systems require users to individually collect information on different modes of transport and combine it to find the optimal route, which is extremely time-consuming. Furthermore, they are unable to respond immediately to changes in traffic conditions (such as delays or service cancellations), making it difficult to respond quickly when unexpected problems occur.

[1697] 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.

[1698] In this invention, the server includes means for a user to input a departure point and a destination, means for collecting public transportation schedules and route information, means for identifying the nearest transfer station or bus stop, means for calculating routes from the departure point to the nearest station and from the nearest station to the destination and generating the resulting integrated data, means for presenting the generated integrated data to the user, means for monitoring traffic conditions in real time during travel and providing delay information, and means for recalculating a new optimal route in the event of a delay and presenting the new optimal route to the user. This not only allows the user to have the optimal route from the departure point to the destination automatically calculated in a single system, but also allows for immediate response to any problems that may arise during travel, enabling smooth and comfortable travel.

[1699] A "user" is an individual or organization that utilizes the system to input a starting point and a destination and obtain optimal route information.

[1700] The "starting point" is the location where the user begins their journey.

[1701] A "destination" is a location where a user ultimately wants to arrive.

[1702] "Public transportation" means transportation available to the general public (e.g., trains, buses, subways, etc.).

[1703] "Schedule" refers to the operating hours and timetables of public transportation.

[1704] "Route information" refers to detailed information about a specific route (e.g., which stations or bus stops to transfer at, travel time, etc.).

[1705] The "nearest station" refers to the train station closest to the user's starting point or destination.

[1706] A "bus stop" is a place where buses stop and passengers board and disembark.

[1707] "Integrated data" refers to data that centrally compiles information on multiple routes.

[1708] "Real-time" refers to reflecting the current situation immediately.

[1709] "Traffic conditions" refers to the current operational status of transportation (e.g., delays, cancellations, etc.).

[1710] "Delay information" refers to information about public transportation being delayed from its scheduled time.

[1711] An "optimal route" is the most efficient route from a starting point to a destination.

[1712] An "alternate route" is a different route that is set up when the optimal route is not available.

[1713] The present invention relates to a system that enables users to travel smoothly from their departure point to their destination. This system allows users to input their departure point and destination, and then collects public transportation schedules and route information in one go, calculates the optimal route, and presents it to the user as integrated data. It also monitors traffic conditions in real time during travel, and if a delay occurs, recalculates the optimal alternative route and presents it to the user, providing users with a smooth and comfortable journey.

[1714] User Input

[1715] 1. The user inputs the starting point and destination using a mobile device or computer. In this case, an example of the starting point is "26-1 Sakuragaokacho, Shibuya-ku, Tokyo," and an example of the destination is "a cafe near Shinjuku Station."

[1716] 2. The terminal converts the input data into JSON format and sends it to the server. This process can be done using general-purpose programming languages ​​such as JavaScript and Python.

[1717] Server processing

[1718] 1. The server analyzes the data received from the device. To do this, it uses the Google Maps API to obtain the latitude and longitude of the departure and destination points and identifies the nearest train station or bus stop.

[1719] 2. The server uses the Google Maps API and the train operation information API to calculate the route from the starting point to the nearest station and from the nearest station to the destination. Specific route information includes walking routes, train timetables, transfer information, etc.

[1720] Integrated data generation and presentation

[1721] 1. The server integrates the acquired information into a single integrated data set. This integrated data set provides a unified view of the user's travel plan.

[1722] 2. The server converts the generated integrated data back into JSON format and sends it back to the user's device.

[1723] 3. The device analyzes the received integrated data and displays it in a visually easy-to-understand format for the user, with important information (such as transfer platform numbers and walking routes) highlighted.

[1724] Real-time support on the go

[1725] 1. The server uses the NAVITIME API, for example, to monitor traffic conditions in real time, thereby constantly monitoring train and bus delay information.

[1726] 2. The server recalculates a new optimal route when a delay occurs and sends that information to the user's device. A generative AI model can be used for the calculation process.

[1727] 3. The device analyzes the new route information and notifies the user, and if necessary, calculates and displays a new walking route using the Google Maps API again.

[1728] Specific examples

[1729] For example, if a user wants to go from 26-1 Sakuragaokacho, Shibuya-ku, Tokyo to a cafe near Shinjuku Station, they input their starting point and destination into the smartphone app. The device sends this information to the server, which then calculates the optimal route. The resulting route is a train ride from Shibuya Station, alighting at Shinjuku Station, and a five-minute walk to the cafe.

[1730] Prompt Sentence Examples

[1731] Design a system that calculates the optimal route for a user to go from 26-1 Sakuragaokacho, Shibuya-ku, Tokyo to a cafe near Shinjuku Station, and suggests alternative routes if there are public transport delays. Explain each step in natural language.

