system

Abstract

This system aims to improve user travel efficiency and provide a stress-free experience by clearly indicating information (such as boarding and exit locations) that allows users to travel to their destinations in the shortest possible time when using public transportation. [Solution] A means for inputting the departure point and destination, A system including means for transmitting input departure and destination information to a server, means for calculating the optimal route based on the information received by the server, means for determining the boarding position and exit position based on the calculated optimal route, and means for transmitting the determined information to a terminal and displaying it to the user.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a 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

Summary of the Invention

Problems to be Solved by the Invention

[0004] When using current public transportation, since information (boarding location, exit location, etc.) for the user to move to the destination in the shortest possible way is unclear, it may take extra time. Also, there is a problem that efficient movement cannot be achieved because the appropriate boarding location and exit are unknown even during transfers. Therefore, it is necessary to improve the user's movement efficiency and realize stress-free movement.

Means for Solving the Problems

[0005] To solve the above problems, the present invention provides a system that includes means for inputting the departure point and destination, means for transmitting the input information to a server, means for the server to calculate the optimal route, means for determining the optimal boarding position and exit, and means for displaying the determined information to the user. With this system, the user can receive specific instructions to reach their destination in the shortest time, enabling efficient and comfortable travel. Platform and exit information for each station is also taken into consideration, and by calculating the optimal route based on real-time train operation status, flexible route guidance that meets the user's needs becomes possible.

[0006] "Departure point" refers to the location where the user begins their journey using public transportation.

[0007] A "destination" is the place the user ultimately wants to reach.

[0008] A "server" is a computer system that performs route calculations based on information sent by users.

[0009] A "terminal" is a device (e.g., a smartphone, tablet, or computer) used by a user to input information and receive responses from a server.

[0010] The "optimal route" refers to the most efficient travel path for the user, taking into account factors such as travel time and the number of transfers.

[0011] "Boarding position" refers to the most efficient spot when boarding a mode of transportation (e.g., train, bus, etc.).

[0012] An "exit" is the most suitable location for a user to reach their destination at a disembarking station or bus stop.

[0013] "Platform information" refers to data about the platforms at each station. This includes information such as entrances, exits, stairs, and elevators.

[0014] "Exit information" refers to data related to the exits of each station and stop. This includes exit numbers, access to surrounding facilities, transfer information to other means of transportation, etc.

[0015] "Operation status" refers to data indicating the current operation information of public transportation. This includes delays during operation, cancellations, congestion status, etc.

Brief Explanation of Drawings

[0016] [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which multiple emotions are mapped. [Figure 10] It shows an emotion map to which multiple emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13]It is a sequence diagram showing the processing flow of the data processing system in Example 2 when the emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when the emotion engine is combined.

Embodiments for Carrying Out the Invention

[0017] Hereinafter, an example of an embodiment of the system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0018] First, the terms used in the following description will be explained.

[0019] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include CPU (Central Processing Unit), GPU (Graphics Processing Unit), GPGPU (General-Purpose computing on Graphics Processing Units), APU (Accelerated Processing Unit), etc.

[0020] In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0021] In the following embodiments, the numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disk (e.g., hard disk), or magnetic tape, etc.

[0022] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0023] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0024] [First Embodiment]

[0025] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0026] As shown in Figure 1, the 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.

[0027] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0028] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0029] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and 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.

[0030] 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 perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0031] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0032] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] As shown in Figure 2, in the data processing device 12, a specific processing 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" related to the technology of this 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 according to the specific processing program 56 executed on the RAM 30.

[0034] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0035] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0036] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0037] This invention is a system that provides route guidance, including the optimal boarding position and exit, to ensure the shortest possible travel time from the point of origin to the destination using public transportation. The following describes the program processing of this system and a specific example based on it in natural language.

[0038] System Overview

[0039] This system calculates and displays the optimal route, boarding position at each station, and exit based on the departure and destination information entered by the user. Specifically, it consists of a terminal, a server, and a map database and a train operation information database.

[0040] Program processing

[0041] 1. User input:

[0042] The user launches the application and enters their departure and destination points. They can also specify their mode of transport (train, bus, etc.) and desired arrival time.

[0043] 2. Data transmission:

[0044] The terminal sends the entered information (departure point, destination, mode of transport, desired arrival time) to the server.

[0045] 3. Server processing:

[0046] Based on the information received by the server, it accesses the map database and the train operation information database, and calculates the optimal route considering the current train conditions.

[0047] Based on the calculated route, the server determines the optimal boarding position and exit from the platform and exit information of each station.

[0048] 4. Submit results:

[0049] The server sends the calculation results (optimal route, boarding location, exit) to the terminal.

[0050] 5. User display:

[0051] The terminal displays the route information it has received to the user.

[0052] Specific example

[0053] 1. The user launches the application, searches for a route from "Station A" to "Station B," and enters the departure point "Station A" and the destination "Station B."

[0054] 2. The terminal converts the user's input information into "Departure point: Station A, Destination: Station B, Mode of transport: Train" and sends it to the server.

[0055] 3. The server calculates the optimal route from "Station A" to "Station B" based on the map database and train operation information. For example, it might select "Train C" as the optimal route.

[0056] 4. The server retrieves platform information for each station from Station A to Station B of "Train C" and determines the optimal boarding position (e.g., front of car 1) and exit (e.g., Exit 1).

[0057] 5. The server sends this information to the terminal as "Means of transport: Train C, Boarding location: Front of car 1, Disembarking station: Station B, Exit: Exit 1".

[0058] 6. The device displays this information on the user's screen:

[0059] Transportation: Train C

[0060] Boarding location: Front of car 1

[0061] Disembarking station: Station B

[0062] Optimal exit: Exit 1

[0063] In this way, users can receive specific instructions to efficiently travel to their destination. This system allows users to improve their travel efficiency and reach their destination in the shortest possible time.

[0064] The key feature of this system is that it calculates routes considering real-time train operation status, and then combines this with platform and exit information for each station to provide the optimal boarding location and exit. This allows users not only to reach their destination but also to utilize the most efficient means of transportation.

[0065] The following describes the processing flow.

[0066] Step 1:

[0067] The user launches the application and enters their departure and destination points. They can also optionally specify their mode of transport (train, bus, etc.) and desired arrival time.

[0068] Step 2:

[0069] The terminal receives input information from the user and converts the departure point, destination, selected mode of transport, and desired arrival time into the format required for subsequent processing.

[0070] Step 3:

[0071] The device sends the converted information to the server. The information sent includes the departure point, destination, mode of transport, and desired arrival time.

[0072] Step 4:

[0073] Based on the information received by the server, it accesses the map database and the traffic information database.

[0074] Step 5:

[0075] The server retrieves a list of available public transportation options (e.g., multiple train lines, bus routes) and evaluates each route.

[0076] Step 6:

[0077] The server calculates the optimal route, taking into account factors such as travel time, number of transfers, and train conditions.

[0078] Step 7:

[0079] The server determines the optimal boarding and exit locations for each route. This process utilizes platform and exit information for each station.

[0080] Step 8:

[0081] The server sends the calculation results to the terminal. The transmitted information includes the optimal route, boarding location, and exit location.

[0082] Step 9:

[0083] The terminal displays route information received by the user in an easy-to-understand manner. Specific details include the mode of transport, optimal boarding location, drop-off point, and optimal exit.

[0084] Step 10:

[0085] Based on the information displayed, the user boards public transport at the designated boarding location and uses the designated exit to reach their destination.

[0086] (Example 1)

[0087] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0088] When using modern public transportation, especially in congested urban areas, simply knowing the route from origin to destination is insufficient for efficient travel. Users need to know the optimal boarding location and the best exit at each station, but manually researching this is difficult, time-consuming, and cumbersome. Furthermore, route guidance that takes real-time train operation status into account is necessary, but conventional systems have been unable to effectively implement this. As a result, user travel efficiency has decreased, and this has become a source of stress.

[0089] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0090] In this invention, the server includes means for the user to input a departure point and destination; means for the terminal to transmit the inputted departure point and destination information to the server; means for the server to calculate the optimal route using a map database and an operation information database based on the received information; means for the server to determine the boarding position and exit position at each station based on the calculated optimal route; and means for transmitting the determined information to the terminal and displaying it to the user. As a result, the user can find out the optimal route, optimal boarding position, and exit from the departure point to the destination in real time, enabling them to use public transportation efficiently.

[0091] "User input" refers to the act of a user entering information such as their departure point and destination into a terminal.

[0092] A "terminal" is a device used by a user to input information or display received information. Examples include smartphones and personal computers.

[0093] A "server" is a central system that receives information sent from terminals, accesses various databases to calculate the optimal route, and sends the results back to the terminals.

[0094] A "map database" is a database that stores detailed information such as geographical location information and train stations.

[0095] A "transportation information database" is a database that stores real-time data such as the operating schedules and delay information of public transportation.

[0096] The "optimal route" is the route that allows the user to reach their destination in the shortest time or with the fewest transfers.

[0097] "Boarding position" refers to the recommended location within a train or bus for users to reach their destination efficiently.

[0098] An "exit" refers to the exit of a station or bus stop that a user should use when they reach their destination.

[0099] "Platform information for each station" refers to information about the layout of station platforms and which trains stop at specific platforms.

[0100] "Real-time" means that the information is current as of the present time and always reflects the latest status.

[0101] This invention provides a system that offers optimal route guidance for users to travel from their starting point to their destination using public transportation in the shortest possible time. The system includes the steps of user input, data transmission, server processing, result transmission, and user display. The following describes embodiments of this system, specifying the concrete hardware and software.

[0102] Hardware and software used

[0103] Terminal: A user device such as a smartphone or PC sends the entered information to the server and displays the calculation results.

[0104] Server: A central device that accesses the database and performs route calculations. This can be a cloud server or an on-premises server.

[0105] Map database: A database that stores geographical location information and station information. For example, a GIS (Geographic Information System) is used.

[0106] Transportation Information Database: A database that stores real-time data such as public transportation schedules and delay information. Real-time data is retrieved via API.

[0107] System Operation Overview

[0108] 1. User input:

[0109] The user launches the application and enters their departure and destination points. The user can also specify their mode of transport and desired arrival time.

[0110] 2. Data transmission:

[0111] The terminal sends the entered information to the server. Protocols such as HTTP requests are used for communication.

[0112] 3. Server processing:

[0113] Based on the information received by the server, it accesses the map database and the train operation information database to calculate the optimal route. The server also considers platform and exit information for each station to determine the optimal boarding location and exit.

[0114] 4. Submit results:

[0115] The server sends the calculation results to the terminal. The results are sent in a standard format such as JSON.

[0116] 5. User display:

[0117] The device analyzes the data it receives and displays it in a user-friendly format.

[0118] Specific example

[0119] Consider a scenario where a user launches the application and searches for a route from "Station A" to "Station B". In this case, the user enters the departure point "Station A" and the destination "Station B", and taps the search button. The device converts the entered information into "Departure point: Station A, Destination: Station B, Mode of transport: Train" and sends it to the server.

[0120] The server calculates the optimal route from "Station A" to "Station B" based on a map database and train operation information. For example, it might select "Train C". It also obtains platform information for each station from "Station A" to "Station B" and determines the optimal boarding position (e.g., front of car 1) and exit (e.g., Exit 1).

[0121] The server sends this information to the terminal as "Transportation: Train C, Boarding location: Front of car 1, Disembarking station: Station B, Exit: Exit 1". The terminal displays this information on the user's screen.

[0122] Prompt example

[0123] Examples of prompts to input into a generative AI model include the following:

[0124] "Please specify the departure and destination stations, and tell me which train to take, which car and which door to use, and which exit to use at the destination station. For example, let's say the departure station is 'Station A' and the destination is 'Station B'."

[0125] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0126] Step 1:

[0127] The user enters the departure point and destination.

[0128] The user launches the application and enters their departure and destination locations into a form. Optionally, they can also enter their desired arrival time and mode of transportation (train, bus, etc.).

[0129] Input: Departure point, destination, desired arrival time, mode of transport

[0130] Output: User input data

[0131] Specific operation: The user enters "Station A" as the departure point and "Station B" as the destination into the text boxes and taps the "Search" button. This input information is stored in a variable within the program.

[0132] Step 2:

[0133] The terminal sends data to the server.

[0134] The terminal sends the information entered by the user to the server. HTTP POST requests are used for communication.

[0135] Input: User input data

[0136] Output: Request data to the server

[0137] Specific operation: The terminal converts the input data into JSON format and sends a "POST / find_route" request to the server. The request data will look something like this: { 'from': 'Station A', 'to': 'Station B', 'arrive_by': '10:00', 'mode': 'Train'}.

[0138] Step 3:

[0139] The server receives the information and calculates the optimal path.

[0140] The server analyzes the received data and accesses map and traffic information databases to calculate the optimal route. Dijkstra's algorithm and the A algorithm are used for route calculation.

[0141] Input: Request data, map data, service information

[0142] Output: Calculated optimal path data

[0143] Specific operation: The server parses the received JSON data and retrieves the coordinate information of the departure point "Station A" and the destination "Station B" from the map database. At the same time, it checks the current train status from the train operation information database and calculates the most efficient route. For example, a route using "Train C" is selected.

[0144] Step 4:

[0145] The server determines the optimal boarding location and exit.

[0146] Based on the calculated optimal route, the server determines the best boarding position and exit from each station's platform and exit information.

[0147] Input: Optimal route data, home information, exit information

[0148] Output: Boarding location and exit information

[0149] Specific operation: The server obtains platform information for each station from Station A to Station B of "Train C," and determines, for example, that the front of Car 1 is the optimal boarding position and Exit 1 is the optimal exit.

[0150] Step 5:

[0151] The server sends the results to the terminal.

[0152] The server sends the calculation results (optimal route, boarding location, exit) to the terminal. An HTTP POST request is used again for communication.

[0153] Input: Boarding location and exit information

[0154] Output: Response data

[0155] Specific operation: The server formats the calculation result into JSON format and sends it to the terminal as a "POST / show_route" request. For example, the response data will be "{ 'route': 'Train C', 'car_position': 'Front of car 1', 'exit': 'Exit 1'}".

[0156] Step 6:

[0157] Display the results on the user's terminal.

[0158] The terminal analyzes the data received from the server and displays it in a format that is easy for the user to understand.

[0159] Input: Response data

[0160] Output: Route information displayed on the user screen

[0161] Specific operation: The application on the device parses the received JSON data and displays specific route, boarding location, and exit information on the user interface. Information such as "Means of transport: Train C", "Boarding location: Front of car 1", "Disembarking station: Station B", and "Optimal exit: Exit 1" is laid out on the screen.

[0162] (Application Example 1)

[0163] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0164] As autonomous vehicles become more widespread, they need to be able to select the appropriate route for users to travel efficiently and quickly from their starting point to their destination. However, current autonomous driving technology struggles to calculate and provide optimal pick-up and drop-off locations to users. Furthermore, there are limited means of optimizing routes while considering real-time operating conditions. As a result, users end up wasting unnecessary time during their journey from departure to destination.

[0165] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0166] In this invention, the server includes means for inputting a departure point and a destination; means for transmitting the inputted departure point and destination information to the server; means for calculating the optimal route based on the information received by the server; means for determining the boarding and exit positions based on the calculated optimal route; means for transmitting the determined information to a terminal and displaying it to the user; means for transmitting the calculation results to the computer system of the autonomous vehicle, which in turn controls the vehicle according to the optimal route; and means for the user to confirm detailed route information and boarding / alighting positions via a smartphone or in-vehicle display device. This enables the autonomous vehicle to select the optimal route in real time and travel efficiently from the departure point to the destination.

[0167] The "starting point" is the point where the user begins their journey.

[0168] The "destination" is the point where the user is expected to finish their journey.

[0169] A "terminal" is a device used by users to input information about their departure point and destination and receive route guidance.

[0170] A "server" is a central processing unit that receives information sent from a terminal, calculates the optimal route, and returns the result.

[0171] The "optimal route" is the route chosen to minimize travel time from the starting point to the destination.

[0172] The "boarding position" is the optimal position for a user to board an autonomous vehicle.

[0173] The "exit location" is the most suitable position for a user to disembark from the autonomous vehicle when they reach their destination.

[0174] An "autonomous vehicle" is a vehicle that can travel on the road without the intervention of a human driver.

[0175] A "computer system" is a system that controls the functions of an autonomous vehicle and manages the vehicle's movement according to a calculated path.

[0176] A "smartphone" is a portable, multi-functional electronic device used by users to input and display information.

[0177] An "in-vehicle display device" is a device installed inside an autonomous vehicle that displays route information to the user.

[0178] "Real-time service status" refers to information showing current traffic conditions and the operating status of trains and buses.

[0179] "Facility information for each station" refers to information that shows the specific location of platforms and exits for each station.

[0180] "Detailed route information" refers to specific information necessary for users to travel efficiently, such as boarding and alighting locations and travel time.

[0181] This invention is a system that provides optimal route guidance by an autonomous vehicle, based on the user's specified origin and destination. The system consists of a terminal, a server, the autonomous vehicle's computer system, and a map database and a traffic information database.

[0182] Program Overview

[0183] The system program uses the following hardware and software:

[0184] Hardware:

[0185] Smartphones (e.g., ANDROID® or iOS)

[0186] Onboard computers for autonomous vehicles (e.g., NVIDIA Drive Platform)

[0187] Server (Central Processing Unit)

[0188] software:

[0189] Map databases (e.g., Google® Maps API)

[0190] Operation information database (e.g., API for public transportation operation information)

[0191] Programming languages ​​(e.g., Python, JavaScript (registered trademark))

[0192] Program Processing Overview

[0193] 1. The user enters the departure and destination locations:

[0194] Users enter their departure and destination points using a smartphone app or a touchscreen in the autonomous vehicle. They can also enter their desired arrival time and mode of transportation as needed.

[0195] 2. Sending information to the server:

[0196] The terminal sends the entered information to the server. The server then receives the origin, destination, and other condition information.

[0197] 3. Calculation of the optimal path:

[0198] The server accesses the map database and the traffic information database to calculate the optimal route based on real-time traffic conditions.

[0199] 4. Determining boarding and alighting locations:

[0200] Based on the calculated route, the server retrieves facility information for each station and determines the optimal boarding and alighting locations.

[0201] 5. Sending and displaying calculation results:

[0202] The server sends the calculation results to the terminal, and the user can check detailed route information and boarding / alighting locations on their smartphone or in-vehicle display device.

[0203] 6. Vehicle control by computer system:

[0204] The autonomous vehicle's computer system receives calculation results from a server and controls the vehicle according to the optimal route. This ensures that the boarding and alighting sequences at each station are executed efficiently.

[0205] Specific example

[0206] For example, suppose a user uses a smartphone app to input their departure point "Station A" and destination "Station B". This information is sent from the device to a server, which then accesses a map database and a traffic information database to calculate the optimal route.

[0207] The server selects the optimal route from "Station A" to "Station B" and retrieves platform and exit information for each station. Based on the calculation, it determines the optimal boarding position (e.g., near the front door) and alighting position (e.g., Exit 2) and sends this information back to the terminal. The user can then confirm this information on their smartphone or in-vehicle display device, allowing them to board the vehicle at the optimal position and alight at the designated exit.

[0208] Examples of prompts for generative AI models

[0209] "Departure point: 'Station A', Destination: 'Station B', Mode of transport: 'Autonomous vehicle', Calculate and display the optimal route and pick-up / drop-off locations."

[0210] The above is an overview of specific embodiments for carrying out this invention. This system enables users to travel efficiently and quickly, minimizing travel time from the point of origin to the destination.

[0211] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0212] Step 1:

[0213] The user enters their departure and destination points using a smartphone app or in-car touchscreen. This may also include desired arrival time and mode of transport. The entered information is formatted as data based on the input format of the user's device.

[0214] Input: Departure point, destination, desired arrival time, mode of transport

[0215] Output: Input information converted into a data format for transmission to the server.

[0216] Step 2:

[0217] The terminal sends the formatted data to the server via wireless communication. This process is carried out while verifying the integrity of the data. If the data is not transmitted correctly, a retransmission process is performed.

[0218] Input: Formatted data (departure point, destination, desired arrival time, mode of transport)

[0219] Output: Confirmation message indicating that transmission to the server is complete.

[0220] Step 3:

[0221] Based on the information received by the server, it accesses the map database and the operation information database to obtain real-time operation status. It uses the database API to query the necessary information and retrieve the current operation status.

[0222] Input: Departure point, destination, desired arrival time, mode of transport

[0223] Output: Current service status, traffic information

[0224] Step 4:

[0225] The server calculates the optimal route based on the information it acquires. The calculation algorithm combines real-time traffic conditions, map information, and desired arrival time to find the shortest route.

