system

Abstract

In particular, the system provides a rapid and effective way to suggest the optimal route, reflecting real-time changes in traffic conditions and road closures, especially during disasters, while also flexibly accommodating users' preferences for detours and points of interest. [Solution] A system including means for collecting traffic information from local governments and manufacturers, means for receiving destinations and points of interest from users as input, means for generating an optimal route based on the collected traffic information, means for presenting the generated optimal route to the user, means for receiving feedback from the user, and means for generating the optimal route again based on the feedback.

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] In current car navigation systems, it is difficult to fully reflect real-time changing traffic conditions and road closure information. Especially in case of disasters, although a prompt proposal of a route is required, it is difficult to present an effective optimal route. In addition, there is a problem of low convenience because it is impossible to flexibly respond to a user's detour or desired stop point. For this reason, there is a demand for providing a car navigation system that can grasp traffic conditions in real time and dynamically propose an optimal route according to a user's request.

Means for Solving the Problems

[0005] To solve the above problems, the present invention provides the following means. Specifically, a system including means for collecting traffic information from local governments and manufacturers, means for receiving destinations and points of interest from users as input, means for generating an optimal route based on the collected traffic information, means for presenting the generated optimal route to the user, means for receiving feedback from the user, and means for generating the optimal route again based on the feedback makes it possible to flexibly respond to traffic conditions that change in real time and provide the optimal route based on the user's requests. Furthermore, since the traffic information includes traffic information provision services and road closure information during disasters, it can be effectively used even in emergencies. In addition, by using artificial intelligence technology as the generation means, more sophisticated route generation is possible.

[0006] A "local government" refers to a local public body or its constituent units.

[0007] A "manufacturer" is a company or organization that primarily produces automobiles and related equipment.

[0008] "Traffic information" refers to traffic-related data such as road conditions, congestion information, and road closure information.

[0009] "Means of collection" refers to methods or techniques for acquiring information automatically or manually.

[0010] The "destination" is the place the user is ultimately aiming for.

[0011] A "stopover point" is a place that a user might want to visit on their way to their destination.

[0012] "Means of acceptance" refers to methods and systems for obtaining input and requests from users.

[0013] "Generation means" refers to functions or technologies that create other information or data based on specific information.

[0014] The "optimal route" is the most efficient moving route set considering traffic conditions and user conditions.

[0015] The "means of presentation" is a method or technology for displaying or transmitting the generated information to the user.

[0016] "Feedback" is information regarding the reaction and additional requests from the user.

[0017] "Artificial intelligence technology" is a technology for making human-like judgments and learning through machine learning and data analysis.

[0018] A "system" is an aggregate of hardware, software, and procedures organized to achieve a specific purpose.

Brief Explanation of Drawings

[0019] [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]Shows an emotion map to which a plurality of emotions are mapped. [Figure 10] Shows an emotion map to which a plurality of 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.

Mode for Carrying Out the Invention

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

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

[0022] In the following embodiments, a processor with a reference number (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of a plurality of arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of a plurality of types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0023] In the following embodiments, signed RAM (Random Access Memory) is a memory that temporarily stores information and is used as work memory by the processor.

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

[0025] 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).

[0026] 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."

[0027] [First Embodiment]

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

[0029] 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.

[0030] 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).

[0031] 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.

[0032] 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.

[0033] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form 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.

[0034] 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.

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

[0036] 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.

[0037] 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.

[0038] 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.

[0039] 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".

[0040] The embodiments for carrying out the present invention will be described in detail.

[0041] First, the present invention relates to a car navigation system that collects traffic information in real time and proposes the optimal route to the user. This system collects and integrates traffic information provided by local governments and manufacturers, and generates the optimal route based on user input information. Furthermore, it has a function to regenerate the route as needed based on user feedback.

[0042] composition

[0043] 1. Server

[0044] Data collection and database updating:

[0045] The server periodically collects traffic information provided by local governments and manufacturers. This includes traffic congestion information, accident information, road closure information, and road condition information during disasters. The collected information is stored and updated in a database.

[0046] Generative AI models:

[0047] The server trains a generative AI model based on collected traffic information and builds an algorithm to generate the optimal route. The generative AI model can dynamically generate the optimal route according to user requests and current conditions.

[0048] 2. Terminal

[0049] Enter and submit user information:

[0050] The terminal accepts the user's destination and points of interest as input. A chatbot is used to collect detailed information such as the user's desired points of interest and waypoints. The collected information is sent to the server.

[0051] Route information provided:

[0052] The system displays optimal route information received from the server to the user. This information includes not only the destination, but also designated points of interest and real-time traffic conditions.

[0053] Feedback processing:

[0054] The system accepts user feedback and additional requests, and resends them to the server. This allows for regeneration according to the user's preferences.

[0055] 3. User

[0056] Input and feedback:

[0057] Users input their destination and points of interest through a chatbot. After the optimal route is suggested, they can also provide feedback if further improvements are needed, requesting a route regeneration.

[0058] Specific example

[0059] For example, consider a case where a user enters "I want to stop at a gas station on the way to Tokyo Station."

[0060] Data collection and analysis:

[0061] The server retrieves the latest information from the traffic information database and performs analysis. It identifies the destination as "Tokyo Station" and the stopping point as "gas station."

[0062] Generating the optimal route:

[0063] The AI ​​model generates the optimal route based on this information, taking into account current traffic conditions. For example, it might suggest a route that avoids congestion while also stopping at gas stations as requested by the user.

[0064] Route suggestion and correction:

[0065] The device displays the initial route to the user and suggests, "This route will take you past two gas stations." If the user provides feedback such as, "Is there a closer gas station?", the server re-analyzes the route and generates a new optimal route. This new route information is sent to the device, and the user is shown, "We have found a new route that goes past a closer gas station."

[0066] In this way, the car navigation system of the present invention can provide an optimal route that dynamically reflects real-time traffic information and user requests.

[0067] The following describes the processing flow.

[0068] Step 1:

[0069] The server periodically collects traffic information provided by local governments and manufacturers. This information includes traffic congestion, accidents, road closures, and road conditions during disasters. The collected information is stored in a database and updated in real time.

[0070] Step 2:

[0071] The terminal accepts the user's destination and points of interest as input. It interactively collects user input through a chatbot (e.g., "I want to stop at a gas station on the way to Tokyo Station"). The entered information is temporarily stored on the terminal.

[0072] Step 3:

[0073] The device sends the collected user input information to the server. This information includes destination, points of interest, and other specific preferences.

[0074] Step 4:

[0075] The server analyzes the received user information. Using natural language processing, it identifies the destination and points of interest, and retrieves the latest traffic information from the database.

[0076] Step 5:

[0077] The server generates the optimal route using AI based on analysis results and traffic information. The generated route is the best possible path, taking into account traffic congestion and road closures, and including the user's desired stops.

[0078] Step 6:

[0079] The server sends the generated optimal route information to the terminal. The route information includes detailed route instructions and information about potential detours.

[0080] Step 7:

[0081] The terminal receives route information from the server and displays it to the user. For example, it might display something like, "If you use this route, there are two gas stations along the way."

[0082] Step 8:

[0083] Users can provide feedback and additional requests regarding the suggested route through the chatbot. For example, they might ask, "Is there a closer gas station?"

[0084] Step 9:

[0085] The device sends the user feedback information back to the server. The server re-analyzes the data and generates the optimal route based on the new conditions.

[0086] Step 10:

[0087] The server generates a new, optimal route based on the feedback and sends it to the terminal. The regenerated route information also takes into account any additional requests from the user.

[0088] Step 11:

[0089] The device receives new, optimal routes and displays them to the user. For example, it might display, "We found a new route that goes through a closer gas station."

[0090] This series of steps allows users to obtain real-time, up-to-date traffic information and the optimal route tailored to their needs.

[0091] (Example 1)

[0092] 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."

[0093] Conventional car navigation systems often fail to adequately reflect real-time traffic information, making it difficult to suggest the optimal route for the user. Furthermore, they lack convenience due to their inability to quickly respond to additional user requests and feedback. Additionally, they do not fully utilize artificial intelligence technology for collecting traffic information and generating optimal routes.

[0094] 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.

[0095] In this invention, the server includes means for collecting traffic information from local governments and manufacturers, means for receiving destinations and points of interest from users as input, means for generating an optimal route based on the collected traffic information, means for presenting the generated optimal route to the user, means for receiving feedback from the user, means for generating the optimal route again based on the feedback, and means for training a generation AI model that provides the generated optimal route to the user. This makes it possible to dynamically reflect real-time traffic information and quickly provide the optimal route that meets the user's needs.

[0096] A "local government" is a local government agency that provides public services and manages administrative affairs.

[0097] A "manufacturer" is a company or organization that produces or manufactures products.

[0098] "Traffic information" refers to traffic-related data such as road congestion, accident information, road closure information, and road conditions during disasters.

[0099] "Means" refers to the methods or devices used to achieve a specific objective.

[0100] A "user" is an individual or group that uses the system.

[0101] The "destination" is the final point that the user aims to reach.

[0102] A "stopover point" is a specific location that a user might want to visit before reaching their destination.

[0103] A "generation method" refers to a method or apparatus that performs calculations or analyses based on specific data to generate results.

[0104] "Presentation means" refers to a method or device for displaying or providing generated information to a user.

[0105] "Feedback" refers to the opinions and requests that users provide regarding the system's suggestions and results.

[0106] A "generative AI model" is an algorithm or program that uses artificial intelligence technology to analyze data and generate specific results.

[0107] "Training methods" refer to the methods and devices used to train models or algorithms.

[0108] Modes for carrying out the invention

[0109] The embodiments for carrying out the present invention will be described in detail. First, the present invention relates to a car navigation system that collects traffic information in real time and proposes the optimal route to the user. This system collects and integrates traffic information provided by local governments and manufacturers and generates the optimal route based on user input information. Furthermore, it has a function to regenerate the route as needed based on user feedback.

[0110] 1. Server roles and processing

[0111] The server is primarily responsible for collecting traffic information, training the AI ​​model for generating traffic, and generating the optimal route. Specifically, it performs the following processes:

[0112] Data collection and database updating:

[0113] The server collects traffic information from local governments and manufacturers via APIs at specific times each day. This information includes traffic congestion, accidents, road closures, and road conditions during disasters. This information is stored in the server's database and updated by comparing it with existing data.

[0114] Training generative AI models and generating optimal routes:

[0115] The server trains a generative AI model based on the collected traffic information. This model uses destination and stopover information received from the user, along with real-time traffic data, to generate the optimal route. The generated route information is then sent to the user's device.

[0116] 2. Terminal roles and processing

[0117] The terminal collects user input information and sends it to the server. It also has the role of presenting the user with the optimal route information received from the server. The specific process is as follows:

[0118] Enter and submit user information:

[0119] The terminal uses a chatbot to receive information about destinations and points of interest entered by the user. For example, if a user enters "I want to stop at a gas station on the way to Tokyo Station," that information is sent to the server.

[0120] Route information provided:

[0121] The terminal, having received optimal route information from the server, presents that information to the user. The displayed information includes the destination, points of interest, and real-time traffic conditions.

[0122] Accepting feedback:

[0123] When a user provides feedback on the suggested route, that information is also sent from the terminal to the server. For example, if a user provides feedback such as "Is there a closer gas station?", that information is sent back to the server, and the process of generating a new optimal route is initiated.

[0124] 3. User roles and operations

[0125] Users input their destination, points of interest, and feedback through a chatbot. This allows the system to suggest the optimal route based on real-time traffic information.

[0126] Specific example:

[0127] For example, consider the process when a user inputs, "I want to stop at a gas station on the way to Tokyo Station."

[0128] Data collection and analysis:

[0129] The server retrieves the latest information from the traffic information database and performs analysis. It identifies the destination as "Tokyo Station" and the stopping point as "gas station."

[0130] Generating the optimal route:

[0131] The AI ​​model generates the optimal route based on this information, taking into account current traffic conditions. For example, it might suggest a route that avoids congestion while also stopping at gas stations as requested by the user.

[0132] Route guidance and feedback:

[0133] The device displays the initial route to the user and suggests, "This route will take you past two gas stations." If the user provides feedback such as, "Is there a closer gas station?", the server re-analyzes the route and generates a new optimal route. This new route information is sent to the device, and the user is shown, "We have found a new route that goes past a closer gas station."

[0134] Example of a prompt:

[0135] This system generates algorithms for car navigation systems. The system receives destination and stopover information from the user and provides the optimal route based on real-time traffic conditions. This system can update a traffic information database and generate the optimal route using a generated AI model.

[0136] In this way, the car navigation system of the present invention can provide an optimal route that dynamically reflects real-time traffic information and user requests.

[0137] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0138] System program processing steps

[0139] Step 1:

[0140] Data collection

[0141] The server collects traffic information from local governments and manufacturers via an API at a specific time each day. The input is traffic information data obtained from the API. The server parses this data, processes it into the required format, and stores it in the database.

[0142] Specific actions:

[0143] The server executes the "Traffic Information Update" script.

[0144] A request is sent to the API endpoint, and the JSON data received as a response is parsed.

[0145] The parsed data is stored in the database.

[0146] Step 2:

[0147] Database update

[0148] The collected traffic information is stored in the server's database. This ensures that the traffic information is always up-to-date. The input is the parsed traffic information data, and the output is the updated state of the database.

[0149] Specific actions:

[0150] The server compares the new data with the existing data.

[0151] Update existing data as needed to keep the database up to date.

[0152] Step 3:

[0153] Enter user information

[0154] The terminal receives information from the user regarding the destination and points of interest. The input is information entered by the user via the chatbot, and the output is data sent to the server.

[0155] Specific actions:

[0156] The user opens the chatbot and enters their destination and points of interest.

[0157] The terminal collects the information entered and sends it to the server.

[0158] Step 4:

[0159] Optimal route generation

[0160] The server generates the optimal route using a generative AI model based on destination and stopover point information received from the user. The input is user information and real-time traffic information data, and the output is the generated optimal route data.

[0161] Specific actions:

[0162] The server receives the user's input information.

[0163] The collected traffic information and input information are supplied to the generating AI model.

[0164] The generative AI model calculates the optimal route and generates the result.

[0165] The generated route information is sent to the terminal.

[0166] Step 5:

[0167] Presenting route information

[0168] The terminal displays the optimal route information received from the server to the user. The input is the optimal route data received from the server, and the output is the data displayed to the user.

[0169] Specific actions:

[0170] The terminal receives route information from the server.

[0171] Route information is displayed to the user on the screen.

[0172] For example, it could display information such as, "There are two gas stations along the route to Tokyo Station."

[0173] Step 6:

[0174] Processing user feedback

[0175] The device receives feedback from the user and sends it back to the server. The input is the feedback information provided by the user, and the output is the data sent to the server.

[0176] Specific actions:

[0177] The user enters feedback into the chatbot.

[0178] The device sends that feedback information to the server.

[0179] Step 7:

[0180] Regenerating the route

[0181] The server generates a new optimal route based on user feedback. The input is feedback information and the latest traffic information data, and the output is the regenerated optimal route data.

[0182] Specific actions:

[0183] The server receives feedback.

[0184] A generative AI model is used to calculate a new optimal route.

[0185] Send the calculation result to the terminal.

[0186] In this way, information exchange between the server, terminal, and user makes it possible to dynamically provide the optimal route based on real-time traffic information.

[0187] (Application Example 1)

[0188] 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."

[0189] Conventional car navigation systems, while providing optimal routes based on real-time traffic information, lacked sufficient integration with autonomous vehicles, requiring user intervention. Furthermore, their feedback-based route regeneration capabilities were inadequate, making sudden changes or optimal responses difficult. This resulted in limitations on user convenience.

[0190] 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.

[0191] In this invention, the server includes means for collecting traffic information from local governments and manufacturers, means for receiving destinations and points of interest from users as input, means for generating an optimal route based on the collected traffic information, means for presenting the generated optimal route to the user, means for receiving feedback from the user, means for generating the optimal route again based on the feedback, and means for issuing instructions related to the operation control of the vehicle. This makes it possible to provide optimal routes for autonomous vehicles based on real-time traffic information, significantly improving user convenience and safety.

[0192] "Local government" refers to a local public body, an organization that functions as a provider of traffic information.

[0193] "Manufacturers" refers to companies that manufacture automobiles and transportation-related equipment, and the term also refers to traffic information provided by these companies.

[0194] "Traffic information" refers to real-time information such as traffic congestion, accidents, road closures, and road conditions during disasters.

[0195] "User" refers to an individual or organization that uses a car navigation system.

[0196] "Destination" refers to the place the user ultimately wants to reach.

[0197] A "stopover point" refers to a location that a user might want to visit on their way to their destination.

[0198] "Generation means" refers to the technologies and algorithms used to calculate the optimal route based on collected traffic information.

[0199] "Presentation means" refers to technologies and devices used to display the generated optimal route on the user's device.

[0200] "Feedback" refers to additional requests and information provided by users.

[0201] "Regeneration means" refers to technologies and algorithms for calculating a new optimal path based on feedback.

[0202] "Vehicle operation control" refers to the operations and instructions related to the driving of autonomous vehicles.

[0203] A "generative AI model" refers to an algorithm or system that uses artificial intelligence (AI) technology to generate the optimal path.

[0204] The embodiments for carrying out the present invention will be described in detail.

[0205] First, the system of this invention collects traffic information from local governments and manufacturers, accepts input from users regarding destinations and points of interest, and generates and presents an optimal route based on that information. It also has a function to receive feedback from users and generate an optimal route again. Furthermore, this system can also issue instructions related to the operation control of vehicles.

[0206] server

[0207] The server has the following functions:

[0208] 1. Data Collection: The server periodically collects traffic information provided by local governments and manufacturers. This information includes traffic congestion information, accident information, road closure information, and road condition information during disasters.

[0209] 2. Use of Generative AI Model: The server trains a generative AI model based on collected traffic information and builds an algorithm to generate the optimal route. The generative AI model can dynamically generate the optimal route according to user requests and current conditions.

[0210] 3. Route generation and presentation: The generated optimal route is sent to the user's terminal and presented to the user.

[0211] As a concrete example, here is a prompt message in which the server identifies the destination as "Tokyo Station" and the stopover point as "gas station":

[0212] Please enter your destination: Tokyo Station

[0213] Please enter your stopping points (multiple points are allowed, separated by commas): Gas station

[0214] terminal

[0215] The device has the following features:

[0216] 1. User Input and Transmission: The terminal accepts input from the user regarding the destination and points of interest. Using a chatbot, it collects detailed information such as the user's desired points of interest and waypoints, and sends it to the server.

[0217] 2. Presenting Route Information: The system presents the user with the optimal route information received from the server. The displayed information includes not only the destination but also designated points of interest and real-time traffic conditions.

[0218] 3. Feedback Processing: User feedback and additional requests are received and resent to the server. This allows for regeneration according to the user's wishes.

[0219] user

[0220] The user performs the following actions:

[0221] 1. Input and Feedback: Users input their destination and points of interest through the chatbot. After the optimal route is presented, they can also provide feedback if further improvements are needed, requesting a route regeneration.

[0222] These functions and operations enable the system of the present invention to dynamically provide the optimal route for the user based on real-time traffic information. In particular, in autonomous vehicles, by issuing instructions related to operation control, it is possible to achieve safe and efficient driving while minimizing user intervention.

[0223] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0224] Step 1:

[0225] The server periodically collects traffic information provided by local governments and manufacturers. This process involves obtaining traffic congestion information, accident information, road closure information, and road condition information during disasters via APIs and databases. The input is traffic information data from various sources, which the server collects, stores in its database, and updates to maintain the latest traffic information. The output is the most recent traffic data stored on the server.

[0226] Step 2:

[0227] The user enters their destination and points of interest using their device. The user enters this information in text format through the device's chatbot. The input is text data of the destination and points of interest, which the device receives and then sends to the server. The output is the user's destination and points of interest data sent to the server.

[0228] Step 3:

[0229] The server references a database of collected traffic information based on the user's destination and stopover data. Here, a generative AI model is used to generate the optimal route. The input consists of the user-specified destination and stopovers, along with the latest traffic information. The server analyzes this data using the generative AI model to generate the optimal route. The output is the generated optimal route information.

[0230] Step 4:

[0231] The server sends the generated optimal route information to the user's terminal. The input is the generated optimal route information, which the server sends to the terminal. The output is the optimal route information displayed on the user's terminal. The user then starts driving based on this information.

