system

Abstract

We provide the system. [Solution] A means for the user to input the starting point and destination, A means of collecting real-time traffic information based on options specified by the user, A means of calculating the optimal route using collected traffic information, A means of sending calculated optimal route information to the user's terminal, A means for displaying and guiding the user through route information received by the user's device, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a persona chatbot control method 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 a conventional navigation system, it is difficult to provide an optimal route because real-time traffic information cannot be fully considered. In particular, if the timing of signal changes and the opening and closing information of level crossings are ignored, users may experience wasted waiting time. Also, it has been a problem that it is difficult to provide a route along specific user options, such as when preferring narrow roads or when wanting to arrive at the destination quickly.

Means for Solving the Problems

[0005] To solve the above-mentioned problems, the present invention provides the following means: a system comprising means for the user to input a starting point and destination, means for collecting real-time traffic information based on options specified by the user, means for calculating the optimal route using the collected traffic information, means for transmitting the calculated optimal route information to the user's terminal, and means for displaying and guiding the user's terminal to the route information received. Furthermore, this system collects information on the timing of signal changes and the opening and closing of railroad crossings, and calculates a route that prioritizes narrow roads or a route that gets to the destination faster based on the user's selection, thereby achieving optimal navigation according to the user's requests.

[0006] "User" refers to a person who uses a navigation system to receive route guidance or the driver of a vehicle.

[0007] The "starting point" indicates the location where navigation begins.

[0008] "Destination" refers to the final location guided by the navigation system.

[0009] "Options" refer to specific route conditions or restrictions that a user can select for the navigation system.

[0010] "Real-time traffic information" refers to the latest data on current traffic conditions, including traffic light timings, railway crossing opening / closing status, and congestion information.

[0011] "The timing of traffic light changes" refers to the specific time and pattern in which a road traffic light changes from red to green, or from green to red.

[0012] "Level crossing opening / closing information" refers to information indicating whether a level crossing is open or closed, and the timing of any changes in that state.

[0013] The "optimal route" refers to the most efficient or preferred path based on the user's selected options and current traffic information.

[0014] "Calculated optimal route information" refers to detailed information about the recommended route calculated based on collected data and user settings.

[0015] "Terminal" refers to a device used by a user to receive, display, and operate navigation information, and includes smartphones and car navigation systems. [Brief explanation of the drawing]

[0016] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This 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] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This 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] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This 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] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This 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 Embodiment 2 when combined with an emotion engine. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when combined with an emotion engine.

Modes for Carrying Out the Invention

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

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

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

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

[0021] In the following embodiments, the 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.

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

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

[0024] [First Embodiment]

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

[0026] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

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

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

[0029] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

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

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

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

[0033] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

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

[0035] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

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

[0037] This invention is a navigation system that collects and analyzes traffic information in real time based on options specified by the user and provides the optimal route, and is specifically implemented as follows.

[0038] 1. Accepting user requests

[0039] Terminal: The user opens a navigation application and enters their starting point (current location) and destination. The user also selects options such as "prioritize narrow roads" or "get to destination quickly."

[0040] Terminal: The entered information is sent to the server as a request.

[0041] 2. Collection of real-time traffic information

[0042] Server: Upon receiving a request from a user, it verifies the origin and destination.

[0043] Server: Retrieves real-time traffic information from traffic information providers. This information includes traffic signal timing, railway crossing opening and closing information, traffic congestion, road construction, and accident information.

[0044] Server: The collected traffic information is temporarily stored in a database.

[0045] 3. Calculating square roots

[0046] Server: Applies a route calculation algorithm based on collected traffic information and user-selected options.

[0047] Server: Generates multiple route candidates and evaluates the following elements for each route.

[0048] Duration

[0049] Waiting time at traffic lights

[0050] railroad crossing waiting time

[0051] Server: Compares the evaluation results of each route and selects the optimal route that best suits the user's specified options.

[0052] 4. Route provision

[0053] Server: Generates optimal route information and sends it to the user's terminal.

[0054] Terminal: Analyzes received route information and displays it on the navigation screen. Simultaneously, voice guidance is initiated, providing real-time directions to the user.