[0226] Input: Current service status, traffic information, map information

[0227] Output: Optimal route information

[0228] Step 5:

[0229] Based on the calculated optimal route, the server retrieves facility information for each station and determines the optimal boarding and alighting locations. It also considers platform and exit information for each station to select the most efficient location.

[0230] Input: Optimal route information, facility information for each station

[0231] Output: boarding location, alighting location

[0232] Step 6:

[0233] The server sends the determined information (optimal route, boarding location, and alighting location) to the terminal. The transmitted information is formatted in a way that can be displayed on the user's terminal screen.

[0234] Input: Optimal route, boarding location, alighting location

[0235] Output: Data to send to the terminal

[0236] Step 7:

[0237] The terminal displays the received information on the user's smartphone or in-vehicle display device. This display includes route information, boarding location, and alighting location, which the user can then review.

[0238] Input: Data to send to the terminal (optimal route, boarding location, alighting location)

[0239] Output: Information displayed on a smartphone or in-vehicle display device.

[0240] Step 8:

[0241] The autonomous vehicle's computer system receives calculation results from a server and controls the vehicle according to the optimal route. Stopping positions at each station are also automatically adjusted.

[0242] Input: Calculation results from the server (optimal route, boarding location, alighting location)

[0243] Output: Vehicle control instructions

[0244] Step 9:

[0245] Users can check detailed route information and pick-up / drop-off locations via their smartphone or in-vehicle display device, and actually pick up and drop off at those locations.

[0246] Input: Information displayed on a smartphone or in-vehicle display device.

[0247] Output: User movement behavior

[0248] The above outlines the processing steps of this system. Each step illustrates how the input information is processed and how it ultimately yields output that enables efficient user movement.

[0249] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0250] The present invention is a system comprising means for inputting the departure and destination points, means for transmitting the input information to a server, means for calculating the optimal route, means for determining the boarding position and exit point, and means for displaying the determined information to the user, further incorporating an emotion engine that recognizes the user's emotions and adjusts the route accordingly. This system provides support for users to travel to their destinations in the shortest and most comfortable way possible using public transportation.

[0251] System Overview

[0252] This system calculates the optimal route, boarding positions and exits at each station, based on the departure and destination information entered by the user. It then further adjusts the route based on the user's emotional state and displays it to the user. Specifically, it consists of a terminal, a server, a map database, a train operation information database, and an emotion engine.

[0253] Program processing

[0254] 1. User input:

[0255] The user launches the application and enters their departure and destination locations. They can also optionally specify their mode of transport and desired arrival time.

[0256] The device recognizes the user's current emotional state via an emotion engine. This emotional state is analyzed using data collected through the smartphone's camera and microphone (such as facial expressions and voice).

[0257] 2. Data transmission:

[0258] The terminal sends the input information and the emotion data analyzed by the emotion engine to the server.

[0259] 3. Server processing:

[0260] Based on the information received by the server, it accesses the map database and the train operation information database, and calculates the optimal route considering the current train conditions.

[0261] Based on the calculated route, the server determines the optimal boarding position and exit from the platform and exit information of each station.

[0262] 4. Application of sentiment data:

[0263] The server adjusts the route based on the user's emotional state, obtained from the emotion engine. For example, if the user is stressed, it prioritizes less congested routes. On the other hand, if the user is relaxed, it suggests routes with good scenery or routes that pass through tourist attractions.

[0264] 5. Submit results:

[0265] The server sends optimized route information to the terminal. This information includes the optimal route, boarding location, exit location, and reasons for the recommendation based on the user's emotional state.

[0266] 6. User display:

[0267] The terminal displays route information received by the user in an easy-to-understand manner. Specifically, this includes the mode of transport used, the optimal boarding location, the optimal drop-off point, the optimal exit, and the reasons for route adjustments based on the user's emotional state.

[0268] Specific example

[0269] Examples of user stress

[0270] 1. The user launches the application and enters the destination: travel from "Station A" to "Station B".

[0271] 2. The device sends user input information and emotional data (stress level) to the server.

[0272] 3. The server calculates the optimal route from "Station A" to "Station B" and selects, for example, "Train C".

[0273] 4. The server prioritizes selecting less congested routes based on the user's stress level. It also determines the optimal boarding position (e.g., the last car) and exit (e.g., Exit 3) for "Train C".

[0274] 5. The server sends this information to the terminal, and the terminal displays it to the user:

[0275] Transportation: Train C

[0276] Boarding location: Last car

[0277] Disembarking station: Station B

[0278] Optimal exit: Exit 3

[0279] Reason for proposal: Less congested routes

[0280] Examples of users being relaxed

[0281] 1. The user launches the application and enters the destination: travel from "Station A" to "Station B".

[0282] 2. The terminal sends the user's input information and emotion data (relaxed state) to the server.

[0283] 3. The server calculates the optimal route from "Station A" to "Station B" and selects, for example, "Train D".

[0284] 4. Based on the user's relaxed state, the server preferentially selects a route with beautiful scenery or a route passing through tourist spots. Also, it determines the optimal boarding position (e.g., the front of Car No. 1) and the exit (e.g., Exit 1) of "Train D".

[0285] 5. The server sends this information to the terminal, and the terminal displays it to the user:

[0286] Transportation means: Train D

[0287] Boarding position: The front of Car No. 1

[0288] Destination station: Station B [[ID=2​​​​​​​​​​​​​​​​​​​​​​​​​​​​

[0296] The terminal activates the emotion engine to recognize the user's emotional state through the user's facial expressions and voice. This data is collected through the smartphone's camera and microphone.

[0297] Step 3:

[0298] The emotion engine analyzes the collected facial expression and voice data to determine the user's current emotional state (e.g., stress, relaxation, joy, etc.).

[0299] Step 4:

[0300] The terminal sends the input departure location, destination, means of transportation, desired arrival time, and the emotion data analyzed by the emotion engine to the server.

[0301] Step 5:

[0302] Based on the information received by the server, access the map database and operation information database.

[0303] Step 6:

[0304] The server obtains a list of available public transportation (e.g., multiple train lines, bus lines) and evaluates each route.

[0305] Step 7:

[0306] The server calculates the optimal route considering travel time, number of transfers, operation status, etc.

[0307] Step 8:

[0308] The server determines the optimal boarding position and exit position for each route. At this time, the platform information and exit information of each station are used.

[0309] Step 9:

[0310] The server adjusts the route based on the user's emotional state, obtained from the emotion engine. For example, if the user is stressed, it prioritizes less congested routes; if the user is relaxed, it suggests routes with scenic views or routes that pass through tourist attractions.

[0311] Step 10:

[0312] The server sends optimized route information to the terminal. This information includes the optimal route, boarding location, exit location, and reasons for the recommendation based on the user's emotional state.

[0313] Step 11:

[0314] The terminal displays route information received by the user in an easy-to-understand manner. Specifically, this includes the mode of transport used, the optimal boarding location, the optimal drop-off point, the optimal exit, and the reasons for route adjustments based on the user's emotional state.

[0315] Step 12:

[0316] Based on the information displayed, the user boards public transport at the designated boarding location and uses the designated exit to reach their destination.

[0317] (Example 2)

[0318] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0319] Conventional route guidance systems only provide the optimal route when a user is using public transportation, and do not flexibly adjust the route according to the user's emotional state. As a result, users often face stressful situations and other emotional discomforts. This invention aims to provide more comfortable travel support that takes the user's emotional state into consideration.

[0320] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0321] In this invention, the server includes means for inputting a departure point and destination; means for transmitting the inputted departure point and destination information to the server; means for calculating the optimal route based on the information received by the server; means for determining the boarding position and exit position based on the calculated optimal route; means for analyzing the user's emotional state; means for adjusting the route based on the analyzed emotional state; and means for transmitting the determined information to a terminal and displaying it to the user. This provides optimal route guidance according to the user's emotional state, enabling a comfortable journey.

[0322] "Departure point" refers to the point where the user begins their journey.

[0323] "Destination" refers to the point where the user is expected to complete their journey.

[0324] "Means" refers to the apparatus or method used to achieve a specific objective.

[0325] A "server" refers to a computer system used to process and manage information on a network.

[0326] A "terminal" refers to a device that a user directly interacts with, and its role is to input and display information.

[0327] The "optimal route" refers to the most efficient or comfortable travel route for a user under specific conditions.

[0328] "Boarding location" refers to the specific point where a user boards public transportation.

[0329] "Exit location" refers to the specific point where a user disembarks from public transportation.

[0330] "Emotional state" refers to the user's psychological and physiological state, which is analyzed from facial expressions, voice, and other factors.

[0331] An "emotion engine" refers to software or a device used to analyze a user's emotional state.

[0332] "Adjusting the pathway" refers to modifying or optimizing an existing pathway based on analyzed emotional states and other conditions.

[0333] A "map database" refers to a database containing geographical information, which is used for route calculations.

[0334] A "service information database" refers to a database containing information on the operating status of public transportation, providing real-time service information.

[0335] "Current operating status" refers to the most recent operating status of public transportation, including information such as delays and congestion.

[0336] This invention provides a system that offers the optimal route when a user travels using public transportation and adjusts the route based on the user's emotional state. The system includes means for inputting the departure and destination points, means for transmitting the input information to a server, means for calculating the optimal route, means for determining the boarding position and exit point, and means for displaying the determined information to the user. Furthermore, it incorporates an emotion engine that recognizes the user's emotions and adjusts the route accordingly.

[0337] System Configuration

[0338] This system consists of the following elements:

[0339] 1. Terminal:

[0340] It is a user-operated device that takes in information about the origin and destination and acquires sentiment data. A smartphone is a concrete example of this.

[0341] The device is equipped with a camera and microphone, which are used to capture the user's facial expressions and voice, and then analyzed by an emotion engine.

[0342] 2. Server:

[0343] This is a central system that receives information transmitted from terminals and performs data processing and route calculations. The server accesses map databases and operational information databases to obtain real-time operational information.

[0344] As specific software examples, we will use the "Google Maps API" and the "Transportation Information API".

[0345] 3. Emotional Engine:

[0346] This is software or a device for analyzing a user's emotional state. It utilizes an emotion analysis library built into a smartphone.

[0347] Based on the analyzed sentiment data, the server further adjusts the optimal route.

[0348] System operation example

[0349] Examples of users experiencing stress

[0350] 1. The user launches the app on their smartphone and enters the departure point "Station A" and the destination "Station B".

[0351] 2. The device captures the user's facial expressions and voice data, and performs emotion analysis to determine if the user is experiencing stress.

[0352] 3. The device sends the entered information and emotion data to the server.

[0353] 4. The server accesses the map database and the train operation information database to calculate the optimal route. For example, it finds the shortest route from "Station A" to "Station B" and selects "Train C".

[0354] 5. The server takes into account the user's stress level and determines less crowded routes, boarding positions (e.g., the last car), and optimal exits (e.g., Exit 3).

[0355] 6. The server sends the coordinated routing information to the terminal, and the terminal displays the following to the user:

[0356] Transportation: Train C

[0357] Boarding location: Last car

[0358] Disembarking station: Station B

[0359] Optimal exit: Exit 3

[0360] Reason for proposal: Less congested routes

[0361] Examples of relaxed users

[0362] 1. The user launches the app on their smartphone and enters the destination: "Station A" to "Station B".

[0363] 2. The device captures the user's facial expressions and voice data, and performs emotion analysis to determine that the user is relaxed.

[0364] 3. The device sends the entered information and emotion data to the server.

[0365] 4. The server accesses the map database and the train operation information database to calculate the optimal route. For example, it might determine the most comfortable route from "Station A" to "Station B" and select "Train D".

[0366] 5. The server takes into account the user's relaxed state and determines a route that includes scenic views and tourist spots, as well as the optimal boarding position (e.g., front of car 1) and exit (e.g., exit 1).

[0367] 6. The server sends the coordinated routing information to the terminal, and the terminal displays the following to the user:

[0368] Transportation: Train D

[0369] Boarding location: Front of car 1

[0370] Disembarking station: Station B

[0371] Optimal exit: Exit 1

[0372] Reason for proposal: A route with good scenery

[0373] Examples of prompt statements using generative AI models include the following:

[0374] The user launches the app and enters their travel time from Station A to Station B. During this process, the app performs an emotional analysis to determine whether the user is stressed or relaxed. Then, it suggests the optimal route, boarding location, and exit.

[0375] This system allows users to receive optimal route guidance tailored to their emotional state, resulting in a comfortable travel experience. The introduction of an emotion engine enables the provision of personalized services that meet the individual needs of each user.

[0376] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0377] Program processing steps and specific actions

[0378] Step 1: User Input

[0379] Input: The user launches the application and enters the departure point "Station A" and the destination "Station B". Optionally, they can also specify their desired arrival time and mode of transport.

[0380] Operation: The user operates a smartphone app. The smartphone's camera and microphone are used to capture the user's facial expressions and voice data in real time.

[0381] Data processing: The device inputs captured facial expressions and audio data into an emotion engine to analyze the user's emotional state.

[0382] Output: Origin, destination, options information, and analyzed sentiment data are generated.

[0383] Step 2: Data transmission

[0384] Input: Origin, destination, optional information, and sentiment data generated by the device.

[0385] Operation: The terminal generates this data as data packets and sends them to the server using the HTTP or HTTPS protocol.

[0386] Output: Data packets sent to the server.

[0387] Step 3: Server Processing

[0388] Input: Data packets received by the server from the terminal.

[0389] Operation: The server analyzes the data packets and extracts origin, destination, option information, and sentiment data. It then accesses a map database (e.g., Google Maps API) and a traffic information database to retrieve current traffic status.

[0390] Data processing: Based on the operational data acquired by the server, the optimal route from the origin to the destination is calculated using an algorithm.

[0391] Output: Optimal route information.

[0392] Step 4: Applying emotional data

[0393] Input: Optimal route information calculated by the server and user sentiment data.

[0394] Operation: The server further adjusts route information based on the user's emotional state (e.g., stressed, relaxed). For example, if the user is stressed, it will select a less congested route; if the user is relaxed, it will select a route with good scenery or one that passes by tourist attractions.

[0395] Data processing: Determine the adjusted route information, optimal boarding location, and optimal exit location.

[0396] Output: Adjusted route information, boarding location, exit location, and reason for recommendation.

[0397] Step 5: Submit Results

[0398] Input: Server-adjusted optimal route information, boarding location, exit location, and reason for recommendation.

[0399] Operation: The server generates this information as a data packet and sends it to the terminal.

[0400] Output: Data packets sent to the terminal.

[0401] Step 6: User Display

[0402] Input: Data packets received by the terminal from the server.

[0403] Operation: The terminal analyzes data packets and displays the mode of transport to be used, the optimal boarding location, the optimal drop-off location, the optimal exit, and the reason for the recommendation on the user interface.

[0404] Output: Optimal route information displayed to the user.

[0405] This program's processing allows users to receive optimal route guidance tailored to their emotional state, enabling a comfortable journey.

[0406] (Application Example 2)

[0407] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0408] Conventional travel route guidance systems provide the optimal route based on input of the origin and destination, but they lacked personalization of service by not considering the user's emotional state. Furthermore, they were unable to provide the optimal route based on whether the passenger was stressed or relaxed. As a result, they failed to deliver a comfortable travel experience for users.

[0409] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for inputting the departure point and destination; means for transmitting the input departure point and destination information to the server; means for calculating the optimal route based on the information received by the server; means for determining the boarding position and exit position based on the calculated optimal route; means for analyzing the passenger's emotional state and transmitting the data to the server; means for adjusting the route based on the emotional state; means for transmitting the determined information to a terminal and displaying it to the passenger; means for the terminal to display the reason for the route adjustment based on the passenger's emotional state; and means for recognizing the passenger's emotional state using a mobile terminal, in-vehicle terminal, or camera. This makes it possible to provide a personalized and optimal travel route according to the user's emotional state.

[0410] The "starting point" is the point where the journey begins.

[0411] A "destination" is the final point of arrival at a destination.

[0412] A "server" is a computer system that receives, transmits, processes, and stores data over a network.

[0413] A "route" is the path taken to travel from a starting point to a destination.

[0414] "Boarding position" refers to the optimal location for passengers to board a mode of transportation.

[0415] An "exit" is a place where passengers disembark from a mode of transportation.

[0416] "Emotional state" refers to the emotional state a passenger is experiencing, such as stress or joy.

[0417] A "mobile device" refers to a portable computing device such as a smartphone or tablet.

[0418] An "in-vehicle terminal" is an electronic device installed in a car that assists with driving and navigation.

[0419] A "camera" is an optical device used to capture images and videos.

[0420] An "emotion engine" is a system that uses devices such as cameras and microphones to identify a user's emotional state and analyze that information.

[0421] A "terminal" refers to a device or equipment on which a user inputs or displays information.

[0422] This invention is a system to help passengers comfortably reach their destination using autonomous vehicles. The system uses the following hardware and software components.

[0423] Hardware configuration

[0424] 1. Mobile devices:

[0425] These are devices, such as smartphones and tablets, that passengers use to input their departure and destination locations.

[0426] 2. In-vehicle terminals:

[0427] These are touch panels or displays installed in autonomous vehicles, used by passengers to input their departure and destination locations and to confirm information.

[0428] 3. Camera:

[0429] This device is installed inside autonomous vehicles to capture passengers' facial expressions and movements and analyze their emotional state.

[0430] Software Configuration

[0431] 1. Emotional Engine:

[0432] This software module analyzes facial expressions and voice data to determine passengers' emotional states in real time. It utilizes OpenCV and common emotion analysis libraries.

[0433] 2. Path Calculation Module:

[0434] It operates on a server and calculates the optimal route based on the received origin and destination data. This calculation utilizes a map database and a traffic information database.

[0435] 3. Server:

[0436] This system receives, transmits, processes, and stores data over a network. The server includes an emotion engine that analyzes facial expressions and voice data, and a route calculation module that uses map data and traffic information.

[0437] Data processing and data calculation

[0438] Camera data:

[0439] The system collects passengers' facial expressions and voice data through cameras and microphones and transmits it to a server in real time. The emotion engine analyzes this data to determine their emotional state (stress, relaxation, etc.).

[0440] Path calculation:

[0441] The server accesses map and traffic information databases to calculate the optimal route from the origin to the destination. Furthermore, it adjusts the route based on the passenger's emotional state, as determined by the emotion engine. For example, if a passenger is stressed, it selects a less congested route; if they are relaxed, it selects a route with good scenery.

[0442] Information transmission and display:

[0443] Once the optimal route information is determined, the server transmits this information to the in-vehicle terminal and displays it to the passengers on the screen. The displayed information includes the optimal route, boarding location, alighting location, exit, and reasons for route adjustments based on emotional state.

[0444] Specific example

[0445] 1. The passenger enters their travel destination from "Station A" to "Station B" using the onboard terminal.

[0446] 2. In-car cameras capture passengers' facial expressions, which are then analyzed by an emotion engine.

[0447] 3. The emotion engine determines that the passenger is stressed and sends data to the server.

[0448] 4. The server calculates the least congested route and transmits the calculated route to the in-vehicle terminal.

[0449] 5. The in-vehicle terminal displays the following information to passengers:

[0450] Transportation: Train C

[0451] Boarding location: Last car

[0452] Disembarking station: Station B

[0453] Optimal exit: Exit 3

[0454] Reason for proposal: Because it is less crowded.

[0455] Example of a prompt

[0456] "Input user emotion data and departure / destination information to recommend the optimal travel route. If the user is stressed, recommend a less congested route; if they are relaxed, recommend a route with good scenery."

[0457] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0458] Step 1:

[0459] The user launches the application on the in-vehicle terminal and enters the departure and destination locations. The information entered includes the departure location, destination, and optionally, the desired arrival time. The entered data is stored on the in-vehicle terminal. Input: Departure location, destination, desired arrival time. Output: Input information stored on the in-vehicle terminal.

[0460] Step 2:

[0461] The device's camera and microphone are used to capture passengers' facial expressions and voices in real time. An emotion engine analyzes this data to determine the user's emotional state (e.g., stress, relaxation). Input: Captured facial and voice data. Output: Analyzed emotional state data.

[0462] Step 3:

[0463] The device sends the user's input origin, destination, and emotional state data analyzed by the emotion engine to the server. Input: Origin, destination, and emotional state data. Output: Data sent to the server.

[0464] Step 4:

[0465] The server calculates the optimal route by accessing a map database and a train operation information database based on the origin, destination, and sentiment status data it receives. Furthermore, platform and exit information for each station is also considered. Input: Origin, destination, map data, train operation information, sentiment status data. Output: Optimal route information.