[0232] Step 5:

[0233] Users input feedback and additional requests through the terminal. For example, feedback such as "Is there a closer gas station?" is possible. The input is the user's feedback text, which the terminal receives and then sends back to the server. The output is the user feedback data sent to the server.

[0234] Step 6:

[0235] The server, based on user feedback, consults the traffic information database again and uses a generative AI model to generate a new optimal route. The input consists of the feedback and the latest traffic information, and the server generates a regenerated optimal route based on this. The output is the newly generated optimal route information.

[0236] Step 7:

[0237] The server sends the regenerated optimal route information to the user's terminal. The input is the regenerated optimal route information, which the server sends to the terminal. The output is the new optimal route information displayed on the user's terminal. The user adjusts their driving based on this information.

[0238] 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.

[0239] The embodiments for carrying out the present invention will be described in detail.

[0240] This invention relates to a car navigation system that collects traffic information in real time and proposes the optimal route to the user. This system collects and integrates traffic information provided by local governments and manufacturers, and generates the optimal route based on user input. Furthermore, it has a function to regenerate the route as needed based on user feedback. In addition, this invention can propose routes that take into account the user's psychological state by incorporating an emotion engine that recognizes the user's emotions.

[0241] composition

[0242] 1. Server

[0243] Data collection and database updating:

[0244] The server periodically acquires traffic information provided by local governments and manufacturers, and the collected information is stored in a database. This includes traffic congestion information, accident information, road closure information, and road condition information during disasters.

[0245] Generative AI models:

[0246] The server trains a generative AI model based on collected traffic information. The generative AI model dynamically generates the optimal route according to the user's requests and current conditions. It also uses user sentiment information provided by the sentiment engine to adjust the tone and content of route suggestions.

[0247] 2. Terminal

[0248] Enter and submit user information:

[0249] The terminal accepts input from the user regarding their destination and points of interest. This input information is collected interactively, for example through a chatbot, and temporarily stored within the terminal. This information is then sent to the server.

[0250] Collection and analysis of emotional information:

[0251] The emotion engine analyzes the user's voice and text data to identify their emotions. The identified emotion information is then sent to the server.

[0252] Route information provided:

[0253] The system displays optimal route information received from the server to the user. The displayed information includes the destination, points of interest, and real-time traffic conditions. An emotion engine adjusts the display method and tone of guidance based on the user's emotions.

[0254] Feedback processing:

[0255] The system receives user feedback and additional requests through a chatbot and sends them to the server.

[0256] 3. User

[0257] Input and feedback:

[0258] Users input their destination and points of interest through a chatbot. After the optimal route is suggested, they can also provide feedback if further improvements are needed and request a route regeneration.

[0259] Specific example

[0260] For example, consider a case where a user inputs "I want to stop at a gas station on the way to Tokyo Station," and this input is accompanied by expressions of stress or anxiety.

[0261] Data collection and analysis:

[0262] The server retrieves the latest information from the traffic information database and performs analysis. It identifies the destination as "Tokyo Station" and the stopping point as "gas station."

[0263] Analysis of emotional information:

[0264] The emotion engine analyzes emotional information from the user's input and voice to detect stress and anxiety.

[0265] Generating the optimal route:

[0266] The generative AI model generates the optimal route based on user instructions and emotional information. For example, it suggests a route that avoids traffic jams, stops at the user's preferred gas station, and further reduces stress.

[0267] Route suggestion and adjustment:

[0268] The terminal presents the generated route to the user and provides guidance such as, "If you use this route, you can stop at two gas stations along the way." The information is presented in a gentle and calming tone to reduce user stress.

[0269] Feedback and regeneration:

[0270] If a user provides feedback such as "Is there a closer gas station?", the server re-analyzes the data and generates an optimal route based on the new conditions. The regenerated route similarly takes into account the user's emotional state, as determined by the emotion engine.

[0271] This series of steps allows users to be presented with the latest traffic information in real time, along with their individual preferences and even their psychological state, to find the optimal route, enabling a comfortable and safe journey.

[0272] The following describes the processing flow.

[0273] Step 1:

[0274] The server periodically collects traffic information provided by local governments and manufacturers. This information includes traffic congestion, accident information, road closure information, and road condition information during disasters. The collected information is stored in a database and updated in real time.

[0275] Step 2:

[0276] The terminal accepts the user's destination and points of interest as input. It interactively collects user input through a chatbot (e.g., "I want to stop at a gas station on the way to Tokyo Station"). The entered information is temporarily stored on the terminal.

[0277] Step 3:

[0278] The emotion engine analyzes the user's voice and text data to identify emotions. For example, it identifies emotions such as stress, anxiety, and joy based on the tone of the user's voice and the input text.

[0279] Step 4:

[0280] The terminal sends the collected user input information and emotion information to the server.

[0281] Step 5:

[0282] The server analyzes the received user information and emotion information. It uses natural language processing to identify the destination and stopover points, and obtains the latest traffic information from the database.

[0283] Step 6:

[0284] The server generates an optimal route using AI based on the analysis results and traffic information. The generated route is an optimal route that takes into account traffic congestion and road closure information, and also includes the stopover points desired by the user. In addition, considering the user's emotion information, it selects a route or guidance method that reduces stress.

[0285] Step 7:

[0286] The server sends the generated optimal route information to the terminal. The route information includes detailed route instructions and information on detour points. It is presented in a tone and content according to the user's emotion.

[0287] Step 8:

[0288] The terminal receives the route information from the server and displays it to the user. For example, it is displayed in the form of "There are two gas stations on this route". Also, when the user is feeling stressed, it provides guidance in a gentle and reassuring tone.

[0289] Step 9:

[0290] Users can provide feedback and additional requests regarding the suggested route through the chatbot. For example, they might ask, "Is there a closer gas station?"

[0291] Step 10:

[0292] The device sends the user feedback information back to the server. The server re-analyzes the data and generates the optimal route based on the new conditions.

[0293] Step 11:

[0294] The server generates a new, optimal route based on feedback and sends it to the terminal. The regenerated route information takes into account the user's additional requests and emotional state.

[0295] Step 12:

[0296] The device receives and displays the new, optimal route to the user. For example, it might say, "We've found a new route that goes through a closer gas station." If the user is feeling stressed, the guidance will be delivered in a calmer tone.

[0297] This series of steps provides users with the most up-to-date traffic information in real time, along with an optimal route that takes into account their individual needs and psychological state.

[0298] (Example 2)

[0299] 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".

[0300] Conventional car navigation systems primarily suggested optimal routes based only on traffic information and the user's destination information. However, they lacked the ability to consider the user's psychological state and feedback when suggesting routes, thus failing to adequately meet the needs of users experiencing stress or anxiety. Furthermore, the lack of a function to receive and regenerate real-time feedback made it difficult to respond quickly and flexibly.

[0301] 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.

[0302] In this invention, the server includes means for collecting traffic information from local governments and manufacturers, means for receiving destinations and points of interest from users as input, means for generating an optimal route based on the collected traffic information, means for presenting the generated optimal route to the user, means for collecting and analyzing user sentiment information, means for receiving feedback from users, and means for generating an optimal route again based on the feedback and sentiment information. This enables flexible and rapid route suggestions that take into account the user's psychological state.

[0303] "Traffic information" refers to data related to road traffic, such as traffic congestion information, accident information, road closure information, and road condition information during disasters.

[0304] A "user" is an individual or group that intends to travel to a destination using a car navigation system.

[0305] "Destination" refers to the place the user wants to reach.

[0306] A "stopover point" refers to a place where a user might consider temporarily staying or visiting on their way to their final destination.

[0307] "Generation means" refers to technology that calculates and proposes the optimal route based on user input information and traffic information.

[0308] "Emotional information" refers to data indicating the psychological state of a user, including emotions such as stress, anxiety, and joy.

[0309] "Feedback" refers to additional requests or evaluations provided by the user.

[0310] "Regeneration means" refers to a technology for recalculating a new optimal route based on feedback and emotional information from the user.

[0311] This invention relates to a car navigation system that collects traffic information in real time and proposes an optimal route considering the emotional information of the user. This system can collect and integrate traffic information provided by local governments and manufacturers, generate an optimal route based on the input information from the user, and further regenerate the route upon receiving feedback from the user.

[0312] Server

[0313] The server has the following functions:

[0314] Data collection and update:

[0315] The server periodically obtains real-time traffic information (such as traffic congestion information, accident information, road closure information, etc.) provided by local governments and manufacturers via an API. The obtained information is stored in a database such as PostgreSQL.

[0316] Training of the generation AI model and route generation:

[0317] Train a generation AI model (such as a general natural language processing model) based on the collected traffic information. This model dynamically generates an optimal route using the user's destination, stop points, real-time traffic conditions, and the user's emotional information provided by the emotion engine. At this time, the following prompt sentences are used:

[0318] If a user says they want to stop at a gas station on their way to Tokyo Station, please generate the optimal route considering traffic information and emotional factors. The user is experiencing stress.

[0319] terminal

[0320] The device has the following features:

[0321] Enter and submit user information:

[0322] The device (e.g., a mobile device) collects information about destinations and points of interest entered by the user through a chatbot. This information is temporarily stored in the device's memory and then sent to the server.

[0323] Collection and analysis of emotional information:

[0324] The device collects the user's voice and text data and analyzes it using an emotion engine (e.g., an emotion analysis API). The analysis results (stress, anxiety, etc.) are sent to the server.

[0325] Route information provided:

[0326] The device displays the optimal route received from the server to the user. This display includes the destination, points of interest, and real-time traffic conditions. The tone of the route guidance is also adjusted according to the user's emotional state.

[0327] Accepting feedback:

[0328] The device receives user feedback and additional requests via a chatbot. This feedback is sent to the server and used to regenerate routes.

[0329] User

[0330] The user performs the following actions:

[0331] Input and feedback:

[0332] Users input their destination and points of interest via the chatbot. For example, they might input, "I want to stop at a gas station on the way to Tokyo Station." After the optimal route is suggested, they can also provide feedback if further improvements are needed, such as "Are there any closer gas stations?"

[0333] Specific example:

[0334] If a user enters "I want to stop at a gas station on the way to Tokyo Station" into the chatbot, the device sends this information to the server. The server generates the optimal route using an AI model based on the collected traffic information, and proposes a route that also takes into account the user's emotional state. The device then informs the user that "this route will allow you to stop at two gas stations along the way," guiding them in a gentle and calm tone to reduce stress. If the user provides feedback such as "Is there a closer gas station?", the server re-analyzes the data and presents the user with a regenerated route based on the new conditions.

[0335] This invention allows users to be presented with the latest traffic information in real time, along with their individual preferences and psychological state, to find the optimal route, enabling comfortable and safe travel.

[0336] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0337] Step 1:

[0338] Data collection

[0339] The server obtains real-time traffic information from traffic information providers via an API. For example, it obtains traffic congestion information, accident information, and road closure information in JSON format. The server analyzes this data, extracts the necessary information, and stores it in a database. The information stored in the database includes location, event type, severity, and timestamp.

[0340] Input: Traffic information obtained from an external API (in JSON format)

[0341] Output: Passage information stored in the database (database update via SQL insert statement)

[0342] Specifically, the server updates the database using the following SQL statement:

[0343] SQL

[0344] INSERT INTO traffic_info (location, event, severity, timestamp)

[0345] VALUES ('Tokyo', 'Accident', 'Severe', '2023-10-01 14:00:00');

[0346] Step 2:

[0347] Enter user information

[0348] The terminal receives information about destinations and points of interest entered by the user through a chatbot. The collected information is temporarily stored in the terminal's memory and then sent to the server.

[0349] Input: User input to the chatbot (text format)

[0350] Output: User destination and stopover information to be sent to the server (in JSON format)

[0351] Specifically, the terminal sends the following JSON data to the server:

[0352] json

[0353] {

[0354] "destination": "Tokyo Station",

[0355] "waypoints": ["Gas Station"]

[0356] }

[0357] Step 3:

[0358] Collection and analysis of emotional information

[0359] The device collects the user's voice and text data and analyzes it using an emotion engine. The emotion engine analyzes the provided data and identifies the user's emotions (stress, anxiety, joy, etc.). The identified emotion information is sent to the server.

[0360] Input: User's voice data or text data (input data)

[0361] Output: Sentiment information as analysis results (JSON format)

[0362] Specifically, the following analysis results are sent to the server:

[0363] json

[0364] {

[0365] "text": "I'm looking for a gas station but I'm worried.",

[0366] "emotion": "stress"

[0367] }

[0368] Step 4:

[0369] Optimal route generation

[0370] The server uses a generative AI model to generate the optimal route based on user input and emotional information. Specifically, it provides the generative AI model with collected traffic information, user instructions, and emotional information as input to generate the best route.

[0371] Input: Traffic information, user's destination and points of interest, sentiment information (internal database and JSON format).

[0372] Output: Optimal route information (JSON format)

[0373] As a concrete example, the following prompt message is input to the generating AI model:

[0374] If a user says they want to stop at a gas station on their way to Tokyo Station, please generate the optimal route considering traffic information and emotional factors. The user is experiencing stress.

[0375] Step 5:

[0376] Presenting route information

[0377] The device displays the optimal route received from the server to the user. This display includes the destination, points of interest, and real-time traffic conditions. The tone of the route guidance is also adjusted according to the user's emotional state.

[0378] Input: Optimal route information received from the server (in JSON format)

[0379] Output: Route information presented to the user (visual display and audio guidance)

[0380] The specific actions presented to the user are as follows:

[0381] "If you use this route, you can stop at two gas stations along the way."

[0382] Step 6:

[0383] Processing user feedback

[0384] The device receives user feedback and additional requests via a chatbot and sends them to the server.

[0385] Input: User feedback (text format)

[0386] Output: Feedback information to send to the server (JSON format)

[0387] As a concrete example of action, consider the following feedback:

[0388] "Is there a gas station closer?"

[0389] Step 7:

[0390] Root regeneration

[0391] The server uses a generative AI model based on user feedback to generate the optimal route again. The regenerated route also takes the user's emotional state into consideration.

[0392] Input: User feedback information (JSON format)

[0393] Output: Regenerated optimal route information (JSON format)

[0394] As a concrete action, the following prompt message is input to the AI ​​model again:

[0395] If a user provides feedback requesting a closer gas station, generate a new, optimal route considering traffic and emotional factors. Users are experiencing stress.

[0396] In this way, the system can provide the optimal route based on real-time, up-to-date traffic information, taking into account the user's psychological state.

[0397] (Application Example 2)

[0398] 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."

[0399] Conventional car navigation systems have the ability to collect real-time traffic information and generate optimal routes, but they do not consider the user's psychological state when suggesting routes. Therefore, inefficient route guidance may be provided even when the user is experiencing stress. Furthermore, the ability to appropriately reflect user feedback and dynamically regenerate routes has been insufficient. Solving these problems and providing a more comfortable and safer driving experience is essential.

[0400] 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.

[0401] In this invention, the server includes means for collecting traffic information from local governments and manufacturers, means for recognizing the user's emotions, means for generating an optimal route based on the collected traffic information, means for presenting the generated optimal route to the user, means for receiving feedback from the user, means for generating the optimal route again based on the feedback, and means for adjusting the optimal route suggestion method based on the recognized emotions. This makes it possible to suggest comfortable and safe routes that reflect the user's psychological state in real time.

[0402] "Local government" refers to local public bodies or similar organizations, and is generally an organization that provides traffic information and disaster information.

[0403] A "manufacturer" is a company or organization that manufactures and provides transportation-related products and infrastructure, and may also be a source of traffic information.

[0404] "Traffic information" refers to all information related to road traffic, including traffic congestion information, accident information, road closure information, and road condition information during disasters.

[0405] "User" refers to an individual or group that uses a car navigation system.

[0406] "Destination" refers to the place the user wants to reach, which is entered into the car's navigation system.

[0407] A "stopover point" refers to a place where a user might want to stop on their way to their destination.

[0408] "Optimal route" refers to the most efficient and safe route, generated based on traffic information and user input.

[0409] "Generation means" refers to devices or software that perform calculations and algorithms for generating the optimal path.

[0410] "Presentation means" refers to displays or audio guidance devices used to show the generated optimal route to the user.

[0411] "Feedback" refers to the evaluations and opinions that users give regarding the paths presented.

[0412] "Regeneration means" refers to devices or software that regenerate the optimal route based on user feedback.

[0413] "Means of recognizing emotions" refers to sensors and data analysis technologies used to analyze a user's emotional state.

[0414] "Means of adjustment" refers to devices or software that modify the method of suggesting the optimal route based on recognized emotions.

[0415] Modes for carrying out the invention

[0416] The embodiments for carrying out the present invention will be described in detail.

[0417] This invention relates to a car navigation system that collects traffic information in real time and proposes the optimal route to the user. This system collects and integrates traffic information provided by local governments and manufacturers, and generates the optimal route based on user feedback. Furthermore, by incorporating an emotion engine that recognizes the user's emotions, it is possible to propose routes that take their psychological state into consideration.

[0418] 1. Server

[0419] The server periodically acquires traffic information provided by local governments and manufacturers and stores it in a database. This includes traffic congestion information, accident information, road closure information, and road condition information during disasters. Based on the collected traffic information, a generative AI model is trained. The generative AI model dynamically generates the optimal route according to the user's requests and current conditions. It also uses the user's sentiment information to adjust the tone and content of route suggestions.

[0420] 2. Terminal

[0421] The terminal accepts input from the user regarding destinations and points of interest. The entered information is temporarily stored on the terminal and then sent to the server. It also features an emotion engine that analyzes the user's voice and text data to identify emotions and sends this information to the server. Furthermore, it displays optimal route information received from the server to the user, adjusting the display method and guidance tone according to the user's emotions. User feedback is also accepted and sent to the server.

[0422] 3. User

[0423] Users input their destination and points of interest through a chatbot. They can also provide feedback after the optimal route is suggested and request a route regeneration.

[0424] System configuration and operation

[0425] In this system, the server uses the following hardware and software:

[0426] APIs as a means of data collection (e.g., Google Maps API, HERE API)

[0427] Database management systems (e.g., MySQL (registered trademark), PostgreSQL)

[0428] Machine learning engines as generative AI models (e.g., TENSORFLOW®, PyTorch)

[0429] Natural language processing tools as emotion engines (e.g., IBM Watson®, Google Cloud Natural Language)

[0430] The device uses the following hardware and software:

[0431] Touchscreens and voice recognition systems for accepting user input (e.g., Google Voice API, Apple Siri)

[0432] Voice and image analysis technologies for identifying emotions (e.g., OpenCV, Microsoft® Azure® Cognitive Services)

[0433] UI / UX interfaces for adjusting display methods and tone (e.g., React Native, Flutter®)

[0434] Adding specific examples

[0435] For example, if a user sets a destination for an autonomous vehicle via a smartphone app and inputs that they want to stop at a cafe along the way, the autonomous driving system will suggest the least stressful route based on the latest traffic information and the user's sentiment data. A chatbot will gently confirm the request and suggest the best cafe, and readjust the route based on the user's feedback.

[0436] Example of a prompt

[0437] Please generate a program for a navigation application for autonomous vehicles. This application will collect real-time traffic information, suggest the optimal route, and use the in-car camera and microphone to recognize passenger emotions. It will adjust the route based on emotion data and combine it with a chatbot for a user-friendly conversation.

[0438] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0439] Step 1:

[0440] The server periodically acquires traffic information provided by local governments and manufacturers. This information is collected via APIs (e.g., Google Maps API, HERE API). The collected traffic congestion information, accident information, road closure information, and road condition information during disasters are stored in a database system (e.g., MySQL, PostgreSQL).

[0441] Input: Traffic information obtained from API

[0442] Output: Traffic information stored in the database

[0443] Step 2:

[0444] The terminal accepts input from the user regarding their destination and points of interest. This information is collected interactively through a chatbot and temporarily stored on the terminal.

[0445] Input: Destination and stopover points entered by the user.

[0446] Output: Input information stored in the device's temporary storage.

[0447] Step 3:

[0448] The device analyzes the user's voice and text data and uses an emotion engine (e.g., IBM Watson, Google Cloud Natural Language) to identify the user's emotions. This emotion information is then sent to the server.

[0449] Input: User's voice data and text data

[0450] Output: Sentiment information sent to the server

[0451] Step 4:

[0452] The server generates the optimal route using a generative AI model (e.g., TensorFlow, PyTorch) based on collected traffic information, user input information, and sentiment information. The generated optimal route is then sent from the server to the terminal.