[0055] Specific example

[0056] Case 1: Route prioritizing narrow roads

[0057] 1. Terminal: User A enters "City Hall" as the destination and selects the "Prioritize narrow roads" option.

[0058] 2. Server: Receives the request and checks user A's current location and destination.

[0059] 3. Server: Retrieves information such as signal change timing, level crossing opening / closing information, and traffic congestion information from traffic information providers and stores it in a database.

[0060] 4. Server: Calculates the optimal route based on the "Prioritize narrower paths" option. Evaluates multiple candidates and selects the best route for user A.

[0061] 5. Server: Sends the optimal route to user A's terminal.

[0062] 6. Terminal: Displays the received route information and starts voice guidance.

[0063] Case 2: When you want to reach your destination quickly

[0064] 1. Terminal: User B enters "station" as the destination and selects the "I want to get to my destination quickly" option.

[0065] 2. Server: Receives the request and checks user B's current location and destination.

[0066] 3. Server: Retrieves information such as signal change timing, level crossing opening / closing information, and traffic congestion information from traffic information providers and stores it in a database.

[0067] 4. Server: Based on the "I want to reach my destination quickly" option, it calculates the optimal route. It evaluates multiple options and selects the route with the shortest waiting time.

[0068] 5. Server: Sends the optimal route to user B's terminal.

[0069] 6. Terminal: Displays the received route information and starts voice guidance.

[0070] The following describes the processing flow.

[0071] Step 1:

[0072] Terminal: The user launches the navigation application and enters the starting point (current location) and destination. The user can also select options such as "prioritize narrow roads" or "get to destination quickly."

[0073] Step 2:

[0074] Terminal: Sends data regarding the entered departure point, destination, and options as a request to the server.

[0075] Step 3:

[0076] Server: Parses the received request to confirm the user's origin and destination, and the selected options.

[0077] Step 4:

[0078] Server: Accesses traffic information providers to obtain real-time traffic information. This information includes traffic signal timing, railway crossing opening and closing information, traffic congestion status, road construction and accident information, etc.

[0079] Step 5:

[0080] Server: Temporarily stores acquired traffic information in a database.

[0081] Step 6:

[0082] Server: Applies a route calculation algorithm based on stored traffic information and user configuration options.

[0083] Step 7:

[0084] Server: Generates multiple route options based on collected real-time information and evaluates the travel time, signal waiting time, and level crossing waiting time for each route.

[0085] Step 8:

[0086] Server: Compares the evaluation results of each route and selects the optimal route that best suits the user's chosen option.

[0087] Step 9:

[0088] Server: Generates optimal route information and sends it to the user's terminal.

[0089] Step 10:

[0090] Terminal: Analyzes received route information and displays it on the navigation screen.

[0091] Step 11:

[0092] Terminal: Starts voice guidance and provides real-time navigation to the user.

[0093] Step 12:

[0094] Terminal: Until the user reaches their destination, it will re-obtain real-time updated traffic information as needed and reroute and optimize the route.

[0095] (Example 1)

[0096] 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."

[0097] Conventional navigation systems have been unable to fully utilize real-time traffic information, making it difficult to provide the optimal route based on user-specified options. Furthermore, because they could not utilize detailed traffic information such as the timing of traffic light changes and the opening and closing of railway crossings, they could not provide optimal guidance for the user's desired route conditions. The objective of this invention is to solve this problem and provide more accurate route guidance.

[0098] 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.

[0099] In this invention, the server includes means for the user to input a starting point and destination, means for collecting real-time traffic information based on options specified by the user, means for temporarily storing the collected traffic information in a database, means for applying a route calculation algorithm based on the stored data, means for selecting the optimal route based on the evaluation results, means for transmitting the calculated optimal route information to the user's terminal, and means for displaying and guiding the user through the route information received by the user's terminal. This enables highly accurate route guidance based on real-time traffic information, including the timing of signal changes and the opening and closing of railway crossings.

[0100] "A means for users to input their starting point and destination" refers to a mechanism that provides an interface for users to input their current location and destination.

[0101] "Means of collecting real-time traffic information based on user-specified options" refers to a system that acquires real-time traffic conditions according to the route conditions selected by the user (for example, "prioritize narrow roads" or "want to reach the destination quickly").