[0466] Step 5:

[0467] The server adjusts the route based on the user's emotional state. For example, if the user is stressed, it will choose a less congested route; if they are relaxed, it will choose a route with good scenery. Input: Optimal route information, emotional state. Output: Adjusted route information.

[0468] Step 6:

[0469] The server sends optimized route information to the terminal. This information includes the route, boarding location, exit location, and reasons based on emotional state. Input: Optimized route information. Output: Route information sent to the terminal.

[0470] Step 7:

[0471] The terminal displays route information received by the passenger in an easy-to-understand manner. The displayed information includes the mode of transport, optimal boarding location, drop-off point, optimal exit, and reasons for route adjustments based on emotional state. Input: Received route information. Output: Displayed route information.

[0472] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating 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.

[0473] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0474] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0475] [Second Embodiment]

[0476] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0477] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0478] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0479] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0480] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0481] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0482] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0483] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0484] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0485] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0486] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0487] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. 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".

[0488] This invention is a system that provides route guidance, including the optimal boarding position and exit, to ensure the shortest possible travel time from the point of origin to the destination using public transportation. The following describes the program processing of this system and a specific example based on it in natural language.

[0489] System Overview

[0490] This system calculates and displays the optimal route, boarding position at each station, and exit based on the departure and destination information entered by the user. Specifically, it consists of a terminal, a server, and a map database and a train operation information database.

[0491] Program processing

[0492] 1. User input:

[0493] The user launches the application and enters their departure and destination points. They can also specify their mode of transport (train, bus, etc.) and desired arrival time.

[0494] 2. Data transmission:

[0495] The terminal sends the entered information (departure point, destination, mode of transport, desired arrival time) to the server.

[0496] 3. Server processing:

[0497] Based on the information received by the server, it accesses the map database and the train operation information database, and calculates the optimal route considering the current train conditions.

[0498] Based on the calculated route, the server determines the optimal boarding position and exit from the platform and exit information of each station.

[0499] 4. Submit results:

[0500] The server sends the calculation results (optimal route, boarding location, exit) to the terminal.

[0501] 5. User display:

[0502] The terminal displays the route information it has received to the user.

[0503] Specific example

[0504] 1. The user launches the application, searches for a route from "Station A" to "Station B," and enters the departure point "Station A" and the destination "Station B."

[0505] 2. The terminal converts the user's input information into "Departure point: Station A, Destination: Station B, Mode of transport: Train" and sends it to the server.

[0506] 3. The server calculates the optimal route from "Station A" to "Station B" based on the map database and train operation information. For example, it might select "Train C" as the optimal route.

[0507] 4. The server retrieves platform information for each station from Station A to Station B of "Train C" and determines the optimal boarding position (e.g., front of car 1) and exit (e.g., Exit 1).

[0508] 5. The server sends this information to the terminal as "Means of transport: Train C, Boarding location: Front of car 1, Disembarking station: Station B, Exit: Exit 1".

[0509] 6. The device displays this information on the user's screen:

[0510] Transportation: Train C

[0511] Boarding location: Front of car 1

[0512] Disembarking station: Station B

[0513] Optimal exit: Exit 1

[0514] In this way, users can receive specific instructions to efficiently travel to their destination. This system allows users to improve their travel efficiency and reach their destination in the shortest possible time.

[0515] The key feature of this system is that it calculates routes considering real-time train operation status, and then combines this with platform and exit information for each station to provide the optimal boarding location and exit. This allows users not only to reach their destination but also to utilize the most efficient means of transportation.

[0516] The following describes the processing flow.

[0517] Step 1:

[0518] The user launches the application and enters their departure and destination points. They can also optionally specify their mode of transport (train, bus, etc.) and desired arrival time.

[0519] Step 2:

[0520] The terminal receives input information from the user and converts the departure point, destination, selected mode of transport, and desired arrival time into the format required for subsequent processing.

[0521] Step 3:

[0522] The device sends the converted information to the server. The information sent includes the departure point, destination, mode of transport, and desired arrival time.

[0523] Step 4:

[0524] Based on the information received by the server, it accesses the map database and the traffic information database.

[0525] Step 5:

[0526] The server retrieves a list of available public transportation options (e.g., multiple train lines, bus routes) and evaluates each route.

[0527] Step 6:

[0528] The server calculates the optimal route, taking into account factors such as travel time, number of transfers, and train conditions.

[0529] Step 7:

[0530] The server determines the optimal boarding and exit locations for each route. This process utilizes platform and exit information for each station.

[0531] Step 8:

[0532] The server sends the calculation results to the terminal. The transmitted information includes the optimal route, boarding location, and exit location.

[0533] Step 9:

[0534] The terminal displays route information received by the user in an easy-to-understand manner. Specific details include the mode of transport, optimal boarding location, drop-off point, and optimal exit.

[0535] Step 10:

[0536] Based on the information displayed, the user boards public transport at the designated boarding location and uses the designated exit to reach their destination.

[0537] (Example 1)

[0538] Next, we will describe Example 1. 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".

[0539] When using modern public transportation, especially in congested urban areas, simply knowing the route from origin to destination is insufficient for efficient travel. Users need to know the optimal boarding location and the best exit at each station, but manually researching this is difficult, time-consuming, and cumbersome. Furthermore, route guidance that takes real-time train operation status into account is necessary, but conventional systems have been unable to effectively implement this. As a result, user travel efficiency has decreased, and this has become a source of stress.

[0540] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0541] In this invention, the server includes means for the user to input a departure point and destination; means for the terminal to transmit the inputted departure point and destination information to the server; means for the server to calculate the optimal route using a map database and an operation information database based on the received information; means for the server to determine the boarding position and exit position at each station based on the calculated optimal route; and means for transmitting the determined information to the terminal and displaying it to the user. As a result, the user can find out the optimal route, optimal boarding position, and exit from the departure point to the destination in real time, enabling them to use public transportation efficiently.

[0542] "User input" refers to the act of a user entering information such as their departure point and destination into a terminal.

[0543] A "terminal" is a device used by a user to input information or display received information. Examples include smartphones and personal computers.

[0544] A "server" is a central system that receives information sent from terminals, accesses various databases to calculate the optimal route, and sends the results back to the terminals.

[0545] A "map database" is a database that stores detailed information such as geographical location information and train stations.

[0546] A "transportation information database" is a database that stores real-time data such as the operating schedules and delay information of public transportation.

[0547] The "optimal route" is the route that allows the user to reach their destination in the shortest time or with the fewest transfers.

[0548] "Boarding position" refers to the recommended location within a train or bus for users to reach their destination efficiently.

[0549] An "exit" refers to the exit of a station or bus stop that a user should use when they reach their destination.

[0550] "Platform information for each station" refers to information about the layout of station platforms and which trains stop at specific platforms.

[0551] "Real-time" means that the information is current as of the present time and always reflects the latest status.

[0552] This invention provides a system that offers optimal route guidance for users to travel from their starting point to their destination using public transportation in the shortest possible time. The system includes the steps of user input, data transmission, server processing, result transmission, and user display. The following describes embodiments of this system, specifying the concrete hardware and software.

[0553] Hardware and software used

[0554] Terminal: A user device such as a smartphone or PC sends the entered information to the server and displays the calculation results.

[0555] Server: A central device that accesses the database and performs route calculations. This can be a cloud server or an on-premises server.

[0556] Map database: A database that stores geographical location information and station information. For example, a GIS (Geographic Information System) is used.

[0557] Transportation Information Database: A database that stores real-time data such as public transportation schedules and delay information. Real-time data is retrieved via API.

[0558] System Operation Overview

[0559] 1. User input:

[0560] The user launches the application and enters their departure and destination points. The user can also specify their mode of transport and desired arrival time.

[0561] 2. Data transmission:

[0562] The terminal sends the entered information to the server. Protocols such as HTTP requests are used for communication.

[0563] 3. Server processing:

[0564] Based on the information received by the server, it accesses the map database and the train operation information database to calculate the optimal route. The server also considers platform and exit information for each station to determine the optimal boarding location and exit.

[0565] 4. Submit results:

[0566] The server sends the calculation results to the terminal. The results are sent in a standard format such as JSON.

[0567] 5. User display:

[0568] The device analyzes the data it receives and displays it in a user-friendly format.

[0569] Specific example

[0570] Consider a scenario where a user launches the application and searches for a route from "Station A" to "Station B". In this case, the user enters the departure point "Station A" and the destination "Station B", and taps the search button. The device converts the entered information into "Departure point: Station A, Destination: Station B, Mode of transport: Train" and sends it to the server.

[0571] The server calculates the optimal route from "Station A" to "Station B" based on a map database and train operation information. For example, it might select "Train C". It also obtains platform information for each station from "Station A" to "Station B" and determines the optimal boarding position (e.g., front of car 1) and exit (e.g., Exit 1).

[0572] The server sends this information to the terminal as "Transportation: Train C, Boarding location: Front of car 1, Disembarking station: Station B, Exit: Exit 1". The terminal displays this information on the user's screen.

[0573] Prompt example

[0574] Examples of prompts to input into a generative AI model include the following:

[0575] "Please specify the departure and destination stations, and tell me which train to take, which car and which door to use, and which exit to use at the destination station. For example, let's say the departure station is 'Station A' and the destination is 'Station B'."

[0576] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0577] Step 1:

[0578] The user enters the departure point and destination.

[0579] The user launches the application and enters their departure and destination locations into a form. Optionally, they can also enter their desired arrival time and mode of transportation (train, bus, etc.).

[0580] Input: Departure point, destination, desired arrival time, mode of transport

[0581] Output: User input data

[0582] Specific operation: The user enters "Station A" as the departure point and "Station B" as the destination into the text boxes and taps the "Search" button. This input information is stored in a variable within the program.

[0583] Step 2:

[0584] The terminal sends data to the server.

[0585] The terminal sends the information entered by the user to the server. HTTP POST requests are used for communication.

[0586] Input: User input data

[0587] Output: Request data to the server

[0588] Specific operation: The terminal converts the input data into JSON format and sends a "POST / find_route" request to the server. The request data will look something like this: { 'from': 'Station A', 'to': 'Station B', 'arrive_by': '10:00', 'mode': 'Train'}.

[0589] Step 3:

[0590] The server receives the information and calculates the optimal path.

[0591] The server analyzes the received data and accesses map and traffic information databases to calculate the optimal route. Dijkstra's algorithm and the A algorithm are used for route calculation.

[0592] Input: Request data, map data, service information

[0593] Output: Calculated optimal path data

[0594] Specific operation: The server parses the received JSON data and retrieves the coordinate information of the departure point "Station A" and the destination "Station B" from the map database. At the same time, it checks the current train status from the train operation information database and calculates the most efficient route. For example, a route using "Train C" is selected.

[0595] Step 4:

[0596] The server determines the optimal boarding location and exit.

[0597] Based on the calculated optimal route, the server determines the best boarding position and exit from each station's platform and exit information.

[0598] Input: Optimal route data, home information, exit information

[0599] Output: Boarding location and exit information

[0600] Specific operation: The server obtains platform information for each station from Station A to Station B of "Train C," and determines, for example, that the front of Car 1 is the optimal boarding position and Exit 1 is the optimal exit.

[0601] Step 5:

[0602] The server sends the results to the terminal.

[0603] The server sends the calculation results (optimal route, boarding location, exit) to the terminal. An HTTP POST request is used again for communication.

[0604] Input: Boarding location and exit information

[0605] Output: Response data

[0606] Specific operation: The server formats the calculation result into JSON format and sends it to the terminal as a "POST / show_route" request. For example, the response data will be "{ 'route': 'Train C', 'car_position': 'Front of car 1', 'exit': 'Exit 1'}".

[0607] Step 6:

[0608] Display the results on the user's terminal.

[0609] The terminal analyzes the data received from the server and displays it in a format that is easy for the user to understand.

[0610] Input: Response data

[0611] Output: Route information displayed on the user screen

[0612] Specific operation: The application on the device parses the received JSON data and displays specific route, boarding location, and exit information on the user interface. Information such as "Means of transport: Train C", "Boarding location: Front of car 1", "Disembarking station: Station B", and "Optimal exit: Exit 1" is laid out on the screen.

[0613] (Application Example 1)

[0614] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0615] As autonomous vehicles become more widespread, they need to be able to select the appropriate route for users to travel efficiently and quickly from their starting point to their destination. However, current autonomous driving technology struggles to calculate and provide optimal pick-up and drop-off locations to users. Furthermore, there are limited means of optimizing routes while considering real-time operating conditions. As a result, users end up wasting unnecessary time during their journey from departure to destination.

[0616] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0617] In this invention, the server includes means for inputting a departure point and a destination; means for transmitting the inputted departure point and destination information to the server; means for calculating the optimal route based on the information received by the server; means for determining the boarding and exit positions based on the calculated optimal route; means for transmitting the determined information to a terminal and displaying it to the user; means for transmitting the calculation results to the computer system of the autonomous vehicle, which in turn controls the vehicle according to the optimal route; and means for the user to confirm detailed route information and boarding / alighting positions via a smartphone or in-vehicle display device. This enables the autonomous vehicle to select the optimal route in real time and travel efficiently from the departure point to the destination.

[0618] The "starting point" is the point where the user begins their journey.

[0619] The "destination" is the point where the user is expected to finish their journey.

[0620] A "terminal" is a device used by users to input information about their departure point and destination and receive route guidance.

[0621] A "server" is a central processing unit that receives information sent from a terminal, calculates the optimal route, and returns the result.

[0622] The "optimal route" is the route chosen to minimize travel time from the starting point to the destination.

[0623] The "boarding position" is the optimal position for a user to board an autonomous vehicle.

[0624] The "exit location" is the most suitable position for a user to disembark from the autonomous vehicle when they reach their destination.

[0625] An "autonomous vehicle" is a vehicle that can travel on the road without the intervention of a human driver.

[0626] A "computer system" is a system that controls the functions of an autonomous vehicle and manages the vehicle's movement according to a calculated path.

[0627] A "smartphone" is a portable, multi-functional electronic device used by users to input and display information.

[0628] An "in-vehicle display device" is a device installed inside an autonomous vehicle that displays route information to the user.

[0629] "Real-time service status" refers to information showing current traffic conditions and the operating status of trains and buses.

[0630] "Facility information for each station" refers to information that shows the specific location of platforms and exits for each station.

[0631] "Detailed route information" refers to specific information necessary for users to travel efficiently, such as boarding and alighting locations and travel time.

[0632] This invention is a system that provides optimal route guidance by an autonomous vehicle, based on the user's specified origin and destination. The system consists of a terminal, a server, the autonomous vehicle's computer system, and a map database and a traffic information database.

[0633] Program Overview

[0634] The system program uses the following hardware and software:

[0635] Hardware:

[0636] Smartphone (e.g., Android or iOS)

[0637] Onboard computers for autonomous vehicles (e.g., NVIDIA Drive Platform)

[0638] Server (Central Processing Unit)

[0639] software:

[0640] Map database (e.g., Google Maps API)

[0641] Operation information database (e.g., API for public transportation operation information)

[0642] Programming languages ​​(e.g., Python, JavaScript)

[0643] Program Processing Overview

[0644] 1. The user enters the departure and destination locations:

[0645] Users enter their departure and destination points using a smartphone app or a touchscreen in the autonomous vehicle. They can also enter their desired arrival time and mode of transportation as needed.

[0646] 2. Sending information to the server:

[0647] The terminal sends the entered information to the server. The server then receives the origin, destination, and other condition information.

[0648] 3. Calculation of the optimal path:

[0649] The server accesses the map database and the traffic information database to calculate the optimal route based on real-time traffic conditions.

[0650] 4. Determining boarding and alighting locations:

[0651] Based on the calculated route, the server retrieves facility information for each station and determines the optimal boarding and alighting locations.

[0652] 5. Sending and displaying calculation results:

[0653] The server sends the calculation results to the terminal, and the user can check detailed route information and boarding / alighting locations on their smartphone or in-vehicle display device.

[0654] 6. Vehicle control by computer system:

[0655] The autonomous vehicle's computer system receives calculation results from a server and controls the vehicle according to the optimal route. This ensures that the boarding and alighting sequences at each station are executed efficiently.

[0656] Specific example

[0657] For example, suppose a user uses a smartphone app to input their departure point "Station A" and destination "Station B". This information is sent from the device to a server, which then accesses a map database and a traffic information database to calculate the optimal route.

[0658] The server selects the optimal route from "Station A" to "Station B" and retrieves platform and exit information for each station. Based on the calculation, it determines the optimal boarding position (e.g., near the front door) and alighting position (e.g., Exit 2) and sends this information back to the terminal. The user can then confirm this information on their smartphone or in-vehicle display device, allowing them to board the vehicle at the optimal position and alight at the designated exit.

[0659] Examples of prompts for generative AI models

[0660] "Departure point: 'Station A', Destination: 'Station B', Mode of transport: 'Autonomous vehicle', Calculate and display the optimal route and pick-up / drop-off locations."

[0661] The above is an overview of specific embodiments for carrying out this invention. This system enables users to travel efficiently and quickly, minimizing travel time from the point of origin to the destination.

[0662] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0663] Step 1:

[0664] The user enters their departure and destination points using a smartphone app or in-car touchscreen. This may also include desired arrival time and mode of transport. The entered information is formatted as data based on the input format of the user's device.

[0665] Input: Departure point, destination, desired arrival time, mode of transport

[0666] Output: Input information converted into a data format for transmission to the server.

[0667] Step 2:

[0668] The terminal sends the formatted data to the server via wireless communication. This process is carried out while verifying the integrity of the data. If the data is not transmitted correctly, a retransmission process is performed.

[0669] Input: Formatted data (departure point, destination, desired arrival time, mode of transport)

[0670] Output: Confirmation message indicating that transmission to the server is complete.

[0671] Step 3:

[0672] Based on the information received by the server, it accesses the map database and the operation information database to obtain real-time operation status. It uses the database API to query the necessary information and retrieve the current operation status.

[0673] Input: Departure point, destination, desired arrival time, mode of transport

[0674] Output: Current service status, traffic information

[0675] Step 4:

[0676] The server calculates the optimal route based on the information it acquires. The calculation algorithm combines real-time traffic conditions, map information, and desired arrival time to find the shortest route.

[0677] Input: Current service status, traffic information, map information

[0678] Output: Optimal route information

[0679] Step 5:

[0680] Based on the calculated optimal route, the server retrieves facility information for each station and determines the optimal boarding and alighting locations. It also considers platform and exit information for each station to select the most efficient location.

[0681] Input: Optimal route information, facility information for each station

[0682] Output: boarding location, alighting location

[0683] Step 6:

[0684] The server sends the determined information (optimal route, boarding location, and alighting location) to the terminal. The transmitted information is formatted in a way that can be displayed on the user's terminal screen.

[0685] Input: Optimal route, boarding location, alighting location

[0686] Output: Data to send to the terminal

[0687] Step 7:

[0688] The terminal displays the received information on the user's smartphone or in-vehicle display device. This display includes route information, boarding location, and alighting location, which the user can then review.

[0689] Input: Data to send to the terminal (optimal route, boarding location, alighting location)

[0690] Output: Information displayed on a smartphone or in-vehicle display device.

[0691] Step 8:

[0692] The autonomous vehicle's computer system receives calculation results from a server and controls the vehicle according to the optimal route. Stopping positions at each station are also automatically adjusted.

[0693] Input: Calculation results from the server (optimal route, boarding location, alighting location)

[0694] Output: Vehicle control instructions

[0695] Step 9:

[0696] Users can check detailed route information and pick-up / drop-off locations via their smartphone or in-vehicle display device, and actually pick up and drop off at those locations.

[0697] Input: Information displayed on a smartphone or in-vehicle display device.

[0698] Output: User movement behavior

[0699] The above outlines the processing steps of this system. Each step illustrates how the input information is processed and how it ultimately yields output that enables efficient user movement.

[0700] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0701] The present invention is a system comprising means for inputting the departure and destination points, means for transmitting the input information to a server, means for calculating the optimal route, means for determining the boarding position and exit point, and means for displaying the determined information to the user, further incorporating an emotion engine that recognizes the user's emotions and adjusts the route accordingly. This system provides support for users to travel to their destinations in the shortest and most comfortable way possible using public transportation.

[0702] System Overview

[0703] This system calculates the optimal route, boarding positions and exits at each station, based on the departure and destination information entered by the user. It then further adjusts the route based on the user's emotional state and displays it to the user. Specifically, it consists of a terminal, a server, a map database, a train operation information database, and an emotion engine.