[0453] Input: Traffic information retrieved from the database, user input information, sentiment information

[0454] Output: Generated optimal path

[0455] Step 5:

[0456] The terminal presents the user with optimal route information sent from the server. The display method and tone of guidance are adjusted based on the user's emotions, as determined by an emotion engine.

[0457] Input: Optimal routing information sent from the server

[0458] Output: Route information presented to the user

[0459] Step 6:

[0460] Users provide feedback on the suggested routes through the chatbot. This feedback information is sent from the device to the server.

[0461] Input: User feedback

[0462] Output: Feedback information sent to the server

[0463] Step 7:

[0464] Based on the feedback information received, the server regenerates the optimal route using a regenerative AI model. The regenerated optimal route information is then adjusted to take emotional information into consideration and sent to the terminal.

[0465] Input: User feedback information, sentiment information, traffic information

[0466] Output: Regenerated optimal route information

[0467] This series of processing steps allows users to obtain the latest traffic information and the optimal route tailored to their psychological state in real time.

[0468] 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.

[0469] 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.

[0470] 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.

[0471] [Second Embodiment]

[0472] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0473] 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.

[0474] 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).

[0475] 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.

[0476] 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.

[0477] 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).

[0478] 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.

[0479] 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.

[0480] 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.

[0481] 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.

[0482] 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.

[0483] 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".

[0484] The embodiments for carrying out the present invention will be described in detail.

[0485] First, the present invention relates to a car navigation system that collects traffic information in real time and proposes the optimal route to the user. This system collects and integrates traffic information provided by local governments and manufacturers, and generates the optimal route based on user input information. Furthermore, it has a function to regenerate the route as needed based on user feedback.

[0486] composition

[0487] 1. Server

[0488] Data collection and database updating:

[0489] The server periodically collects traffic information provided by local governments and manufacturers. This includes traffic congestion information, accident information, road closure information, and road condition information during disasters. The collected information is stored and updated in a database.

[0490] Generative AI models:

[0491] The server trains a generative AI model based on collected traffic information and builds an algorithm to generate the optimal route. The generative AI model can dynamically generate the optimal route according to user requests and current conditions.

[0492] 2. Terminal

[0493] Enter and submit user information:

[0494] The terminal accepts the user's destination and points of interest as input. A chatbot is used to collect detailed information such as the user's desired points of interest and waypoints. The collected information is sent to the server.

[0495] Route information provided:

[0496] The system displays optimal route information received from the server to the user. This information includes not only the destination, but also designated points of interest and real-time traffic conditions.

[0497] Feedback processing:

[0498] The system accepts user feedback and additional requests, and resends them to the server. This allows for regeneration according to the user's preferences.

[0499] 3. User

[0500] Input and feedback:

[0501] Users input their destination and points of interest through a chatbot. After the optimal route is suggested, they can also provide feedback if further improvements are needed, requesting a route regeneration.

[0502] Specific example

[0503] For example, consider a case where a user enters "I want to stop at a gas station on the way to Tokyo Station."

[0504] Data collection and analysis:

[0505] The server retrieves the latest information from the traffic information database and performs analysis. It identifies the destination as "Tokyo Station" and the stopping point as "gas station."

[0506] Generating the optimal route:

[0507] The AI ​​model generates the optimal route based on this information, taking into account current traffic conditions. For example, it might suggest a route that avoids congestion while also stopping at gas stations as requested by the user.

[0508] Route suggestion and correction:

[0509] The device displays the initial route to the user and suggests, "This route will take you past two gas stations." If the user provides feedback such as, "Is there a closer gas station?", the server re-analyzes the route and generates a new optimal route. This new route information is sent to the device, and the user is shown, "We have found a new route that goes past a closer gas station."

[0510] In this way, the car navigation system of the present invention can provide an optimal route that dynamically reflects real-time traffic information and user requests.

[0511] The following describes the processing flow.

[0512] Step 1:

[0513] The server periodically collects traffic information provided by local governments and manufacturers. This information includes traffic congestion, accidents, road closures, and road conditions during disasters. The collected information is stored in a database and updated in real time.

[0514] Step 2:

[0515] The terminal accepts the user's destination and points of interest as input. It interactively collects user input through a chatbot (e.g., "I want to stop at a gas station on the way to Tokyo Station"). The entered information is temporarily stored on the terminal.

[0516] Step 3:

[0517] The device sends the collected user input information to the server. This information includes destination, points of interest, and other specific preferences.

[0518] Step 4:

[0519] The server analyzes the received user information. Using natural language processing, it identifies the destination and points of interest, and retrieves the latest traffic information from the database.

[0520] Step 5:

[0521] The server generates the optimal route using AI based on analysis results and traffic information. The generated route is the best possible path, taking into account traffic congestion and road closures, and including the user's desired stops.

[0522] Step 6:

[0523] The server sends the generated optimal route information to the terminal. The route information includes detailed route instructions and information about potential detours.

[0524] Step 7:

[0525] The terminal receives route information from the server and displays it to the user. For example, it might display something like, "If you use this route, there are two gas stations along the way."

[0526] Step 8:

[0527] Users can provide feedback and additional requests regarding the suggested route through the chatbot. For example, they might ask, "Is there a closer gas station?"

[0528] Step 9:

[0529] The device sends the user feedback information back to the server. The server re-analyzes the data and generates the optimal route based on the new conditions.

[0530] Step 10:

[0531] The server generates a new, optimal route based on the feedback and sends it to the terminal. The regenerated route information also takes into account any additional requests from the user.

[0532] Step 11:

[0533] The device receives new, optimal routes and displays them to the user. For example, it might display, "We found a new route that goes through a closer gas station."

[0534] This series of steps allows users to obtain real-time, up-to-date traffic information and the optimal route tailored to their needs.

[0535] (Example 1)

[0536] 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."

[0537] Conventional car navigation systems often fail to adequately reflect real-time traffic information, making it difficult to suggest the optimal route for the user. Furthermore, they lack convenience due to their inability to quickly respond to additional user requests and feedback. Additionally, they do not fully utilize artificial intelligence technology for collecting traffic information and generating optimal routes.

[0538] 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.

[0539] In this invention, the server includes means for collecting traffic information from local governments and manufacturers, means for receiving destinations and points of interest from users as input, means for generating an optimal route based on the collected traffic information, means for presenting the generated optimal route to the user, means for receiving feedback from the user, means for generating the optimal route again based on the feedback, and means for training a generation AI model that provides the generated optimal route to the user. This makes it possible to dynamically reflect real-time traffic information and quickly provide the optimal route that meets the user's needs.

[0540] A "local government" is a local government agency that provides public services and manages administrative affairs.

[0541] A "manufacturer" is a company or organization that produces or manufactures products.

[0542] "Traffic information" refers to traffic-related data such as road congestion, accident information, road closure information, and road conditions during disasters.

[0543] "Means" refers to the methods or devices used to achieve a specific objective.

[0544] A "user" is an individual or group that uses the system.

[0545] The "destination" is the final point that the user aims to reach.

[0546] A "stopover point" is a specific location that a user might want to visit before reaching their destination.

[0547] A "generation method" refers to a method or apparatus that performs calculations or analyses based on specific data to generate results.

[0548] "Presentation means" refers to a method or device for displaying or providing generated information to a user.

[0549] "Feedback" refers to the opinions and requests that users provide regarding the system's suggestions and results.

[0550] A "generative AI model" is an algorithm or program that uses artificial intelligence technology to analyze data and generate specific results.

[0551] "Training methods" refer to the methods and devices used to train models or algorithms.

[0552] Modes for carrying out the invention

[0553] The embodiments for carrying out the present invention will be described in detail. First, the present invention relates to a car navigation system that collects traffic information in real time and proposes the optimal route to the user. This system collects and integrates traffic information provided by local governments and manufacturers and generates the optimal route based on user input information. Furthermore, it has a function to regenerate the route as needed based on user feedback.

[0554] 1. Server roles and processing

[0555] The server is primarily responsible for collecting traffic information, training the AI ​​model for generating traffic, and generating the optimal route. Specifically, it performs the following processes:

[0556] Data collection and database updating:

[0557] The server collects traffic information from local governments and manufacturers via APIs at specific times each day. This information includes traffic congestion, accidents, road closures, and road conditions during disasters. This information is stored in the server's database and updated by comparing it with existing data.

[0558] Training generative AI models and generating optimal routes:

[0559] The server trains a generative AI model based on the collected traffic information. This model uses destination and stopover information received from the user, along with real-time traffic data, to generate the optimal route. The generated route information is then sent to the user's device.

[0560] 2. Terminal roles and processing

[0561] The terminal collects user input information and sends it to the server. It also has the role of presenting the user with the optimal route information received from the server. The specific process is as follows:

[0562] Enter and submit user information:

[0563] The terminal uses a chatbot to receive information about destinations and points of interest entered by the user. For example, if a user enters "I want to stop at a gas station on the way to Tokyo Station," that information is sent to the server.

[0564] Route information provided:

[0565] The terminal, having received optimal route information from the server, presents that information to the user. The displayed information includes the destination, points of interest, and real-time traffic conditions.

[0566] Accepting feedback:

[0567] When a user provides feedback on the suggested route, that information is also sent from the terminal to the server. For example, if a user provides feedback such as "Is there a closer gas station?", that information is sent back to the server, and the process of generating a new optimal route is initiated.

[0568] 3. User roles and operations

[0569] Users input their destination, points of interest, and feedback through a chatbot. This allows the system to suggest the optimal route based on real-time traffic information.

[0570] Specific example:

[0571] For example, consider the process when a user inputs, "I want to stop at a gas station on the way to Tokyo Station."

[0572] Data collection and analysis:

[0573] The server retrieves the latest information from the traffic information database and performs analysis. It identifies the destination as "Tokyo Station" and the stopping point as "gas station."

[0574] Generating the optimal route:

[0575] The AI ​​model generates the optimal route based on this information, taking into account current traffic conditions. For example, it might suggest a route that avoids congestion while also stopping at gas stations as requested by the user.

[0576] Route guidance and feedback:

[0577] The device displays the initial route to the user and suggests, "This route will take you past two gas stations." If the user provides feedback such as, "Is there a closer gas station?", the server re-analyzes the route and generates a new optimal route. This new route information is sent to the device, and the user is shown, "We have found a new route that goes past a closer gas station."

[0578] Example of a prompt:

[0579] This system generates algorithms for car navigation systems. The system receives destination and stopover information from the user and provides the optimal route based on real-time traffic conditions. This system can update a traffic information database and generate the optimal route using a generated AI model.

[0580] In this way, the car navigation system of the present invention can provide an optimal route that dynamically reflects real-time traffic information and user requests.

[0581] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0582] System program processing steps

[0583] Step 1:

[0584] Data collection

[0585] The server collects traffic information from local governments and manufacturers via an API at a specific time each day. The input is traffic information data obtained from the API. The server parses this data, processes it into the required format, and stores it in the database.

[0586] Specific actions:

[0587] The server executes the "Traffic Information Update" script.

[0588] A request is sent to the API endpoint, and the JSON data received as a response is parsed.

[0589] The parsed data is stored in the database.

[0590] Step 2:

[0591] Database update

[0592] The collected traffic information is stored in the server's database. This ensures that the traffic information is always up-to-date. The input is the parsed traffic information data, and the output is the updated state of the database.

[0593] Specific actions:

[0594] The server compares the new data with the existing data.

[0595] Update existing data as needed to keep the database up to date.

[0596] Step 3:

[0597] Enter user information

[0598] The terminal receives information from the user regarding the destination and points of interest. The input is information entered by the user via the chatbot, and the output is data sent to the server.

[0599] Specific actions:

[0600] The user opens the chatbot and enters their destination and points of interest.

[0601] The terminal collects the information entered and sends it to the server.

[0602] Step 4:

[0603] Optimal route generation

[0604] The server generates the optimal route using a generative AI model based on destination and stopover point information received from the user. The input is user information and real-time traffic information data, and the output is the generated optimal route data.

[0605] Specific actions:

[0606] The server receives the user's input information.

[0607] The collected traffic information and input information are supplied to the generating AI model.

[0608] The generative AI model calculates the optimal route and generates the result.

[0609] The generated route information is sent to the terminal.

[0610] Step 5:

[0611] Presenting route information

[0612] The terminal displays the optimal route information received from the server to the user. The input is the optimal route data received from the server, and the output is the data displayed to the user.

[0613] Specific actions:

[0614] The terminal receives route information from the server.

[0615] Route information is displayed to the user on the screen.

[0616] For example, it could display information such as, "There are two gas stations along the route to Tokyo Station."

[0617] Step 6:

[0618] Processing user feedback

[0619] The device receives feedback from the user and sends it back to the server. The input is the feedback information provided by the user, and the output is the data sent to the server.

[0620] Specific actions:

[0621] The user enters feedback into the chatbot.

[0622] The device sends that feedback information to the server.

[0623] Step 7:

[0624] Regenerating the route

[0625] The server generates a new optimal route based on user feedback. The input is feedback information and the latest traffic information data, and the output is the regenerated optimal route data.

[0626] Specific actions:

[0627] The server receives feedback.

[0628] A generative AI model is used to calculate a new optimal route.

[0629] Send the calculation result to the terminal.

[0630] In this way, information exchange between the server, terminal, and user makes it possible to dynamically provide the optimal route based on real-time traffic information.

[0631] (Application Example 1)

[0632] 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."

[0633] Conventional car navigation systems, while providing optimal routes based on real-time traffic information, lacked sufficient integration with autonomous vehicles, requiring user intervention. Furthermore, their feedback-based route regeneration capabilities were inadequate, making sudden changes or optimal responses difficult. This resulted in limitations on user convenience.

[0634] 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.

[0635] In this invention, the server includes means for collecting traffic information from local governments and manufacturers, means for receiving destinations and points of interest from users as input, means for generating an optimal route based on the collected traffic information, means for presenting the generated optimal route to the user, means for receiving feedback from the user, means for generating the optimal route again based on the feedback, and means for issuing instructions related to the operation control of the vehicle. This makes it possible to provide optimal routes for autonomous vehicles based on real-time traffic information, significantly improving user convenience and safety.

[0636] "Local government" refers to a local public body, an organization that functions as a provider of traffic information.

[0637] "Manufacturers" refers to companies that manufacture automobiles and transportation-related equipment, and the term also refers to traffic information provided by these companies.

[0638] "Traffic information" refers to real-time information such as traffic congestion, accidents, road closures, and road conditions during disasters.

[0639] "User" refers to an individual or organization that uses a car navigation system.

[0640] "Destination" refers to the place the user ultimately wants to reach.

[0641] A "stopover point" refers to a location that a user might want to visit on their way to their destination.

[0642] "Generation means" refers to the technologies and algorithms used to calculate the optimal route based on collected traffic information.

[0643] "Presentation means" refers to technologies and devices used to display the generated optimal route on the user's device.

[0644] "Feedback" refers to additional requests and information provided by users.

[0645] "Regeneration means" refers to technologies and algorithms for calculating a new optimal path based on feedback.

[0646] "Vehicle operation control" refers to the operations and instructions related to the driving of autonomous vehicles.

[0647] A "generative AI model" refers to an algorithm or system that uses artificial intelligence (AI) technology to generate the optimal path.

[0648] The embodiments for carrying out the present invention will be described in detail.

[0649] First, the system of this invention collects traffic information from local governments and manufacturers, accepts input from users regarding destinations and points of interest, and generates and presents an optimal route based on that information. It also has a function to receive feedback from users and generate an optimal route again. Furthermore, this system can also issue instructions related to the operation control of vehicles.

[0650] server

[0651] The server has the following functions:

[0652] 1. Data Collection: The server periodically collects traffic information provided by local governments and manufacturers. This information includes traffic congestion information, accident information, road closure information, and road condition information during disasters.

[0653] 2. Use of Generative AI Model: The server trains a generative AI model based on collected traffic information and builds an algorithm to generate the optimal route. The generative AI model can dynamically generate the optimal route according to user requests and current conditions.

[0654] 3. Route generation and presentation: The generated optimal route is sent to the user's terminal and presented to the user.

[0655] As a concrete example, here is a prompt message in which the server identifies the destination as "Tokyo Station" and the stopover point as "gas station":

[0656] Please enter your destination: Tokyo Station

[0657] Please enter your stopping points (multiple points are allowed, separated by commas): Gas station

[0658] terminal

[0659] The device has the following features:

[0660] 1. User Input and Transmission: The terminal accepts input from the user regarding the destination and points of interest. Using a chatbot, it collects detailed information such as the user's desired points of interest and waypoints, and sends it to the server.

[0661] 2. Presenting Route Information: The system presents the user with the optimal route information received from the server. The displayed information includes not only the destination but also designated points of interest and real-time traffic conditions.

[0662] 3. Feedback Processing: User feedback and additional requests are received and resent to the server. This allows for regeneration according to the user's wishes.

[0663] user

[0664] The user performs the following actions:

[0665] 1. Input and Feedback: Users input their destination and points of interest through the chatbot. After the optimal route is presented, they can also provide feedback if further improvements are needed, requesting a route regeneration.

[0666] These functions and operations enable the system of the present invention to dynamically provide the optimal route for the user based on real-time traffic information. In particular, in autonomous vehicles, by issuing instructions related to operation control, it is possible to achieve safe and efficient driving while minimizing user intervention.

[0667] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0668] Step 1:

[0669] The server periodically collects traffic information provided by local governments and manufacturers. This process involves obtaining traffic congestion information, accident information, road closure information, and road condition information during disasters via APIs and databases. The input is traffic information data from various sources, which the server collects, stores in its database, and updates to maintain the latest traffic information. The output is the most recent traffic data stored on the server.

[0670] Step 2:

[0671] The user enters their destination and points of interest using their device. The user enters this information in text format through the device's chatbot. The input is text data of the destination and points of interest, which the device receives and then sends to the server. The output is the user's destination and points of interest data sent to the server.

[0672] Step 3:

[0673] The server references a database of collected traffic information based on the user's destination and stopover data. Here, a generative AI model is used to generate the optimal route. The input consists of the user-specified destination and stopovers, along with the latest traffic information. The server analyzes this data using the generative AI model to generate the optimal route. The output is the generated optimal route information.

[0674] Step 4:

[0675] The server sends the generated optimal route information to the user's terminal. The input is the generated optimal route information, which the server sends to the terminal. The output is the optimal route information displayed on the user's terminal. The user then starts driving based on this information.

[0676] Step 5:

[0677] Users input feedback and additional requests through the terminal. For example, feedback such as "Is there a closer gas station?" is possible. The input is the user's feedback text, which the terminal receives and then sends back to the server. The output is the user feedback data sent to the server.

[0678] Step 6:

[0679] The server, based on user feedback, consults the traffic information database again and uses a generative AI model to generate a new optimal route. The input consists of the feedback and the latest traffic information, and the server generates a regenerated optimal route based on this. The output is the newly generated optimal route information.

[0680] Step 7:

[0681] The server sends the regenerated optimal route information to the user's terminal. The input is the regenerated optimal route information, which the server sends to the terminal. The output is the new optimal route information displayed on the user's terminal. The user adjusts their driving based on this information.

[0682] 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.

[0683] The embodiments for carrying out the present invention will be described in detail.

[0684] This invention relates to a car navigation system that collects traffic information in real time and proposes the optimal route to the user. This system collects and integrates traffic information provided by local governments and manufacturers, and generates the optimal route based on user input. Furthermore, it has a function to regenerate the route as needed based on user feedback. In addition, this invention can propose routes that take into account the user's psychological state by incorporating an emotion engine that recognizes the user's emotions.

[0685] composition

[0686] 1. Server

[0687] Data collection and database updating:

[0688] The server periodically acquires traffic information provided by local governments and manufacturers, and the collected information is stored in a database. This includes traffic congestion information, accident information, road closure information, and road condition information during disasters.

[0689] Generative AI models:

[0690] The server trains a generative AI model based on collected traffic information. The generative AI model dynamically generates the optimal route according to the user's requests and current conditions. It also uses user sentiment information provided by the sentiment engine to adjust the tone and content of route suggestions.

[0691] 2. Terminal

[0692] Enter and submit user information:

[0693] The terminal accepts input from the user regarding their destination and points of interest. This input information is collected interactively, for example through a chatbot, and temporarily stored within the terminal. This information is then sent to the server.