[1732] This allows users to travel more smoothly without having to switch between multiple applications, and by monitoring traffic conditions in real time and providing adaptive support, it also reduces the frustration of unexpected delays.

[1733] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1734] Step 1:

[1735] The user uses a mobile device or PC to input the starting point (e.g., "26-1 Sakuragaoka-cho, Shibuya-ku, Tokyo") and the destination (e.g., "a cafe near Shinjuku Station").

[1736] Specific behavior: A user opens the application, manually enters the starting point and destination in the input form, and presses the submit button when the input is complete.

[1737] Input and Output: The input is the address information of the starting point and the destination, and the output is these addresses formatted as JSON.

[1738] Step 2:

[1739] The terminal converts the data entered by the user into JSON format and sends it to the server.

[1740] What happens: The device application collects the input information, converts it to JSON format using JavaScript or Python code, and then sends an HTTP request to the corresponding API endpoint.

[1741] Input and Output: The input is the address information of the starting point and the destination, and the output is the JSON format data sent to the server.

[1742] Step 3:

[1743] The server analyzes the JSON data received from the device and calls the geographic information API to obtain the geographic information (latitude and longitude) of the departure and destination points.

[1744] What happens: The server parses the received JSON data, extracts the address information, and then sends a request to the Google Maps API to convert the address information into latitude and longitude coordinates.

[1745] Input and Output: The input is address information in JSON format, and the output is latitude and longitude information.

[1746] Step 4:

[1747] The server calls a geographic information API to identify the nearest transfer station or bus stop based on the geographic information of the departure point and destination.

[1748] Specific operation: The server also uses the Google Maps API to search for the nearest train station or bus stop based on the acquired latitude and longitude information.

[1749] Input and output: The input is the latitude and longitude information of the departure point and destination, and the output is the name and location information of the nearest station or bus stop.

[1750] Step 5:

[1751] Based on the information on the nearest station and bus stop, the server obtains the walking route from the starting point to the nearest station or bus stop from the Google Maps API.

[1752] Specific operation: The server requests a route search from the Google Maps API using the latitude and longitude of the starting point and the latitude and longitude of the nearest station or bus stop.

[1753] Input and output: The input is the latitude and longitude information of the starting point and the nearest station, and the output is walking route information.

[1754] Step 6:

[1755] The server calls the public transport API to obtain route information for public transport from the nearest station to the station nearest to the destination.

[1756] Specific operation: Based on the information of the nearest station to the departure point and the nearest station to the destination, the server sends a request to the public transportation API to obtain operation schedules and route information.

[1757] Input and output: The input is the name information of the nearest station to the departure point and the nearest station to the destination, and the output is public transport route information.

[1758] Step 7:

[1759] The server obtains walking route information from the nearest station to the destination from the Google Maps API.

[1760] Specific operation: The server requests a route search from the Google Maps API using the latitude and longitude of the station nearest to the destination and the latitude and longitude of the destination.

[1761] Input and output: The input is the nearest station to the destination and the latitude and longitude information of the destination, and the output is walking route information.

[1762] Step 8:

[1763] The server integrates all this information and generates a comprehensive travel plan.

[1764] Specific operation: The server integrates the acquired walking routes, public transport routes and transfer information and converts them into a single integrated data in JSON format.

[1765] Input and Output: The input is the route information obtained at each stage, and the output is the integrated data.

[1766] Step 9:

[1767] The server returns the generated integrated data to the user terminal.

[1768] Specific operation: The server sends the generated integrated data in JSON format to the user's device as an HTTP response.

[1769] Input and Output: The input is the generated integrated data, and the output is the integrated data sent to the user terminal.

[1770] Step 10:

[1771] The terminal analyzes the integrated data received from the server and displays it on the UI in a format that is easy for the user to understand.

[1772] Specific behavior: The device parses the received JSON data, extracts the necessary information, and displays it in the UI component, highlighting particularly important elements (such as platform number and detailed walking route).

[1773] Input and Output: The input is the consolidated data received from the server, and the output is the visual route information displayed to the user.

[1774] Step 11:

[1775] The server monitors traffic conditions in real time while traveling and recalculates a new optimal route if delays occur.

[1776] How it works: The server continuously retrieves data from the real-time traffic information API and recalculates a new route in the event of delays or cancellations.

[1777] Input and Output: The input is real-time traffic situation information, and the output is new optimal route information.

[1778] Step 12:

[1779] The server notifies the user terminal of the new optimum route.

[1780] Specific operation: The server retransmits the newly calculated route information to the user terminal and notifies it as an HTTP response.

[1781] Input and Output: The input is the new optimal route information, and the output is the notification to the user terminal.

[1782] Step 13:

[1783] The device analyzes the received new route information and presents it to the user again, recalculating and displaying a new walking route if necessary.