[0704] Program processing

[0705] 1. User input:

[0706] The user launches the application and enters their departure and destination locations. They can also optionally specify their mode of transport and desired arrival time.

[0707] The device recognizes the user's current emotional state via an emotion engine. This emotional state is analyzed using data collected through the smartphone's camera and microphone (such as facial expressions and voice).

[0708] 2. Data transmission:

[0709] The terminal sends the input information and the emotion data analyzed by the emotion engine to the server.

[0710] 3. Server processing:

[0711] Based on the information received by the server, it accesses the map database and the train operation information database, and calculates the optimal route considering the current train conditions.

[0712] Based on the calculated route, the server determines the optimal boarding position and exit from the platform and exit information of each station.

[0713] 4. Application of sentiment data:

[0714] The server adjusts the route based on the user's emotional state, obtained from the emotion engine. For example, if the user is stressed, it prioritizes less congested routes. On the other hand, if the user is relaxed, it suggests routes with good scenery or routes that pass through tourist attractions.

[0715] 5. Submit results:

[0716] The server sends optimized route information to the terminal. This information includes the optimal route, boarding location, exit location, and reasons for the recommendation based on the user's emotional state.

[0717] 6. User display:

[0718] The terminal displays route information received by the user in an easy-to-understand manner. Specifically, this includes the mode of transport used, the optimal boarding location, the optimal drop-off point, the optimal exit, and the reasons for route adjustments based on the user's emotional state.

[0719] Specific example

[0720] Examples of user stress

[0721] 1. The user launches the application and enters the destination: travel from "Station A" to "Station B".

[0722] 2. The device sends user input information and emotional data (stress level) to the server.

[0723] 3. The server calculates the optimal route from "Station A" to "Station B" and selects, for example, "Train C".

[0724] 4. The server prioritizes selecting less congested routes based on the user's stress level. It also determines the optimal boarding position (e.g., the last car) and exit (e.g., Exit 3) for "Train C".

[0725] 5. The server sends this information to the terminal, and the terminal displays it to the user:

[0726] Transportation: Train C

[0727] Boarding location: Last car

[0728] Disembarking station: Station B

[0729] Optimal exit: Exit 3

[0730] Reason for proposal: Less congested routes

[0731] Examples of users being relaxed

[0732] 1. The user launches the application and enters the destination: travel from "Station A" to "Station B".

[0733] 2. The device sends user input information and emotional data (relaxed state) to the server.

[0734] 3. The server calculates the optimal route from "Station A" to "Station B" and selects, for example, "Train D".

[0735] 4. The server prioritizes selecting routes with good scenery or those that pass through tourist spots, based on the user's relaxation state. It also determines the optimal boarding position (e.g., front of car 1) and exit (e.g., exit 1) for "Train D".

[0736] 5. The server sends this information to the terminal, and the terminal displays it to the user:

[0737] Transportation: Train D

[0738] Boarding location: Front of car 1

[0739] Disembarking station: Station B

[0740] Optimal exit: Exit 1

[0741] Reason for proposal: A route with good scenery

[0742] This system allows users to receive optimal route guidance tailored to their emotional state, resulting in a more comfortable travel experience. The introduction of an emotion engine enables the provision of personalized services that meet the individual needs of each user.

[0743] The following describes the processing flow.

[0744] Step 1:

[0745] The user launches the application and enters their departure and destination points. They can also optionally specify their mode of transport (train, bus, etc.) and desired arrival time.

[0746] Step 2:

[0747] The device activates an emotion engine to recognize the user's emotional state through their facial expressions and voice. This data is collected through the smartphone's camera and microphone.

[0748] Step 3:

[0749] The emotion engine analyzes collected facial expressions and voice data to determine the user's current emotional state (e.g., stress, relaxation, joy).

[0750] Step 4:

[0751] The terminal sends the entered departure point, destination, mode of transport, desired arrival time, and sentiment data analyzed by the sentiment engine to the server.

[0752] Step 5:

[0753] Based on the information received by the server, it accesses the map database and the traffic information database.

[0754] Step 6:

[0755] The server retrieves a list of available public transportation options (e.g., multiple train lines, bus routes) and evaluates each route.

[0756] Step 7:

[0757] The server calculates the optimal route, taking into account factors such as travel time, number of transfers, and train conditions.

[0758] Step 8:

[0759] The server determines the optimal boarding and exit locations for each route. This process utilizes platform and exit information for each station.

[0760] Step 9:

[0761] The server adjusts the route based on the user's emotional state, obtained from the emotion engine. For example, if the user is stressed, it prioritizes less congested routes; if the user is relaxed, it suggests routes with scenic views or routes that pass through tourist attractions.

[0762] Step 10:

[0763] The server sends optimized route information to the terminal. This information includes the optimal route, boarding location, exit location, and reasons for the recommendation based on the user's emotional state.

[0764] Step 11:

[0765] The terminal displays route information received by the user in an easy-to-understand manner. Specifically, this includes the mode of transport used, the optimal boarding location, the optimal drop-off point, the optimal exit, and the reasons for route adjustments based on the user's emotional state.

[0766] Step 12:

[0767] Based on the information displayed, the user boards public transport at the designated boarding location and uses the designated exit to reach their destination.

[0768] (Example 2)

[0769] Next, we will describe Example 2. 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".

[0770] Conventional route guidance systems only provide the optimal route when a user is using public transportation, and do not flexibly adjust the route according to the user's emotional state. As a result, users often face stressful situations and other emotional discomforts. This invention aims to provide more comfortable travel support that takes the user's emotional state into consideration.

[0771] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0772] In this invention, the server includes means for inputting a departure point and destination; means for transmitting the inputted departure point and destination information to the server; means for calculating the optimal route based on the information received by the server; means for determining the boarding position and exit position based on the calculated optimal route; means for analyzing the user's emotional state; means for adjusting the route based on the analyzed emotional state; and means for transmitting the determined information to a terminal and displaying it to the user. This provides optimal route guidance according to the user's emotional state, enabling a comfortable journey.

[0773] "Departure point" refers to the point where the user begins their journey.

[0774] "Destination" refers to the point where the user is expected to complete their journey.

[0775] "Means" refers to the apparatus or method used to achieve a specific objective.

[0776] A "server" refers to a computer system used to process and manage information on a network.

[0777] A "terminal" refers to a device that a user directly interacts with, and its role is to input and display information.

[0778] The "optimal route" refers to the most efficient or comfortable travel route for a user under specific conditions.

[0779] "Boarding location" refers to the specific point where a user boards public transportation.

[0780] "Exit location" refers to the specific point where a user disembarks from public transportation.

[0781] "Emotional state" refers to the user's psychological and physiological state, which is analyzed from facial expressions, voice, and other factors.

[0782] An "emotion engine" refers to software or a device used to analyze a user's emotional state.

[0783] "Adjusting the pathway" refers to modifying or optimizing an existing pathway based on analyzed emotional states and other conditions.

[0784] A "map database" refers to a database containing geographical information, which is used for route calculations.

[0785] A "service information database" refers to a database containing information on the operating status of public transportation, providing real-time service information.

[0786] "Current operating status" refers to the most recent operating status of public transportation, including information such as delays and congestion.

[0787] This invention provides a system that offers the optimal route when a user travels using public transportation and adjusts the route based on the user's emotional state. The system includes means for inputting the departure and destination points, means for transmitting the input information to a server, means for calculating the optimal route, means for determining the boarding position and exit point, and means for displaying the determined information to the user. Furthermore, it incorporates an emotion engine that recognizes the user's emotions and adjusts the route accordingly.

[0788] System Configuration

[0789] This system consists of the following elements:

[0790] 1. Terminal:

[0791] It is a user-operated device that takes in information about the origin and destination and acquires sentiment data. A smartphone is a concrete example of this.

[0792] The device is equipped with a camera and microphone, which are used to capture the user's facial expressions and voice, and then analyzed by an emotion engine.

[0793] 2. Server:

[0794] This is a central system that receives information transmitted from terminals and performs data processing and route calculations. The server accesses map databases and operational information databases to obtain real-time operational information.

[0795] As specific software examples, we will use the "Google Maps API" and the "Transportation Information API".

[0796] 3. Emotional Engine:

[0797] This is software or a device for analyzing a user's emotional state. It utilizes an emotion analysis library built into a smartphone.

[0798] Based on the analyzed sentiment data, the server further adjusts the optimal route.

[0799] System operation example

[0800] Examples of users experiencing stress

[0801] 1. The user launches the app on their smartphone and enters the departure point "Station A" and the destination "Station B".

[0802] 2. The device captures the user's facial expressions and voice data, and performs emotion analysis to determine if the user is experiencing stress.

[0803] 3. The device sends the entered information and emotion data to the server.

[0804] 4. The server accesses the map database and the train operation information database to calculate the optimal route. For example, it finds the shortest route from "Station A" to "Station B" and selects "Train C".

[0805] 5. The server takes into account the user's stress level and determines less crowded routes, boarding positions (e.g., the last car), and optimal exits (e.g., Exit 3).

[0806] 6. The server sends the coordinated routing information to the terminal, and the terminal displays the following to the user:

[0807] Transportation: Train C

[0808] Boarding location: Last car

[0809] Disembarking station: Station B

[0810] Optimal exit: Exit 3

[0811] Reason for proposal: Less congested routes

[0812] Examples of relaxed users

[0813] 1. The user launches the app on their smartphone and enters the destination: "Station A" to "Station B".

[0814] 2. The device captures the user's facial expressions and voice data, and performs emotion analysis to determine that the user is relaxed.

[0815] 3. The device sends the entered information and emotion data to the server.

[0816] 4. The server accesses the map database and the train operation information database to calculate the optimal route. For example, it might determine the most comfortable route from "Station A" to "Station B" and select "Train D".

[0817] 5. The server takes into account the user's relaxed state and determines a route that includes scenic views and tourist spots, as well as the optimal boarding position (e.g., front of car 1) and exit (e.g., exit 1).

[0818] 6. The server sends the coordinated routing information to the terminal, and the terminal displays the following to the user:

[0819] Transportation: Train D

[0820] Boarding location: Front of car 1

[0821] Disembarking station: Station B

[0822] Optimal exit: Exit 1

[0823] Reason for proposal: A route with good scenery

[0824] Examples of prompt statements using generative AI models include the following:

[0825] The user launches the app and enters their travel time from Station A to Station B. During this process, the app performs an emotional analysis to determine whether the user is stressed or relaxed. Then, it suggests the optimal route, boarding location, and exit.

[0826] This system allows users to receive optimal route guidance tailored to their emotional state, resulting in a comfortable travel experience. The introduction of an emotion engine enables the provision of personalized services that meet the individual needs of each user.

[0827] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0828] Program processing steps and specific actions

[0829] Step 1: User Input

[0830] Input: The user launches the application and enters the departure point "Station A" and the destination "Station B". Optionally, they can also specify their desired arrival time and mode of transport.

[0831] Operation: The user operates a smartphone app. The smartphone's camera and microphone are used to capture the user's facial expressions and voice data in real time.

[0832] Data processing: The device inputs captured facial expressions and audio data into an emotion engine to analyze the user's emotional state.

[0833] Output: Origin, destination, options information, and analyzed sentiment data are generated.

[0834] Step 2: Data transmission

[0835] Input: Origin, destination, optional information, and sentiment data generated by the device.

[0836] Operation: The terminal generates this data as data packets and sends them to the server using the HTTP or HTTPS protocol.

[0837] Output: Data packets sent to the server.

[0838] Step 3: Server Processing

[0839] Input: Data packets received by the server from the terminal.

[0840] Operation: The server analyzes the data packets and extracts origin, destination, option information, and sentiment data. It then accesses a map database (e.g., Google Maps API) and a traffic information database to retrieve current traffic status.

[0841] Data processing: Based on the operational data acquired by the server, the optimal route from the origin to the destination is calculated using an algorithm.

[0842] Output: Optimal route information.

[0843] Step 4: Applying emotional data

[0844] Input: Optimal route information calculated by the server and user sentiment data.

[0845] Operation: The server further adjusts route information based on the user's emotional state (e.g., stressed, relaxed). For example, if the user is stressed, it will select a less congested route; if the user is relaxed, it will select a route with good scenery or one that passes by tourist attractions.

[0846] Data processing: Determine the adjusted route information, optimal boarding location, and optimal exit location.

[0847] Output: Adjusted route information, boarding location, exit location, and reason for recommendation.

[0848] Step 5: Submit Results

[0849] Input: Server-adjusted optimal route information, boarding location, exit location, and reason for recommendation.

[0850] Operation: The server generates this information as a data packet and sends it to the terminal.

[0851] Output: Data packets sent to the terminal.

[0852] Step 6: User Display

[0853] Input: Data packets received by the terminal from the server.

[0854] Operation: The terminal analyzes data packets and displays the mode of transport to be used, the optimal boarding location, the optimal drop-off location, the optimal exit, and the reason for the recommendation on the user interface.

[0855] Output: Optimal route information displayed to the user.

[0856] This program's processing allows users to receive optimal route guidance tailored to their emotional state, enabling a comfortable journey.

[0857] (Application Example 2)

[0858] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0859] Conventional travel route guidance systems provide the optimal route based on input of the origin and destination, but they lacked personalization of service by not considering the user's emotional state. Furthermore, they were unable to provide the optimal route based on whether the passenger was stressed or relaxed. As a result, they failed to deliver a comfortable travel experience for users.

[0860] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for inputting the departure point and destination; means for transmitting the input departure point and destination information to the server; means for calculating the optimal route based on the information received by the server; means for determining the boarding position and exit position based on the calculated optimal route; means for analyzing the passenger's emotional state and transmitting the data to the server; means for adjusting the route based on the emotional state; means for transmitting the determined information to a terminal and displaying it to the passenger; means for the terminal to display the reason for the route adjustment based on the passenger's emotional state; and means for recognizing the passenger's emotional state using a mobile terminal, in-vehicle terminal, or camera. This makes it possible to provide a personalized and optimal travel route according to the user's emotional state.

[0861] The "starting point" is the point where the journey begins.

[0862] A "destination" is the final point of arrival at a destination.

[0863] A "server" is a computer system that receives, transmits, processes, and stores data over a network.

[0864] A "route" is the path taken to travel from a starting point to a destination.

[0865] "Boarding position" refers to the optimal location for passengers to board a mode of transportation.

[0866] An "exit" is a place where passengers disembark from a mode of transportation.

[0867] "Emotional state" refers to the emotional state a passenger is experiencing, such as stress or joy.

[0868] A "mobile device" refers to a portable computing device such as a smartphone or tablet.

[0869] An "in-vehicle terminal" is an electronic device installed in a car that assists with driving and navigation.

[0870] A "camera" is an optical device used to capture images and videos.

[0871] An "emotion engine" is a system that uses devices such as cameras and microphones to identify a user's emotional state and analyze that information.

[0872] A "terminal" refers to a device or equipment on which a user inputs or displays information.

[0873] This invention is a system to help passengers comfortably reach their destination using autonomous vehicles. The system uses the following hardware and software components.

[0874] Hardware configuration

[0875] 1. Mobile devices:

[0876] These are devices, such as smartphones and tablets, that passengers use to input their departure and destination locations.

[0877] 2. In-vehicle terminals:

[0878] These are touch panels or displays installed in autonomous vehicles, used by passengers to input their departure and destination locations and to confirm information.

[0879] 3. Camera:

[0880] This device is installed inside autonomous vehicles to capture passengers' facial expressions and movements and analyze their emotional state.

[0881] Software Configuration

[0882] 1. Emotional Engine:

[0883] This software module analyzes facial expressions and voice data to determine passengers' emotional states in real time. It utilizes OpenCV and common emotion analysis libraries.

[0884] 2. Path Calculation Module:

[0885] It operates on a server and calculates the optimal route based on the received origin and destination data. This calculation utilizes a map database and a traffic information database.

[0886] 3. Server:

[0887] This system receives, transmits, processes, and stores data over a network. The server includes an emotion engine that analyzes facial expressions and voice data, and a route calculation module that uses map data and traffic information.

[0888] Data processing and data calculation

[0889] Camera data:

[0890] The system collects passengers' facial expressions and voice data through cameras and microphones and transmits it to a server in real time. The emotion engine analyzes this data to determine their emotional state (stress, relaxation, etc.).

[0891] Path calculation:

[0892] The server accesses map and traffic information databases to calculate the optimal route from the origin to the destination. Furthermore, it adjusts the route based on the passenger's emotional state, as determined by the emotion engine. For example, if a passenger is stressed, it selects a less congested route; if they are relaxed, it selects a route with good scenery.

[0893] Information transmission and display:

[0894] Once the optimal route information is determined, the server transmits this information to the in-vehicle terminal and displays it to the passengers on the screen. The displayed information includes the optimal route, boarding location, alighting location, exit, and reasons for route adjustments based on emotional state.

[0895] Specific example

[0896] 1. The passenger enters their travel destination from "Station A" to "Station B" using the onboard terminal.

[0897] 2. In-car cameras capture passengers' facial expressions, which are then analyzed by an emotion engine.

[0898] 3. The emotion engine determines that the passenger is stressed and sends data to the server.

[0899] 4. The server calculates the least congested route and transmits the calculated route to the in-vehicle terminal.

[0900] 5. The in-vehicle terminal displays the following information to passengers:

[0901] Transportation: Train C

[0902] Boarding location: Last car

[0903] Disembarking station: Station B

[0904] Optimal exit: Exit 3

[0905] Reason for proposal: Because it is less crowded.

[0906] Example of a prompt

[0907] "Input user emotion data and departure / destination information to recommend the optimal travel route. If the user is stressed, recommend a less congested route; if they are relaxed, recommend a route with good scenery."

[0908] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0909] Step 1:

[0910] The user launches the application on the in-vehicle terminal and enters the departure and destination locations. The information entered includes the departure location, destination, and optionally, the desired arrival time. The entered data is stored on the in-vehicle terminal. Input: Departure location, destination, desired arrival time. Output: Input information stored on the in-vehicle terminal.

[0911] Step 2:

[0912] The device's camera and microphone are used to capture passengers' facial expressions and voices in real time. An emotion engine analyzes this data to determine the user's emotional state (e.g., stress, relaxation). Input: Captured facial and voice data. Output: Analyzed emotional state data.

[0913] Step 3:

[0914] The device sends the user's input origin, destination, and emotional state data analyzed by the emotion engine to the server. Input: Origin, destination, and emotional state data. Output: Data sent to the server.

[0915] Step 4:

[0916] The server calculates the optimal route by accessing a map database and a train operation information database based on the origin, destination, and sentiment status data it receives. Furthermore, platform and exit information for each station is also considered. Input: Origin, destination, map data, train operation information, sentiment status data. Output: Optimal route information.

[0917] Step 5:

[0918] The server adjusts the route based on the user's emotional state. For example, if the user is stressed, it will choose a less congested route; if they are relaxed, it will choose a route with good scenery. Input: Optimal route information, emotional state. Output: Adjusted route information.

[0919] Step 6:

[0920] The server sends optimized route information to the terminal. This information includes the route, boarding location, exit location, and reasons based on emotional state. Input: Optimized route information. Output: Route information sent to the terminal.

[0921] Step 7:

[0922] The terminal displays route information received by the passenger in an easy-to-understand manner. The displayed information includes the mode of transport, optimal boarding location, drop-off point, optimal exit, and reasons for route adjustments based on emotional state. Input: Received route information. Output: Displayed route information.

[0923] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0924] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0925] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0926] [Third Embodiment]

[0927] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0928] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0929] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0930] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0931] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0932] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0933] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0934] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0935] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0936] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0937] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0938] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0939] This invention is a system that provides route guidance, including the optimal boarding position and exit, to ensure the shortest possible travel time from the point of origin to the destination using public transportation. The following describes the program processing of this system and a specific example based on it in natural language.

[0940] System Overview

[0941] This system calculates and displays the optimal route, boarding position at each station, and exit based on the departure and destination information entered by the user. Specifically, it consists of a terminal, a server, and a map database and a train operation information database.

[0942] Program processing

[0943] 1. User input:

[0944] The user launches the application and enters their departure and destination points. They can also specify their mode of transport (train, bus, etc.) and desired arrival time.

[0945] 2. Data transmission:

[0946] The terminal sends the entered information (departure point, destination, mode of transport, desired arrival time) to the server.

[0947] 3. Server processing:

[0948] Based on the information received by the server, it accesses the map database and the train operation information database, and calculates the optimal route considering the current train conditions.

[0949] Based on the calculated route, the server determines the optimal boarding position and exit from the platform and exit information of each station.

[0950] 4. Submit results:

[0951] The server sends the calculation results (optimal route, boarding location, exit) to the terminal.