[0694] Collection and analysis of emotional information:

[0695] The emotion engine analyzes the user's voice and text data to identify their emotions. The identified emotion information is then sent to the server.

[0696] Route information provided:

[0697] The system displays optimal route information received from the server to the user. The displayed information includes the destination, points of interest, and real-time traffic conditions. An emotion engine adjusts the display method and tone of guidance based on the user's emotions.

[0698] Feedback processing:

[0699] The system receives user feedback and additional requests through a chatbot and sends them to the server.

[0700] 3. User

[0701] Input and feedback:

[0702] Users input their destination and points of interest through a chatbot. After the optimal route is suggested, they can also provide feedback if further improvements are needed and request a route regeneration.

[0703] Specific example

[0704] For example, consider a case where a user inputs "I want to stop at a gas station on the way to Tokyo Station," and this input is accompanied by expressions of stress or anxiety.

[0705] Data collection and analysis:

[0706] The server retrieves the latest information from the traffic information database and performs analysis. It identifies the destination as "Tokyo Station" and the stopping point as "gas station."

[0707] Analysis of emotional information:

[0708] The emotion engine analyzes emotional information from the user's input and voice to detect stress and anxiety.

[0709] Generating the optimal route:

[0710] The generative AI model generates the optimal route based on user instructions and emotional information. For example, it suggests a route that avoids traffic jams, stops at the user's preferred gas station, and further reduces stress.

[0711] Route suggestion and adjustment:

[0712] The terminal presents the generated route to the user and provides guidance such as, "If you use this route, you can stop at two gas stations along the way." The information is presented in a gentle and calming tone to reduce user stress.

[0713] Feedback and regeneration:

[0714] If a user provides feedback such as "Is there a closer gas station?", the server re-analyzes the data and generates an optimal route based on the new conditions. The regenerated route similarly takes into account the user's emotional state, as determined by the emotion engine.

[0715] This series of steps allows users to be presented with the latest traffic information in real time, along with their individual preferences and even their psychological state, to find the optimal route, enabling a comfortable and safe journey.

[0716] The following describes the processing flow.

[0717] Step 1:

[0718] The server periodically collects traffic information provided by local governments and manufacturers. This information includes traffic congestion, accident information, road closure information, and road condition information during disasters. The collected information is stored in a database and updated in real time.

[0719] Step 2:

[0720] The terminal accepts the user's destination and points of interest as input. It interactively collects user input through a chatbot (e.g., "I want to stop at a gas station on the way to Tokyo Station"). The entered information is temporarily stored on the terminal.

[0721] Step 3:

[0722] The emotion engine analyzes the user's voice and text data to identify emotions. For example, it identifies emotions such as stress, anxiety, and joy based on the user's tone of voice and entered text.

[0723] Step 4:

[0724] The device transmits the collected user input information and sentiment information to the server.

[0725] Step 5:

[0726] The server analyzes the received user information and sentiment information. It uses natural language processing to identify destinations and points of interest, and retrieves the latest traffic information from the database.

[0727] Step 6:

[0728] The server generates the optimal route using AI based on analysis results and traffic information. The generated route is the best possible path, taking into account traffic congestion and road closures, and including the user's desired stops. It also considers the user's emotional state to select a route and guidance method that reduces stress.

[0729] Step 7:

[0730] The server sends the generated optimal route information to the terminal. This route information includes detailed directions and information on potential detours. It is presented in a tone and content that reflects the user's emotions.

[0731] Step 8:

[0732] The terminal receives route information from the server and displays it to the user. For example, it might display something like, "If you use this route, there are two gas stations along the way." Furthermore, if the user is feeling stressed, the guidance will be provided in a calm and reassuring tone.

[0733] Step 9:

[0734] Users can provide feedback and additional requests regarding the suggested route through the chatbot. For example, they might ask, "Is there a closer gas station?"

[0735] Step 10:

[0736] The device sends the user feedback information back to the server. The server re-analyzes the data and generates the optimal route based on the new conditions.

[0737] Step 11:

[0738] The server generates a new, optimal route based on feedback and sends it to the terminal. The regenerated route information takes into account the user's additional requests and emotional state.

[0739] Step 12:

[0740] The device receives and displays the new, optimal route to the user. For example, it might say, "We've found a new route that goes through a closer gas station." If the user is feeling stressed, the guidance will be delivered in a calmer tone.

[0741] This series of steps provides users with the most up-to-date traffic information in real time, along with an optimal route that takes into account their individual needs and psychological state.

[0742] (Example 2)

[0743] 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".

[0744] Conventional car navigation systems primarily suggested optimal routes based only on traffic information and the user's destination information. However, they lacked the ability to consider the user's psychological state and feedback when suggesting routes, thus failing to adequately meet the needs of users experiencing stress or anxiety. Furthermore, the lack of a function to receive and regenerate real-time feedback made it difficult to respond quickly and flexibly.

[0745] 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.

[0746] In this invention, the server includes means for collecting traffic information from local governments and manufacturers, means for receiving destinations and points of interest from users as input, means for generating an optimal route based on the collected traffic information, means for presenting the generated optimal route to the user, means for collecting and analyzing user sentiment information, means for receiving feedback from users, and means for generating an optimal route again based on the feedback and sentiment information. This enables flexible and rapid route suggestions that take into account the user's psychological state.

[0747] "Traffic information" refers to data related to road traffic, such as traffic congestion information, accident information, road closure information, and road condition information during disasters.

[0748] A "user" is an individual or group that intends to travel to a destination using a car navigation system.

[0749] "Destination" refers to the place the user wants to reach.

[0750] A "stopover point" refers to a place where a user might consider temporarily staying or visiting on their way to their final destination.

[0751] "Generation means" refers to technology that calculates and proposes the optimal route based on user input information and traffic information.

[0752] "Emotional information" refers to data that indicates the user's psychological state, including emotions such as stress, anxiety, and joy.

[0753] "Feedback" refers to additional requests or evaluations provided by users.

[0754] "Regeneration methods" refer to technologies that recalculate the optimal route based on user feedback and emotional information.

[0755] This invention relates to a car navigation system that collects traffic information in real time and proposes an optimal route that takes into account the user's emotional information. This system collects and integrates traffic information provided by local governments and manufacturers, generates an optimal route based on user input information, and can further regenerate the route based on user feedback.

[0756] server

[0757] The server has the following functions:

[0758] Data collection and updating:

[0759] The server periodically retrieves real-time traffic information (e.g., traffic congestion information, accident information, road closure information, etc.) provided by local governments and manufacturers via APIs. The retrieved information is stored in a database such as PostgreSQL.

[0760] Training and route generation for generative AI models:

[0761] A generative AI model (e.g., a general natural language processing model) is trained based on the collected traffic information. This model dynamically generates the optimal route using the user's destination and points of interest, real-time traffic conditions, and user sentiment information provided by the sentiment engine. The following prompt statements are used during this process:

[0762] If a user says they want to stop at a gas station on their way to Tokyo Station, please generate the optimal route considering traffic information and emotional factors. The user is experiencing stress.

[0763] terminal

[0764] The device has the following features:

[0765] Enter and submit user information:

[0766] The device (e.g., a mobile device) collects information about destinations and points of interest entered by the user through a chatbot. This information is temporarily stored in the device's memory and then sent to the server.

[0767] Collection and analysis of emotional information:

[0768] The device collects the user's voice and text data and analyzes it using an emotion engine (e.g., an emotion analysis API). The analysis results (stress, anxiety, etc.) are sent to the server.

[0769] Route information provided:

[0770] The device displays the optimal route received from the server to the user. This display includes the destination, points of interest, and real-time traffic conditions. The tone of the route guidance is also adjusted according to the user's emotional state.

[0771] Accepting feedback:

[0772] The device receives user feedback and additional requests via a chatbot. This feedback is sent to the server and used to regenerate routes.

[0773] User

[0774] The user performs the following actions:

[0775] Input and feedback:

[0776] Users input their destination and points of interest via the chatbot. For example, they might input, "I want to stop at a gas station on the way to Tokyo Station." After the optimal route is suggested, they can also provide feedback if further improvements are needed, such as "Are there any closer gas stations?"

[0777] Specific example:

[0778] If a user enters "I want to stop at a gas station on the way to Tokyo Station" into the chatbot, the device sends this information to the server. The server generates the optimal route using an AI model based on the collected traffic information, and proposes a route that also takes into account the user's emotional state. The device then informs the user that "this route will allow you to stop at two gas stations along the way," guiding them in a gentle and calm tone to reduce stress. If the user provides feedback such as "Is there a closer gas station?", the server re-analyzes the data and presents the user with a regenerated route based on the new conditions.

[0779] This invention allows users to be presented with the latest traffic information in real time, along with their individual preferences and psychological state, to find the optimal route, enabling comfortable and safe travel.

[0780] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0781] Step 1:

[0782] Data collection

[0783] The server obtains real-time traffic information from traffic information providers via an API. For example, it obtains traffic congestion information, accident information, and road closure information in JSON format. The server analyzes this data, extracts the necessary information, and stores it in a database. The information stored in the database includes location, event type, severity, and timestamp.

[0784] Input: Traffic information obtained from an external API (in JSON format)

[0785] Output: Passage information stored in the database (database update via SQL insert statement)

[0786] Specifically, the server updates the database using the following SQL statement:

[0787] SQL

[0788] INSERT INTO traffic_info (location, event, severity, timestamp)

[0789] VALUES ('Tokyo', 'Accident', 'Severe', '2023-10-01 14:00:00');

[0790] Step 2:

[0791] Enter user information

[0792] The terminal receives information about destinations and points of interest entered by the user through a chatbot. The collected information is temporarily stored in the terminal's memory and then sent to the server.

[0793] Input: User input to the chatbot (text format)

[0794] Output: User destination and stopover information to be sent to the server (in JSON format)

[0795] Specifically, the terminal sends the following JSON data to the server:

[0796] json

[0797] {

[0798] "destination": "Tokyo Station",

[0799] "waypoints": ["Gas Station"]

[0800] }

[0801] Step 3:

[0802] Collection and analysis of emotional information

[0803] The device collects the user's voice and text data and analyzes it using an emotion engine. The emotion engine analyzes the provided data and identifies the user's emotions (stress, anxiety, joy, etc.). The identified emotion information is sent to the server.

[0804] Input: User's voice data or text data (input data)

[0805] Output: Sentiment information as analysis results (JSON format)

[0806] Specifically, the following analysis results are sent to the server:

[0807] json

[0808] {

[0809] "text": "I'm looking for a gas station but I'm worried.",

[0810] "emotion": "stress"

[0811] }

[0812] Step 4:

[0813] Optimal route generation

[0814] The server uses a generative AI model to generate the optimal route based on user input and emotional information. Specifically, it provides the generative AI model with collected traffic information, user instructions, and emotional information as input to generate the best route.

[0815] Input: Traffic information, user's destination and points of interest, sentiment information (internal database and JSON format).

[0816] Output: Optimal route information (JSON format)

[0817] As a concrete example, the following prompt message is input to the generating AI model:

[0818] If a user says they want to stop at a gas station on their way to Tokyo Station, please generate the optimal route considering traffic information and emotional factors. The user is experiencing stress.

[0819] Step 5:

[0820] Presenting route information

[0821] The device displays the optimal route received from the server to the user. This display includes the destination, points of interest, and real-time traffic conditions. The tone of the route guidance is also adjusted according to the user's emotional state.

[0822] Input: Optimal route information received from the server (in JSON format)

[0823] Output: Route information presented to the user (visual display and audio guidance)

[0824] The specific actions presented to the user are as follows:

[0825] "If you use this route, you can stop at two gas stations along the way."

[0826] Step 6:

[0827] Processing user feedback

[0828] The device receives user feedback and additional requests via a chatbot and sends them to the server.

[0829] Input: User feedback (text format)

[0830] Output: Feedback information to send to the server (JSON format)

[0831] As a concrete example of action, consider the following feedback:

[0832] "Is there a gas station closer?"

[0833] Step 7:

[0834] Root regeneration

[0835] The server uses a generative AI model based on user feedback to generate the optimal route again. The regenerated route also takes the user's emotional state into consideration.

[0836] Input: User feedback information (JSON format)

[0837] Output: Regenerated optimal route information (JSON format)

[0838] As a concrete action, the following prompt message is input to the AI ​​model again:

[0839] If a user provides feedback requesting a closer gas station, generate a new, optimal route considering traffic and emotional factors. Users are experiencing stress.

[0840] In this way, the system can provide the optimal route based on real-time, up-to-date traffic information, taking into account the user's psychological state.

[0841] (Application Example 2)

[0842] 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."

[0843] Conventional car navigation systems have the ability to collect real-time traffic information and generate optimal routes, but they do not consider the user's psychological state when suggesting routes. Therefore, inefficient route guidance may be provided even when the user is experiencing stress. Furthermore, the ability to appropriately reflect user feedback and dynamically regenerate routes has been insufficient. Solving these problems and providing a more comfortable and safer driving experience is essential.

[0844] 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.

[0845] In this invention, the server includes means for collecting traffic information from local governments and manufacturers, means for recognizing the user's emotions, means for generating an optimal route based on the collected traffic information, means for presenting the generated optimal route to the user, means for receiving feedback from the user, means for generating the optimal route again based on the feedback, and means for adjusting the optimal route suggestion method based on the recognized emotions. This makes it possible to suggest comfortable and safe routes that reflect the user's psychological state in real time.

[0846] "Local government" refers to local public bodies or similar organizations, and is generally an organization that provides traffic information and disaster information.

[0847] A "manufacturer" is a company or organization that manufactures and provides transportation-related products and infrastructure, and may also be a source of traffic information.

[0848] "Traffic information" refers to all information related to road traffic, including traffic congestion information, accident information, road closure information, and road condition information during disasters.

[0849] "User" refers to an individual or group that uses a car navigation system.

[0850] "Destination" refers to the place the user wants to reach, which is entered into the car's navigation system.

[0851] A "stopover point" refers to a place where a user might want to stop on their way to their destination.

[0852] "Optimal route" refers to the most efficient and safe route, generated based on traffic information and user input.

[0853] "Generation means" refers to devices or software that perform calculations and algorithms for generating the optimal path.

[0854] "Presentation means" refers to displays or audio guidance devices used to show the generated optimal route to the user.

[0855] "Feedback" refers to the evaluations and opinions that users give regarding the paths presented.

[0856] "Regeneration means" refers to devices or software that regenerate the optimal route based on user feedback.

[0857] "Means of recognizing emotions" refers to sensors and data analysis technologies used to analyze a user's emotional state.

[0858] "Means of adjustment" refers to devices or software that modify the method of suggesting the optimal route based on recognized emotions.

[0859] Modes for carrying out the invention

[0860] The embodiments for carrying out the present invention will be described in detail.

[0861] This invention relates to a car navigation system that collects traffic information in real time and proposes the optimal route to the user. This system collects and integrates traffic information provided by local governments and manufacturers, and generates the optimal route based on user feedback. Furthermore, by incorporating an emotion engine that recognizes the user's emotions, it is possible to propose routes that take their psychological state into consideration.

[0862] 1. Server

[0863] The server periodically acquires traffic information provided by local governments and manufacturers and stores it in a database. This includes traffic congestion information, accident information, road closure information, and road condition information during disasters. Based on the collected traffic information, a generative AI model is trained. The generative AI model dynamically generates the optimal route according to the user's requests and current conditions. It also uses the user's sentiment information to adjust the tone and content of route suggestions.

[0864] 2. Terminal

[0865] The terminal accepts input from the user regarding destinations and points of interest. The entered information is temporarily stored on the terminal and then sent to the server. It also features an emotion engine that analyzes the user's voice and text data to identify emotions and sends this information to the server. Furthermore, it displays optimal route information received from the server to the user, adjusting the display method and guidance tone according to the user's emotions. User feedback is also accepted and sent to the server.

[0866] 3. User

[0867] Users input their destination and points of interest through a chatbot. They can also provide feedback after the optimal route is suggested and request a route regeneration.

[0868] System configuration and operation

[0869] In this system, the server uses the following hardware and software:

[0870] APIs as a means of data collection (e.g., Google Maps API, HERE API)

[0871] Database management systems (e.g., MySQL, PostgreSQL)

[0872] Machine learning engines as generative AI models (e.g., TensorFlow, PyTorch)

[0873] Natural language processing tools as emotion engines (e.g., IBM Watson, Google Cloud Natural Language)

[0874] The device uses the following hardware and software:

[0875] Touchscreens and voice recognition systems for accepting user input (e.g., Google Voice API, Apple Siri)

[0876] Voice and image analysis technologies for identifying emotions (e.g., OpenCV, Microsoft Azure Cognitive Services)

[0877] UI / UX interfaces for adjusting display methods and tone (e.g., React Native, Flutter)

[0878] Adding specific examples

[0879] For example, if a user sets a destination for an autonomous vehicle via a smartphone app and inputs that they want to stop at a cafe along the way, the autonomous driving system will suggest the least stressful route based on the latest traffic information and the user's sentiment data. A chatbot will gently confirm the request and suggest the best cafe, and readjust the route based on the user's feedback.

[0880] Example of a prompt

[0881] Please generate a program for a navigation application for autonomous vehicles. This application will collect real-time traffic information, suggest the optimal route, and use the in-car camera and microphone to recognize passenger emotions. It will adjust the route based on emotion data and combine it with a chatbot for a user-friendly conversation.

[0882] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0883] Step 1:

[0884] The server periodically acquires traffic information provided by local governments and manufacturers. This information is collected via APIs (e.g., Google Maps API, HERE API). The collected traffic congestion information, accident information, road closure information, and road condition information during disasters are stored in a database system (e.g., MySQL, PostgreSQL).

[0885] Input: Traffic information obtained from API

[0886] Output: Traffic information stored in the database

[0887] Step 2:

[0888] The terminal accepts input from the user regarding their destination and points of interest. This information is collected interactively through a chatbot and temporarily stored on the terminal.

[0889] Input: Destination and stopover points entered by the user.

[0890] Output: Input information stored in the device's temporary storage.

[0891] Step 3:

[0892] The device analyzes the user's voice and text data and uses an emotion engine (e.g., IBM Watson, Google Cloud Natural Language) to identify the user's emotions. This emotion information is then sent to the server.

[0893] Input: User's voice data and text data

[0894] Output: Sentiment information sent to the server

[0895] Step 4:

[0896] The server generates the optimal route using a generative AI model (e.g., TensorFlow, PyTorch) based on collected traffic information, user input information, and sentiment information. The generated optimal route is then sent from the server to the terminal.

[0897] Input: Traffic information retrieved from the database, user input information, sentiment information

[0898] Output: Generated optimal path

[0899] Step 5:

[0900] The terminal presents the user with optimal route information sent from the server. The display method and tone of guidance are adjusted based on the user's emotions, as determined by an emotion engine.

[0901] Input: Optimal routing information sent from the server

[0902] Output: Route information presented to the user

[0903] Step 6:

[0904] Users provide feedback on the suggested routes through the chatbot. This feedback information is sent from the device to the server.

[0905] Input: User feedback

[0906] Output: Feedback information sent to the server

[0907] Step 7:

[0908] Based on the feedback information received, the server regenerates the optimal route using a regenerative AI model. The regenerated optimal route information is then adjusted to take emotional information into consideration and sent to the terminal.

[0909] Input: User feedback information, sentiment information, traffic information

[0910] Output: Regenerated optimal route information

[0911] This series of processing steps allows users to obtain the latest traffic information and the optimal route tailored to their psychological state in real time.

[0912] 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.

[0913] 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.

[0914] 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.

[0915] [Third Embodiment]

[0916] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0917] 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.

[0918] 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).

[0919] 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.

[0920] 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.

[0921] 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).

[0922] 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.

[0923] 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.

[0924] 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.

[0925] 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.

[0926] 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.

[0927] 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".

[0928] The embodiments for carrying out the present invention will be described in detail.

[0929] First, the present invention relates to a car navigation system that collects traffic information in real time and proposes the optimal route to the user. This system collects and integrates traffic information provided by local governments and manufacturers, and generates the optimal route based on user input information. Furthermore, it has a function to regenerate the route as needed based on user feedback.

[0930] composition

[0931] 1. Server

[0932] Data collection and database updating:

[0933] The server periodically collects traffic information provided by local governments and manufacturers. This includes traffic congestion information, accident information, road closure information, and road condition information during disasters. The collected information is stored and updated in a database.