[1784] Specific behavior: The device parses the newly received JSON data, extracts the necessary information, and displays it in the UI. If necessary, it calculates a new walking route using the Google Maps API and presents it to the user again.

[1785] Input and Output: The input is the new route information received from the server, and the output is the new route information displayed to the user.

[1786] (Application example 1)

[1787] 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."

[1788] When autonomous vehicles travel, they often encounter different traffic conditions and obstacles, which can make smooth travel difficult. In particular, when transportation delays or accidents occur, appropriate responses cannot be made, causing great inconvenience to users. In addition, autonomous vehicles often lack the information they need to determine the optimal route in real time. To solve these problems, a system is needed that can obtain traffic information in real time and adaptively provide the optimal route.

[1789] 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.

[1790] In this invention, the server includes means for a user to input a departure point and a destination, means for collecting transportation schedules and route information, means for calculating an optimal route and generating it as integrated data, means for presenting the generated integrated data to the user, means for monitoring traffic conditions during travel and providing delay information in real time, means for recalculating an optimal alternative route in the event of a delay and presenting it to the user, means for collecting route information specifically for autonomous vehicles, means for generating instructions for the autonomous vehicle to travel the optimal route, and means for detecting traffic obstructions while the autonomous vehicle is in operation and calculating an alternative route. This enables smooth travel using autonomous vehicles based on real-time traffic information.

[1791] "Means for a user to input a starting point and a destination" refers to a device or interface that allows a user to input information about their starting point and destination.

[1792] "Means for collecting transport schedule and route information" refers to software and hardware for obtaining information on public transport schedules and routes and storing it in the system.

[1793] "Means for calculating the optimal route and generating it as integrated data" is a function that analyzes multiple routes based on collected information, calculates the most efficient route among them, and generates it as a single integrated data.

[1794] The "means for presenting the generated integrated data to the user" refers to a device or system for providing the calculated optimum route information to the user visually or audibly.

[1795] "Means for monitoring traffic conditions while traveling and providing delay information in real time" refers to technology that monitors traffic conditions in real time, detects delays and obstacles, and immediately notifies users.

[1796] "Means for recalculating the optimal alternative route in the event of a delay and presenting it to the user" is a function that calculates a new alternative route and notifies the user when a delay occurs on the planned route due to changes in traffic conditions.

[1797] "Means for collecting route information specifically for autonomous vehicles" refers to technologies and devices for collecting route information specifically for the operation of autonomous vehicles.

[1798] The "means for generating instructions for an autonomous vehicle to travel along an optimal route" is a function for generating specific instructions for operating an autonomous vehicle along an optimal route.

[1799] "Means for detecting obstacles while an autonomous vehicle is in operation and calculating an alternative route" refers to technology that allows an autonomous vehicle to detect obstacles while in operation and calculate a safe and efficient alternative route.

[1800] This invention provides a system that calculates an optimal route in real time and adaptively responds to traffic conditions when a user travels to a destination using an autonomous vehicle. This system includes the following configuration and functions.

[1801] System Configuration

[1802] 1. User Device

[1803] Smartphones, tablets, and vehicle-mounted head-mounted displays (HMDs)

[1804] This allows the user to input a starting point and a destination.

[1805] 2. Server

[1806] High-performance computing facilities in cloud environments or data centers

[1807] A back-end system for collecting transport schedule and route information and calculating optimal routes.

[1808] 3. Self-driving vehicles

[1809] Equipped with sensors such as GPS, cameras, LiDAR, and radar, it acquires location information and traffic conditions in real time.

[1810] It receives instructions from the server and moves along the optimal route.

[1811] Program processing

[1812] Data Acquisition and Input

[1813] The user terminal provides an interface for the user to input the starting point and destination. The information entered by the user is converted into an appropriate format, such as JSON, and sent to the server.

[1814] Route calculation

[1815] Based on the received departure and destination information, the server calls the transportation schedule API and geographic information API to calculate the optimal route.

[1816] Data Integration

[1817] The calculated route information is generated as a single integrated data set and sent back to the user's device, which analyzes the data and displays it in an easy-to-understand UI.

[1818] Real-time monitoring

[1819] The server monitors traffic conditions in real time, detecting delays and accidents. If a delay occurs, the server immediately recalculates the optimal alternative route and notifies the user.

[1820] Operation of autonomous vehicles

[1821] The autonomous vehicle receives instructions from the server and moves along the optimal route. If an obstacle is detected, the autonomous vehicle will calculate an alternative route and control itself to move safely.

[1822] Specific examples

[1823] For example, a user inputs their starting point "Shibuya" and destination "Shinjuku" on their smartphone. The device sends this information to a server, which then uses a public transport API to calculate the optimal route. As a result, a train route from Shibuya to Shinjuku is suggested. If a train is delayed during travel, the server recalculates an alternative route and notifies the application. The same applies when traveling in an autonomous vehicle, where traffic conditions are monitored in real time and the optimal route is provided.