[0102] "Means for temporarily storing collected traffic information in a database" refers to a mechanism for temporarily storing collected traffic information in a database for use in subsequent processing.

[0103] "A means of applying a route calculation algorithm based on saved data" refers to a mechanism that executes an algorithm that calculates routes using traffic information stored in a database.

[0104] "Method for selecting the optimal route based on evaluation results" refers to a system that selects the route that best suits the user's specified conditions based on the evaluation results of the route calculation algorithm.

[0105] "Means for sending calculated optimal route information to the user's terminal" refers to a mechanism for sending information about the optimal route selected by the server to the user's terminal.

[0106] "Means for displaying and guiding users through route information received by the user's device" refers to a system that displays route information received by the user's device on the screen and provides directions to the user through voice guidance or other means.

[0107] "Information on the timing of traffic signal changes and the opening and closing of level crossings" refers to information regarding the timing of changes in traffic signals and the opening and closing of level crossings.

[0108] A "route that prioritizes narrow roads" refers to a route that prioritizes the use of narrow roads, and includes criteria for selecting a route with many narrow roads.

[0109] A "fastest route to the destination" is a route that prioritizes getting the user to their destination in the shortest possible time.

[0110] This invention is a navigation system that collects and analyzes traffic information in real time based on user-specified options and provides the optimal route. A specific embodiment of this system is described in detail below.

[0111] System Configuration

[0112] This navigation system consists of a user terminal, a server, and a database. The user terminal is a mobile device such as a smartphone, with a navigation application installed. The server collects and stores real-time traffic information and calculates routes. The database temporarily stores the collected traffic information.

[0113] Hardware and software to be used

[0114] User's device:

[0115] These are mobile devices such as smartphones and tablets, which provide the interface for applications.

[0116] server:

[0117] It collects, stores, and calculates routes based on traffic information. The server has software installed that interacts with traffic information providers (e.g., Google® Maps API, HERE Technologies).

[0118] Database:

[0119] Relational databases such as MySQL (registered trademark) and PostgreSQL are used to temporarily store traffic information.

[0120] System operation

[0121] 1. Accepting user requests:

[0122] The user opens the navigation app and enters their starting point (usually their current location) and destination. They also select options such as "prioritize narrow roads" or "get to destination quickly." This information is sent to the server in JSON format.

[0123] 2. Gathering real-time traffic information:

[0124] The server receives requests from users and communicates with traffic information providers to obtain real-time traffic information. This includes information such as traffic light change timings, railway crossing opening and closing information, traffic congestion, road construction, and accident information. This information is temporarily stored in a database.

[0125] 3. Square root calculation:

[0126] The server applies a route calculation algorithm based on traffic information stored in the database and user options. It generates multiple route candidates and evaluates factors such as travel time, traffic light waiting time, and railway crossing waiting time for each route. It then selects the most suitable route.

[0127] 4. Route provision:

[0128] The server generates calculated optimal route information and sends it to the user's device. The user's device analyzes the received route information and displays it on the navigation screen. Simultaneously, voice guidance begins, providing the user with real-time directions.

[0129] Specific example

[0130] For example, if a user enters "City Hall" as their destination in the app and selects the "Prioritize narrow roads" option, the server receives the request, retrieves real-time traffic information, and stores it in the database. Then, based on the "Prioritize narrow roads" option, it calculates the optimal route and sends the result to the user's device. The user's device displays the received route information and begins voice guidance.

[0131] Example of a prompt

[0132] "Please give me directions to the city hall, prioritizing narrower roads."

[0133] "Please tell me the shortest route to the station."

[0134] This invention enables highly accurate route guidance based on real-time, detailed traffic information.

[0135] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0136] Step 1: Accepting user requests

[0137] User: The user launches a navigation app on their smartphone and enters their starting point (usually their current location) and destination. They also select options such as "prioritize narrow roads" or "get to destination quickly."

[0138] Input: Departure point, destination, and optional information.

[0139] Terminal: Converts the entered information into a JSON-formatted request object and sends it to the server as an HTTP POST request.

[0140] Output: Request object in JSON format.

[0141] Step 2: Gathering real-time traffic information

[0142] Server: Receives requests from users and parses the origin, destination, and options.

[0143] Input: Request object in JSON format.