[0934] Generative AI models:

[0935] The server trains a generative AI model based on collected traffic information and builds an algorithm to generate the optimal route. The generative AI model can dynamically generate the optimal route according to user requests and current conditions.

[0936] 2. Terminal

[0937] Enter and submit user information:

[0938] The terminal accepts the user's destination and points of interest as input. A chatbot is used to collect detailed information such as the user's desired points of interest and waypoints. The collected information is sent to the server.

[0939] Route information provided:

[0940] The system displays optimal route information received from the server to the user. This information includes not only the destination, but also designated points of interest and real-time traffic conditions.

[0941] Feedback processing:

[0942] The system accepts user feedback and additional requests, and resends them to the server. This allows for regeneration according to the user's preferences.

[0943] 3. User

[0944] Input and feedback:

[0945] Users input their destination and points of interest through a chatbot. After the optimal route is suggested, they can also provide feedback if further improvements are needed, requesting a route regeneration.

[0946] Specific example

[0947] For example, consider a case where a user enters "I want to stop at a gas station on the way to Tokyo Station."

[0948] Data collection and analysis:

[0949] The server retrieves the latest information from the traffic information database and performs analysis. It identifies the destination as "Tokyo Station" and the stopping point as "gas station."

[0950] Generating the optimal route:

[0951] The AI ​​model generates the optimal route based on this information, taking into account current traffic conditions. For example, it might suggest a route that avoids congestion while also stopping at gas stations as requested by the user.

[0952] Route suggestion and correction:

[0953] The device displays the initial route to the user and suggests, "This route will take you past two gas stations." If the user provides feedback such as, "Is there a closer gas station?", the server re-analyzes the route and generates a new optimal route. This new route information is sent to the device, and the user is shown, "We have found a new route that goes past a closer gas station."

[0954] In this way, the car navigation system of the present invention can provide an optimal route that dynamically reflects real-time traffic information and user requests.

[0955] The following describes the processing flow.

[0956] Step 1:

[0957] The server periodically collects traffic information provided by local governments and manufacturers. This information includes traffic congestion, accidents, road closures, and road conditions during disasters. The collected information is stored in a database and updated in real time.

[0958] Step 2:

[0959] The terminal accepts the user's destination and points of interest as input. It interactively collects user input through a chatbot (e.g., "I want to stop at a gas station on the way to Tokyo Station"). The entered information is temporarily stored on the terminal.

[0960] Step 3:

[0961] The device sends the collected user input information to the server. This information includes destination, points of interest, and other specific preferences.

[0962] Step 4:

[0963] The server analyzes the received user information. Using natural language processing, it identifies the destination and points of interest, and retrieves the latest traffic information from the database.

[0964] Step 5:

[0965] The server generates the optimal route using AI based on analysis results and traffic information. The generated route is the best possible path, taking into account traffic congestion and road closures, and including the user's desired stops.

[0966] Step 6:

[0967] The server sends the generated optimal route information to the terminal. The route information includes detailed route instructions and information about potential detours.

[0968] Step 7:

[0969] The terminal receives route information from the server and displays it to the user. For example, it might display something like, "If you use this route, there are two gas stations along the way."

[0970] Step 8:

[0971] Users can provide feedback and additional requests regarding the suggested route through the chatbot. For example, they might ask, "Is there a closer gas station?"

[0972] Step 9:

[0973] The device sends the user feedback information back to the server. The server re-analyzes the data and generates the optimal route based on the new conditions.

[0974] Step 10:

[0975] The server generates a new, optimal route based on the feedback and sends it to the terminal. The regenerated route information also takes into account any additional requests from the user.

[0976] Step 11:

[0977] The device receives new, optimal routes and displays them to the user. For example, it might display, "We found a new route that goes through a closer gas station."

[0978] This series of steps allows users to obtain real-time, up-to-date traffic information and the optimal route tailored to their needs.

[0979] (Example 1)

[0980] 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."

[0981] Conventional car navigation systems often fail to adequately reflect real-time traffic information, making it difficult to suggest the optimal route for the user. Furthermore, they lack convenience due to their inability to quickly respond to additional user requests and feedback. Additionally, they do not fully utilize artificial intelligence technology for collecting traffic information and generating optimal routes.

[0982] 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.

[0983] In this invention, the server includes means for collecting traffic information from local governments and manufacturers, means for receiving destinations and points of interest from users as input, means for generating an optimal route based on the collected traffic information, means for presenting the generated optimal route to the user, means for receiving feedback from the user, means for generating the optimal route again based on the feedback, and means for training a generation AI model that provides the generated optimal route to the user. This makes it possible to dynamically reflect real-time traffic information and quickly provide the optimal route that meets the user's needs.

[0984] A "local government" is a local government agency that provides public services and manages administrative affairs.

[0985] A "manufacturer" is a company or organization that produces or manufactures products.

[0986] "Traffic information" refers to traffic-related data such as road congestion, accident information, road closure information, and road conditions during disasters.

[0987] "Means" refers to the methods or devices used to achieve a specific objective.

[0988] A "user" is an individual or group that uses the system.

[0989] The "destination" is the final point that the user aims to reach.

[0990] A "stopover point" is a specific location that a user might want to visit before reaching their destination.

[0991] A "generation method" refers to a method or apparatus that performs calculations or analyses based on specific data to generate results.

[0992] "Presentation means" refers to a method or device for displaying or providing generated information to a user.

[0993] "Feedback" refers to the opinions and requests that users provide regarding the system's suggestions and results.

[0994] A "generative AI model" is an algorithm or program that uses artificial intelligence technology to analyze data and generate specific results.

[0995] "Training methods" refer to the methods and devices used to train models or algorithms.

[0996] Modes for carrying out the invention

[0997] The embodiments for carrying out the present invention will be described in detail. First, the present invention relates to a car navigation system that collects traffic information in real time and proposes the optimal route to the user. This system collects and integrates traffic information provided by local governments and manufacturers and generates the optimal route based on user input information. Furthermore, it has a function to regenerate the route as needed based on user feedback.

[0998] 1. Server roles and processing

[0999] The server is primarily responsible for collecting traffic information, training the AI ​​model for generating traffic, and generating the optimal route. Specifically, it performs the following processes:

[1000] Data collection and database updating:

[1001] The server collects traffic information from local governments and manufacturers via APIs at specific times each day. This information includes traffic congestion, accidents, road closures, and road conditions during disasters. This information is stored in the server's database and updated by comparing it with existing data.

[1002] Training generative AI models and generating optimal routes:

[1003] The server trains a generative AI model based on the collected traffic information. This model uses destination and stopover information received from the user, along with real-time traffic data, to generate the optimal route. The generated route information is then sent to the user's device.

[1004] 2. Terminal roles and processing

[1005] The terminal collects user input information and sends it to the server. It also has the role of presenting the user with the optimal route information received from the server. The specific process is as follows:

[1006] Enter and submit user information:

[1007] The terminal uses a chatbot to receive information about destinations and points of interest entered by the user. For example, if a user enters "I want to stop at a gas station on the way to Tokyo Station," that information is sent to the server.

[1008] Route information provided:

[1009] The terminal, having received optimal route information from the server, presents that information to the user. The displayed information includes the destination, points of interest, and real-time traffic conditions.

[1010] Accepting feedback:

[1011] When a user provides feedback on the suggested route, that information is also sent from the terminal to the server. For example, if a user provides feedback such as "Is there a closer gas station?", that information is sent back to the server, and the process of generating a new optimal route is initiated.

[1012] 3. User roles and operations

[1013] Users input their destination, points of interest, and feedback through a chatbot. This allows the system to suggest the optimal route based on real-time traffic information.

[1014] Specific example:

[1015] For example, consider the process when a user inputs, "I want to stop at a gas station on the way to Tokyo Station."

[1016] Data collection and analysis:

[1017] The server retrieves the latest information from the traffic information database and performs analysis. It identifies the destination as "Tokyo Station" and the stopping point as "gas station."

[1018] Generating the optimal route:

[1019] The AI ​​model generates the optimal route based on this information, taking into account current traffic conditions. For example, it might suggest a route that avoids congestion while also stopping at gas stations as requested by the user.

[1020] Route guidance and feedback:

[1021] The device displays the initial route to the user and suggests, "This route will take you past two gas stations." If the user provides feedback such as, "Is there a closer gas station?", the server re-analyzes the route and generates a new optimal route. This new route information is sent to the device, and the user is shown, "We have found a new route that goes past a closer gas station."

[1022] Example of a prompt:

[1023] This system generates algorithms for car navigation systems. The system receives destination and stopover information from the user and provides the optimal route based on real-time traffic conditions. This system can update a traffic information database and generate the optimal route using a generated AI model.

[1024] In this way, the car navigation system of the present invention can provide an optimal route that dynamically reflects real-time traffic information and user requests.

[1025] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1026] System program processing steps

[1027] Step 1:

[1028] Data collection

[1029] The server collects traffic information from local governments and manufacturers via an API at a specific time each day. The input is traffic information data obtained from the API. The server parses this data, processes it into the required format, and stores it in the database.

[1030] Specific actions:

[1031] The server executes the "Traffic Information Update" script.

[1032] A request is sent to the API endpoint, and the JSON data received as a response is parsed.

[1033] The parsed data is stored in the database.

[1034] Step 2:

[1035] Database update

[1036] The collected traffic information is stored in the server's database. This ensures that the traffic information is always up-to-date. The input is the parsed traffic information data, and the output is the updated state of the database.

[1037] Specific actions:

[1038] The server compares the new data with the existing data.

[1039] Update existing data as needed to keep the database up to date.

[1040] Step 3:

[1041] Enter user information

[1042] The terminal receives information from the user regarding the destination and points of interest. The input is information entered by the user via the chatbot, and the output is data sent to the server.

[1043] Specific actions:

[1044] The user opens the chatbot and enters their destination and points of interest.

[1045] The terminal collects the information entered and sends it to the server.

[1046] Step 4:

[1047] Optimal route generation

[1048] The server generates the optimal route using a generative AI model based on destination and stopover point information received from the user. The input is user information and real-time traffic information data, and the output is the generated optimal route data.

[1049] Specific actions:

[1050] The server receives the user's input information.

[1051] The collected traffic information and input information are supplied to the generating AI model.

[1052] The generative AI model calculates the optimal route and generates the result.

[1053] The generated route information is sent to the terminal.

[1054] Step 5:

[1055] Presenting route information

[1056] The terminal displays the optimal route information received from the server to the user. The input is the optimal route data received from the server, and the output is the data displayed to the user.

[1057] Specific actions:

[1058] The terminal receives route information from the server.

[1059] Route information is displayed to the user on the screen.

[1060] For example, it could display information such as, "There are two gas stations along the route to Tokyo Station."

[1061] Step 6:

[1062] Processing user feedback

[1063] The device receives feedback from the user and sends it back to the server. The input is the feedback information provided by the user, and the output is the data sent to the server.

[1064] Specific actions:

[1065] The user enters feedback into the chatbot.

[1066] The device sends that feedback information to the server.

[1067] Step 7:

[1068] Regenerating the route

[1069] The server generates a new optimal route based on user feedback. The input is feedback information and the latest traffic information data, and the output is the regenerated optimal route data.

[1070] Specific actions:

[1071] The server receives feedback.

[1072] A generative AI model is used to calculate a new optimal route.

[1073] Send the calculation result to the terminal.

[1074] In this way, information exchange between the server, terminal, and user makes it possible to dynamically provide the optimal route based on real-time traffic information.

[1075] (Application Example 1)

[1076] 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."

[1077] Conventional car navigation systems, while providing optimal routes based on real-time traffic information, lacked sufficient integration with autonomous vehicles, requiring user intervention. Furthermore, their feedback-based route regeneration capabilities were inadequate, making sudden changes or optimal responses difficult. This resulted in limitations on user convenience.

[1078] 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.

[1079] In this invention, the server includes means for collecting traffic information from local governments and manufacturers, means for receiving destinations and points of interest from users as input, means for generating an optimal route based on the collected traffic information, means for presenting the generated optimal route to the user, means for receiving feedback from the user, means for generating the optimal route again based on the feedback, and means for issuing instructions related to the operation control of the vehicle. This makes it possible to provide optimal routes for autonomous vehicles based on real-time traffic information, significantly improving user convenience and safety.

[1080] "Local government" refers to a local public body, an organization that functions as a provider of traffic information.

[1081] "Manufacturers" refers to companies that manufacture automobiles and transportation-related equipment, and the term also refers to traffic information provided by these companies.

[1082] "Traffic information" refers to real-time information such as traffic congestion, accidents, road closures, and road conditions during disasters.

[1083] "User" refers to an individual or organization that uses a car navigation system.

[1084] "Destination" refers to the place the user ultimately wants to reach.

[1085] A "stopover point" refers to a location that a user might want to visit on their way to their destination.

[1086] "Generation means" refers to the technologies and algorithms used to calculate the optimal route based on collected traffic information.

[1087] "Presentation means" refers to technologies and devices used to display the generated optimal route on the user's device.

[1088] "Feedback" refers to additional requests and information provided by users.

[1089] "Regeneration means" refers to technologies and algorithms for calculating a new optimal path based on feedback.

[1090] "Vehicle operation control" refers to the operations and instructions related to the driving of autonomous vehicles.

[1091] A "generative AI model" refers to an algorithm or system that uses artificial intelligence (AI) technology to generate the optimal path.

[1092] The embodiments for carrying out the present invention will be described in detail.

[1093] First, the system of this invention collects traffic information from local governments and manufacturers, accepts input from users regarding destinations and points of interest, and generates and presents an optimal route based on that information. It also has a function to receive feedback from users and generate an optimal route again. Furthermore, this system can also issue instructions related to the operation control of vehicles.

[1094] server

[1095] The server has the following functions:

[1096] 1. Data Collection: The server periodically collects traffic information provided by local governments and manufacturers. This information includes traffic congestion information, accident information, road closure information, and road condition information during disasters.

[1097] 2. Use of Generative AI Model: The server trains a generative AI model based on collected traffic information and builds an algorithm to generate the optimal route. The generative AI model can dynamically generate the optimal route according to user requests and current conditions.

[1098] 3. Route generation and presentation: The generated optimal route is sent to the user's terminal and presented to the user.

[1099] As a concrete example, here is a prompt message in which the server identifies the destination as "Tokyo Station" and the stopover point as "gas station":

[1100] Please enter your destination: Tokyo Station

[1101] Please enter your stopping points (multiple points are allowed, separated by commas): Gas station

[1102] terminal

[1103] The device has the following features:

[1104] 1. User Input and Transmission: The terminal accepts input from the user regarding the destination and points of interest. Using a chatbot, it collects detailed information such as the user's desired points of interest and waypoints, and sends it to the server.

[1105] 2. Presenting Route Information: The system presents the user with the optimal route information received from the server. The displayed information includes not only the destination but also designated points of interest and real-time traffic conditions.

[1106] 3. Feedback Processing: User feedback and additional requests are received and resent to the server. This allows for regeneration according to the user's wishes.

[1107] user

[1108] The user performs the following actions:

[1109] 1. Input and Feedback: Users input their destination and points of interest through the chatbot. After the optimal route is presented, they can also provide feedback if further improvements are needed, requesting a route regeneration.

[1110] These functions and operations enable the system of the present invention to dynamically provide the optimal route for the user based on real-time traffic information. In particular, in autonomous vehicles, by issuing instructions related to operation control, it is possible to achieve safe and efficient driving while minimizing user intervention.

[1111] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1112] Step 1:

[1113] The server periodically collects traffic information provided by local governments and manufacturers. This process involves obtaining traffic congestion information, accident information, road closure information, and road condition information during disasters via APIs and databases. The input is traffic information data from various sources, which the server collects, stores in its database, and updates to maintain the latest traffic information. The output is the most recent traffic data stored on the server.

[1114] Step 2:

[1115] The user enters their destination and points of interest using their device. The user enters this information in text format through the device's chatbot. The input is text data of the destination and points of interest, which the device receives and then sends to the server. The output is the user's destination and points of interest data sent to the server.

[1116] Step 3:

[1117] The server references a database of collected traffic information based on the user's destination and stopover data. Here, a generative AI model is used to generate the optimal route. The input consists of the user-specified destination and stopovers, along with the latest traffic information. The server analyzes this data using the generative AI model to generate the optimal route. The output is the generated optimal route information.

[1118] Step 4:

[1119] The server sends the generated optimal route information to the user's terminal. The input is the generated optimal route information, which the server sends to the terminal. The output is the optimal route information displayed on the user's terminal. The user then starts driving based on this information.

[1120] Step 5:

[1121] Users input feedback and additional requests through the terminal. For example, feedback such as "Is there a closer gas station?" is possible. The input is the user's feedback text, which the terminal receives and then sends back to the server. The output is the user feedback data sent to the server.

[1122] Step 6:

[1123] The server, based on user feedback, consults the traffic information database again and uses a generative AI model to generate a new optimal route. The input consists of the feedback and the latest traffic information, and the server generates a regenerated optimal route based on this. The output is the newly generated optimal route information.

[1124] Step 7:

[1125] The server sends the regenerated optimal route information to the user's terminal. The input is the regenerated optimal route information, which the server sends to the terminal. The output is the new optimal route information displayed on the user's terminal. The user adjusts their driving based on this information.

[1126] 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.

[1127] The embodiments for carrying out the present invention will be described in detail.

[1128] This invention relates to a car navigation system that collects traffic information in real time and proposes the optimal route to the user. This system collects and integrates traffic information provided by local governments and manufacturers, and generates the optimal route based on user input. Furthermore, it has a function to regenerate the route as needed based on user feedback. In addition, this invention can propose routes that take into account the user's psychological state by incorporating an emotion engine that recognizes the user's emotions.

[1129] composition

[1130] 1. Server

[1131] Data collection and database updating:

[1132] The server periodically acquires traffic information provided by local governments and manufacturers, and the collected information is stored in a database. This includes traffic congestion information, accident information, road closure information, and road condition information during disasters.

[1133] Generative AI models:

[1134] The server trains a generative AI model based on collected traffic information. The generative AI model dynamically generates the optimal route according to the user's requests and current conditions. It also uses user sentiment information provided by the sentiment engine to adjust the tone and content of route suggestions.

[1135] 2. Terminal

[1136] Enter and submit user information:

[1137] The terminal accepts input from the user regarding their destination and points of interest. This input information is collected interactively, for example through a chatbot, and temporarily stored within the terminal. This information is then sent to the server.

[1138] Collection and analysis of emotional information:

[1139] The emotion engine analyzes the user's voice and text data to identify their emotions. The identified emotion information is then sent to the server.

[1140] Route information provided:

[1141] The system displays optimal route information received from the server to the user. The displayed information includes the destination, points of interest, and real-time traffic conditions. An emotion engine adjusts the display method and tone of guidance based on the user's emotions.

[1142] Feedback processing:

[1143] The system receives user feedback and additional requests through a chatbot and sends them to the server.

[1144] 3. User

[1145] Input and feedback:

[1146] Users input their destination and points of interest through a chatbot. After the optimal route is suggested, they can also provide feedback if further improvements are needed and request a route regeneration.

[1147] Specific example

[1148] For example, consider a case where a user inputs "I want to stop at a gas station on the way to Tokyo Station," and this input is accompanied by expressions of stress or anxiety.

[1149] Data collection and analysis:

[1150] The server retrieves the latest information from the traffic information database and performs analysis. It identifies the destination as "Tokyo Station" and the stopping point as "gas station."

[1151] Analysis of emotional information:

[1152] The emotion engine analyzes emotional information from the user's input and voice to detect stress and anxiety.

[1153] Generating the optimal route:

[1154] The generative AI model generates the optimal route based on user instructions and emotional information. For example, it suggests a route that avoids traffic jams, stops at the user's preferred gas station, and further reduces stress.

[1155] Route suggestion and adjustment:

[1156] The terminal presents the generated route to the user and provides guidance such as, "If you use this route, you can stop at two gas stations along the way." The information is presented in a gentle and calming tone to reduce user stress.

[1157] Feedback and regeneration:

[1158] If a user provides feedback such as "Is there a closer gas station?", the server re-analyzes the data and generates an optimal route based on the new conditions. The regenerated route similarly takes into account the user's emotional state, as determined by the emotion engine.