[1824] Prompt Sentence Examples

[1825] "Design an app system that suggests the best route for a self-driving vehicle from Shibuya to Shinjuku in Tokyo, and notifies the driver by recalculating the route based on real-time traffic conditions."

[1826] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1827] Step 1:

[1828] Input: The user inputs a starting point and a destination.

[1829] Operation: The user device receives the departure and destination information entered by the user (e.g., "Shibuya" and "Shinjuku"). The user device converts this information into JSON format and sends it to the server.

[1830] Output: The start and end points are sent to the server in JSON format.

[1831] Step 2:

[1832] Input: The departure and destination information received by the server from the device.

[1833] How it works: The server analyzes the received departure and destination information and uses a geographic information API to identify the nearest train station or bus stop near the user's home. Based on this data, the server calculates the optimal route.

[1834] Output: Information on the nearest station and bus stop, as well as the best route information.

[1835] Step 3:

[1836] Input: Information on the nearest station or bus stop, and optimal route information.

[1837] How it works: The server collects route information from the nearest station or bus stop to the station nearest to the destination using public transport APIs (train and bus timetables). The collected information is compiled into a single integrated data set.

[1838] Output: Overall route information as consolidated data.

[1839] Step 4:

[1840] Input: Integrated data.

[1841] Operation: The server returns the generated integrated data to the user terminal, which receives and analyzes the integrated data.

[1842] Output: Parsed route information.

[1843] Step 5:

[1844] Input: Parsed route information.

[1845] Operation: The user device presents the analyzed route information to the user in an easy-to-read format, highlighting particularly important information (such as transfer platform numbers and walking routes).

[1846] Output: Optimal route information presented to the user.

[1847] Step 6:

[1848] Input: Real-time traffic data.

[1849] How it works: During the journey, the server monitors traffic conditions in real time, obtaining information about delays and obstacles. If a delay occurs, it recalculates a new optimal route.

[1850] Output: Delay information and best alternative route.

[1851] Step 7:

[1852] Input: The new optimal route.

[1853] Operation: The server notifies the user device of the new, recalculated optimal route. The user device analyzes the new route information and notifies the user. If necessary, it uses the map API to calculate and display the new walking route.

[1854] Output: The new optimal route information presented to the user.

[1855] Step 8:

[1856] Input: Real-time sensor information from an autonomous vehicle.

[1857] How it works: Autonomous vehicles acquire real-time location information and traffic conditions through sensors such as GPS, cameras, LiDAR, and radar. Based on the acquired data, they receive instructions from a server to move along the optimal route, and if they detect an obstacle, they calculate an alternative route themselves.

[1858] Output: Safe and efficient route.

[1859] 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.

[1860] This invention relates to a service that enables users to travel smoothly from their departure point to their destination. The system collects public transport schedules and route information in one place when the user inputs their departure point and destination, calculates the optimal route, and presents the integrated data to the user. It also has a function to monitor traffic conditions in real time during travel and recalculate the optimal alternative route and notify the user in the event of a delay.

[1861] Furthermore, the present invention incorporates an emotion engine that recognizes the user's emotions, using the user's facial recognition system and voice analysis system to detect the user's emotions, and can adjust the way guidance information is presented based on the user's emotions, or provide a more comfortable alternative route depending on the user's stress level.

[1862] Processing flow and specific operations

[1863] User Input

[1864] 1. The user enters their home address (e.g., "26-1 Sakuragaoka-cho, Shibuya-ku, Tokyo") and the address of their destination (e.g., "a cafe near Shinjuku Station") into their mobile device or PC.

[1865] 2. The device converts this input information into an appropriate format (such as JSON) and sends it to the server.

[1866] Route calculation and information acquisition

[1867] 1. The server analyzes the home and destination information received from the device and accesses the geographic information API to identify the nearest train station or bus stop near the home.

[1868] 2. The server calculates the transportation method (walking, bus, etc.) from home to the nearest station or bus stop.

[1869] 3. The server calls the transportation API (train and bus timetables) and obtains route information from the nearest station or bus stop to the station nearest to the destination.

[1870] 4. The server uses a map API to calculate the walking route from the nearest station to the destination.

[1871] 5. The server generates all the acquired information (nearest station, bus stop, train and bus departure times, boarding location, detailed transfer routes, walking routes, etc.) as integrated data.

[1872] 6. The server returns the generated integrated data to the user terminal.

[1873] Display to users and operation of the emotion engine

[1874] 1. The terminal analyzes the integrated data received from the server and displays the information using an appropriate UI to make it easy for the user to understand.

[1875] 2. The device will highlight particularly important information (e.g., platform numbers for transfers and walking routes).

[1876] 3. The device uses a built-in emotion engine to recognize the user's face and analyze their voice to detect their current emotions.