[0144] Server: Communicates with traffic information providers to obtain real-time traffic data. This information includes traffic congestion, traffic light change timing, railway crossing opening / closing information, road construction, and accident information.

[0145] Data processing: The acquired traffic information is formatted into an appropriate format.

[0146] Output: Real-time traffic information.

[0147] Step 3: Temporarily save traffic information

[0148] Server: Temporarily stores the acquired traffic information in a database (e.g., MySQL).

[0149] Input: Real-time traffic information.

[0150] Database: Stores traffic information.

[0151] Output: Success / Failure status.

[0152] Step 4: Calculating square roots

[0153] Server: Applies a route calculation algorithm based on temporarily stored traffic information and user-specified options. The A-search algorithm is commonly used.

[0154] Input: Traffic information, user options.

[0155] Data calculation: Calculate and evaluate the travel time, traffic light waiting time, and railroad crossing waiting time for each route candidate.

[0156] Output: Multiple route candidates evaluated.

[0157] Step 5: Selecting the optimal route

[0158] Server: Selects the optimal route from the evaluated route candidates based on the user's specified options.

[0159] Input: Evaluation results, user options.

[0160] Data processing: Comparison of evaluation scores.

[0161] Output: Optimal route information.

[0162] Step 6: Sending Route Information

[0163] Server: Converts optimal route information into JSON format and sends it to the user's terminal.

[0164] Input: Optimal route information.

[0165] Data processing: Convert to JSON format.

[0166] Output: Route information in JSON format.

[0167] Step 7: Display and guidance of route information

[0168] Terminal: Analyzes received route information and displays it on the navigation screen. Simultaneously, voice guidance begins.

[0169] Input: Route information in JSON format.

[0170] Data processing: Converts data to a format suitable for screen display and audio guidance.

[0171] Output: Navigation screen display and voice guidance.

[0172] Example prompt statements

[0173] "Please give me directions to the city hall, prioritizing narrower roads."

[0174] "Please tell me the shortest route to the station."

[0175] This allows users to receive real-time, optimal route guidance based on specified conditions.

[0176] (Application Example 1)

[0177] 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."

[0178] Conventional navigation systems fail to fully utilize real-time traffic information, making it particularly difficult for autonomous vehicles to select optimal routes that take into account traffic light wait times, railway crossing wait times, and road congestion. Furthermore, flexible route suggestions based on user choices are difficult, resulting in a lack of safety and efficiency. As a result, the operation of autonomous vehicles involves wasted time and energy, leading to a decrease in overall operational efficiency.

[0179] 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.

[0180] In this invention, the server includes means for the user to input a starting point and destination, means for collecting real-time traffic information based on options specified by the user, means for obtaining real-time traffic information from sensors of the autonomous vehicle and an external traffic information provider, means for calculating the optimal route based on the collected traffic information and the user's selection, and means for providing the optimal route as visual and voice guidance. This enables the selection of the optimal route considering real-time traffic conditions, realizes flexible guidance according to the user's selection, and improves the operational efficiency and safety of the autonomous vehicle.

[0181] The "starting point" is the current location or starting point that the user sets when starting navigation.

[0182] A "destination" is the location that the user sets as the target location for the navigation system to guide them to.

[0183] "Options" refer to the conditions and priorities that the user specifies for route selection within the navigation system.

[0184] "Real-time traffic information" refers to the latest traffic condition data obtained from traffic information providers, vehicle sensors, etc.

[0185] An "autonomous vehicle" is a vehicle that operates autonomously using a system, without requiring operation by a human driver.

[0186] A "sensor" is a device used to detect the surrounding conditions of a vehicle and collect data.

[0187] A "traffic information provider" is a service that provides traffic-related data such as road conditions, congestion, and traffic light timings.

[0188] "Methods for calculating routes" refer to algorithms that calculate the optimal travel route based on user input information and collected traffic data.

[0189] "Visual navigation" refers to visual navigation information displayed on digital displays or interfaces.

[0190] "Voice guidance" refers to real-time voice navigation instructions provided through a speaker.

[0191] "User selection" refers to the preferences and conditions that users individually set within the navigation system.

[0192] This invention is a navigation system that collects and analyzes traffic information in real time based on user-specified options and provides the optimal route. It can particularly improve the operational efficiency and safety of autonomous vehicles.