[0952] 5. User display:

[0953] The terminal displays the route information it has received to the user.

[0954] Specific example

[0955] 1. The user launches the application, searches for a route from "Station A" to "Station B," and enters the departure point "Station A" and the destination "Station B."

[0956] 2. The terminal converts the user's input information into "Departure point: Station A, Destination: Station B, Mode of transport: Train" and sends it to the server.

[0957] 3. The server calculates the optimal route from "Station A" to "Station B" based on the map database and train operation information. For example, it might select "Train C" as the optimal route.

[0958] 4. The server retrieves platform information for each station from Station A to Station B of "Train C" and determines the optimal boarding position (e.g., front of car 1) and exit (e.g., Exit 1).

[0959] 5. The server sends this information to the terminal as "Means of transport: Train C, Boarding location: Front of car 1, Disembarking station: Station B, Exit: Exit 1".

[0960] 6. The device displays this information on the user's screen:

[0961] Transportation: Train C

[0962] Boarding location: Front of car 1

[0963] Disembarking station: Station B

[0964] Optimal exit: Exit 1

[0965] In this way, users can receive specific instructions to efficiently travel to their destination. This system allows users to improve their travel efficiency and reach their destination in the shortest possible time.

[0966] The key feature of this system is that it calculates routes considering real-time train operation status, and then combines this with platform and exit information for each station to provide the optimal boarding location and exit. This allows users not only to reach their destination but also to utilize the most efficient means of transportation.

[0967] The following describes the processing flow.

[0968] Step 1:

[0969] The user launches the application and enters their departure and destination points. They can also optionally specify their mode of transport (train, bus, etc.) and desired arrival time.

[0970] Step 2:

[0971] The terminal receives input information from the user and converts the departure point, destination, selected mode of transport, and desired arrival time into the format required for subsequent processing.

[0972] Step 3:

[0973] The device sends the converted information to the server. The information sent includes the departure point, destination, mode of transport, and desired arrival time.

[0974] Step 4:

[0975] Based on the information received by the server, it accesses the map database and the traffic information database.

[0976] Step 5:

[0977] The server retrieves a list of available public transportation options (e.g., multiple train lines, bus routes) and evaluates each route.

[0978] Step 6:

[0979] The server calculates the optimal route, taking into account factors such as travel time, number of transfers, and train conditions.

[0980] Step 7:

[0981] The server determines the optimal boarding and exit locations for each route. This process utilizes platform and exit information for each station.

[0982] Step 8:

[0983] The server sends the calculation results to the terminal. The transmitted information includes the optimal route, boarding location, and exit location.

[0984] Step 9:

[0985] The terminal displays route information received by the user in an easy-to-understand manner. Specific details include the mode of transport, optimal boarding location, drop-off point, and optimal exit.

[0986] Step 10:

[0987] Based on the information displayed, the user boards public transport at the designated boarding location and uses the designated exit to reach their destination.

[0988] (Example 1)

[0989] Next, we will describe Example 1. 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."

[0990] When using modern public transportation, especially in congested urban areas, simply knowing the route from origin to destination is insufficient for efficient travel. Users need to know the optimal boarding location and the best exit at each station, but manually researching this is difficult, time-consuming, and cumbersome. Furthermore, route guidance that takes real-time train operation status into account is necessary, but conventional systems have been unable to effectively implement this. As a result, user travel efficiency has decreased, and this has become a source of stress.

[0991] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0992] In this invention, the server includes means for the user to input a departure point and destination; means for the terminal to transmit the inputted departure point and destination information to the server; means for the server to calculate the optimal route using a map database and an operation information database based on the received information; means for the server to determine the boarding position and exit position at each station based on the calculated optimal route; and means for transmitting the determined information to the terminal and displaying it to the user. As a result, the user can find out the optimal route, optimal boarding position, and exit from the departure point to the destination in real time, enabling them to use public transportation efficiently.

[0993] "User input" refers to the act of a user entering information such as their departure point and destination into a terminal.

[0994] A "terminal" is a device used by a user to input information or display received information. Examples include smartphones and personal computers.

[0995] A "server" is a central system that receives information sent from terminals, accesses various databases to calculate the optimal route, and sends the results back to the terminals.

[0996] A "map database" is a database that stores detailed information such as geographical location information and train stations.

[0997] A "transportation information database" is a database that stores real-time data such as the operating schedules and delay information of public transportation.

[0998] The "optimal route" is the route that allows the user to reach their destination in the shortest time or with the fewest transfers.

[0999] "Boarding position" refers to the recommended location within a train or bus for users to reach their destination efficiently.

[1000] An "exit" refers to the exit of a station or bus stop that a user should use when they reach their destination.

[1001] "Platform information for each station" refers to information about the layout of station platforms and which trains stop at specific platforms.

[1002] "Real-time" means that the information is current as of the present time and always reflects the latest status.

[1003] This invention provides a system that offers optimal route guidance for users to travel from their starting point to their destination using public transportation in the shortest possible time. The system includes the steps of user input, data transmission, server processing, result transmission, and user display. The following describes embodiments of this system, specifying the concrete hardware and software.

[1004] Hardware and software used

[1005] Terminal: A user device such as a smartphone or PC sends the entered information to the server and displays the calculation results.

[1006] Server: A central device that accesses the database and performs route calculations. This can be a cloud server or an on-premises server.

[1007] Map database: A database that stores geographical location information and station information. For example, a GIS (Geographic Information System) is used.

[1008] Transportation Information Database: A database that stores real-time data such as public transportation schedules and delay information. Real-time data is retrieved via API.

[1009] System Operation Overview

[1010] 1. User input:

[1011] The user launches the application and enters their departure and destination points. The user can also specify their mode of transport and desired arrival time.

[1012] 2. Data transmission:

[1013] The terminal sends the entered information to the server. Protocols such as HTTP requests are used for communication.

[1014] 3. Server processing:

[1015] Based on the information received by the server, it accesses the map database and the train operation information database to calculate the optimal route. The server also considers platform and exit information for each station to determine the optimal boarding location and exit.

[1016] 4. Submit results:

[1017] The server sends the calculation results to the terminal. The results are sent in a standard format such as JSON.

[1018] 5. User display:

[1019] The device analyzes the data it receives and displays it in a user-friendly format.

[1020] Specific example

[1021] Consider a scenario where a user launches the application and searches for a route from "Station A" to "Station B". In this case, the user enters the departure point "Station A" and the destination "Station B", and taps the search button. The device converts the entered information into "Departure point: Station A, Destination: Station B, Mode of transport: Train" and sends it to the server.

[1022] The server calculates the optimal route from "Station A" to "Station B" based on a map database and train operation information. For example, it might select "Train C". It also obtains platform information for each station from "Station A" to "Station B" and determines the optimal boarding position (e.g., front of car 1) and exit (e.g., Exit 1).

[1023] The server sends this information to the terminal as "Transportation: Train C, Boarding location: Front of car 1, Disembarking station: Station B, Exit: Exit 1". The terminal displays this information on the user's screen.

[1024] Prompt example

[1025] Examples of prompts to input into a generative AI model include the following:

[1026] "Please specify the departure and destination stations, and tell me which train to take, which car and which door to use, and which exit to use at the destination station. For example, let's say the departure station is 'Station A' and the destination is 'Station B'."

[1027] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1028] Step 1:

[1029] The user enters the departure point and destination.

[1030] The user launches the application and enters their departure and destination locations into a form. Optionally, they can also enter their desired arrival time and mode of transportation (train, bus, etc.).

[1031] Input: Departure point, destination, desired arrival time, mode of transport

[1032] Output: User input data

[1033] Specific operation: The user enters "Station A" as the departure point and "Station B" as the destination into the text boxes and taps the "Search" button. This input information is stored in a variable within the program.

[1034] Step 2:

[1035] The terminal sends data to the server.

[1036] The terminal sends the information entered by the user to the server. HTTP POST requests are used for communication.

[1037] Input: User input data

[1038] Output: Request data to the server

[1039] Specific operation: The terminal converts the input data into JSON format and sends a "POST / find_route" request to the server. The request data will look something like this: { 'from': 'Station A', 'to': 'Station B', 'arrive_by': '10:00', 'mode': 'Train'}.

[1040] Step 3:

[1041] The server receives the information and calculates the optimal path.

[1042] The server analyzes the received data and accesses map and traffic information databases to calculate the optimal route. Dijkstra's algorithm and the A algorithm are used for route calculation.

[1043] Input: Request data, map data, service information

[1044] Output: Calculated optimal path data

[1045] Specific operation: The server parses the received JSON data and retrieves the coordinate information of the departure point "Station A" and the destination "Station B" from the map database. At the same time, it checks the current train status from the train operation information database and calculates the most efficient route. For example, a route using "Train C" is selected.

[1046] Step 4:

[1047] The server determines the optimal boarding location and exit.

[1048] Based on the calculated optimal route, the server determines the best boarding position and exit from each station's platform and exit information.

[1049] Input: Optimal route data, home information, exit information

[1050] Output: Boarding location and exit information

[1051] Specific operation: The server obtains platform information for each station from Station A to Station B of "Train C," and determines, for example, that the front of Car 1 is the optimal boarding position and Exit 1 is the optimal exit.

[1052] Step 5:

[1053] The server sends the results to the terminal.

[1054] The server sends the calculation results (optimal route, boarding location, exit) to the terminal. An HTTP POST request is used again for communication.

[1055] Input: Boarding location and exit information

[1056] Output: Response data

[1057] Specific operation: The server formats the calculation result into JSON format and sends it to the terminal as a "POST / show_route" request. For example, the response data will be "{ 'route': 'Train C', 'car_position': 'Front of car 1', 'exit': 'Exit 1'}".

[1058] Step 6:

[1059] Display the results on the user's terminal.

[1060] The terminal analyzes the data received from the server and displays it in a format that is easy for the user to understand.

[1061] Input: Response data

[1062] Output: Route information displayed on the user screen

[1063] Specific operation: The application on the device parses the received JSON data and displays specific route, boarding location, and exit information on the user interface. Information such as "Means of transport: Train C", "Boarding location: Front of car 1", "Disembarking station: Station B", and "Optimal exit: Exit 1" is laid out on the screen.

[1064] (Application Example 1)

[1065] Next, we will explain Application Example 1. In the following explanation, 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."

[1066] As autonomous vehicles become more widespread, they need to be able to select the appropriate route for users to travel efficiently and quickly from their starting point to their destination. However, current autonomous driving technology struggles to calculate and provide optimal pick-up and drop-off locations to users. Furthermore, there are limited means of optimizing routes while considering real-time operating conditions. As a result, users end up wasting unnecessary time during their journey from departure to destination.

[1067] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[1068] In this invention, the server includes means for inputting a departure point and a destination; means for transmitting the inputted departure point and destination information to the server; means for calculating the optimal route based on the information received by the server; means for determining the boarding and exit positions based on the calculated optimal route; means for transmitting the determined information to a terminal and displaying it to the user; means for transmitting the calculation results to the computer system of the autonomous vehicle, which in turn controls the vehicle according to the optimal route; and means for the user to confirm detailed route information and boarding / alighting positions via a smartphone or in-vehicle display device. This enables the autonomous vehicle to select the optimal route in real time and travel efficiently from the departure point to the destination.

[1069] The "starting point" is the point where the user begins their journey.

[1070] The "destination" is the point where the user is expected to finish their journey.

[1071] A "terminal" is a device used by users to input information about their departure point and destination and receive route guidance.

[1072] A "server" is a central processing unit that receives information sent from a terminal, calculates the optimal route, and returns the result.

[1073] The "optimal route" is the route chosen to minimize travel time from the starting point to the destination.

[1074] The "boarding position" is the optimal position for a user to board an autonomous vehicle.

[1075] The "exit location" is the most suitable position for a user to disembark from the autonomous vehicle when they reach their destination.

[1076] An "autonomous vehicle" is a vehicle that can travel on the road without the intervention of a human driver.

[1077] A "computer system" is a system that controls the functions of an autonomous vehicle and manages the vehicle's movement according to a calculated path.

[1078] A "smartphone" is a portable, multi-functional electronic device used by users to input and display information.

[1079] An "in-vehicle display device" is a device installed inside an autonomous vehicle that displays route information to the user.

[1080] "Real-time service status" refers to information showing current traffic conditions and the operating status of trains and buses.

[1081] "Facility information for each station" refers to information that shows the specific location of platforms and exits for each station.

[1082] "Detailed route information" refers to specific information necessary for users to travel efficiently, such as boarding and alighting locations and travel time.

[1083] This invention is a system that provides optimal route guidance by an autonomous vehicle, based on the user's specified origin and destination. The system consists of a terminal, a server, the autonomous vehicle's computer system, and a map database and a traffic information database.

[1084] Program Overview

[1085] The system program uses the following hardware and software:

[1086] Hardware:

[1087] Smartphone (e.g., Android or iOS)

[1088] Onboard computers for autonomous vehicles (e.g., NVIDIA Drive Platform)

[1089] Server (Central Processing Unit)

[1090] software:

[1091] Map database (e.g., Google Maps API)

[1092] Operation information database (e.g., API for public transportation operation information)

[1093] Programming languages ​​(e.g., Python, JavaScript)

[1094] Program Processing Overview

[1095] 1. The user enters the departure and destination locations:

[1096] Users enter their departure and destination points using a smartphone app or a touchscreen in the autonomous vehicle. They can also enter their desired arrival time and mode of transportation as needed.

[1097] 2. Sending information to the server:

[1098] The terminal sends the entered information to the server. The server then receives the origin, destination, and other condition information.

[1099] 3. Calculation of the optimal path:

[1100] The server accesses the map database and the traffic information database to calculate the optimal route based on real-time traffic conditions.

[1101] 4. Determining boarding and alighting locations:

[1102] Based on the calculated route, the server retrieves facility information for each station and determines the optimal boarding and alighting locations.

[1103] 5. Sending and displaying calculation results:

[1104] The server sends the calculation results to the terminal, and the user can check detailed route information and boarding / alighting locations on their smartphone or in-vehicle display device.

[1105] 6. Vehicle control by computer system:

[1106] The autonomous vehicle's computer system receives calculation results from a server and controls the vehicle according to the optimal route. This ensures that the boarding and alighting sequences at each station are executed efficiently.

[1107] Specific example

[1108] For example, suppose a user uses a smartphone app to input their departure point "Station A" and destination "Station B". This information is sent from the device to a server, which then accesses a map database and a traffic information database to calculate the optimal route.

[1109] The server selects the optimal route from "Station A" to "Station B" and retrieves platform and exit information for each station. Based on the calculation, it determines the optimal boarding position (e.g., near the front door) and alighting position (e.g., Exit 2) and sends this information back to the terminal. The user can then confirm this information on their smartphone or in-vehicle display device, allowing them to board the vehicle at the optimal position and alight at the designated exit.

[1110] Examples of prompts for generative AI models

[1111] "Departure point: 'Station A', Destination: 'Station B', Mode of transport: 'Autonomous vehicle', Calculate and display the optimal route and pick-up / drop-off locations."

[1112] The above is an overview of specific embodiments for carrying out this invention. This system enables users to travel efficiently and quickly, minimizing travel time from the point of origin to the destination.

[1113] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1114] Step 1:

[1115] The user enters their departure and destination points using a smartphone app or in-car touchscreen. This may also include desired arrival time and mode of transport. The entered information is formatted as data based on the input format of the user's device.

[1116] Input: Departure point, destination, desired arrival time, mode of transport

[1117] Output: Input information converted into a data format for transmission to the server.

[1118] Step 2:

[1119] The terminal sends the formatted data to the server via wireless communication. This process is carried out while verifying the integrity of the data. If the data is not transmitted correctly, a retransmission process is performed.

[1120] Input: Formatted data (departure point, destination, desired arrival time, mode of transport)

[1121] Output: Confirmation message indicating that transmission to the server is complete.

[1122] Step 3:

[1123] Based on the information received by the server, it accesses the map database and the operation information database to obtain real-time operation status. It uses the database API to query the necessary information and retrieve the current operation status.

[1124] Input: Departure point, destination, desired arrival time, mode of transport

[1125] Output: Current service status, traffic information

[1126] Step 4:

[1127] The server calculates the optimal route based on the information it acquires. The calculation algorithm combines real-time traffic conditions, map information, and desired arrival time to find the shortest route.

[1128] Input: Current service status, traffic information, map information

[1129] Output: Optimal route information

[1130] Step 5:

[1131] Based on the calculated optimal route, the server retrieves facility information for each station and determines the optimal boarding and alighting locations. It also considers platform and exit information for each station to select the most efficient location.

[1132] Input: Optimal route information, facility information for each station

[1133] Output: boarding location, alighting location

[1134] Step 6:

[1135] The server sends the determined information (optimal route, boarding location, and alighting location) to the terminal. The transmitted information is formatted in a way that can be displayed on the user's terminal screen.

[1136] Input: Optimal route, boarding location, alighting location

[1137] Output: Data to send to the terminal

[1138] Step 7:

[1139] The terminal displays the received information on the user's smartphone or in-vehicle display device. This display includes route information, boarding location, and alighting location, which the user can then review.

[1140] Input: Data to send to the terminal (optimal route, boarding location, alighting location)

[1141] Output: Information displayed on a smartphone or in-vehicle display device.

[1142] Step 8:

[1143] The autonomous vehicle's computer system receives calculation results from a server and controls the vehicle according to the optimal route. Stopping positions at each station are also automatically adjusted.

[1144] Input: Calculation results from the server (optimal route, boarding location, alighting location)

[1145] Output: Vehicle control instructions

[1146] Step 9:

[1147] Users can check detailed route information and pick-up / drop-off locations via their smartphone or in-vehicle display device, and actually pick up and drop off at those locations.

[1148] Input: Information displayed on a smartphone or in-vehicle display device.

[1149] Output: User movement behavior

[1150] The above outlines the processing steps of this system. Each step illustrates how the input information is processed and how it ultimately yields output that enables efficient user movement.

[1151] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[1152] The present invention is a system comprising means for inputting the departure and destination points, means for transmitting the input information to a server, means for calculating the optimal route, means for determining the boarding position and exit point, and means for displaying the determined information to the user, further incorporating an emotion engine that recognizes the user's emotions and adjusts the route accordingly. This system provides support for users to travel to their destinations in the shortest and most comfortable way possible using public transportation.

[1153] System Overview

[1154] This system calculates the optimal route, boarding positions and exits at each station, based on the departure and destination information entered by the user. It then further adjusts the route based on the user's emotional state and displays it to the user. Specifically, it consists of a terminal, a server, a map database, a train operation information database, and an emotion engine.

[1155] Program processing

[1156] 1. User input:

[1157] The user launches the application and enters their departure and destination locations. They can also optionally specify their mode of transport and desired arrival time.

[1158] The device recognizes the user's current emotional state via an emotion engine. This emotional state is analyzed using data collected through the smartphone's camera and microphone (such as facial expressions and voice).

[1159] 2. Data transmission:

[1160] The terminal sends the input information and the emotion data analyzed by the emotion engine to the server.

[1161] 3. Server processing:

[1162] Based on the information received by the server, it accesses the map database and the train operation information database, and calculates the optimal route considering the current train conditions.

[1163] Based on the calculated route, the server determines the optimal boarding position and exit from the platform and exit information of each station.

[1164] 4. Application of sentiment data:

[1165] The server adjusts the route based on the user's emotional state, obtained from the emotion engine. For example, if the user is stressed, it prioritizes less congested routes. On the other hand, if the user is relaxed, it suggests routes with good scenery or routes that pass through tourist attractions.

[1166] 5. Submit results:

[1167] The server sends optimized route information to the terminal. This information includes the optimal route, boarding location, exit location, and reasons for the recommendation based on the user's emotional state.

[1168] 6. User display:

[1169] The terminal displays route information received by the user in an easy-to-understand manner. Specifically, this includes the mode of transport used, the optimal boarding location, the optimal drop-off point, the optimal exit, and the reasons for route adjustments based on the user's emotional state.

[1170] Specific example

[1171] Examples of user stress

[1172] 1. The user launches the application and enters the destination: travel from "Station A" to "Station B".

[1173] 2. The device sends user input information and emotional data (stress level) to the server.

[1174] 3. The server calculates the optimal route from "Station A" to "Station B" and selects, for example, "Train C".

[1175] 4. The server prioritizes selecting less congested routes based on the user's stress level. It also determines the optimal boarding position (e.g., the last car) and exit (e.g., Exit 3) for "Train C".