[1877] 4. The emotion engine adjusts the display method based on the user's emotions. For example, if it determines that the user is under high stress, it displays more detailed and concise guidance information.

[1878] 5. If the emotion engine detects the user's stress level, it notifies the server to provide an alternative relaxing route (e.g., an avoidance route or a route through a park).

[1879] Support on the move

[1880] 1. The server monitors traffic information (train and bus operation status) in real time.

[1881] 2. If a delay occurs during the journey, the server recalculates a new optimal route.

[1882] 3. The server notifies the user terminal of the new optimal route.

[1883] 4. The device analyzes the new route information and notifies the user.

[1884] 5. The device will calculate and display a new walking route, again using the Maps API if necessary.

[1885] 6. After the user arrives at the station nearest to their destination, the device will display detailed walking route instructions to help the user reach their destination without getting lost.

[1886] Specific examples

[1887] For example, if a user wants to go from 26-1 Sakuragaokacho, Shibuya-ku, Tokyo to a cafe near Shinjuku Station, the user enters the address of the starting point and destination into a smartphone app. The device sends this information to a server, which then calculates the optimal route. The resulting route is to board the Yamanote Line from Shibuya Station, get off at Shinjuku Station, and walk five minutes from the west exit. If the Yamanote Line is delayed during travel, the server calculates an alternative route using the Saikyo Line and notifies the user's device. The device then displays the new route information and recalculates the walking route to the cafe and presents it to the user.

[1888] Furthermore, if the emotion engine detects that the user is becoming tense during their trip, it will support them by displaying more detailed and easy-to-understand guidance information and offering relaxing alternative routes. This way, users can avoid the hassle of switching between multiple applications and enjoy a smoother journey. Furthermore, by monitoring traffic conditions in real time and utilizing the emotion engine to provide adaptive support, stress caused by unexpected delays can also be reduced.

[1889] The processing flow will be explained below.

[1890] Step 1:

[1891] Using a mobile device or PC, the user inputs their home address (e.g., "26-1 Sakuragaokacho, Shibuya-ku, Tokyo") and the address of their destination (e.g., "a cafe near Shinjuku Station").

[1892] Step 2:

[1893] The terminal converts the input information into an appropriate format (such as JSON) and sends it to the server.

[1894] Step 3:

[1895] The server analyzes the home and destination information received from the terminal.

[1896] Step 4:

[1897] The server accesses a geographic information API to identify the nearest train station or bus stop near the user's home.

[1898] Step 5:

[1899] The server calculates the transportation method (walking, bus, etc.) to the nearest station or bus stop.

[1900] Step 6:

[1901] The server calls the transportation API (train and bus timetables) and obtains route information from the nearest station or bus stop to the station nearest to the destination.

[1902] Step 7:

[1903] The server uses a map API to calculate the walking route from the nearest station to the destination.

[1904] Step 8:

[1905] The server generates all the information it has acquired (nearest station, bus stop, train and bus departure times, boarding location, detailed transfer routes, walking routes, etc.) as integrated data.

[1906] Step 9:

[1907] The server returns the generated integrated data to the user terminal.

[1908] Step 10:

[1909] The terminal analyzes the integrated data received from the server.

[1910] Step 11:

[1911] The terminal displays information using an appropriate UI to make it easy for the user to understand.

[1912] Step 12:

[1913] The device highlights particularly important information (e.g., platform numbers for transfers and walking routes).

[1914] Step 13:

[1915] The device uses a built-in emotion engine to recognize the user's face and analyze their voice to detect their current emotions.

[1916] Step 14:

[1917] The emotion engine adjusts the display method based on the user's emotions. For example, if it determines that the user is nervous, it displays more detailed and concise guidance information.

[1918] Step 15:

[1919] The server monitors traffic information (train and bus operation status) in real time.

[1920] Step 16:

[1921] If a delay occurs during the journey, the server recalculates a new optimal route.

[1922] Step 17:

[1923] The server notifies the user terminal of the new optimum route.

[1924] Step 18:

[1925] If the emotion engine detects the user's stress level, it notifies the server to provide an alternative route to relaxation (e.g., a route that avoids crowds or a route through a park).

[1926] Step 19:

[1927] The terminal analyzes the new route information and notifies the user.

[1928] Step 20:

[1929] The device will again use the map API to calculate and display a new walking route if necessary.

[1930] Step 21:

[1931] Once the user arrives at the station nearest to their destination, the device will display detailed walking route instructions to help the user reach their destination without getting lost.

[1932] Specific examples

[1933] For example, if a user wants to go from 26-1 Sakuragaokacho, Shibuya-ku, Tokyo to a cafe near Shinjuku Station, the user enters the address of the starting point and destination into a smartphone app. The device sends this information to a server, which then calculates the optimal route. The resulting route is to board the Yamanote Line from Shibuya Station, get off at Shinjuku Station, and walk five minutes from the west exit. If the Yamanote Line is delayed during travel, the server calculates an alternative route using the Saikyo Line and notifies the user's device. The device then displays the new route information and recalculates the walking route to the cafe and presents it to the user.