[0193] System Configuration

[0194] This system consists of the following main components:

[0195] 1. User terminal:

[0196] The user enters the starting point and destination.

[0197] Users can set options such as "prioritize narrow roads" or "arrive at destination quickly."

[0198] 2. Server:

[0199] Receives requests from user terminals.

[0200] Real-time traffic information is obtained from sensors in the autonomous vehicle and from external traffic information providers.

[0201] The collected traffic information is stored in a database, and the necessary data is queried in real time.

[0202] Based on the user's selected options, the optimal route is calculated using Dijkstra's algorithm.

[0203] The calculated optimal route is sent to the user's device.

[0204] 3. Autonomous vehicles:

[0205] A central vehicle computer (e.g., a general-purpose GPU-based driving platform) is used.

[0206] Use an infotainment system (e.g., a real-time operating system).

[0207] Environmental recognition is performed using data from various sensors (e.g., cameras, LiDAR, RADAR).

[0208] Flow of operations

[0209] 1. Accepting user requests:

[0210] The user opens the navigation application and enters the starting point, destination, and any options. This information is sent to the server.

[0211] 2. Gathering real-time traffic information:

[0212] The server collects data on current traffic conditions (such as when traffic lights change, when level crossings are open or closed, and how congested the area is) from traffic information providers and vehicle sensors.

[0213] The collected information is stored in a database, enabling fast queries.

[0214] 3. Square root calculation:

[0215] Based on the collected traffic information and the options specified by the user, the server uses Dijkstra's algorithm to calculate multiple routes and select the optimal route.

[0216] 4. Route provision:

[0217] The optimal route information is sent to the user's device, and visual and voice guidance begins. This allows the user to receive guidance in real time.

[0218] Specific example

[0219] As a concrete example, consider a scenario where user A enters "City Hall" as their destination and selects the "Prioritize narrow roads" option. In this case, the server performs the following actions:

[0220] 1. The server checks user A's current location and destination.

[0221] 2. The server retrieves information such as the timing of signal changes, railway crossing opening and closing information, and traffic congestion information from traffic information providers and stores it in a database.

[0222] 3. Based on the "Prioritize narrower paths" option, the server uses Dijkstra's algorithm to calculate the optimal route.

[0223] 4. The server sends the calculated optimal route to user A's terminal, and user A's terminal starts visual and voice guidance.

[0224] Example of a prompt:

[0225] If the user enters "City Hall" as the destination and selects the "Prioritize narrow roads" option:

[0226] By analyzing real-time traffic data obtained from sensors and APIs, Dijkstra's algorithm calculates the optimal route that prioritizes narrow roads.

[0227] The calculated route is evaluated in a database and provided with visual and audio guidance.

[0228] As described above, this invention is a system that makes maximum use of real-time traffic information to provide optimal route guidance for autonomous vehicles.

[0229] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0230] Step 1:

[0231] The user opens the navigation application and enters their starting point, destination, and options. At this stage, the input includes the starting point (GPS location), destination (address or location information), and user-selected options (e.g., "prioritize narrow roads" or "get to destination quickly"). This information is then sent from the application to the server.

[0232] Step 2:

[0233] The server receives a request from the user. The request includes the origin, destination, and options. The server analyzes this information to determine the scope of the traffic information to be collected next. Specifically, it sets the geographical range from the user's current location to their destination.

[0234] Step 3:

[0235] The server acquires real-time traffic information from sensors in autonomous vehicles and from external traffic information providers (e.g., traffic information APIs). Input data includes signal change timings, level crossing opening / closing information, traffic congestion information, and accident information. This data is temporarily stored in a database on the server.

[0236] Step 4:

[0237] The server generates multiple route options based on collected traffic information and user-selected options. Specifically, it uses Dijkstra's algorithm to calculate the optimal route. Input data consists of traffic information and user options, while output is multiple route options and their evaluation results.

[0238] Step 5:

[0239] The server evaluates the generated route candidates and selects the most suitable route. Evaluation criteria include travel time, traffic light waiting times, railway crossing waiting times, and road types. The optimal route is the one that best matches the user's specified options.