[1176] 5. The server sends this information to the terminal, and the terminal displays it to the user:

[1177] Transportation: Train C

[1178] Boarding location: Last car

[1179] Disembarking station: Station B

[1180] Optimal exit: Exit 3

[1181] Reason for proposal: Less congested routes

[1182] Examples of users being relaxed

[1183] 1. The user launches the application and enters the destination: travel from "Station A" to "Station B".

[1184] 2. The device sends user input information and emotional data (relaxed state) to the server.

[1185] 3. The server calculates the optimal route from "Station A" to "Station B" and selects, for example, "Train D".

[1186] 4. The server prioritizes selecting routes with good scenery or those that pass through tourist spots, based on the user's relaxation state. It also determines the optimal boarding position (e.g., front of car 1) and exit (e.g., exit 1) for "Train D".

[1187] 5. The server sends this information to the terminal, and the terminal displays it to the user:

[1188] Transportation: Train D

[1189] Boarding location: Front of car 1

[1190] Disembarking station: Station B

[1191] Optimal exit: Exit 1

[1192] Reason for proposal: A route with good scenery

[1193] This system allows users to receive optimal route guidance tailored to their emotional state, resulting in a more comfortable travel experience. The introduction of an emotion engine enables the provision of personalized services that meet the individual needs of each user.

[1194] The following describes the processing flow.

[1195] Step 1:

[1196] The user launches the application and enters their departure and destination points. They can also optionally specify their mode of transport (train, bus, etc.) and desired arrival time.

[1197] Step 2:

[1198] The device activates an emotion engine to recognize the user's emotional state through their facial expressions and voice. This data is collected through the smartphone's camera and microphone.

[1199] Step 3:

[1200] The emotion engine analyzes collected facial expressions and voice data to determine the user's current emotional state (e.g., stress, relaxation, joy).

[1201] Step 4:

[1202] The terminal sends the entered departure point, destination, mode of transport, desired arrival time, and sentiment data analyzed by the sentiment engine to the server.

[1203] Step 5:

[1204] Based on the information received by the server, it accesses the map database and the traffic information database.

[1205] Step 6:

[1206] The server retrieves a list of available public transportation options (e.g., multiple train lines, bus routes) and evaluates each route.

[1207] Step 7:

[1208] The server calculates the optimal route, taking into account factors such as travel time, number of transfers, and train conditions.

[1209] Step 8:

[1210] The server determines the optimal boarding and exit locations for each route. This process utilizes platform and exit information for each station.

[1211] Step 9:

[1212] The server adjusts the route based on the user's emotional state, obtained from the emotion engine. For example, if the user is stressed, it prioritizes less congested routes; if the user is relaxed, it suggests routes with scenic views or routes that pass through tourist attractions.

[1213] Step 10:

[1214] The server sends optimized route information to the terminal. This information includes the optimal route, boarding location, exit location, and reasons for the recommendation based on the user's emotional state.

[1215] Step 11:

[1216] The terminal displays route information received by the user in an easy-to-understand manner. Specifically, this includes the mode of transport used, the optimal boarding location, the optimal drop-off point, the optimal exit, and the reasons for route adjustments based on the user's emotional state.

[1217] Step 12:

[1218] Based on the information displayed, the user boards public transport at the designated boarding location and uses the designated exit to reach their destination.

[1219] (Example 2)

[1220] Next, we will describe Example 2. 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."

[1221] Conventional route guidance systems only provide the optimal route when a user is using public transportation, and do not flexibly adjust the route according to the user's emotional state. As a result, users often face stressful situations and other emotional discomforts. This invention aims to provide more comfortable travel support that takes the user's emotional state into consideration.

[1222] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[1223] In this invention, the server includes means for inputting a departure point and destination; means for transmitting the inputted departure point and destination information to the server; means for calculating the optimal route based on the information received by the server; means for determining the boarding position and exit position based on the calculated optimal route; means for analyzing the user's emotional state; means for adjusting the route based on the analyzed emotional state; and means for transmitting the determined information to a terminal and displaying it to the user. This provides optimal route guidance according to the user's emotional state, enabling a comfortable journey.

[1224] "Departure point" refers to the point where the user begins their journey.

[1225] "Destination" refers to the point where the user is expected to complete their journey.

[1226] "Means" refers to the apparatus or method used to achieve a specific objective.

[1227] A "server" refers to a computer system used to process and manage information on a network.

[1228] A "terminal" refers to a device that a user directly interacts with, and its role is to input and display information.

[1229] The "optimal route" refers to the most efficient or comfortable travel route for a user under specific conditions.

[1230] "Boarding location" refers to the specific point where a user boards public transportation.

[1231] "Exit location" refers to the specific point where a user disembarks from public transportation.

[1232] "Emotional state" refers to the user's psychological and physiological state, which is analyzed from facial expressions, voice, and other factors.

[1233] An "emotion engine" refers to software or a device used to analyze a user's emotional state.

[1234] "Adjusting the pathway" refers to modifying or optimizing an existing pathway based on analyzed emotional states and other conditions.

[1235] A "map database" refers to a database containing geographical information, which is used for route calculations.

[1236] A "service information database" refers to a database containing information on the operating status of public transportation, providing real-time service information.

[1237] "Current operating status" refers to the most recent operating status of public transportation, including information such as delays and congestion.

[1238] This invention provides a system that offers the optimal route when a user travels using public transportation and adjusts the route based on the user's emotional state. The system includes means for inputting the departure and destination points, means for transmitting the input information to a server, means for calculating the optimal route, means for determining the boarding position and exit point, and means for displaying the determined information to the user. Furthermore, it incorporates an emotion engine that recognizes the user's emotions and adjusts the route accordingly.

[1239] System Configuration

[1240] This system consists of the following elements:

[1241] 1. Terminal:

[1242] It is a user-operated device that takes in information about the origin and destination and acquires sentiment data. A smartphone is a concrete example of this.

[1243] The device is equipped with a camera and microphone, which are used to capture the user's facial expressions and voice, and then analyzed by an emotion engine.

[1244] 2. Server:

[1245] This is a central system that receives information transmitted from terminals and performs data processing and route calculations. The server accesses map databases and operational information databases to obtain real-time operational information.

[1246] As specific software examples, we will use the "Google Maps API" and the "Transportation Information API".

[1247] 3. Emotional Engine:

[1248] This is software or a device for analyzing a user's emotional state. It utilizes an emotion analysis library built into a smartphone.

[1249] Based on the analyzed sentiment data, the server further adjusts the optimal route.

[1250] System operation example

[1251] Examples of users experiencing stress

[1252] 1. The user launches the app on their smartphone and enters the departure point "Station A" and the destination "Station B".

[1253] 2. The device captures the user's facial expressions and voice data, and performs emotion analysis to determine if the user is experiencing stress.

[1254] 3. The device sends the entered information and emotion data to the server.

[1255] 4. The server accesses the map database and the train operation information database to calculate the optimal route. For example, it finds the shortest route from "Station A" to "Station B" and selects "Train C".

[1256] 5. The server takes into account the user's stress level and determines less crowded routes, boarding positions (e.g., the last car), and optimal exits (e.g., Exit 3).

[1257] 6. The server sends the coordinated routing information to the terminal, and the terminal displays the following to the user:

[1258] Transportation: Train C

[1259] Boarding location: Last car

[1260] Disembarking station: Station B

[1261] Optimal exit: Exit 3

[1262] Reason for proposal: Less congested routes

[1263] Examples of relaxed users

[1264] 1. The user launches the app on their smartphone and enters the destination: "Station A" to "Station B".

[1265] 2. The device captures the user's facial expressions and voice data, and performs emotion analysis to determine that the user is relaxed.

[1266] 3. The device sends the entered information and emotion data to the server.

[1267] 4. The server accesses the map database and the train operation information database to calculate the optimal route. For example, it might determine the most comfortable route from "Station A" to "Station B" and select "Train D".

[1268] 5. The server takes into account the user's relaxed state and determines a route that includes scenic views and tourist spots, as well as the optimal boarding position (e.g., front of car 1) and exit (e.g., exit 1).

[1269] 6. The server sends the coordinated routing information to the terminal, and the terminal displays the following to the user:

[1270] Transportation: Train D

[1271] Boarding location: Front of car 1

[1272] Disembarking station: Station B

[1273] Optimal exit: Exit 1

[1274] Reason for proposal: A route with good scenery

[1275] Examples of prompt statements using generative AI models include the following:

[1276] The user launches the app and enters their travel time from Station A to Station B. During this process, the app performs an emotional analysis to determine whether the user is stressed or relaxed. Then, it suggests the optimal route, boarding location, and exit.

[1277] This system allows users to receive optimal route guidance tailored to their emotional state, resulting in a comfortable travel experience. The introduction of an emotion engine enables the provision of personalized services that meet the individual needs of each user.

[1278] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1279] Program processing steps and specific actions

[1280] Step 1: User Input

[1281] Input: The user launches the application and enters the departure point "Station A" and the destination "Station B". Optionally, they can also specify their desired arrival time and mode of transport.

[1282] Operation: The user operates a smartphone app. The smartphone's camera and microphone are used to capture the user's facial expressions and voice data in real time.

[1283] Data processing: The device inputs captured facial expressions and audio data into an emotion engine to analyze the user's emotional state.

[1284] Output: Origin, destination, options information, and analyzed sentiment data are generated.

[1285] Step 2: Data transmission

[1286] Input: Origin, destination, optional information, and sentiment data generated by the device.

[1287] Operation: The terminal generates this data as data packets and sends them to the server using the HTTP or HTTPS protocol.

[1288] Output: Data packets sent to the server.

[1289] Step 3: Server Processing

[1290] Input: Data packets received by the server from the terminal.

[1291] Operation: The server analyzes the data packets and extracts origin, destination, option information, and sentiment data. It then accesses a map database (e.g., Google Maps API) and a traffic information database to retrieve current traffic status.

[1292] Data processing: Based on the operational data acquired by the server, the optimal route from the origin to the destination is calculated using an algorithm.

[1293] Output: Optimal route information.

[1294] Step 4: Applying emotional data

[1295] Input: Optimal route information calculated by the server and user sentiment data.

[1296] Operation: The server further adjusts route information based on the user's emotional state (e.g., stressed, relaxed). For example, if the user is stressed, it will select a less congested route; if the user is relaxed, it will select a route with good scenery or one that passes by tourist attractions.

[1297] Data processing: Determine the adjusted route information, optimal boarding location, and optimal exit location.

[1298] Output: Adjusted route information, boarding location, exit location, and reason for recommendation.

[1299] Step 5: Submit Results

[1300] Input: Server-adjusted optimal route information, boarding location, exit location, and reason for recommendation.

[1301] Operation: The server generates this information as a data packet and sends it to the terminal.

[1302] Output: Data packets sent to the terminal.

[1303] Step 6: User Display

[1304] Input: Data packets received by the terminal from the server.

[1305] Operation: The terminal analyzes data packets and displays the mode of transport to be used, the optimal boarding location, the optimal drop-off location, the optimal exit, and the reason for the recommendation on the user interface.

[1306] Output: Optimal route information displayed to the user.

[1307] This program's processing allows users to receive optimal route guidance tailored to their emotional state, enabling a comfortable journey.

[1308] (Application Example 2)

[1309] Next, we will explain application example 2. In the following explanation, 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."

[1310] Conventional travel route guidance systems provide the optimal route based on input of the origin and destination, but they lacked personalization of service by not considering the user's emotional state. Furthermore, they were unable to provide the optimal route based on whether the passenger was stressed or relaxed. As a result, they failed to deliver a comfortable travel experience for users.

[1311] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for inputting the departure point and destination; means for transmitting the input departure point and destination information to the server; means for calculating the optimal route based on the information received by the server; means for determining the boarding position and exit position based on the calculated optimal route; means for analyzing the passenger's emotional state and transmitting the data to the server; means for adjusting the route based on the emotional state; means for transmitting the determined information to a terminal and displaying it to the passenger; means for the terminal to display the reason for the route adjustment based on the passenger's emotional state; and means for recognizing the passenger's emotional state using a mobile terminal, in-vehicle terminal, or camera. This makes it possible to provide a personalized and optimal travel route according to the user's emotional state.

[1312] The "starting point" is the point where the journey begins.

[1313] A "destination" is the final point of arrival at a destination.

[1314] A "server" is a computer system that receives, transmits, processes, and stores data over a network.

[1315] A "route" is the path taken to travel from a starting point to a destination.

[1316] "Boarding position" refers to the optimal location for passengers to board a mode of transportation.

[1317] An "exit" is a place where passengers disembark from a mode of transportation.

[1318] "Emotional state" refers to the emotional state a passenger is experiencing, such as stress or joy.

[1319] A "mobile device" refers to a portable computing device such as a smartphone or tablet.

[1320] An "in-vehicle terminal" is an electronic device installed in a car that assists with driving and navigation.

[1321] A "camera" is an optical device used to capture images and videos.

[1322] An "emotion engine" is a system that uses devices such as cameras and microphones to identify a user's emotional state and analyze that information.

[1323] A "terminal" refers to a device or equipment on which a user inputs or displays information.

[1324] This invention is a system to help passengers comfortably reach their destination using autonomous vehicles. The system uses the following hardware and software components.

[1325] Hardware configuration

[1326] 1. Mobile devices:

[1327] These are devices, such as smartphones and tablets, that passengers use to input their departure and destination locations.

[1328] 2. In-vehicle terminals:

[1329] These are touch panels or displays installed in autonomous vehicles, used by passengers to input their departure and destination locations and to confirm information.

[1330] 3. Camera:

[1331] This device is installed inside autonomous vehicles to capture passengers' facial expressions and movements and analyze their emotional state.

[1332] Software Configuration

[1333] 1. Emotional Engine:

[1334] This software module analyzes facial expressions and voice data to determine passengers' emotional states in real time. It utilizes OpenCV and common emotion analysis libraries.

[1335] 2. Path Calculation Module:

[1336] It operates on a server and calculates the optimal route based on the received origin and destination data. This calculation utilizes a map database and a traffic information database.

[1337] 3. Server:

[1338] This system receives, transmits, processes, and stores data over a network. The server includes an emotion engine that analyzes facial expressions and voice data, and a route calculation module that uses map data and traffic information.

[1339] Data processing and data calculation

[1340] Camera data:

[1341] The system collects passengers' facial expressions and voice data through cameras and microphones and transmits it to a server in real time. The emotion engine analyzes this data to determine their emotional state (stress, relaxation, etc.).

[1342] Path calculation:

[1343] The server accesses map and traffic information databases to calculate the optimal route from the origin to the destination. Furthermore, it adjusts the route based on the passenger's emotional state, as determined by the emotion engine. For example, if a passenger is stressed, it selects a less congested route; if they are relaxed, it selects a route with good scenery.

[1344] Information transmission and display:

[1345] Once the optimal route information is determined, the server transmits this information to the in-vehicle terminal and displays it to the passengers on the screen. The displayed information includes the optimal route, boarding location, alighting location, exit, and reasons for route adjustments based on emotional state.

[1346] Specific example

[1347] 1. The passenger enters their travel destination from "Station A" to "Station B" using the onboard terminal.

[1348] 2. In-car cameras capture passengers' facial expressions, which are then analyzed by an emotion engine.

[1349] 3. The emotion engine determines that the passenger is stressed and sends data to the server.

[1350] 4. The server calculates the least congested route and transmits the calculated route to the in-vehicle terminal.

[1351] 5. The in-vehicle terminal displays the following information to passengers:

[1352] Transportation: Train C

[1353] Boarding location: Last car

[1354] Disembarking station: Station B

[1355] Optimal exit: Exit 3

[1356] Reason for proposal: Because it is less crowded.

[1357] Example of a prompt

[1358] "Input user emotion data and departure / destination information to recommend the optimal travel route. If the user is stressed, recommend a less congested route; if they are relaxed, recommend a route with good scenery."

[1359] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1360] Step 1:

[1361] The user launches the application on the in-vehicle terminal and enters the departure and destination locations. The information entered includes the departure location, destination, and optionally, the desired arrival time. The entered data is stored on the in-vehicle terminal. Input: Departure location, destination, desired arrival time. Output: Input information stored on the in-vehicle terminal.

[1362] Step 2:

[1363] The device's camera and microphone are used to capture passengers' facial expressions and voices in real time. An emotion engine analyzes this data to determine the user's emotional state (e.g., stress, relaxation). Input: Captured facial and voice data. Output: Analyzed emotional state data.

[1364] Step 3:

[1365] The device sends the user's input origin, destination, and emotional state data analyzed by the emotion engine to the server. Input: Origin, destination, and emotional state data. Output: Data sent to the server.

[1366] Step 4:

[1367] The server calculates the optimal route by accessing a map database and a train operation information database based on the origin, destination, and sentiment status data it receives. Furthermore, platform and exit information for each station is also considered. Input: Origin, destination, map data, train operation information, sentiment status data. Output: Optimal route information.

[1368] Step 5:

[1369] The server adjusts the route based on the user's emotional state. For example, if the user is stressed, it will choose a less congested route; if they are relaxed, it will choose a route with good scenery. Input: Optimal route information, emotional state. Output: Adjusted route information.

[1370] Step 6:

[1371] The server sends optimized route information to the terminal. This information includes the route, boarding location, exit location, and reasons based on emotional state. Input: Optimized route information. Output: Route information sent to the terminal.

[1372] Step 7:

[1373] The terminal displays route information received by the passenger in an easy-to-understand manner. The displayed information includes the mode of transport, optimal boarding location, drop-off point, optimal exit, and reasons for route adjustments based on emotional state. Input: Received route information. Output: Displayed route information.

[1374] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1375] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1376] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[1377] [Fourth Embodiment]

[1378] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[1379] As shown in Figure 7, the 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.

[1380] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1381] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[1382] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[1383] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[1384] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[1385] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive 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 robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[1386] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[1387] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[1388] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1389] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[1390] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1391] This invention is a system that provides route guidance, including the optimal boarding position and exit, to ensure the shortest possible travel time from the point of origin to the destination using public transportation. The following describes the program processing of this system and a specific example based on it in natural language.

[1392] System Overview

[1393] This system calculates and displays the optimal route, boarding position at each station, and exit based on the departure and destination information entered by the user. Specifically, it consists of a terminal, a server, and a map database and a train operation information database.

[1394] Program processing

[1395] 1. User input:

[1396] The user launches the application and enters their departure and destination points. They can also specify their mode of transport (train, bus, etc.) and desired arrival time.

[1397] 2. Data transmission:

[1398] The terminal sends the entered information (departure point, destination, mode of transport, desired arrival time) to the server.

[1399] 3. Server processing:

[1400] Based on the information received by the server, it accesses the map database and the train operation information database, and calculates the optimal route considering the current train conditions.

[1401] Based on the calculated route, the server determines the optimal boarding position and exit from the platform and exit information of each station.

[1402] 4. Submit results:

[1403] The server sends the calculation results (optimal route, boarding location, exit) to the terminal.

[1404] 5. User display:

[1405] The terminal displays the route information it has received to the user.

[1406] Specific example

[1407] 1. The user launches the application, searches for a route from "Station A" to "Station B," and enters the departure point "Station A" and the destination "Station B."

[1408] 2. The terminal converts the user's input information into "Departure point: Station A, Destination: Station B, Mode of transport: Train" and sends it to the server.

[1409] 3. The server calculates the optimal route from "Station A" to "Station B" based on the map database and train operation information. For example, it might select "Train C" as the optimal route.

[1410] 4. The server retrieves platform information for each station from Station A to Station B of "Train C" and determines the optimal boarding position (e.g., front of car 1) and exit (e.g., Exit 1).

[1411] 5. The server sends this information to the terminal as "Means of transport: Train C, Boarding location: Front of car 1, Disembarking station: Station B, Exit: Exit 1".

[1412] 6. The device displays this information on the user's screen:

[1413] Transportation: Train C

[1414] Boarding location: Front of car 1

[1415] Disembarking station: Station B

[1416] Optimal exit: Exit 1

[1417] In this way, users can receive specific instructions to efficiently travel to their destination. This system allows users to improve their travel efficiency and reach their destination in the shortest possible time.

[1418] The key feature of this system is that it calculates routes considering real-time train operation status, and then combines this with platform and exit information for each station to provide the optimal boarding location and exit. This allows users not only to reach their destination but also to utilize the most efficient means of transportation.

[1419] The following describes the processing flow.

[1420] Step 1:

[1421] The user launches the application and enters their departure and destination points. They can also optionally specify their mode of transport (train, bus, etc.) and desired arrival time.

[1422] Step 2:

[1423] The terminal receives input information from the user and converts the departure point, destination, selected mode of transport, and desired arrival time into the format required for subsequent processing.