[1934] Furthermore, if the emotion engine detects that the user is becoming tense during their trip, it will support them by displaying more detailed and easy-to-understand guidance information and offering relaxing alternative routes. This way, users can avoid the hassle of switching between multiple applications and enjoy a smoother journey. Furthermore, by monitoring traffic conditions in real time and utilizing the emotion engine to provide adaptive support, stress caused by unexpected delays can also be reduced.

[1935] Example 2

[1936] 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."

[1937] In modern transportation systems, users are required to efficiently plan the optimal route from their departure point to their destination. However, individually collecting information such as transportation schedules, route information, and real-time delay information is time-consuming and places a significant burden on users. Furthermore, users are prone to stress due to the lack of means to quickly respond when a delay occurs during travel. Furthermore, users' emotional state is not taken into consideration, which can increase stress during travel. These are important issues that need to be resolved.

[1938] 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.

[1939] In this invention, the server includes a means for collecting public transportation schedules and route information, a means for identifying the nearest station or bus stop and calculating the optimal route, and a means for detecting the user's emotions and providing guidance information in an adaptive manner. This allows the server to provide all the information the user needs in one place and quickly respond to delays during travel. Furthermore, providing guidance information according to the user's emotional state can reduce stress during travel.

[1940] "User" refers to an individual or organization that uses the system to obtain route information from a starting point to a destination.

[1941] The "starting point" indicates the location where the user starts moving.

[1942] A "destination" indicates the location where the user completes their journey.

[1943] "Public transportation" refers to public transportation means such as trains and buses.

[1944] "Schedule" refers to information about the operating hours and departure times of public transportation.

[1945] "Route information" refers to information about the route from the starting point to the destination.

[1946] "Nearest station" refers to the train station closest to the departure point or destination.

[1947] "Bus stop" refers to the bus stop closest to the departure point or destination.

[1948] The "optimal route" refers to the route that best satisfies conditions such as travel time and number of transfers.

[1949] "Integrated data" refers to data obtained from multiple sources that are combined into one.

[1950] "Traffic conditions" refers to the operation status of public transportation and road congestion.

[1951] "Delay information" refers to information when public transportation services are delayed from their scheduled times.

[1952] An "alternate route" is a different route used in the event of a delay or other problem.

[1953] "Emotion" refers to the user's state of mind.

[1954] "Emotion detection" refers to determining a user's emotional state from their facial expressions and voice.

[1955] "Adaptive method" refers to a method of changing the form and content of information provided depending on the emotional state of the user.

[1956] The present invention relates to a system that enables users to travel smoothly from their starting point to their destination. This system calculates the optimal route by having the user input their starting point and destination, and presents the route to the user as integrated data. It also has the function of monitoring traffic conditions in real time during travel and recalculating the optimal alternative route in the event of a delay, and notifying the user. Furthermore, the system incorporates an emotion engine that recognizes the user's emotions, and can adjust the way in which guidance information is presented based on the user's emotional state.

[1957] System Configuration

[1958] Hardware and Software Configuration

[1959] This system mainly consists of the following hardware and software:

[1960] 1. Terminal: A device such as a smartphone or PC that allows the user to input their starting point and destination. The terminal must be equipped with an internet connection, a camera, and a microphone.

[1961] 2. Server: A cloud-based system that analyzes data and calculates routes. The server has high-speed processing power and storage capacity to manage large amounts of data.

[1962] 3. API: An interface for obtaining route information, such as a geographical information API (e.g., Google Maps API) or a public transportation API (e.g., NAVITIME API).

[1963] 4. Emotion engine: Software that recognizes the user's face and analyzes their voice to detect their emotions.

[1964] Program processing flow and specific examples

[1965] User Input

[1966] The user enters their home address (e.g., "26-1 Sakuragaokacho, Shibuya-ku, Tokyo") and the address of their destination (e.g., "a cafe near Shinjuku Station") into their mobile device or PC. The device converts this input information into a format such as JSON and sends it to the server.

[1967] Route calculation and information integration

[1968] The server analyzes the home and destination information received from the device and identifies the nearest train station or bus stop near the home by accessing the Google Maps API. It then uses the NAVITIME API and other services to obtain public transportation schedules and route information and calculates the optimal route from the home to the destination. It then generates integrated data from all the information it has obtained and sends it back to the user's device.

[1969] Information presentation to users and operation of the emotion engine

[1970] The device analyzes the integrated data received from the server and displays the information in an easy-to-understand UI. It highlights particularly important information (e.g., platform numbers for transfers and walking routes). It also uses an emotion engine to analyze the user's face and voice and adjusts the display method based on the user's emotions. If the device determines that the user is under high stress, it displays more detailed and concise guidance information and offers relaxing alternative routes.