[0240] Step 6:

[0241] The server generates optimal route information and sends it to the user's terminal. The input is the evaluated optimal route information, and the output is a data packet for display on the user's terminal.

[0242] Step 7:

[0243] The system analyzes route information received by the user's device and displays it on the navigation screen. Specific actions include displaying visual guidance and initiating voice guidance. Input data is route information transmitted from the server, and output is the display screen and voice guidance. Users can receive real-time navigation guidance.

[0244] 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.

[0245] This invention is a navigation system that collects and analyzes traffic information in real time based on user-specified options and provides the optimal route. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it enables more flexible route guidance tailored to the user's state. Specific embodiments are described below.

[0246] 1. Accepting user requests

[0247] Terminal: The user launches the navigation application and enters the starting point (current location) and destination. The user selects options such as "prioritize narrow roads" or "get to destination quickly."

[0248] Device: Additionally, the emotion engine is activated, recognizing emotions from the user's voice and facial expressions.

[0249] For example, if a user displays expressions of anger or impatience, the emotion engine recognizes this as "stress."

[0250] Terminal: Sends the input data and recognized emotion information as a request to the server.

[0251] 2. Collection of real-time traffic information

[0252] Server: Receives requests from users and verifies the origin and destination, as well as the selected options and sentiment information.

[0253] Server: Accesses traffic information providers to obtain real-time traffic information. This information includes traffic signal timing, railway crossing opening and closing information, traffic congestion status, road construction and accident information, etc.

[0254] Server: The acquired traffic information is temporarily stored in the database.

[0255] 3. Calculating square roots

[0256] Server: Applies a route calculation algorithm based on stored traffic information, user settings options, and sentiment information.

[0257] For example, if the system detects that a user is experiencing stress, it will select a route with smoother traffic flow and shorter waiting times.

[0258] Server: Generates multiple route options and evaluates the travel time, signal waiting time, and level crossing waiting time for each route.

[0259] Server: Compares the evaluation results of each route and selects the optimal route that best suits the user's options and sentiment information.

[0260] 4. Route provision

[0261] Server: Generates optimal route information and sends it to the user's terminal.

[0262] Terminal: Analyzes received route information and displays it on the navigation screen. Simultaneously, voice guidance is initiated, providing real-time directions to the user.

[0263] Specific example

[0264] Case 1: Optimal route selection using an emotion engine

[0265] 1. Terminal: User A enters "City Hall" as the destination and selects the "Prioritize narrow roads" option.

[0266] 2. Terminal: The emotion engine detects anxiety from user A's voice.

[0267] 3. Terminal: Sends the input data and recognized emotion information to the server.

[0268] 4. Server: Receives the request and verifies the origin and destination, options, and sentiment information.

[0269] 5. Server: Retrieves information such as signal change timing, level crossing opening / closing information, and traffic congestion information from traffic information providers and stores it in a database.

[0270] 6. Server: Calculates the optimal route based on the "Prioritize narrower paths" option and the server's emotional state (emotional information indicating anxiety).

[0271] 7. Server: Evaluate each route candidate and select the optimal route for user A.

[0272] 8. Server: Sends the optimal route to user A's terminal.

[0273] 9. Terminal: Displays the received route information and starts voice guidance.

[0274] Case 2: Route reselection based on an emotion engine

[0275] 1. Terminal: User B enters "station" as the destination and selects the "I want to get to my destination quickly" option.

[0276] 2. Device: The emotion engine detects stress from user B's facial expressions.

[0277] 3. Terminal: Transmits the input data and the recognized emotion information to the server.

[0278] 4. Server: Receives the request, and checks the departure point, destination, options, and emotion information.

[0279] 5. Server: Obtains the timing of signal changes, opening and closing information of level crossings, traffic congestion information, etc. from the traffic information provider, and saves them in the database.

[0280] 6. Server: Calculates the optimal route based on the "want to arrive at the destination quickly" option and the stressed emotion.

[0281] 7. Server: Evaluates each route candidate and selects the optimal route for User B.

[0282] 8. Server: Transmits the optimal route to User B's terminal.

[0283] 9. Terminal: Displays the received route information and starts voice guidance.

[0284] The processing flow will be described below.