[1159] This series of steps allows users to be presented with the latest traffic information in real time, along with their individual preferences and even their psychological state, to find the optimal route, enabling a comfortable and safe journey.

[1160] The following describes the processing flow.

[1161] Step 1:

[1162] The server periodically collects traffic information provided by local governments and manufacturers. This information includes traffic congestion, accident information, road closure information, and road condition information during disasters. The collected information is stored in a database and updated in real time.

[1163] Step 2:

[1164] The terminal accepts the user's destination and points of interest as input. It interactively collects user input through a chatbot (e.g., "I want to stop at a gas station on the way to Tokyo Station"). The entered information is temporarily stored on the terminal.

[1165] Step 3:

[1166] The emotion engine analyzes the user's voice and text data to identify emotions. For example, it identifies emotions such as stress, anxiety, and joy based on the user's tone of voice and entered text.

[1167] Step 4:

[1168] The device transmits the collected user input information and sentiment information to the server.

[1169] Step 5:

[1170] The server analyzes the received user information and sentiment information. It uses natural language processing to identify destinations and points of interest, and retrieves the latest traffic information from the database.

[1171] Step 6:

[1172] The server generates the optimal route using AI based on analysis results and traffic information. The generated route is the best possible path, taking into account traffic congestion and road closures, and including the user's desired stops. It also considers the user's emotional state to select a route and guidance method that reduces stress.

[1173] Step 7:

[1174] The server sends the generated optimal route information to the terminal. This route information includes detailed directions and information on potential detours. It is presented in a tone and content that reflects the user's emotions.

[1175] Step 8:

[1176] The terminal receives route information from the server and displays it to the user. For example, it might display something like, "If you use this route, there are two gas stations along the way." Furthermore, if the user is feeling stressed, the guidance will be provided in a calm and reassuring tone.

[1177] Step 9:

[1178] Users can provide feedback and additional requests regarding the suggested route through the chatbot. For example, they might ask, "Is there a closer gas station?"

[1179] Step 10:

[1180] The device sends the user feedback information back to the server. The server re-analyzes the data and generates the optimal route based on the new conditions.

[1181] Step 11:

[1182] The server generates a new, optimal route based on feedback and sends it to the terminal. The regenerated route information takes into account the user's additional requests and emotional state.

[1183] Step 12:

[1184] The device receives and displays the new, optimal route to the user. For example, it might say, "We've found a new route that goes through a closer gas station." If the user is feeling stressed, the guidance will be delivered in a calmer tone.

[1185] This series of steps provides users with the most up-to-date traffic information in real time, along with an optimal route that takes into account their individual needs and psychological state.

[1186] (Example 2)

[1187] 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."

[1188] Conventional car navigation systems primarily suggested optimal routes based only on traffic information and the user's destination information. However, they lacked the ability to consider the user's psychological state and feedback when suggesting routes, thus failing to adequately meet the needs of users experiencing stress or anxiety. Furthermore, the lack of a function to receive and regenerate real-time feedback made it difficult to respond quickly and flexibly.

[1189] 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.

[1190] In this invention, the server includes means for collecting traffic information from local governments and manufacturers, means for receiving destinations and points of interest from users as input, means for generating an optimal route based on the collected traffic information, means for presenting the generated optimal route to the user, means for collecting and analyzing user sentiment information, means for receiving feedback from users, and means for generating an optimal route again based on the feedback and sentiment information. This enables flexible and rapid route suggestions that take into account the user's psychological state.

[1191] "Traffic information" refers to data related to road traffic, such as traffic congestion information, accident information, road closure information, and road condition information during disasters.

[1192] A "user" is an individual or group that intends to travel to a destination using a car navigation system.

[1193] "Destination" refers to the place the user wants to reach.

[1194] A "stopover point" refers to a place where a user might consider temporarily staying or visiting on their way to their final destination.

[1195] "Generation means" refers to technology that calculates and proposes the optimal route based on user input information and traffic information.

[1196] "Emotional information" refers to data that indicates the user's psychological state, including emotions such as stress, anxiety, and joy.

[1197] "Feedback" refers to additional requests or evaluations provided by users.

[1198] "Regeneration methods" refer to technologies that recalculate the optimal route based on user feedback and emotional information.

[1199] This invention relates to a car navigation system that collects traffic information in real time and proposes an optimal route that takes into account the user's emotional information. This system collects and integrates traffic information provided by local governments and manufacturers, generates an optimal route based on user input information, and can further regenerate the route based on user feedback.

[1200] server

[1201] The server has the following functions:

[1202] Data collection and updating:

[1203] The server periodically retrieves real-time traffic information (e.g., traffic congestion information, accident information, road closure information, etc.) provided by local governments and manufacturers via APIs. The retrieved information is stored in a database such as PostgreSQL.

[1204] Training and route generation for generative AI models:

[1205] A generative AI model (e.g., a general natural language processing model) is trained based on the collected traffic information. This model dynamically generates the optimal route using the user's destination and points of interest, real-time traffic conditions, and user sentiment information provided by the sentiment engine. The following prompt statements are used during this process:

[1206] If a user says they want to stop at a gas station on their way to Tokyo Station, please generate the optimal route considering traffic information and emotional factors. The user is experiencing stress.

[1207] terminal

[1208] The device has the following features:

[1209] Enter and submit user information:

[1210] The device (e.g., a mobile device) collects information about destinations and points of interest entered by the user through a chatbot. This information is temporarily stored in the device's memory and then sent to the server.

[1211] Collection and analysis of emotional information:

[1212] The device collects the user's voice and text data and analyzes it using an emotion engine (e.g., an emotion analysis API). The analysis results (stress, anxiety, etc.) are sent to the server.

[1213] Route information provided:

[1214] The device displays the optimal route received from the server to the user. This display includes the destination, points of interest, and real-time traffic conditions. The tone of the route guidance is also adjusted according to the user's emotional state.

[1215] Accepting feedback:

[1216] The device receives user feedback and additional requests via a chatbot. This feedback is sent to the server and used to regenerate routes.

[1217] User

[1218] The user performs the following actions:

[1219] Input and feedback:

[1220] Users input their destination and points of interest via the chatbot. For example, they might input, "I want to stop at a gas station on the way to Tokyo Station." After the optimal route is suggested, they can also provide feedback if further improvements are needed, such as "Are there any closer gas stations?"

[1221] Specific example:

[1222] If a user enters "I want to stop at a gas station on the way to Tokyo Station" into the chatbot, the device sends this information to the server. The server generates the optimal route using an AI model based on the collected traffic information, and proposes a route that also takes into account the user's emotional state. The device then informs the user that "this route will allow you to stop at two gas stations along the way," guiding them in a gentle and calm tone to reduce stress. If the user provides feedback such as "Is there a closer gas station?", the server re-analyzes the data and presents the user with a regenerated route based on the new conditions.

[1223] This invention allows users to be presented with the latest traffic information in real time, along with their individual preferences and psychological state, to find the optimal route, enabling comfortable and safe travel.

[1224] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1225] Step 1:

[1226] Data collection

[1227] The server obtains real-time traffic information from traffic information providers via an API. For example, it obtains traffic congestion information, accident information, and road closure information in JSON format. The server analyzes this data, extracts the necessary information, and stores it in a database. The information stored in the database includes location, event type, severity, and timestamp.

[1228] Input: Traffic information obtained from an external API (in JSON format)

[1229] Output: Passage information stored in the database (database update via SQL insert statement)

[1230] Specifically, the server updates the database using the following SQL statement:

[1231] SQL

[1232] INSERT INTO traffic_info (location, event, severity, timestamp)

[1233] VALUES ('Tokyo', 'Accident', 'Severe', '2023-10-01 14:00:00');

[1234] Step 2:

[1235] Enter user information

[1236] The terminal receives information about destinations and points of interest entered by the user through a chatbot. The collected information is temporarily stored in the terminal's memory and then sent to the server.

[1237] Input: User input to the chatbot (text format)

[1238] Output: User destination and stopover information to be sent to the server (in JSON format)

[1239] Specifically, the terminal sends the following JSON data to the server:

[1240] json

[1241] {

[1242] "destination": "Tokyo Station",

[1243] "waypoints": ["Gas Station"]

[1244] }

[1245] Step 3:

[1246] Collection and analysis of emotional information

[1247] The device collects the user's voice and text data and analyzes it using an emotion engine. The emotion engine analyzes the provided data and identifies the user's emotions (stress, anxiety, joy, etc.). The identified emotion information is sent to the server.

[1248] Input: User's voice data or text data (input data)

[1249] Output: Sentiment information as analysis results (JSON format)

[1250] Specifically, the following analysis results are sent to the server:

[1251] json

[1252] {

[1253] "text": "I'm looking for a gas station but I'm worried.",

[1254] "emotion": "stress"

[1255] }

[1256] Step 4:

[1257] Optimal route generation

[1258] The server uses a generative AI model to generate the optimal route based on user input and emotional information. Specifically, it provides the generative AI model with collected traffic information, user instructions, and emotional information as input to generate the best route.

[1259] Input: Traffic information, user's destination and points of interest, sentiment information (internal database and JSON format).

[1260] Output: Optimal route information (JSON format)

[1261] As a concrete example, the following prompt message is input to the generating AI model:

[1262] If a user says they want to stop at a gas station on their way to Tokyo Station, please generate the optimal route considering traffic information and emotional factors. The user is experiencing stress.

[1263] Step 5:

[1264] Presenting route information

[1265] The device displays the optimal route received from the server to the user. This display includes the destination, points of interest, and real-time traffic conditions. The tone of the route guidance is also adjusted according to the user's emotional state.

[1266] Input: Optimal route information received from the server (in JSON format)

[1267] Output: Route information presented to the user (visual display and audio guidance)

[1268] The specific actions presented to the user are as follows:

[1269] "If you use this route, you can stop at two gas stations along the way."

[1270] Step 6:

[1271] Processing user feedback

[1272] The device receives user feedback and additional requests via a chatbot and sends them to the server.

[1273] Input: User feedback (text format)

[1274] Output: Feedback information to send to the server (JSON format)

[1275] As a concrete example of action, consider the following feedback:

[1276] "Is there a gas station closer?"

[1277] Step 7:

[1278] Root regeneration

[1279] The server uses a generative AI model based on user feedback to generate the optimal route again. The regenerated route also takes the user's emotional state into consideration.

[1280] Input: User feedback information (JSON format)

[1281] Output: Regenerated optimal route information (JSON format)

[1282] As a concrete action, the following prompt message is input to the AI ​​model again:

[1283] If a user provides feedback requesting a closer gas station, generate a new, optimal route considering traffic and emotional factors. Users are experiencing stress.

[1284] In this way, the system can provide the optimal route based on real-time, up-to-date traffic information, taking into account the user's psychological state.

[1285] (Application Example 2)

[1286] 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."

[1287] Conventional car navigation systems have the ability to collect real-time traffic information and generate optimal routes, but they do not consider the user's psychological state when suggesting routes. Therefore, inefficient route guidance may be provided even when the user is experiencing stress. Furthermore, the ability to appropriately reflect user feedback and dynamically regenerate routes has been insufficient. Solving these problems and providing a more comfortable and safer driving experience is essential.

[1288] 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.

[1289] In this invention, the server includes means for collecting traffic information from local governments and manufacturers, means for recognizing the user's emotions, means for generating an optimal route based on the collected traffic information, means for presenting the generated optimal route to the user, means for receiving feedback from the user, means for generating the optimal route again based on the feedback, and means for adjusting the optimal route suggestion method based on the recognized emotions. This makes it possible to suggest comfortable and safe routes that reflect the user's psychological state in real time.

[1290] "Local government" refers to local public bodies or similar organizations, and is generally an organization that provides traffic information and disaster information.

[1291] A "manufacturer" is a company or organization that manufactures and provides transportation-related products and infrastructure, and may also be a source of traffic information.

[1292] "Traffic information" refers to all information related to road traffic, including traffic congestion information, accident information, road closure information, and road condition information during disasters.

[1293] "User" refers to an individual or group that uses a car navigation system.

[1294] "Destination" refers to the place the user wants to reach, which is entered into the car's navigation system.

[1295] A "stopover point" refers to a place where a user might want to stop on their way to their destination.

[1296] "Optimal route" refers to the most efficient and safe route, generated based on traffic information and user input.

[1297] "Generation means" refers to devices or software that perform calculations and algorithms for generating the optimal path.

[1298] "Presentation means" refers to displays or audio guidance devices used to show the generated optimal route to the user.

[1299] "Feedback" refers to the evaluations and opinions that users give regarding the paths presented.

[1300] "Regeneration means" refers to devices or software that regenerate the optimal route based on user feedback.

[1301] "Means of recognizing emotions" refers to sensors and data analysis technologies used to analyze a user's emotional state.

[1302] "Means of adjustment" refers to devices or software that modify the method of suggesting the optimal route based on recognized emotions.

[1303] Modes for carrying out the invention

[1304] The embodiments for carrying out the present invention will be described in detail.

[1305] This invention relates to a car navigation system that collects traffic information in real time and proposes the optimal route to the user. This system collects and integrates traffic information provided by local governments and manufacturers, and generates the optimal route based on user feedback. Furthermore, by incorporating an emotion engine that recognizes the user's emotions, it is possible to propose routes that take their psychological state into consideration.

[1306] 1. Server

[1307] The server periodically acquires traffic information provided by local governments and manufacturers and stores it in a database. This includes traffic congestion information, accident information, road closure information, and road condition information during disasters. Based on the collected traffic information, a generative AI model is trained. The generative AI model dynamically generates the optimal route according to the user's requests and current conditions. It also uses the user's sentiment information to adjust the tone and content of route suggestions.

[1308] 2. Terminal

[1309] The terminal accepts input from the user regarding destinations and points of interest. The entered information is temporarily stored on the terminal and then sent to the server. It also features an emotion engine that analyzes the user's voice and text data to identify emotions and sends this information to the server. Furthermore, it displays optimal route information received from the server to the user, adjusting the display method and guidance tone according to the user's emotions. User feedback is also accepted and sent to the server.

[1310] 3. User

[1311] Users input their destination and points of interest through a chatbot. They can also provide feedback after the optimal route is suggested and request a route regeneration.

[1312] System configuration and operation

[1313] In this system, the server uses the following hardware and software:

[1314] APIs as a means of data collection (e.g., Google Maps API, HERE API)

[1315] Database management systems (e.g., MySQL, PostgreSQL)

[1316] Machine learning engines as generative AI models (e.g., TensorFlow, PyTorch)

[1317] Natural language processing tools as emotion engines (e.g., IBM Watson, Google Cloud Natural Language)

[1318] The device uses the following hardware and software:

[1319] Touchscreens and voice recognition systems for accepting user input (e.g., Google Voice API, Apple Siri)

[1320] Voice and image analysis technologies for identifying emotions (e.g., OpenCV, Microsoft Azure Cognitive Services)

[1321] UI / UX interfaces for adjusting display methods and tone (e.g., React Native, Flutter)

[1322] Adding specific examples

[1323] For example, if a user sets a destination for an autonomous vehicle via a smartphone app and inputs that they want to stop at a cafe along the way, the autonomous driving system will suggest the least stressful route based on the latest traffic information and the user's sentiment data. A chatbot will gently confirm the request and suggest the best cafe, and readjust the route based on the user's feedback.

[1324] Example of a prompt

[1325] Please generate a program for a navigation application for autonomous vehicles. This application will collect real-time traffic information, suggest the optimal route, and use the in-car camera and microphone to recognize passenger emotions. It will adjust the route based on emotion data and combine it with a chatbot for a user-friendly conversation.

[1326] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1327] Step 1:

[1328] The server periodically acquires traffic information provided by local governments and manufacturers. This information is collected via APIs (e.g., Google Maps API, HERE API). The collected traffic congestion information, accident information, road closure information, and road condition information during disasters are stored in a database system (e.g., MySQL, PostgreSQL).

[1329] Input: Traffic information obtained from API

[1330] Output: Traffic information stored in the database

[1331] Step 2:

[1332] The terminal accepts input from the user regarding their destination and points of interest. This information is collected interactively through a chatbot and temporarily stored on the terminal.

[1333] Input: Destination and stopover points entered by the user.

[1334] Output: Input information stored in the device's temporary storage.

[1335] Step 3:

[1336] The device analyzes the user's voice and text data and uses an emotion engine (e.g., IBM Watson, Google Cloud Natural Language) to identify the user's emotions. This emotion information is then sent to the server.

[1337] Input: User's voice data and text data

[1338] Output: Sentiment information sent to the server

[1339] Step 4:

[1340] The server generates the optimal route using a generative AI model (e.g., TensorFlow, PyTorch) based on collected traffic information, user input information, and sentiment information. The generated optimal route is then sent from the server to the terminal.

[1341] Input: Traffic information retrieved from the database, user input information, sentiment information

[1342] Output: Generated optimal path

[1343] Step 5:

[1344] The terminal presents the user with optimal route information sent from the server. The display method and tone of guidance are adjusted based on the user's emotions, as determined by an emotion engine.

[1345] Input: Optimal routing information sent from the server

[1346] Output: Route information presented to the user

[1347] Step 6:

[1348] Users provide feedback on the suggested routes through the chatbot. This feedback information is sent from the device to the server.

[1349] Input: User feedback

[1350] Output: Feedback information sent to the server

[1351] Step 7:

[1352] Based on the feedback information received, the server regenerates the optimal route using a regenerative AI model. The regenerated optimal route information is then adjusted to take emotional information into consideration and sent to the terminal.

[1353] Input: User feedback information, sentiment information, traffic information

[1354] Output: Regenerated optimal route information

[1355] This series of processing steps allows users to obtain the latest traffic information and the optimal route tailored to their psychological state in real time.

[1356] 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.

[1357] 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.

[1358] 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.

[1359] [Fourth Embodiment]

[1360] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[1361] 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.

[1362] 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).

[1363] 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.

[1364] 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.

[1365] 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).

[1366] 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.

[1367] 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.

[1368] 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.

[1369] 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.

[1370] 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.

[1371] 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.

[1372] 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".

[1373] The embodiments for carrying out the present invention will be described in detail.

[1374] First, the present invention relates to a car navigation system that collects traffic information in real time and proposes the optimal route to the user. This system collects and integrates traffic information provided by local governments and manufacturers, and generates the optimal route based on user input information. Furthermore, it has a function to regenerate the route as needed based on user feedback.

[1375] composition

[1376] 1. Server

[1377] Data collection and database updating:

[1378] The server periodically collects traffic information provided by local governments and manufacturers. This includes traffic congestion information, accident information, road closure information, and road condition information during disasters. The collected information is stored and updated in a database.

[1379] Generative AI models:

[1380] The server trains a generative AI model based on collected traffic information and builds an algorithm to generate the optimal route. The generative AI model can dynamically generate the optimal route according to user requests and current conditions.

[1381] 2. Terminal

[1382] Enter and submit user information:

[1383] The terminal accepts the user's destination and points of interest as input. A chatbot is used to collect detailed information such as the user's desired points of interest and waypoints. The collected information is sent to the server.

[1384] Route information provided:

[1385] The system displays optimal route information received from the server to the user. This information includes not only the destination, but also designated points of interest and real-time traffic conditions.

[1386] Feedback processing:

[1387] The system accepts user feedback and additional requests, and resends them to the server. This allows for regeneration according to the user's preferences.

[1388] 3. User

[1389] Input and feedback:

[1390] Users input their destination and points of interest through a chatbot. After the optimal route is suggested, they can also provide feedback if further improvements are needed, requesting a route regeneration.

[1391] Specific example

[1392] For example, consider a case where a user enters "I want to stop at a gas station on the way to Tokyo Station."

[1393] Data collection and analysis:

[1394] The server retrieves the latest information from the traffic information database and performs analysis. It identifies the destination as "Tokyo Station" and the stopping point as "gas station."

[1395] Generating the optimal route:

[1396] The AI ​​model generates the optimal route based on this information, taking into account current traffic conditions. For example, it might suggest a route that avoids congestion while also stopping at gas stations as requested by the user.

[1397] Route suggestion and correction:

[1398] The device displays the initial route to the user and suggests, "This route will take you past two gas stations." If the user provides feedback such as, "Is there a closer gas station?", the server re-analyzes the route and generates a new optimal route. This new route information is sent to the device, and the user is shown, "We have found a new route that goes past a closer gas station."

[1399] In this way, the car navigation system of the present invention can provide an optimal route that dynamically reflects real-time traffic information and user requests.