[1971] Support on the move

[1972] The server monitors traffic information in real time, and if a delay occurs during travel, it recalculates a new optimal route and notifies the user's device. The device then analyzes the new route information and notifies the user, allowing the user to continue traveling smoothly.

[1973] Specific examples

[1974] For example, if a user wants to go from 26-1 Sakuragaokacho, Shibuya-ku, Tokyo to a cafe near Shinjuku Station, the user enters the address of the starting point and destination into a smartphone app. The device sends this information to the server, which then uses the Google Maps API and NAVITIME API to calculate the optimal route. The resulting route is to board the Yamanote Line from Shibuya Station, get off at Shinjuku Station, and walk five minutes from the west exit. If the Yamanote Line is delayed during travel, the server calculates an alternative route using the Saikyo Line and notifies the user's device. The device then displays the new route information and recalculates the walking route to the cafe and presents it to the user.

[1975] Prompt Sentence Examples

[1976] "Please calculate the optimal route from the starting point '26-1 Sakuragaokacho, Shibuya-ku, Tokyo' to the destination 'a cafe near Shinjuku Station'. Please also include a detailed walking route to the destination. If possible, please also provide guidance on what to do if you become nervous during the trip."

[1977] The present invention provides users with all the traffic information they need in one place, allowing for quick responses to delays while traveling, and by providing information based on the user's emotional state, it is possible to reduce stress while traveling.

[1978] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1979] Step 1: User Input

[1980] The user enters their home address (e.g., "26-1 Sakuragaokacho, Shibuya-ku, Tokyo") and the address of their destination (e.g., "a cafe near Shinjuku Station") into a dedicated application on their smartphone or PC. The entered information is the user's starting point and destination data. When the user presses the "Search" button, the device receives this information and sends it to the next processing step.

[1981] input:

[1982] Address of departure point (e.g., "26-1 Sakuragaokacho, Shibuya-ku, Tokyo")

[1983] Destination address (e.g., "a cafe near Shinjuku Station")

[1984] output:

[1985] Origin and destination data converted to JSON format

[1986] Specific behavior:

[1987] The user enters address information into the application's input field and presses the "Search" button to complete the input.

[1988] Step 2: Send device data

[1989] The terminal converts the address data entered by the user into JSON format and sends it to the server. This conversion is for the purpose of improving data consistency and transmission efficiency. The terminal then sends this data to the server as an HTTP POST request.

[1990] input:

[1991] Origin and destination data converted to JSON format

[1992] output:

[1993] The HTTP POST request sent to the server

[1994] Specific behavior:

[1995] The terminal converts the data entered by the user into JSON format and sends it as an HTTP POST request to the server.

[1996] Step 3: Data analysis and route calculation on the server

[1997] 1. Data analysis: The server analyzes the address information received from the terminal to identify the starting point and destination.

[1998] 2. Identifying the nearest station or bus stop: The server uses the geographic information API to identify the nearest station or bus stop near the departure point.

[1999] 3. Calculating transportation: The server calculates the appropriate transportation method (walking, bus, etc.) from home to the nearest station or bus stop.

[2000] 4. Obtain route information: The server uses the public transport API to obtain public transport schedule and route information.

[2001] 5. Calculating walking route: The server calculates the walking route from the nearest station to the destination to the destination.

[2002] 6. Generation of integrated data: All acquired information is integrated to generate comprehensive route data.

[2003] input:

[2004] HTTP POST request sent to the server

[2005] Origin and destination information based on geographical API

[2006] Schedule and route information obtained from public transport APIs

[2007] output:

[2008] Integrated Route Data

[2009] Specific behavior:

[2010] The server uses a programming language such as Python to send requests to the Google Maps API or NAVITIME API, obtain the necessary data, and generate integrated data.

[2011] Step 4: Sending route information from the server to the device

[2012] The server then sends the generated integrated data back to the device, which includes the nearest stations, departure times, transfer details, walking routes, etc.

[2013] input:

[2014] Integrated Route Data

[2015] output:

[2016] Route data sent to the device as an HTTP response

[2017] Specific behavior:

[2018] The server sends the integrated data to the terminal as an HTTP response.

[2019] Step 5: Displaying consolidated data on the terminal

[2020] The device analyzes the integrated data received from the server and displays the information on the UI of a dedicated application, highlighting particularly important information (e.g., platform numbers for transfers and walking routes).

[2021] input:

[2022] Aggregated data received from the server

[2023] output:

[2024] Route information displayed to users

[2025] Specific behavior:

[2026] The terminal analyzes the data received from the server and displays it in the format best suited to the application.

[2027] Step 6: Detect and adjust user emotions with the emotion engine

[2028] 1. Facial recognition and voice analysis: The device's built-in emotion engine performs facial recognition and voice analysis of the user.