[0285] Step 1:

[0286] Terminal: The user launches the navigation application and enters the departure point (current location) and the destination. The user selects options such as "prioritize narrow roads" or "want to arrive at the destination quickly".

[0287] Step 2:

[0288] Terminal: The emotion engine is launched, and the emotion is recognized from the user's voice and expression. For example, the user's expression is captured through the camera, and voice analysis is performed using voice recognition technology.

[0289] Step 3:

[0290] Device: The emotion engine analyzes the emotional information it recognizes to determine whether the user is feeling "anxiety" or "stress."

[0291] Step 4:

[0292] Terminal: Sends the origin, destination, user-selected options, and sentiment information as a request to the server.

[0293] Step 5:

[0294] Server: Analyzes incoming requests to determine the user's origin, destination, options, and sentiment information.

[0295] Step 6:

[0296] Server: Accesses traffic information providers to obtain real-time traffic information such as signal change timing, level crossing opening and closing information, traffic congestion status, road construction and accident information.

[0297] Step 7:

[0298] Server: Temporarily stores acquired traffic information in a database.

[0299] Step 8:

[0300] Server: Applies route calculation algorithms based on stored traffic information, user selection options, and sentiment information.

[0301] Step 9:

[0302] Server: Generates multiple route options and evaluates the travel time, signal waiting time, and level crossing waiting time for each route.

[0303] Step 10:

[0304] Server: Compare the evaluation results of each route and select the optimal route considering the option of "prioritize narrow roads" and the sense of impatience.

[0305] Step 11:

[0306] Server: Create the optimal route information and send it to the user's terminal.

[0307] Step 12:

[0308] Terminal: Analyze the received route information and display it on the navigation screen. Also start the corresponding voice guidance.

[0309] Step 13:

[0310] Terminal: The user starts moving towards the destination.

[0311] Step 14:

[0312] Terminal: Continuously monitor the user's emotional information during movement and send updated information to the server as needed.

[0313] Step 15:

[0314] Server: Based on the real-time traffic information and the updated emotional information of the user, recalculate the optimal route and reroute if necessary.

[0315] Step 16:

[0316] Terminal: Receive the new route information and update the navigation screen. Continuously execute the series of processes until the user reaches the destination.

[0317] (Example 2)

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

[0319] Conventional navigation systems have the problem of failing to alleviate user stress and anxiety because they provide route guidance without considering the user's emotional state. Furthermore, route calculations based solely on real-time traffic information have the challenge of not being able to flexibly respond to individual user needs (for example, wanting to choose a quiet route or wanting to reach the destination quickly).

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

[0321] In this invention, the server includes means for the user to input a starting point and destination, means for collecting real-time traffic information based on options specified by the user, means for calculating an optimal route using the collected traffic information and the user's emotional information, means for transmitting the calculated optimal route information to the user's terminal, and means for displaying and guiding the user's terminal to the route information received. This enables the provision of an optimal route according to the user's emotional state and flexible route guidance that reflects real-time traffic information and the user's individual needs.

[0322] The "starting point" refers to the location where the user begins their route to their current location or destination.

[0323] "Destination" refers to the place the user ultimately wants to reach.

[0324] "Options" refer to the conditions and settings that users prioritize in route guidance. For example, these include "I want to get to my destination quickly" or "Prioritize narrow roads."

[0325] "Real-time traffic information" refers to the most up-to-date information in time, such as current traffic conditions, traffic light change timings, railway crossing opening and closing information, traffic congestion status, road construction and accident information.

[0326] "Emotional information" refers to the emotional state analyzed from the user's voice, facial expressions, and other behaviors. Examples include stress, anxiety, and anger.

[0327] A "route calculation algorithm" refers to a method for calculating the optimal route based on collected traffic information, user settings, and sentiment information. Examples include the A algorithm and Dijkstra's algorithm.

[0328] "Terminal" refers to devices used by users, such as mobile phones, tablets, and car navigation systems.

[0329] A "server" refers to a central processing unit that processes requests sent by users, collects and analyzes necessary information, and sends the results to the user's terminal.

[0330] "Route information" refers to detailed data about the calculated route. This includes the route itself, estimated travel time, traffic light waiting times, railway crossing waiting times, etc.