[1400] The following describes the processing flow.

[1401] Step 1:

[1402] The server periodically collects traffic information provided by local governments and manufacturers. This information includes traffic congestion, accidents, road closures, and road conditions during disasters. The collected information is stored in a database and updated in real time.

[1403] Step 2:

[1404] The terminal accepts the user's destination and points of interest as input. It interactively collects user input through a chatbot (e.g., "I want to stop at a gas station on the way to Tokyo Station"). The entered information is temporarily stored on the terminal.

[1405] Step 3:

[1406] The device sends the collected user input information to the server. This information includes destination, points of interest, and other specific preferences.

[1407] Step 4:

[1408] The server analyzes the received user information. Using natural language processing, it identifies the destination and points of interest, and retrieves the latest traffic information from the database.

[1409] Step 5:

[1410] The server generates the optimal route using AI based on analysis results and traffic information. The generated route is the best possible path, taking into account traffic congestion and road closures, and including the user's desired stops.

[1411] Step 6:

[1412] The server sends the generated optimal route information to the terminal. The route information includes detailed route instructions and information about potential detours.

[1413] Step 7:

[1414] The terminal receives route information from the server and displays it to the user. For example, it might display something like, "If you use this route, there are two gas stations along the way."

[1415] Step 8:

[1416] Users can provide feedback and additional requests regarding the suggested route through the chatbot. For example, they might ask, "Is there a closer gas station?"

[1417] Step 9:

[1418] The device sends the user feedback information back to the server. The server re-analyzes the data and generates the optimal route based on the new conditions.

[1419] Step 10:

[1420] The server generates a new, optimal route based on the feedback and sends it to the terminal. The regenerated route information also takes into account any additional requests from the user.

[1421] Step 11:

[1422] The device receives new, optimal routes and displays them to the user. For example, it might display, "We found a new route that goes through a closer gas station."

[1423] This series of steps allows users to obtain real-time, up-to-date traffic information and the optimal route tailored to their needs.

[1424] (Example 1)

[1425] 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".

[1426] Conventional car navigation systems often fail to adequately reflect real-time traffic information, making it difficult to suggest the optimal route for the user. Furthermore, they lack convenience due to their inability to quickly respond to additional user requests and feedback. Additionally, they do not fully utilize artificial intelligence technology for collecting traffic information and generating optimal routes.

[1427] 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.

[1428] In this invention, the server includes means for collecting traffic information from local governments and manufacturers, means for receiving destinations and points of interest from users as input, means for generating an optimal route based on the collected traffic information, means for presenting the generated optimal route to the user, means for receiving feedback from the user, means for generating the optimal route again based on the feedback, and means for training a generation AI model that provides the generated optimal route to the user. This makes it possible to dynamically reflect real-time traffic information and quickly provide the optimal route that meets the user's needs.

[1429] A "local government" is a local government agency that provides public services and manages administrative affairs.

[1430] A "manufacturer" is a company or organization that produces or manufactures products.

[1431] "Traffic information" refers to traffic-related data such as road congestion, accident information, road closure information, and road conditions during disasters.

[1432] "Means" refers to the methods or devices used to achieve a specific objective.

[1433] A "user" is an individual or group that uses the system.

[1434] The "destination" is the final point that the user aims to reach.

[1435] A "stopover point" is a specific location that a user might want to visit before reaching their destination.

[1436] A "generation method" refers to a method or apparatus that performs calculations or analyses based on specific data to generate results.

[1437] "Presentation means" refers to a method or device for displaying or providing generated information to a user.

[1438] "Feedback" refers to the opinions and requests that users provide regarding the system's suggestions and results.

[1439] A "generative AI model" is an algorithm or program that uses artificial intelligence technology to analyze data and generate specific results.

[1440] "Training methods" refer to the methods and devices used to train models or algorithms.

[1441] Modes for carrying out the invention

[1442] The embodiments for carrying out the present invention will be described in detail. First, the present invention relates to a car navigation system that collects traffic information in real time and proposes the optimal route to the user. This system collects and integrates traffic information provided by local governments and manufacturers and generates the optimal route based on user input information. Furthermore, it has a function to regenerate the route as needed based on user feedback.

[1443] 1. Server roles and processing

[1444] The server is primarily responsible for collecting traffic information, training the AI ​​model for generating traffic, and generating the optimal route. Specifically, it performs the following processes:

[1445] Data collection and database updating:

[1446] The server collects traffic information from local governments and manufacturers via APIs at specific times each day. This information includes traffic congestion, accidents, road closures, and road conditions during disasters. This information is stored in the server's database and updated by comparing it with existing data.

[1447] Training generative AI models and generating optimal routes:

[1448] The server trains a generative AI model based on the collected traffic information. This model uses destination and stopover information received from the user, along with real-time traffic data, to generate the optimal route. The generated route information is then sent to the user's device.

[1449] 2. Terminal roles and processing

[1450] The terminal collects user input information and sends it to the server. It also has the role of presenting the user with the optimal route information received from the server. The specific process is as follows:

[1451] Enter and submit user information:

[1452] The terminal uses a chatbot to receive information about destinations and points of interest entered by the user. For example, if a user enters "I want to stop at a gas station on the way to Tokyo Station," that information is sent to the server.

[1453] Route information provided:

[1454] The terminal, having received optimal route information from the server, presents that information to the user. The displayed information includes the destination, points of interest, and real-time traffic conditions.

[1455] Accepting feedback:

[1456] When a user provides feedback on the suggested route, that information is also sent from the terminal to the server. For example, if a user provides feedback such as "Is there a closer gas station?", that information is sent back to the server, and the process of generating a new optimal route is initiated.

[1457] 3. User roles and operations

[1458] Users input their destination, points of interest, and feedback through a chatbot. This allows the system to suggest the optimal route based on real-time traffic information.

[1459] Specific example:

[1460] For example, consider the process when a user inputs, "I want to stop at a gas station on the way to Tokyo Station."

[1461] Data collection and analysis:

[1462] The server retrieves the latest information from the traffic information database and performs analysis. It identifies the destination as "Tokyo Station" and the stopping point as "gas station."

[1463] Generating the optimal route:

[1464] The AI ​​model generates the optimal route based on this information, taking into account current traffic conditions. For example, it might suggest a route that avoids congestion while also stopping at gas stations as requested by the user.

[1465] Route guidance and feedback:

[1466] The device displays the initial route to the user and suggests, "This route will take you past two gas stations." If the user provides feedback such as, "Is there a closer gas station?", the server re-analyzes the route and generates a new optimal route. This new route information is sent to the device, and the user is shown, "We have found a new route that goes past a closer gas station."

[1467] Example of a prompt:

[1468] This system generates algorithms for car navigation systems. The system receives destination and stopover information from the user and provides the optimal route based on real-time traffic conditions. This system can update a traffic information database and generate the optimal route using a generated AI model.

[1469] In this way, the car navigation system of the present invention can provide an optimal route that dynamically reflects real-time traffic information and user requests.

[1470] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1471] System program processing steps

[1472] Step 1:

[1473] Data collection

[1474] The server collects traffic information from local governments and manufacturers via an API at a specific time each day. The input is traffic information data obtained from the API. The server parses this data, processes it into the required format, and stores it in the database.

[1475] Specific actions:

[1476] The server executes the "Traffic Information Update" script.

[1477] A request is sent to the API endpoint, and the JSON data received as a response is parsed.

[1478] The parsed data is stored in the database.

[1479] Step 2:

[1480] Database update

[1481] The collected traffic information is stored in the server's database. This ensures that the traffic information is always up-to-date. The input is the parsed traffic information data, and the output is the updated state of the database.

[1482] Specific actions:

[1483] The server compares the new data with the existing data.

[1484] Update existing data as needed to keep the database up to date.

[1485] Step 3:

[1486] Enter user information

[1487] The terminal receives information from the user regarding the destination and points of interest. The input is information entered by the user via the chatbot, and the output is data sent to the server.

[1488] Specific actions:

[1489] The user opens the chatbot and enters their destination and points of interest.

[1490] The terminal collects the information entered and sends it to the server.

[1491] Step 4:

[1492] Optimal route generation

[1493] The server generates the optimal route using a generative AI model based on destination and stopover point information received from the user. The input is user information and real-time traffic information data, and the output is the generated optimal route data.

[1494] Specific actions:

[1495] The server receives the user's input information.

[1496] The collected traffic information and input information are supplied to the generating AI model.

[1497] The generative AI model calculates the optimal route and generates the result.

[1498] The generated route information is sent to the terminal.

[1499] Step 5:

[1500] Presenting route information

[1501] The terminal displays the optimal route information received from the server to the user. The input is the optimal route data received from the server, and the output is the data displayed to the user.

[1502] Specific actions:

[1503] The terminal receives route information from the server.

[1504] Route information is displayed to the user on the screen.

[1505] For example, it could display information such as, "There are two gas stations along the route to Tokyo Station."

[1506] Step 6:

[1507] Processing user feedback

[1508] The device receives feedback from the user and sends it back to the server. The input is the feedback information provided by the user, and the output is the data sent to the server.

[1509] Specific actions:

[1510] The user enters feedback into the chatbot.

[1511] The device sends that feedback information to the server.

[1512] Step 7:

[1513] Regenerating the route

[1514] The server generates a new optimal route based on user feedback. The input is feedback information and the latest traffic information data, and the output is the regenerated optimal route data.

[1515] Specific actions:

[1516] The server receives feedback.

[1517] A generative AI model is used to calculate a new optimal route.

[1518] Send the calculation result to the terminal.

[1519] In this way, information exchange between the server, terminal, and user makes it possible to dynamically provide the optimal route based on real-time traffic information.

[1520] (Application Example 1)

[1521] 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".

[1522] Conventional car navigation systems, while providing optimal routes based on real-time traffic information, lacked sufficient integration with autonomous vehicles, requiring user intervention. Furthermore, their feedback-based route regeneration capabilities were inadequate, making sudden changes or optimal responses difficult. This resulted in limitations on user convenience.

[1523] 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.

[1524] In this invention, the server includes means for collecting traffic information from local governments and manufacturers, means for receiving destinations and points of interest from users as input, means for generating an optimal route based on the collected traffic information, means for presenting the generated optimal route to the user, means for receiving feedback from the user, means for generating the optimal route again based on the feedback, and means for issuing instructions related to the operation control of the vehicle. This makes it possible to provide optimal routes for autonomous vehicles based on real-time traffic information, significantly improving user convenience and safety.

[1525] "Local government" refers to a local public body, an organization that functions as a provider of traffic information.

[1526] "Manufacturers" refers to companies that manufacture automobiles and transportation-related equipment, and the term also refers to traffic information provided by these companies.

[1527] "Traffic information" refers to real-time information such as traffic congestion, accidents, road closures, and road conditions during disasters.

[1528] "User" refers to an individual or organization that uses a car navigation system.

[1529] "Destination" refers to the place the user ultimately wants to reach.

[1530] A "stopover point" refers to a location that a user might want to visit on their way to their destination.

[1531] "Generation means" refers to the technologies and algorithms used to calculate the optimal route based on collected traffic information.

[1532] "Presentation means" refers to technologies and devices used to display the generated optimal route on the user's device.

[1533] "Feedback" refers to additional requests and information provided by users.

[1534] "Regeneration means" refers to technologies and algorithms for calculating a new optimal path based on feedback.

[1535] "Vehicle operation control" refers to the operations and instructions related to the driving of autonomous vehicles.

[1536] A "generative AI model" refers to an algorithm or system that uses artificial intelligence (AI) technology to generate the optimal path.

[1537] The embodiments for carrying out the present invention will be described in detail.

[1538] First, the system of this invention collects traffic information from local governments and manufacturers, accepts input from users regarding destinations and points of interest, and generates and presents an optimal route based on that information. It also has a function to receive feedback from users and generate an optimal route again. Furthermore, this system can also issue instructions related to the operation control of vehicles.

[1539] server

[1540] The server has the following functions:

[1541] 1. Data Collection: The server periodically collects traffic information provided by local governments and manufacturers. This information includes traffic congestion information, accident information, road closure information, and road condition information during disasters.

[1542] 2. Use of Generative AI Model: The server trains a generative AI model based on collected traffic information and builds an algorithm to generate the optimal route. The generative AI model can dynamically generate the optimal route according to user requests and current conditions.

[1543] 3. Route generation and presentation: The generated optimal route is sent to the user's terminal and presented to the user.

[1544] As a concrete example, here is a prompt message in which the server identifies the destination as "Tokyo Station" and the stopover point as "gas station":

[1545] Please enter your destination: Tokyo Station

[1546] Please enter your stopping points (multiple points are allowed, separated by commas): Gas station

[1547] terminal

[1548] The device has the following features:

[1549] 1. User Input and Transmission: The terminal accepts input from the user regarding the destination and points of interest. Using a chatbot, it collects detailed information such as the user's desired points of interest and waypoints, and sends it to the server.

[1550] 2. Presenting Route Information: The system presents the user with the optimal route information received from the server. The displayed information includes not only the destination but also designated points of interest and real-time traffic conditions.

[1551] 3. Feedback Processing: User feedback and additional requests are received and resent to the server. This allows for regeneration according to the user's wishes.

[1552] user

[1553] The user performs the following actions:

[1554] 1. Input and Feedback: Users input their destination and points of interest through the chatbot. After the optimal route is presented, they can also provide feedback if further improvements are needed, requesting a route regeneration.

[1555] These functions and operations enable the system of the present invention to dynamically provide the optimal route for the user based on real-time traffic information. In particular, in autonomous vehicles, by issuing instructions related to operation control, it is possible to achieve safe and efficient driving while minimizing user intervention.

[1556] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1557] Step 1:

[1558] The server periodically collects traffic information provided by local governments and manufacturers. This process involves obtaining traffic congestion information, accident information, road closure information, and road condition information during disasters via APIs and databases. The input is traffic information data from various sources, which the server collects, stores in its database, and updates to maintain the latest traffic information. The output is the most recent traffic data stored on the server.

[1559] Step 2:

[1560] The user enters their destination and points of interest using their device. The user enters this information in text format through the device's chatbot. The input is text data of the destination and points of interest, which the device receives and then sends to the server. The output is the user's destination and points of interest data sent to the server.

[1561] Step 3:

[1562] The server references a database of collected traffic information based on the user's destination and stopover data. Here, a generative AI model is used to generate the optimal route. The input consists of the user-specified destination and stopovers, along with the latest traffic information. The server analyzes this data using the generative AI model to generate the optimal route. The output is the generated optimal route information.

[1563] Step 4:

[1564] The server sends the generated optimal route information to the user's terminal. The input is the generated optimal route information, which the server sends to the terminal. The output is the optimal route information displayed on the user's terminal. The user then starts driving based on this information.

[1565] Step 5:

[1566] Users input feedback and additional requests through the terminal. For example, feedback such as "Is there a closer gas station?" is possible. The input is the user's feedback text, which the terminal receives and then sends back to the server. The output is the user feedback data sent to the server.

[1567] Step 6:

[1568] The server, based on user feedback, consults the traffic information database again and uses a generative AI model to generate a new optimal route. The input consists of the feedback and the latest traffic information, and the server generates a regenerated optimal route based on this. The output is the newly generated optimal route information.

[1569] Step 7:

[1570] The server sends the regenerated optimal route information to the user's terminal. The input is the regenerated optimal route information, which the server sends to the terminal. The output is the new optimal route information displayed on the user's terminal. The user adjusts their driving based on this information.

[1571] 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.

[1572] The embodiments for carrying out the present invention will be described in detail.

[1573] This invention relates to a car navigation system that collects traffic information in real time and proposes the optimal route to the user. This system collects and integrates traffic information provided by local governments and manufacturers, and generates the optimal route based on user input. Furthermore, it has a function to regenerate the route as needed based on user feedback. In addition, this invention can propose routes that take into account the user's psychological state by incorporating an emotion engine that recognizes the user's emotions.

[1574] composition

[1575] 1. Server

[1576] Data collection and database updating:

[1577] The server periodically acquires traffic information provided by local governments and manufacturers, and the collected information is stored in a database. This includes traffic congestion information, accident information, road closure information, and road condition information during disasters.

[1578] Generative AI models:

[1579] The server trains a generative AI model based on collected traffic information. The generative AI model dynamically generates the optimal route according to the user's requests and current conditions. It also uses user sentiment information provided by the sentiment engine to adjust the tone and content of route suggestions.

[1580] 2. Terminal

[1581] Enter and submit user information:

[1582] The terminal accepts input from the user regarding their destination and points of interest. This input information is collected interactively, for example through a chatbot, and temporarily stored within the terminal. This information is then sent to the server.

[1583] Collection and analysis of emotional information:

[1584] The emotion engine analyzes the user's voice and text data to identify their emotions. The identified emotion information is then sent to the server.

[1585] Route information provided:

[1586] The system displays optimal route information received from the server to the user. The displayed information includes the destination, points of interest, and real-time traffic conditions. An emotion engine adjusts the display method and tone of guidance based on the user's emotions.

[1587] Feedback processing:

[1588] The system receives user feedback and additional requests through a chatbot and sends them to the server.

[1589] 3. User

[1590] Input and feedback:

[1591] Users input their destination and points of interest through a chatbot. After the optimal route is suggested, they can also provide feedback if further improvements are needed and request a route regeneration.

[1592] Specific example

[1593] For example, consider a case where a user inputs "I want to stop at a gas station on the way to Tokyo Station," and this input is accompanied by expressions of stress or anxiety.

[1594] Data collection and analysis:

[1595] The server retrieves the latest information from the traffic information database and performs analysis. It identifies the destination as "Tokyo Station" and the stopping point as "gas station."

[1596] Analysis of emotional information:

[1597] The emotion engine analyzes emotional information from the user's input and voice to detect stress and anxiety.

[1598] Generating the optimal route:

[1599] The generative AI model generates the optimal route based on user instructions and emotional information. For example, it suggests a route that avoids traffic jams, stops at the user's preferred gas station, and further reduces stress.

[1600] Route suggestion and adjustment:

[1601] The terminal presents the generated route to the user and provides guidance such as, "If you use this route, you can stop at two gas stations along the way." The information is presented in a gentle and calming tone to reduce user stress.

[1602] Feedback and regeneration:

[1603] If a user provides feedback such as "Is there a closer gas station?", the server re-analyzes the data and generates an optimal route based on the new conditions. The regenerated route similarly takes into account the user's emotional state, as determined by the emotion engine.

[1604] This series of steps allows users to be presented with the latest traffic information in real time, along with their individual preferences and even their psychological state, to find the optimal route, enabling a comfortable and safe journey.

[1605] The following describes the processing flow.

[1606] Step 1:

[1607] The server periodically collects traffic information provided by local governments and manufacturers. This information includes traffic congestion, accident information, road closure information, and road condition information during disasters. The collected information is stored in a database and updated in real time.

[1608] Step 2:

[1609] The terminal accepts the user's destination and points of interest as input. It interactively collects user input through a chatbot (e.g., "I want to stop at a gas station on the way to Tokyo Station"). The entered information is temporarily stored on the terminal.

[1610] Step 3:

[1611] The emotion engine analyzes the user's voice and text data to identify emotions. For example, it identifies emotions such as stress, anxiety, and joy based on the user's tone of voice and entered text.

[1612] Step 4:

[1613] The device transmits the collected user input information and sentiment information to the server.

[1614] Step 5:

[1615] The server analyzes the received user information and sentiment information. It uses natural language processing to identify destinations and points of interest, and retrieves the latest traffic information from the database.

[1616] Step 6:

[1617] The server generates the optimal route using AI based on analysis results and traffic information. The generated route is the best possible path, taking into account traffic congestion and road closures, and including the user's desired stops. It also considers the user's emotional state to select a route and guidance method that reduces stress.

[1618] Step 7:

[1619] The server sends the generated optimal route information to the terminal. This route information includes detailed directions and information on potential detours. It is presented in a tone and content that reflects the user's emotions.

[1620] Step 8:

[1621] The terminal receives route information from the server and displays it to the user. For example, it might display something like, "If you use this route, there are two gas stations along the way." Furthermore, if the user is feeling stressed, the guidance will be provided in a calm and reassuring tone.

[1622] Step 9:

[1623] Users can provide feedback and additional requests regarding the suggested route through the chatbot. For example, they might ask, "Is there a closer gas station?"