[1424] Step 3:

[1425] The device sends the converted information to the server. The information sent includes the departure point, destination, mode of transport, and desired arrival time.

[1426] Step 4:

[1427] Based on the information received by the server, it accesses the map database and the traffic information database.

[1428] Step 5:

[1429] The server retrieves a list of available public transportation options (e.g., multiple train lines, bus routes) and evaluates each route.

[1430] Step 6:

[1431] The server calculates the optimal route, taking into account factors such as travel time, number of transfers, and train conditions.

[1432] Step 7:

[1433] The server determines the optimal boarding and exit locations for each route. This process utilizes platform and exit information for each station.

[1434] Step 8:

[1435] The server sends the calculation results to the terminal. The transmitted information includes the optimal route, boarding location, and exit location.

[1436] Step 9:

[1437] The terminal displays route information received by the user in an easy-to-understand manner. Specific details include the mode of transport, optimal boarding location, drop-off point, and optimal exit.

[1438] Step 10:

[1439] Based on the information displayed, the user boards public transport at the designated boarding location and uses the designated exit to reach their destination.

[1440] (Example 1)

[1441] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1442] When using modern public transportation, especially in congested urban areas, simply knowing the route from origin to destination is insufficient for efficient travel. Users need to know the optimal boarding location and the best exit at each station, but manually researching this is difficult, time-consuming, and cumbersome. Furthermore, route guidance that takes real-time train operation status into account is necessary, but conventional systems have been unable to effectively implement this. As a result, user travel efficiency has decreased, and this has become a source of stress.

[1443] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[1444] In this invention, the server includes means for the user to input a departure point and destination; means for the terminal to transmit the inputted departure point and destination information to the server; means for the server to calculate the optimal route using a map database and an operation information database based on the received information; means for the server to determine the boarding position and exit position at each station based on the calculated optimal route; and means for transmitting the determined information to the terminal and displaying it to the user. As a result, the user can find out the optimal route, optimal boarding position, and exit from the departure point to the destination in real time, enabling them to use public transportation efficiently.

[1445] "User input" refers to the act of a user entering information such as their departure point and destination into a terminal.

[1446] A "terminal" is a device used by a user to input information or display received information. Examples include smartphones and personal computers.

[1447] A "server" is a central system that receives information sent from terminals, accesses various databases to calculate the optimal route, and sends the results back to the terminals.

[1448] A "map database" is a database that stores detailed information such as geographical location information and train stations.

[1449] A "transportation information database" is a database that stores real-time data such as the operating schedules and delay information of public transportation.

[1450] The "optimal route" is the route that allows the user to reach their destination in the shortest time or with the fewest transfers.

[1451] "Boarding position" refers to the recommended location within a train or bus for users to reach their destination efficiently.

[1452] An "exit" refers to the exit of a station or bus stop that a user should use when they reach their destination.

[1453] "Platform information for each station" refers to information about the layout of station platforms and which trains stop at specific platforms.

[1454] "Real-time" means that the information is current as of the present time and always reflects the latest status.

[1455] This invention provides a system that offers optimal route guidance for users to travel from their starting point to their destination using public transportation in the shortest possible time. The system includes the steps of user input, data transmission, server processing, result transmission, and user display. The following describes embodiments of this system, specifying the concrete hardware and software.

[1456] Hardware and software used

[1457] Terminal: A user device such as a smartphone or PC sends the entered information to the server and displays the calculation results.

[1458] Server: A central device that accesses the database and performs route calculations. This can be a cloud server or an on-premises server.

[1459] Map database: A database that stores geographical location information and station information. For example, a GIS (Geographic Information System) is used.

[1460] Transportation Information Database: A database that stores real-time data such as public transportation schedules and delay information. Real-time data is retrieved via API.

[1461] System Operation Overview

[1462] 1. User input:

[1463] The user launches the application and enters their departure and destination points. The user can also specify their mode of transport and desired arrival time.

[1464] 2. Data transmission:

[1465] The terminal sends the entered information to the server. Protocols such as HTTP requests are used for communication.

[1466] 3. Server processing:

[1467] Based on the information received by the server, it accesses the map database and the train operation information database to calculate the optimal route. The server also considers platform and exit information for each station to determine the optimal boarding location and exit.

[1468] 4. Submit results:

[1469] The server sends the calculation results to the terminal. The results are sent in a standard format such as JSON.

[1470] 5. User display:

[1471] The device analyzes the data it receives and displays it in a user-friendly format.

[1472] Specific example

[1473] Consider a scenario where a user launches the application and searches for a route from "Station A" to "Station B". In this case, the user enters the departure point "Station A" and the destination "Station B", and taps the search button. The device converts the entered information into "Departure point: Station A, Destination: Station B, Mode of transport: Train" and sends it to the server.

[1474] The server calculates the optimal route from "Station A" to "Station B" based on a map database and train operation information. For example, it might select "Train C". It also obtains platform information for each station from "Station A" to "Station B" and determines the optimal boarding position (e.g., front of car 1) and exit (e.g., Exit 1).

[1475] The server sends this information to the terminal as "Transportation: Train C, Boarding location: Front of car 1, Disembarking station: Station B, Exit: Exit 1". The terminal displays this information on the user's screen.

[1476] Prompt example

[1477] Examples of prompts to input into a generative AI model include the following:

[1478] "Please specify the departure and destination stations, and tell me which train to take, which car and which door to use, and which exit to use at the destination station. For example, let's say the departure station is 'Station A' and the destination is 'Station B'."

[1479] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1480] Step 1:

[1481] The user enters the departure point and destination.

[1482] The user launches the application and enters their departure and destination locations into a form. Optionally, they can also enter their desired arrival time and mode of transportation (train, bus, etc.).

[1483] Input: Departure point, destination, desired arrival time, mode of transport

[1484] Output: User input data

[1485] Specific operation: The user enters "Station A" as the departure point and "Station B" as the destination into the text boxes and taps the "Search" button. This input information is stored in a variable within the program.

[1486] Step 2:

[1487] The terminal sends data to the server.

[1488] The terminal sends the information entered by the user to the server. HTTP POST requests are used for communication.

[1489] Input: User input data

[1490] Output: Request data to the server

[1491] Specific operation: The terminal converts the input data into JSON format and sends a "POST / find_route" request to the server. The request data will look something like this: { 'from': 'Station A', 'to': 'Station B', 'arrive_by': '10:00', 'mode': 'Train'}.

[1492] Step 3:

[1493] The server receives the information and calculates the optimal path.

[1494] The server analyzes the received data and accesses map and traffic information databases to calculate the optimal route. Dijkstra's algorithm and the A algorithm are used for route calculation.

[1495] Input: Request data, map data, service information

[1496] Output: Calculated optimal path data

[1497] Specific operation: The server parses the received JSON data and retrieves the coordinate information of the departure point "Station A" and the destination "Station B" from the map database. At the same time, it checks the current train status from the train operation information database and calculates the most efficient route. For example, a route using "Train C" is selected.

[1498] Step 4:

[1499] The server determines the optimal boarding location and exit.

[1500] Based on the calculated optimal route, the server determines the best boarding position and exit from each station's platform and exit information.

[1501] Input: Optimal route data, home information, exit information

[1502] Output: Boarding location and exit information

[1503] Specific operation: The server obtains platform information for each station from Station A to Station B of "Train C," and determines, for example, that the front of Car 1 is the optimal boarding position and Exit 1 is the optimal exit.

[1504] Step 5:

[1505] The server sends the results to the terminal.

[1506] The server sends the calculation results (optimal route, boarding location, exit) to the terminal. An HTTP POST request is used again for communication.

[1507] Input: Boarding location and exit information

[1508] Output: Response data

[1509] Specific operation: The server formats the calculation result into JSON format and sends it to the terminal as a "POST / show_route" request. For example, the response data will be "{ 'route': 'Train C', 'car_position': 'Front of car 1', 'exit': 'Exit 1'}".

[1510] Step 6:

[1511] Display the results on the user's terminal.

[1512] The terminal analyzes the data received from the server and displays it in a format that is easy for the user to understand.

[1513] Input: Response data

[1514] Output: Route information displayed on the user screen

[1515] Specific operation: The application on the device parses the received JSON data and displays specific route, boarding location, and exit information on the user interface. Information such as "Means of transport: Train C", "Boarding location: Front of car 1", "Disembarking station: Station B", and "Optimal exit: Exit 1" is laid out on the screen.

[1516] (Application Example 1)

[1517] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1518] As autonomous vehicles become more widespread, they need to be able to select the appropriate route for users to travel efficiently and quickly from their starting point to their destination. However, current autonomous driving technology struggles to calculate and provide optimal pick-up and drop-off locations to users. Furthermore, there are limited means of optimizing routes while considering real-time operating conditions. As a result, users end up wasting unnecessary time during their journey from departure to destination.

[1519] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[1520] In this invention, the server includes means for inputting a departure point and a destination; means for transmitting the inputted departure point and destination information to the server; means for calculating the optimal route based on the information received by the server; means for determining the boarding and exit positions based on the calculated optimal route; means for transmitting the determined information to a terminal and displaying it to the user; means for transmitting the calculation results to the computer system of the autonomous vehicle, which in turn controls the vehicle according to the optimal route; and means for the user to confirm detailed route information and boarding / alighting positions via a smartphone or in-vehicle display device. This enables the autonomous vehicle to select the optimal route in real time and travel efficiently from the departure point to the destination.

[1521] The "starting point" is the point where the user begins their journey.

[1522] The "destination" is the point where the user is expected to finish their journey.

[1523] A "terminal" is a device used by users to input information about their departure point and destination and receive route guidance.

[1524] A "server" is a central processing unit that receives information sent from a terminal, calculates the optimal route, and returns the result.

[1525] The "optimal route" is the route chosen to minimize travel time from the starting point to the destination.

[1526] The "boarding position" is the optimal position for a user to board an autonomous vehicle.

[1527] The "exit location" is the most suitable position for a user to disembark from the autonomous vehicle when they reach their destination.

[1528] An "autonomous vehicle" is a vehicle that can travel on the road without the intervention of a human driver.

[1529] A "computer system" is a system that controls the functions of an autonomous vehicle and manages the vehicle's movement according to a calculated path.

[1530] A "smartphone" is a portable, multi-functional electronic device used by users to input and display information.

[1531] An "in-vehicle display device" is a device installed inside an autonomous vehicle that displays route information to the user.

[1532] "Real-time service status" refers to information showing current traffic conditions and the operating status of trains and buses.

[1533] "Facility information for each station" refers to information that shows the specific location of platforms and exits for each station.

[1534] "Detailed route information" refers to specific information necessary for users to travel efficiently, such as boarding and alighting locations and travel time.

[1535] This invention is a system that provides optimal route guidance by an autonomous vehicle, based on the user's specified origin and destination. The system consists of a terminal, a server, the autonomous vehicle's computer system, and a map database and a traffic information database.

[1536] Program Overview

[1537] The system program uses the following hardware and software:

[1538] Hardware:

[1539] Smartphone (e.g., Android or iOS)

[1540] Onboard computers for autonomous vehicles (e.g., NVIDIA Drive Platform)

[1541] Server (Central Processing Unit)

[1542] software:

[1543] Map database (e.g., Google Maps API)

[1544] Operation information database (e.g., API for public transportation operation information)

[1545] Programming languages ​​(e.g., Python, JavaScript)

[1546] Program Processing Overview

[1547] 1. The user enters the departure and destination locations:

[1548] Users enter their departure and destination points using a smartphone app or a touchscreen in the autonomous vehicle. They can also enter their desired arrival time and mode of transportation as needed.

[1549] 2. Sending information to the server:

[1550] The terminal sends the entered information to the server. The server then receives the origin, destination, and other condition information.

[1551] 3. Calculation of the optimal path:

[1552] The server accesses the map database and the traffic information database to calculate the optimal route based on real-time traffic conditions.

[1553] 4. Determining boarding and alighting locations:

[1554] Based on the calculated route, the server retrieves facility information for each station and determines the optimal boarding and alighting locations.

[1555] 5. Sending and displaying calculation results:

[1556] The server sends the calculation results to the terminal, and the user can check detailed route information and boarding / alighting locations on their smartphone or in-vehicle display device.

[1557] 6. Vehicle control by computer system:

[1558] The autonomous vehicle's computer system receives calculation results from a server and controls the vehicle according to the optimal route. This ensures that the boarding and alighting sequences at each station are executed efficiently.

[1559] Specific example

[1560] For example, suppose a user uses a smartphone app to input their departure point "Station A" and destination "Station B". This information is sent from the device to a server, which then accesses a map database and a traffic information database to calculate the optimal route.

[1561] The server selects the optimal route from "Station A" to "Station B" and retrieves platform and exit information for each station. Based on the calculation, it determines the optimal boarding position (e.g., near the front door) and alighting position (e.g., Exit 2) and sends this information back to the terminal. The user can then confirm this information on their smartphone or in-vehicle display device, allowing them to board the vehicle at the optimal position and alight at the designated exit.

[1562] Examples of prompts for generative AI models

[1563] "Departure point: 'Station A', Destination: 'Station B', Mode of transport: 'Autonomous vehicle', Calculate and display the optimal route and pick-up / drop-off locations."

[1564] The above is an overview of specific embodiments for carrying out this invention. This system enables users to travel efficiently and quickly, minimizing travel time from the point of origin to the destination.

[1565] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1566] Step 1:

[1567] The user enters their departure and destination points using a smartphone app or in-car touchscreen. This may also include desired arrival time and mode of transport. The entered information is formatted as data based on the input format of the user's device.

[1568] Input: Departure point, destination, desired arrival time, mode of transport

[1569] Output: Input information converted into a data format for transmission to the server.

[1570] Step 2:

[1571] The terminal sends the formatted data to the server via wireless communication. This process is carried out while verifying the integrity of the data. If the data is not transmitted correctly, a retransmission process is performed.

[1572] Input: Formatted data (departure point, destination, desired arrival time, mode of transport)

[1573] Output: Confirmation message indicating that transmission to the server is complete.

[1574] Step 3:

[1575] Based on the information received by the server, it accesses the map database and the operation information database to obtain real-time operation status. It uses the database API to query the necessary information and retrieve the current operation status.

[1576] Input: Departure point, destination, desired arrival time, mode of transport

[1577] Output: Current service status, traffic information

[1578] Step 4:

[1579] The server calculates the optimal route based on the information it acquires. The calculation algorithm combines real-time traffic conditions, map information, and desired arrival time to find the shortest route.

[1580] Input: Current service status, traffic information, map information

[1581] Output: Optimal route information

[1582] Step 5:

[1583] Based on the calculated optimal route, the server retrieves facility information for each station and determines the optimal boarding and alighting locations. It also considers platform and exit information for each station to select the most efficient location.

[1584] Input: Optimal route information, facility information for each station

[1585] Output: boarding location, alighting location

[1586] Step 6:

[1587] The server sends the determined information (optimal route, boarding location, and alighting location) to the terminal. The transmitted information is formatted in a way that can be displayed on the user's terminal screen.

[1588] Input: Optimal route, boarding location, alighting location

[1589] Output: Data to send to the terminal

[1590] Step 7:

[1591] The terminal displays the received information on the user's smartphone or in-vehicle display device. This display includes route information, boarding location, and alighting location, which the user can then review.

[1592] Input: Data to send to the terminal (optimal route, boarding location, alighting location)

[1593] Output: Information displayed on a smartphone or in-vehicle display device.

[1594] Step 8:

[1595] The autonomous vehicle's computer system receives calculation results from a server and controls the vehicle according to the optimal route. Stopping positions at each station are also automatically adjusted.

[1596] Input: Calculation results from the server (optimal route, boarding location, alighting location)

[1597] Output: Vehicle control instructions

[1598] Step 9:

[1599] Users can check detailed route information and pick-up / drop-off locations via their smartphone or in-vehicle display device, and actually pick up and drop off at those locations.

[1600] Input: Information displayed on a smartphone or in-vehicle display device.

[1601] Output: User movement behavior

[1602] The above outlines the processing steps of this system. Each step illustrates how the input information is processed and how it ultimately yields output that enables efficient user movement.

[1603] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[1604] The present invention is a system comprising means for inputting the departure and destination points, means for transmitting the input information to a server, means for calculating the optimal route, means for determining the boarding position and exit point, and means for displaying the determined information to the user, further incorporating an emotion engine that recognizes the user's emotions and adjusts the route accordingly. This system provides support for users to travel to their destinations in the shortest and most comfortable way possible using public transportation.

[1605] System Overview

[1606] This system calculates the optimal route, boarding positions and exits at each station, based on the departure and destination information entered by the user. It then further adjusts the route based on the user's emotional state and displays it to the user. Specifically, it consists of a terminal, a server, a map database, a train operation information database, and an emotion engine.

[1607] Program processing

[1608] 1. User input:

[1609] The user launches the application and enters their departure and destination locations. They can also optionally specify their mode of transport and desired arrival time.

[1610] The device recognizes the user's current emotional state via an emotion engine. This emotional state is analyzed using data collected through the smartphone's camera and microphone (such as facial expressions and voice).

[1611] 2. Data transmission:

[1612] The terminal sends the input information and the emotion data analyzed by the emotion engine to the server.

[1613] 3. Server processing:

[1614] Based on the information received by the server, it accesses the map database and the train operation information database, and calculates the optimal route considering the current train conditions.

[1615] Based on the calculated route, the server determines the optimal boarding position and exit from the platform and exit information of each station.

[1616] 4. Application of sentiment data:

[1617] The server adjusts the route based on the user's emotional state, obtained from the emotion engine. For example, if the user is stressed, it prioritizes less congested routes. On the other hand, if the user is relaxed, it suggests routes with good scenery or routes that pass through tourist attractions.

[1618] 5. Submit results:

[1619] The server sends optimized route information to the terminal. This information includes the optimal route, boarding location, exit location, and reasons for the recommendation based on the user's emotional state.

[1620] 6. User display:

[1621] The terminal displays route information received by the user in an easy-to-understand manner. Specifically, this includes the mode of transport used, the optimal boarding location, the optimal drop-off point, the optimal exit, and the reasons for route adjustments based on the user's emotional state.

[1622] Specific example

[1623] Examples of user stress

[1624] 1. The user launches the application and enters the destination: travel from "Station A" to "Station B".

[1625] 2. The device sends user input information and emotional data (stress level) to the server.

[1626] 3. The server calculates the optimal route from "Station A" to "Station B" and selects, for example, "Train C".

[1627] 4. The server prioritizes selecting less congested routes based on the user's stress level. It also determines the optimal boarding position (e.g., the last car) and exit (e.g., Exit 3) for "Train C".

[1628] 5. The server sends this information to the terminal, and the terminal displays it to the user:

[1629] Transportation: Train C

[1630] Boarding location: Last car

[1631] Disembarking station: Station B

[1632] Optimal exit: Exit 3

[1633] Reason for proposal: Less congested routes

[1634] Examples of users being relaxed

[1635] 1. The user launches the application and enters the destination: travel from "Station A" to "Station B".

[1636] 2. The device sends user input information and emotional data (relaxed state) to the server.

[1637] 3. The server calculates the optimal route from "Station A" to "Station B" and selects, for example, "Train D".

[1638] 4. The server prioritizes selecting routes with good scenery or those that pass through tourist spots, based on the user's relaxation state. It also determines the optimal boarding position (e.g., front of car 1) and exit (e.g., exit 1) for "Train D".

[1639] 5. The server sends this information to the terminal, and the terminal displays it to the user:

[1640] Transportation: Train D

[1641] Boarding location: Front of car 1

[1642] Disembarking station: Station B

[1643] Optimal exit: Exit 1

[1644] Reason for proposal: A route with good scenery

[1645] This system allows users to receive optimal route guidance tailored to their emotional state, resulting in a more comfortable travel experience. The introduction of an emotion engine enables the provision of personalized services that meet the individual needs of each user.

[1646] The following describes the processing flow.

[1647] Step 1:

[1648] The user launches the application and enters their departure and destination points. They can also optionally specify their mode of transport (train, bus, etc.) and desired arrival time.

[1649] Step 2:

[1650] The device activates an emotion engine to recognize the user's emotional state through their facial expressions and voice. This data is collected through the smartphone's camera and microphone.

[1651] Step 3:

[1652] The emotion engine analyzes collected facial expressions and voice data to determine the user's current emotional state (e.g., stress, relaxation, joy).

[1653] Step 4:

[1654] The terminal sends the entered departure point, destination, mode of transport, desired arrival time, and sentiment data analyzed by the sentiment engine to the server.

[1655] Step 5:

[1656] Based on the information received by the server, it accesses the map database and the traffic information database.