[2029] 2. Display content adjustment: The emotion engine adjusts the display content based on the detected emotions. If stress is detected to be high, the guidance information will be displayed in more detail and concisely.

[2030] 3. Providing alternative routes: The emotion engine sends a notification to the server to provide alternative routes to relax depending on the user's stress level.

[2031] input:

[2032] User's facial image and voice data

[2033] output:

[2034] Adjusted guidance information

[2035] Notifying the server

[2036] Specific behavior:

[2037] The device's camera and microphone collect the user's face and voice, and the emotion engine analyzes them to determine the user's emotions. The system adjusts the display content to take appropriate action and sends notifications to the server as necessary.

[2038] Step 7: Real-time traffic monitoring and route updates

[2039] 1. Traffic information monitoring: The server monitors the train and bus operation status in real time.

[2040] 2. Recalculation on Delay: If a delay occurs during travel, the server recalculates a new optimal route.

[2041] 3. Notification to the terminal: The server notifies the terminal of the new route information.

[2042] 4. Displaying the new route: The device analyzes the new route information and notifies the user. If necessary, it calculates and displays a new walking route using the map API.

[2043] input:

[2044] Real-time traffic information

[2045] output:

[2046] New route information

[2047] Specific behavior:

[2048] The server periodically calls the traffic information API to obtain the current operating conditions, and if a delay occurs, calculates a new optimal route and notifies the device. The device then displays the new route to the user.

[2049] Through the above process, users can obtain optimal route information and receive real-time support while traveling. This system is expected to make users' travels smoother and stress-free.

[2050] (Application example 2)

[2051] 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."

[2052] The present invention relates to a system that enables users to travel smoothly and comfortably. Conventional mobility assistance systems have limitations in optimizing routes and providing delay information, and are unable to consider the user's emotional state. Furthermore, the control of autonomous vehicles is limited, making it difficult to provide an optimal travel experience. Therefore, there is a need for systems that can present guidance information according to the user's emotional state and enable smooth travel using autonomous vehicles.

[2053] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[2054] In this invention, the server includes: means for a user to input a departure point and a destination; means for collecting transportation schedules and route information; means for calculating an optimal route and generating it as integrated data; means for presenting the generated integrated data to the user; means for monitoring traffic conditions during travel and providing delay information in real time; means for recalculating an optimal alternative route in the event of a delay and presenting it to the user; means for adjusting the presentation method of guidance information based on the user's emotions, which includes an emotion engine that recognizes the user's emotions; means for sending instructions about the optimal route to an autonomous vehicle and means for controlling the autonomous vehicle. This enables smooth and comfortable travel by utilizing an autonomous vehicle that adapts to the user's emotional state.

[2055] The "means by which a user inputs their starting point and destination" refers to the interface that a user uses to set a route to their destination, and is provided through a device such as a smartphone, tablet, or PC.

[2056] "Means for collecting transport schedule and route information" refers to a system or module for obtaining timetables and route information for transport such as trains and buses, and collects information using APIs and databases.

[2057] The "means for calculating the optimal route and generating it as integrated data" refers to an algorithm and calculation system for calculating the optimal travel route based on the starting point and destination entered by the user and generating the result as integrated data.

[2058] The "means for presenting the generated integrated data to the user" refers to an interface that visually or audibly presents the calculated optimal route to the user, and displays the information through a display such as a smartphone or smart glasses.

[2059] "Means for monitoring traffic conditions while traveling and providing delay information in real time" refers to a system for monitoring the real-time conditions of roads and transportation facilities while traveling and providing delay information to users immediately.

[2060] "Means for recalculating the optimal alternative route in the event of a delay and presenting it to the user" refers to an algorithm and interface for recalculating the optimal route when a delay occurs in a transportation service or route and presenting that information to the user.

[2061] An "emotion engine that recognizes the user's emotions" is software or hardware that can analyze the user's facial expressions and voice data and detect their current emotional state.

[2062] The "means for adjusting the method of presenting guidance information" is a system that dynamically changes the method and timing of displaying guidance information based on the detected emotional state of the user.

[2063] The "means for transmitting optimal route instructions to an autonomous vehicle" is a system for communicating information about the calculated optimal route to an autonomous vehicle and transmitting...

Claims

1. means for a user to input a starting point and a destination; a means of collecting transit schedule and route information; A means for calculating an optimal route and generating it as integrated data; means for presenting the generated integrated data to a user; A means of monitoring traffic conditions while travelling and providing real-time delay information; a means for recalculating an optimal alternative route in the event of a delay and presenting it to the user; A system including:

2. 10. The system of claim 1, further comprising means for calculating and presenting a walking route to the user.

3. 2. The system of claim 1, further comprising means for identifying the nearest transfer station or bus stop.

Images