[1624] Step 10:

[1625] The device sends the user feedback information back to the server. The server re-analyzes the data and generates the optimal route based on the new conditions.

[1626] Step 11:

[1627] The server generates a new, optimal route based on feedback and sends it to the terminal. The regenerated route information takes into account the user's additional requests and emotional state.

[1628] Step 12:

[1629] The device receives and displays the new, optimal route to the user. For example, it might say, "We've found a new route that goes through a closer gas station." If the user is feeling stressed, the guidance will be delivered in a calmer tone.

[1630] This series of steps provides users with the most up-to-date traffic information in real time, along with an optimal route that takes into account their individual needs and psychological state.

[1631] (Example 2)

[1632] 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".

[1633] Conventional car navigation systems primarily suggested optimal routes based only on traffic information and the user's destination information. However, they lacked the ability to consider the user's psychological state and feedback when suggesting routes, thus failing to adequately meet the needs of users experiencing stress or anxiety. Furthermore, the lack of a function to receive and regenerate real-time feedback made it difficult to respond quickly and flexibly.

[1634] 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.

[1635] In this invention, the server includes means for collecting traffic information from local governments and manufacturers, means for receiving destinations and points of interest from users as input, means for generating an optimal route based on the collected traffic information, means for presenting the generated optimal route to the user, means for collecting and analyzing user sentiment information, means for receiving feedback from users, and means for generating an optimal route again based on the feedback and sentiment information. This enables flexible and rapid route suggestions that take into account the user's psychological state.

[1636] "Traffic information" refers to data related to road traffic, such as traffic congestion information, accident information, road closure information, and road condition information during disasters.

[1637] A "user" is an individual or group that intends to travel to a destination using a car navigation system.

[1638] "Destination" refers to the place the user wants to reach.

[1639] A "stopover point" refers to a place where a user might consider temporarily staying or visiting on their way to their final destination.

[1640] "Generation means" refers to technology that calculates and proposes the optimal route based on user input information and traffic information.

[1641] "Emotional information" refers to data that indicates the user's psychological state, including emotions such as stress, anxiety, and joy.

[1642] "Feedback" refers to additional requests or evaluations provided by users.

[1643] "Regeneration methods" refer to technologies that recalculate the optimal route based on user feedback and emotional information.

[1644] This invention relates to a car navigation system that collects traffic information in real time and proposes an optimal route that takes into account the user's emotional information. This system collects and integrates traffic information provided by local governments and manufacturers, generates an optimal route based on user input information, and can further regenerate the route based on user feedback.

[1645] server

[1646] The server has the following functions:

[1647] Data collection and updating:

[1648] The server periodically retrieves real-time traffic information (e.g., traffic congestion information, accident information, road closure information, etc.) provided by local governments and manufacturers via APIs. The retrieved information is stored in a database such as PostgreSQL.

[1649] Training and route generation for generative AI models:

[1650] A generative AI model (e.g., a general natural language processing model) is trained based on the collected traffic information. This model dynamically generates the optimal route using the user's destination and points of interest, real-time traffic conditions, and user sentiment information provided by the sentiment engine. The following prompt statements are used during this process:

[1651] If a user says they want to stop at a gas station on their way to Tokyo Station, please generate the optimal route considering traffic information and emotional factors. The user is experiencing stress.

[1652] terminal

[1653] The device has the following features:

[1654] Enter and submit user information:

[1655] The device (e.g., a mobile device) collects information about destinations and points of interest entered by the user through a chatbot. This information is temporarily stored in the device's memory and then sent to the server.

[1656] Collection and analysis of emotional information:

[1657] The device collects the user's voice and text data and analyzes it using an emotion engine (e.g., an emotion analysis API). The analysis results (stress, anxiety, etc.) are sent to the server.

[1658] Route information provided:

[1659] The device displays the optimal route received from the server to the user. This display includes the destination, points of interest, and real-time traffic conditions. The tone of the route guidance is also adjusted according to the user's emotional state.

[1660] Accepting feedback:

[1661] The device receives user feedback and additional requests via a chatbot. This feedback is sent to the server and used to regenerate routes.

[1662] User

[1663] The user performs the following actions:

[1664] Input and feedback:

[1665] Users input their destination and points of interest via the chatbot. For example, they might input, "I want to stop at a gas station on the way to Tokyo Station." After the optimal route is suggested, they can also provide feedback if further improvements are needed, such as "Are there any closer gas stations?"

[1666] Specific example:

[1667] If a user enters "I want to stop at a gas station on the way to Tokyo Station" into the chatbot, the device sends this information to the server. The server generates the optimal route using an AI model based on the collected traffic information, and proposes a route that also takes into account the user's emotional state. The device then informs the user that "this route will allow you to stop at two gas stations along the way," guiding them in a gentle and calm tone to reduce stress. If the user provides feedback such as "Is there a closer gas station?", the server re-analyzes the data and presents the user with a regenerated route based on the new conditions.

[1668] This invention allows users to be presented with the latest traffic information in real time, along with their individual preferences and psychological state, to find the optimal route, enabling comfortable and safe travel.

[1669] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1670] Step 1:

[1671] Data collection

[1672] The server obtains real-time traffic information from traffic information providers via an API. For example, it obtains traffic congestion information, accident information, and road closure information in JSON format. The server analyzes this data, extracts the necessary information, and stores it in a database. The information stored in the database includes location, event type, severity, and timestamp.

[1673] Input: Traffic information obtained from an external API (in JSON format)

[1674] Output: Passage information stored in the database (database update via SQL insert statement)

[1675] Specifically, the server updates the database using the following SQL statement:

[1676] SQL

[1677] INSERT INTO traffic_info (location, event, severity, timestamp)

[1678] VALUES ('Tokyo', 'Accident', 'Severe', '2023-10-01 14:00:00');

[1679] Step 2:

[1680] Enter user information

[1681] The terminal receives information about destinations and points of interest entered by the user through a chatbot. The collected information is temporarily stored in the terminal's memory and then sent to the server.

[1682] Input: User input to the chatbot (text format)

[1683] Output: User destination and stopover information to be sent to the server (in JSON format)

[1684] Specifically, the terminal sends the following JSON data to the server:

[1685] json

[1686] {

[1687] "destination": "Tokyo Station",

[1688] "waypoints": ["Gas Station"]

[1689] }

[1690] Step 3:

[1691] Collection and analysis of emotional information

[1692] The device collects the user's voice and text data and analyzes it using an emotion engine. The emotion engine analyzes the provided data and identifies the user's emotions (stress, anxiety, joy, etc.). The identified emotion information is sent to the server.

[1693] Input: User's voice data or text data (input data)

[1694] Output: Sentiment information as analysis results (JSON format)

[1695] Specifically, the following analysis results are sent to the server:

[1696] json

[1697] {

[1698] "text": "I'm looking for a gas station but I'm worried.",

[1699] "emotion": "stress"

[1700] }

[1701] Step 4:

[1702] Optimal route generation

[1703] The server uses a generative AI model to generate the optimal route based on user input and emotional information. Specifically, it provides the generative AI model with collected traffic information, user instructions, and emotional information as input to generate the best route.

[1704] Input: Traffic information, user's destination and points of interest, sentiment information (internal database and JSON format).

[1705] Output: Optimal route information (JSON format)

[1706] As a concrete example, the following prompt message is input to the generating AI model:

[1707] If a user says they want to stop at a gas station on their way to Tokyo Station, please generate the optimal route considering traffic information and emotional factors. The user is experiencing stress.

[1708] Step 5:

[1709] Presenting route information

[1710] The device displays the optimal route received from the server to the user. This display includes the destination, points of interest, and real-time traffic conditions. The tone of the route guidance is also adjusted according to the user's emotional state.

[1711] Input: Optimal route information received from the server (in JSON format)

[1712] Output: Route information presented to the user (visual display and audio guidance)

[1713] The specific actions presented to the user are as follows:

[1714] "If you use this route, you can stop at two gas stations along the way."

[1715] Step 6:

[1716] Processing user feedback

[1717] The device receives user feedback and additional requests via a chatbot and sends them to the server.

[1718] Input: User feedback (text format)

[1719] Output: Feedback information to send to the server (JSON format)

[1720] As a concrete example of action, consider the following feedback:

[1721] "Is there a gas station closer?"

[1722] Step 7:

[1723] Root regeneration

[1724] The server uses a generative AI model based on user feedback to generate the optimal route again. The regenerated route also takes the user's emotional state into consideration.

[1725] Input: User feedback information (JSON format)

[1726] Output: Regenerated optimal route information (JSON format)

[1727] As a concrete action, the following prompt message is input to the AI ​​model again:

[1728] If a user provides feedback requesting a closer gas station, generate a new, optimal route considering traffic and emotional factors. Users are experiencing stress.

[1729] In this way, the system can provide the optimal route based on real-time, up-to-date traffic information, taking into account the user's psychological state.

[1730] (Application Example 2)

[1731] 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".

[1732] Conventional car navigation systems have the ability to collect real-time traffic information and generate optimal routes, but they do not consider the user's psychological state when suggesting routes. Therefore, inefficient route guidance may be provided even when the user is experiencing stress. Furthermore, the ability to appropriately reflect user feedback and dynamically regenerate routes has been insufficient. Solving these problems and providing a more comfortable and safer driving experience is essential.

[1733] 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.

[1734] In this invention, the server includes means for collecting traffic information from local governments and manufacturers, means for recognizing the user's emotions, means for generating an optimal route based on the collected traffic information, means for presenting the generated optimal route to the user, means for receiving feedback from the user, means for generating the optimal route again based on the feedback, and means for adjusting the optimal route suggestion method based on the recognized emotions. This makes it possible to suggest comfortable and safe routes that reflect the user's psychological state in real time.

[1735] "Local government" refers to local public bodies or similar organizations, and is generally an organization that provides traffic information and disaster information.

[1736] A "manufacturer" is a company or organization that manufactures and provides transportation-related products and infrastructure, and may also be a source of traffic information.

[1737] "Traffic information" refers to all information related to road traffic, including traffic congestion information, accident information, road closure information, and road condition information during disasters.

[1738] "User" refers to an individual or group that uses a car navigation system.

[1739] "Destination" refers to the place the user wants to reach, which is entered into the car's navigation system.

[1740] A "stopover point" refers to a place where a user might want to stop on their way to their destination.

[1741] "Optimal route" refers to the most efficient and safe route, generated based on traffic information and user input.

[1742] "Generation means" refers to devices or software that perform calculations and algorithms for generating the optimal path.

[1743] "Presentation means" refers to displays or audio guidance devices used to show the generated optimal route to the user.

[1744] "Feedback" refers to the evaluations and opinions that users give regarding the paths presented.

[1745] "Regeneration means" refers to devices or software that regenerate the optimal route based on user feedback.

[1746] "Means of recognizing emotions" refers to sensors and data analysis technologies used to analyze a user's emotional state.

[1747] "Means of adjustment" refers to devices or software that modify the method of suggesting the optimal route based on recognized emotions.

[1748] Modes for carrying out the invention

[1749] The embodiments for carrying out the present invention will be described in detail.

[1750] This invention relates to a car navigation system that collects traffic information in real time and proposes the optimal route to the user. This system collects and integrates traffic information provided by local governments and manufacturers, and generates the optimal route based on user feedback. Furthermore, by incorporating an emotion engine that recognizes the user's emotions, it is possible to propose routes that take their psychological state into consideration.

[1751] 1. Server

[1752] The server periodically acquires traffic information provided by local governments and manufacturers and stores it in a database. This includes traffic congestion information, accident information, road closure information, and road condition information during disasters. Based on the collected traffic information, a generative AI model is trained. The generative AI model dynamically generates the optimal route according to the user's requests and current conditions. It also uses the user's sentiment information to adjust the tone and content of route suggestions.

[1753] 2. Terminal

[1754] The terminal accepts input from the user regarding destinations and points of interest. The entered information is temporarily stored on the terminal and then sent to the server. It also features an emotion engine that analyzes the user's voice and text data to identify emotions and sends this information to the server. Furthermore, it displays optimal route information received from the server to the user, adjusting the display method and guidance tone according to the user's emotions. User feedback is also accepted and sent to the server.

[1755] 3. User

[1756] Users input their destination and points of interest through a chatbot. They can also provide feedback after the optimal route is suggested and request a route regeneration.

[1757] System configuration and operation

[1758] In this system, the server uses the following hardware and software:

[1759] APIs as a means of data collection (e.g., Google Maps API, HERE API)

[1760] Database management systems (e.g., MySQL, PostgreSQL)

[1761] Machine learning engines as generative AI models (e.g., TensorFlow, PyTorch)

[1762] Natural language processing tools as emotion engines (e.g., IBM Watson, Google Cloud Natural Language)

[1763] The device uses the following hardware and software:

[1764] Touchscreens and voice recognition systems for accepting user input (e.g., Google Voice API, Apple Siri)

[1765] Voice and image analysis technologies for identifying emotions (e.g., OpenCV, Microsoft Azure Cognitive Services)

[1766] UI / UX interfaces for adjusting display methods and tone (e.g., React Native, Flutter)

[1767] Adding specific examples

[1768] For example, if a user sets a destination for an autonomous vehicle via a smartphone app and inputs that they want to stop at a cafe along the way, the autonomous driving system will suggest the least stressful route based on the latest traffic information and the user's sentiment data. A chatbot will gently confirm the request and suggest the best cafe, and readjust the route based on the user's feedback.

[1769] Example of a prompt

[1770] Please generate a program for a navigation application for autonomous vehicles. This application will collect real-time traffic information, suggest the optimal route, and use the in-car camera and microphone to recognize passenger emotions. It will adjust the route based on emotion data and combine it with a chatbot for a user-friendly conversation.

[1771] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1772] Step 1:

[1773] The server periodically acquires traffic information provided by local governments and manufacturers. This information is collected via APIs (e.g., Google Maps API, HERE API). The collected traffic congestion information, accident information, road closure information, and road condition information during disasters are stored in a database system (e.g., MySQL, PostgreSQL).

[1774] Input: Traffic information obtained from API

[1775] Output: Traffic information stored in the database

[1776] Step 2:

[1777] The terminal accepts input from the user regarding their destination and points of interest. This information is collected interactively through a chatbot and temporarily stored on the terminal.

[1778] Input: Destination and stopover points entered by the user.

[1779] Output: Input information stored in the device's temporary storage.

[1780] Step 3:

[1781] The device analyzes the user's voice and text data and uses an emotion engine (e.g., IBM Watson, Google Cloud Natural Language) to identify the user's emotions. This emotion information is then sent to the server.

[1782] Input: User's voice data and text data

[1783] Output: Sentiment information sent to the server

[1784] Step 4:

[1785] The server generates the optimal route using a generative AI model (e.g., TensorFlow, PyTorch) based on collected traffic information, user input information, and sentiment information. The generated optimal route is then sent from the server to the terminal.

[1786] Input: Traffic information retrieved from the database, user input information, sentiment information

[1787] Output: Generated optimal path

[1788] Step 5:

[1789] The terminal presents the user with optimal route information sent from the server. The display method and tone of guidance are adjusted based on the user's emotions, as determined by an emotion engine.

[1790] Input: Optimal routing information sent from the server

[1791] Output: Route information presented to the user

[1792] Step 6:

[1793] Users provide feedback on the suggested routes through the chatbot. This feedback information is sent from the device to the server.

[1794] Input: User feedback

[1795] Output: Feedback information sent to the server

[1796] Step 7:

[1797] Based on the feedback information received, the server regenerates the optimal route using a regenerative AI model. The regenerated optimal route information is then adjusted to take emotional information into consideration and sent to the terminal.

[1798] Input: User feedback information, sentiment information, traffic information

[1799] Output: Regenerated optimal route information

[1800] This series of processing steps allows users to obtain the latest traffic information and the optimal route tailored to their psychological state in real time.

[1801] 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.

[1802] 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.

[1803] 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.

[1804] 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.

[1805] 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.

[1806] 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.

[1807] 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.

[1808] 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.

[1809] 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."

[1810] 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.

[1811] 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.

[1812] 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.

[1813] 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.

[1814] 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.

[1815] 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.

[1816] 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.

[1817] 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.

[1818] 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.

[1819] 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.

[1820] 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.

[1821] 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.

[1822] The following is further disclosed regarding the embodiments described above.

[1823] (Claim 1)

[1824] Means of collecting traffic information by local governments and manufacturers,

[1825] A means of receiving destinations and points of interest from users as input,

[1826] A generation means for generating an optimal route based on collected traffic information,

[1827] A means of presenting the generated optimal path to the user,

[1828] A means of receiving user feedback,

[1829] A means for generating the optimal path again based on feedback,

[1830] A system that includes this.

[1831] (Claim 2)

[1832] The system according to claim 1, wherein the traffic information includes traffic information provision services and road closure information in the event of a disaster.

[1833] (Claim 3)

[1834] The system according to claim 1, wherein the generation means uses artificial intelligence technology.

[1835] "Example 1"

[1836] (Claim 1)

[1837] Means of collecting traffic information by local governments and manufacturers,

[1838] A means of receiving destinations and points of interest from users as input,

[1839] A generation means for generating an optimal route based on collected traffic information,

[1840] A means of presenting the generated optimal path to the user,

[1841] A means of receiving user feedback,

[1842] A means for generating the optimal path again based on feedback,

[1843] A means for training a generative AI model that provides the user with the generated optimal path,

[1844] A system that includes this.

[1845] (Claim 2)

[1846] The system according to claim 1, wherein the traffic information includes traffic information provision services and road closure information in the event of a disaster.

[1847] (Claim 3)

[1848] The system according to claim 1, wherein the generation means uses artificial intelligence technology.

[1849] "Application Example 1"

[1850] (Claim 1)

[1851] Means of collecting traffic information by local governments and manufacturers,

[1852] A means of receiving destinations and points of interest from users as input,

[1853] A generation means for generating an optimal route based on collected traffic information,

[1854] A means of presenting the generated optimal path to the user,

[1855] A means of receiving user feedback,

[1856] A means for generating the optimal path again based on feedback,

[1857] Means for issuing instructions related to the operation control of a vehicle,

[1858] A system that includes this.

[1859] (Claim 2)

[1860] The system according to claim 1, wherein the traffic information includes traffic information provision services and road closure information in the event of a disaster.

[1861] (Claim 3)

[1862] The system according to claim 1, wherein the generation means uses a generation AI model.

[1863] "Example 2 of combining an emotion engine"

[1864] (Claim 1)

[1865] Means of collecting traffic information by local governments and manufacturers,

[1866] A means of receiving destinations and points of interest from users as input,

[1867] A generation means for generating an optimal route based on collected traffic information,

[1868] A means of presenting the generated optimal path to the user,

[1869] A means of collecting and analyzing user sentiment information,

[1870] A means of receiving user feedback,

[1871] A means of regenerating the optimal path based on feedback and emotional information,

[1872] A system that includes this.

[1873] (Claim 2)

[1874] The system according to claim 1, wherein the traffic information includes traffic information provision services and road closure information in the event of a disaster.

[1875] (Claim 3)

[1876] The system according to claim 1, wherein the generation means uses artificial intelligence technology.

[1877] "Application example 2 when combining with an emotional engine"

[1878] (Claim 1)

[1879] Means of collecting traffic information by local governments and manufacturers,

[1880] A means of receiving destinations and points of interest from users as input,

[1881] A generation means for generating an optimal route based on collected traffic information,

[1882] A means of presenting the generated optimal path to the user,

[1883] A means of receiving user feedback,

[1884] A means for generating the optimal path again based on feedback,

[1885] Means of recognizing user emotions,

[1886] A means for adjusting the method of suggesting the optimal route based on recognized emotions,

[1887] A system that includes this.

[1888] (Claim 2)

[1889] The system according to claim 1, wherein the traffic information includes traffic information provision services and road closure information in the event of a disaster.

[1890] (Claim 3)

[1891] The system according to claim 1, wherein the generation means uses artificial intelligence technology. [Explanation of Symbols]

[1892] 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. Means of collecting traffic information by local governments and manufacturers, A means of receiving destinations and points of interest from users as input, A generation means for generating an optimal route based on collected traffic information, A means of presenting the generated optimal path to the user, A means of receiving user feedback, A means for generating the optimal path again based on feedback, A system that includes this.

2. The system according to claim 1, wherein the traffic information includes traffic information provision services and road closure information in the event of a disaster.

3. The system according to claim 1, wherein the generation means uses artificial intelligence technology.

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