[1657] Step 6:

[1658] The server retrieves a list of available public transportation options (e.g., multiple train lines, bus routes) and evaluates each route.

[1659] Step 7:

[1660] The server calculates the optimal route, taking into account factors such as travel time, number of transfers, and train conditions.

[1661] Step 8:

[1662] The server determines the optimal boarding and exit locations for each route. This process utilizes platform and exit information for each station.

[1663] Step 9:

[1664] The server adjusts the route based on the user's emotional state, obtained from the emotion engine. For example, if the user is stressed, it prioritizes less congested routes; if the user is relaxed, it suggests routes with scenic views or routes that pass through tourist attractions.

[1665] Step 10:

[1666] The server sends optimized route information to the terminal. This information includes the optimal route, boarding location, exit location, and reasons for the recommendation based on the user's emotional state.

[1667] Step 11:

[1668] The terminal displays route information received by the user in an easy-to-understand manner. Specifically, this includes the mode of transport used, the optimal boarding location, the optimal drop-off point, the optimal exit, and the reasons for route adjustments based on the user's emotional state.

[1669] Step 12:

[1670] Based on the information displayed, the user boards public transport at the designated boarding location and uses the designated exit to reach their destination.

[1671] (Example 2)

[1672] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1673] Conventional route guidance systems only provide the optimal route when a user is using public transportation, and do not flexibly adjust the route according to the user's emotional state. As a result, users often face stressful situations and other emotional discomforts. This invention aims to provide more comfortable travel support that takes the user's emotional state into consideration.

[1674] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[1675] In this invention, the server includes means for inputting a departure point and destination; means for transmitting the inputted departure point and destination information to the server; means for calculating the optimal route based on the information received by the server; means for determining the boarding position and exit position based on the calculated optimal route; means for analyzing the user's emotional state; means for adjusting the route based on the analyzed emotional state; and means for transmitting the determined information to a terminal and displaying it to the user. This provides optimal route guidance according to the user's emotional state, enabling a comfortable journey.

[1676] "Departure point" refers to the point where the user begins their journey.

[1677] "Destination" refers to the point where the user is expected to complete their journey.

[1678] "Means" refers to the apparatus or method used to achieve a specific objective.

[1679] A "server" refers to a computer system used to process and manage information on a network.

[1680] A "terminal" refers to a device that a user directly interacts with, and its role is to input and display information.

[1681] The "optimal route" refers to the most efficient or comfortable travel route for a user under specific conditions.

[1682] "Boarding location" refers to the specific point where a user boards public transportation.

[1683] "Exit location" refers to the specific point where a user disembarks from public transportation.

[1684] "Emotional state" refers to the user's psychological and physiological state, which is analyzed from facial expressions, voice, and other factors.

[1685] An "emotion engine" refers to software or a device used to analyze a user's emotional state.

[1686] "Adjusting the pathway" refers to modifying or optimizing an existing pathway based on analyzed emotional states and other conditions.

[1687] A "map database" refers to a database containing geographical information, which is used for route calculations.

[1688] A "service information database" refers to a database containing information on the operating status of public transportation, providing real-time service information.

[1689] "Current operating status" refers to the most recent operating status of public transportation, including information such as delays and congestion.

[1690] This invention provides a system that offers the optimal route when a user travels using public transportation and adjusts the route based on the user's emotional state. The system includes means for inputting the departure and destination points, means for transmitting the input information to a server, means for calculating the optimal route, means for determining the boarding position and exit point, and means for displaying the determined information to the user. Furthermore, it incorporates an emotion engine that recognizes the user's emotions and adjusts the route accordingly.

[1691] System Configuration

[1692] This system consists of the following elements:

[1693] 1. Terminal:

[1694] It is a user-operated device that takes in information about the origin and destination and acquires sentiment data. A smartphone is a concrete example of this.

[1695] The device is equipped with a camera and microphone, which are used to capture the user's facial expressions and voice, and then analyzed by an emotion engine.

[1696] 2. Server:

[1697] This is a central system that receives information transmitted from terminals and performs data processing and route calculations. The server accesses map databases and operational information databases to obtain real-time operational information.

[1698] As specific software examples, we will use the "Google Maps API" and the "Transportation Information API".

[1699] 3. Emotional Engine:

[1700] This is software or a device for analyzing a user's emotional state. It utilizes an emotion analysis library built into a smartphone.

[1701] Based on the analyzed sentiment data, the server further adjusts the optimal route.

[1702] System operation example

[1703] Examples of users experiencing stress

[1704] 1. The user launches the app on their smartphone and enters the departure point "Station A" and the destination "Station B".

[1705] 2. The device captures the user's facial expressions and voice data, and performs emotion analysis to determine if the user is experiencing stress.

[1706] 3. The device sends the entered information and emotion data to the server.

[1707] 4. The server accesses the map database and the train operation information database to calculate the optimal route. For example, it finds the shortest route from "Station A" to "Station B" and selects "Train C".

[1708] 5. The server takes into account the user's stress level and determines less crowded routes, boarding positions (e.g., the last car), and optimal exits (e.g., Exit 3).

[1709] 6. The server sends the coordinated routing information to the terminal, and the terminal displays the following to the user:

[1710] Transportation: Train C

[1711] Boarding location: Last car

[1712] Disembarking station: Station B

[1713] Optimal exit: Exit 3

[1714] Reason for proposal: Less congested routes

[1715] Examples of relaxed users

[1716] 1. The user launches the app on their smartphone and enters the destination: "Station A" to "Station B".

[1717] 2. The device captures the user's facial expressions and voice data, and performs emotion analysis to determine that the user is relaxed.

[1718] 3. The device sends the entered information and emotion data to the server.

[1719] 4. The server accesses the map database and the train operation information database to calculate the optimal route. For example, it might determine the most comfortable route from "Station A" to "Station B" and select "Train D".

[1720] 5. The server takes into account the user's relaxed state and determines a route that includes scenic views and tourist spots, as well as the optimal boarding position (e.g., front of car 1) and exit (e.g., exit 1).

[1721] 6. The server sends the coordinated routing information to the terminal, and the terminal displays the following to the user:

[1722] Transportation: Train D

[1723] Boarding location: Front of car 1

[1724] Disembarking station: Station B

[1725] Optimal exit: Exit 1

[1726] Reason for proposal: A route with good scenery

[1727] Examples of prompt statements using generative AI models include the following:

[1728] The user launches the app and enters their travel time from Station A to Station B. During this process, the app performs an emotional analysis to determine whether the user is stressed or relaxed. Then, it suggests the optimal route, boarding location, and exit.

[1729] This system allows users to receive optimal route guidance tailored to their emotional state, resulting in a comfortable travel experience. The introduction of an emotion engine enables the provision of personalized services that meet the individual needs of each user.

[1730] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1731] Program processing steps and specific actions

[1732] Step 1: User Input

[1733] Input: The user launches the application and enters the departure point "Station A" and the destination "Station B". Optionally, they can also specify their desired arrival time and mode of transport.

[1734] Operation: The user operates a smartphone app. The smartphone's camera and microphone are used to capture the user's facial expressions and voice data in real time.

[1735] Data processing: The device inputs captured facial expressions and audio data into an emotion engine to analyze the user's emotional state.

[1736] Output: Origin, destination, options information, and analyzed sentiment data are generated.

[1737] Step 2: Data transmission

[1738] Input: Origin, destination, optional information, and sentiment data generated by the device.

[1739] Operation: The terminal generates this data as data packets and sends them to the server using the HTTP or HTTPS protocol.

[1740] Output: Data packets sent to the server.

[1741] Step 3: Server Processing

[1742] Input: Data packets received by the server from the terminal.

[1743] Operation: The server analyzes the data packets and extracts origin, destination, option information, and sentiment data. It then accesses a map database (e.g., Google Maps API) and a traffic information database to retrieve current traffic status.

[1744] Data processing: Based on the operational data acquired by the server, the optimal route from the origin to the destination is calculated using an algorithm.

[1745] Output: Optimal route information.

[1746] Step 4: Applying emotional data

[1747] Input: Optimal route information calculated by the server and user sentiment data.

[1748] Operation: The server further adjusts route information based on the user's emotional state (e.g., stressed, relaxed). For example, if the user is stressed, it will select a less congested route; if the user is relaxed, it will select a route with good scenery or one that passes by tourist attractions.

[1749] Data processing: Determine the adjusted route information, optimal boarding location, and optimal exit location.

[1750] Output: Adjusted route information, boarding location, exit location, and reason for recommendation.

[1751] Step 5: Submit Results

[1752] Input: Server-adjusted optimal route information, boarding location, exit location, and reason for recommendation.

[1753] Operation: The server generates this information as a data packet and sends it to the terminal.

[1754] Output: Data packets sent to the terminal.

[1755] Step 6: User Display

[1756] Input: Data packets received by the terminal from the server.

[1757] Operation: The terminal analyzes data packets and displays the mode of transport to be used, the optimal boarding location, the optimal drop-off location, the optimal exit, and the reason for the recommendation on the user interface.

[1758] Output: Optimal route information displayed to the user.

[1759] This program's processing allows users to receive optimal route guidance tailored to their emotional state, enabling a comfortable journey.

[1760] (Application Example 2)

[1761] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1762] Conventional travel route guidance systems provide the optimal route based on input of the origin and destination, but they lacked personalization of service by not considering the user's emotional state. Furthermore, they were unable to provide the optimal route based on whether the passenger was stressed or relaxed. As a result, they failed to deliver a comfortable travel experience for users.

[1763] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for inputting the departure point and destination; means for transmitting the input departure point and destination information to the server; means for calculating the optimal route based on the information received by the server; means for determining the boarding position and exit position based on the calculated optimal route; means for analyzing the passenger's emotional state and transmitting the data to the server; means for adjusting the route based on the emotional state; means for transmitting the determined information to a terminal and displaying it to the passenger; means for the terminal to display the reason for the route adjustment based on the passenger's emotional state; and means for recognizing the passenger's emotional state using a mobile terminal, in-vehicle terminal, or camera. This makes it possible to provide a personalized and optimal travel route according to the user's emotional state.

[1764] The "starting point" is the point where the journey begins.

[1765] A "destination" is the final point of arrival at a destination.

[1766] A "server" is a computer system that receives, transmits, processes, and stores data over a network.

[1767] A "route" is the path taken to travel from a starting point to a destination.

[1768] "Boarding position" refers to the optimal location for passengers to board a mode of transportation.

[1769] An "exit" is a place where passengers disembark from a mode of transportation.

[1770] "Emotional state" refers to the emotional state a passenger is experiencing, such as stress or joy.

[1771] A "mobile device" refers to a portable computing device such as a smartphone or tablet.

[1772] An "in-vehicle terminal" is an electronic device installed in a car that assists with driving and navigation.

[1773] A "camera" is an optical device used to capture images and videos.

[1774] An "emotion engine" is a system that uses devices such as cameras and microphones to identify a user's emotional state and analyze that information.

[1775] A "terminal" refers to a device or equipment on which a user inputs or displays information.

[1776] This invention is a system to help passengers comfortably reach their destination using autonomous vehicles. The system uses the following hardware and software components.

[1777] Hardware configuration

[1778] 1. Mobile devices:

[1779] These are devices, such as smartphones and tablets, that passengers use to input their departure and destination locations.

[1780] 2. In-vehicle terminals:

[1781] These are touch panels or displays installed in autonomous vehicles, used by passengers to input their departure and destination locations and to confirm information.

[1782] 3. Camera:

[1783] This device is installed inside autonomous vehicles to capture passengers' facial expressions and movements and analyze their emotional state.

[1784] Software Configuration

[1785] 1. Emotional Engine:

[1786] This software module analyzes facial expressions and voice data to determine passengers' emotional states in real time. It utilizes OpenCV and common emotion analysis libraries.

[1787] 2. Path Calculation Module:

[1788] It operates on a server and calculates the optimal route based on the received origin and destination data. This calculation utilizes a map database and a traffic information database.

[1789] 3. Server:

[1790] This system receives, transmits, processes, and stores data over a network. The server includes an emotion engine that analyzes facial expressions and voice data, and a route calculation module that uses map data and traffic information.

[1791] Data processing and data calculation

[1792] Camera data:

[1793] The system collects passengers' facial expressions and voice data through cameras and microphones and transmits it to a server in real time. The emotion engine analyzes this data to determine their emotional state (stress, relaxation, etc.).

[1794] Path calculation:

[1795] The server accesses map and traffic information databases to calculate the optimal route from the origin to the destination. Furthermore, it adjusts the route based on the passenger's emotional state, as determined by the emotion engine. For example, if a passenger is stressed, it selects a less congested route; if they are relaxed, it selects a route with good scenery.

[1796] Information transmission and display:

[1797] Once the optimal route information is determined, the server transmits this information to the in-vehicle terminal and displays it to the passengers on the screen. The displayed information includes the optimal route, boarding location, alighting location, exit, and reasons for route adjustments based on emotional state.

[1798] Specific example

[1799] 1. The passenger enters their travel destination from "Station A" to "Station B" using the onboard terminal.

[1800] 2. In-car cameras capture passengers' facial expressions, which are then analyzed by an emotion engine.

[1801] 3. The emotion engine determines that the passenger is stressed and sends data to the server.

[1802] 4. The server calculates the least congested route and transmits the calculated route to the in-vehicle terminal.

[1803] 5. The in-vehicle terminal displays the following information to passengers:

[1804] Transportation: Train C

[1805] Boarding location: Last car

[1806] Disembarking station: Station B

[1807] Optimal exit: Exit 3

[1808] Reason for proposal: Because it is less crowded.

[1809] Example of a prompt

[1810] "Input user emotion data and departure / destination information to recommend the optimal travel route. If the user is stressed, recommend a less congested route; if they are relaxed, recommend a route with good scenery."

[1811] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1812] Step 1:

[1813] The user launches the application on the in-vehicle terminal and enters the departure and destination locations. The information entered includes the departure location, destination, and optionally, the desired arrival time. The entered data is stored on the in-vehicle terminal. Input: Departure location, destination, desired arrival time. Output: Input information stored on the in-vehicle terminal.

[1814] Step 2:

[1815] The device's camera and microphone are used to capture passengers' facial expressions and voices in real time. An emotion engine analyzes this data to determine the user's emotional state (e.g., stress, relaxation). Input: Captured facial and voice data. Output: Analyzed emotional state data.

[1816] Step 3:

[1817] The device sends the user's input origin, destination, and emotional state data analyzed by the emotion engine to the server. Input: Origin, destination, and emotional state data. Output: Data sent to the server.

[1818] Step 4:

[1819] The server calculates the optimal route by accessing a map database and a train operation information database based on the origin, destination, and sentiment status data it receives. Furthermore, platform and exit information for each station is also considered. Input: Origin, destination, map data, train operation information, sentiment status data. Output: Optimal route information.

[1820] Step 5:

[1821] The server adjusts the route based on the user's emotional state. For example, if the user is stressed, it will choose a less congested route; if they are relaxed, it will choose a route with good scenery. Input: Optimal route information, emotional state. Output: Adjusted route information.

[1822] Step 6:

[1823] The server sends optimized route information to the terminal. This information includes the route, boarding location, exit location, and reasons based on emotional state. Input: Optimized route information. Output: Route information sent to the terminal.

[1824] Step 7:

[1825] The terminal displays route information received by the passenger in an easy-to-understand manner. The displayed information includes the mode of transport, optimal boarding location, drop-off point, optimal exit, and reasons for route adjustments based on emotional state. Input: Received route information. Output: Displayed route information.

[1826] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1827] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1828] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[1829] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1830] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[1831] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[1832] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[1833] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[1834] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[1835] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[1836] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[1837] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[1838] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[1839] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1840] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[1841] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[1842] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[1843] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[1844] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[1845] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[1846] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference.

[1847] The following is further disclosed regarding the embodiments described above.

[1848] (Claim 1)

[1849] A means of entering the departure point and destination,

[1850] Means for transmitting the entered departure and destination information to a server,

[1851] A means for calculating the optimal route based on the information received by the server,

[1852] Means for determining boarding and exit positions based on the calculated optimal route,

[1853] A system that includes means for transmitting determined information to a terminal and displaying it to the user.

[1854] (Claim 2)

[1855] The system according to claim 1, characterized in that the means for determining the boarding position and exit position determines the optimal position by taking into consideration platform information and exit information for each station.

[1856] (Claim 3)

[1857] The system according to claim 1, characterized in that the server calculates the optimal route in real time, taking into account the current operating conditions.

[1858] "Example 1"

[1859] (Claim 1)

[1860] A means for the user to enter their departure and destination locations,

[1861] A means for transmitting the departure and destination information entered by the terminal to the server,

[1862] A means for calculating the optimal route using a map database and a traffic information database based on information received by the server,

[1863] A means by which the server determines the boarding position and exit position at each station based on the calculated optimal route,

[1864] A system that includes means for transmitting determined information to a terminal and displaying it to the user.

[1865] (Claim 2)

[1866] The system according to claim 1, characterized in that the server determines the boarding position and exit position by taking into account platform information and exit information for each station.

[1867] (Claim 3)

[1868] The system according to claim 1, characterized in that the server uses a traffic information database to consider the current traffic conditions and calculates the optimal route in real time.

[1869] "Application Example 1"

[1870] (Claim 1)

[1871] A means of entering the departure point and destination,

[1872] Means for transmitting the entered departure and destination information to a server,

[1873] A means for calculating the optimal route based on the information received by the server,

[1874] Means for determining boarding and exit positions based on the calculated optimal route,

[1875] A means of transmitting the determined information to the terminal and displaying it to the user,

[1876] A means for transmitting calculation results to the computer system of an autonomous vehicle, and for the computer system to control the vehicle according to the optimal route,

[1877] A means by which the user can check detailed route information and pick-up / drop-off locations via a smartphone or in-vehicle display device,

[1878] A system that includes this.

[1879] (Claim 2)

[1880] The system according to claim 1, characterized in that the means for determining the boarding position and exit position determines the optimal position by taking into consideration the facility information and exit information of each station.

[1881] (Claim 3)

[1882] The system according to claim 1, characterized in that the server calculates the optimal route in real time, taking into account the current operating conditions.

[1883] "Example 2 of combining an emotion engine"

[1884] (Claim 1)

[1885] A means of entering the departure point and destination,

[1886] Means for transmitting the entered departure and destination information to a server,

[1887] A means for calculating the optimal route based on the information received by the server,

[1888] Means for determining boarding and exit positions based on the calculated optimal route,

[1889] A means for analyzing the emotional state of users,

[1890] A means of adjusting the pathway based on the analyzed emotional state,

[1891] A means of transmitting the determined information to the terminal and displaying it to the user,

[1892] A system that includes this.

[1893] (Claim 2)

[1894] The system according to claim 1, characterized in that the means for determining the boarding position and exit position determines the optimal position by taking into consideration platform information and exit information for each station.

[1895] (Claim 3)

[1896] The system according to claim 1, characterized in that the server calculates the optimal route in real time, taking into account the current operating conditions.

[1897] "Application example 2 when combining with an emotional engine"

[1898] (Claim 1)

[1899] A means of entering the departure point and destination,

[1900] Means for transmitting the entered departure and destination information to a server,

[1901] A means for calculating the optimal route based on the information received by the server,

[1902] Means for determining boarding and exit positions based on the calculated optimal route,

[1903] A means of analyzing the emotional state of passengers and transmitting that data to a server,

[1904] Means of adjusting pathways based on emotional state,

[1905] A means of transmitting the determined information to a terminal and displaying it to the passengers,

[1906] The terminal provides a means of displaying the reason for route adjustment based on the passenger's emotional state,

[1907] A means of recognizing the emotional state of passengers using a mobile device, in-vehicle device, or camera,

[1908] A system that includes this.

[1909] (Claim 2)

[1910] The system according to claim 1, characterized in that the means for determining the boarding position and exit position determines the optimal position by taking into consideration platform information and exit information for each station.

[1911] (Claim 3)

[1912] The system according to claim 1, characterized in that the server calculates the optimal route in real time considering the current operating conditions and further adjusts the route based on the emotional state of the passengers. [Explanation of Symbols]

[1913] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of entering the departure point and destination, Means for transmitting the entered departure and destination information to a server, A means for calculating the optimal route based on the information received by the server, Means for determining boarding and exit positions based on the calculated optimal route, A system that includes means for transmitting determined information to a terminal and displaying it to the user.

2. The system according to claim 1, characterized in that the means for determining the boarding position and exit position determines the optimal position by taking into consideration platform information and exit information for each station.

3. The system according to claim 1, characterized in that the server calculates the optimal route in real time, taking into account the current operating conditions.

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