[0331] This invention is a navigation system that collects and analyzes traffic information in real time based on user-specified options and emotional information, and provides the optimal route. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it enables more flexible route guidance tailored to the user's state.

[0332] First, the user launches the navigation application and enters their starting point (current location) and destination. The user can select options such as "prioritize narrow roads" or "get to destination quickly." The device has a built-in emotion engine that recognizes the user's emotions in real time from their voice and facial expressions. For example, if the user shows signs of anger or impatience, the emotion engine recognizes this as "stress."

[0333] Next, the terminal sends the entered data and recognized sentiment information as a request to the server. The server receives the request from the user and verifies the origin and destination, as well as the selected options and sentiment information. The server then accesses a traffic information provider (e.g., Google Maps API or Here API) to obtain real-time traffic information. This information includes traffic light change timings, railway crossing opening and closing information, traffic congestion, road construction and accident information, etc. The retrieved traffic information is temporarily stored in a database.

[0334] The server applies a route calculation algorithm based on stored traffic information, user settings options, and emotional information. For example, if the server detects that the user is stressed, it selects a route with smooth traffic flow and minimal waiting times. The server generates multiple route options and evaluates the travel time, traffic light waiting times, and railway crossing waiting times for each route. It compares the evaluation results of each route and selects the optimal route that best suits the user's options and emotional information.

[0335] Once the optimal route information is generated, the server sends it to the user's terminal. The terminal analyzes the received route information and displays it on the navigation screen. Simultaneously, voice guidance begins, providing instructions to the user in real time.

[0336] For example, suppose user A enters "City Hall" as their destination and selects the "Prioritize narrow roads" option. If the emotion engine detects impatience from user A's voice, the device sends this information to the server. The server receives the request and retrieves information such as traffic light timings, railway crossing opening / closing information, and traffic congestion information from a traffic information provider. Then, based on the "Prioritize narrow roads" option and the impatient emotion information, it calculates the optimal route and sends it to user A's device. The device displays the received route information and starts voice guidance.

[0337] As another example, suppose user B enters "station" as their destination and selects the "I want to get to my destination quickly" option. If the emotion engine detects stress from user B's facial expression, the terminal sends the entered data and the recognized emotion information to the server. The server receives the request and retrieves information such as traffic signal timing, level crossing opening / closing information, and traffic congestion information from a traffic information provider. It then calculates the optimal route based on the "I want to get to my destination quickly" option and stress emotion, and sends it to user B's terminal. The terminal displays the received route information and starts voice guidance.

[0338] (Example of a prompt message)

[0339] "Explain how, after the user enters their starting point and destination and selects an option, the emotion engine recognizes the user's emotions and calculates the optimal route."

[0340] "Please describe, in natural language, the processing flow of a navigation system that collects real-time traffic information and takes user sentiment into consideration."

[0341] This invention enables the provision of optimal routes according to the user's emotional state, allowing for flexible route guidance that reflects real-time traffic information and the user's individual needs. Furthermore, by combining it with an emotion engine, an improvement in the user experience can be expected.

[0342] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0343] Step 1:

[0344] The terminal launches the navigation application, and the user enters the starting point and destination. The user selects options such as "I want to get to the destination quickly" or "Prioritize narrow roads." The terminal receives the starting point, destination, and options as input. The terminal receives this input data and proceeds to the next step.

[0345] Step 2:

[0346] The device activates an emotion engine to recognize emotional information from the user's voice and facial expressions. Specifically, it uses the device's camera and microphone to capture facial expressions and voice, and a generative AI model analyzes this data. The user's voice and image data are provided to the emotion engine as input. The emotion engine analyzes this data and outputs emotional information, such as whether the user is feeling stressed.

[0347] Step 3:

[0348] The terminal sends collected origin, destination, options, and sentiment information to the server. As input, request data containing origin, destination, options, and sentiment information is sent from the terminal to the server. This data is transmitted via communication protocols such as HTTP or WebSocket.

[0349] Step 4:

[0350] The server analyzes the request data received from the terminal to confirm the origin and destination, as well as the selected options and sentiment information. The request data is provided to the server as input. The server analyzes this data and extracts the information necessary for route calculation.

[0351] Step 5:

[0352] The server sends API requests to traffic information providers to obtain real-time traffic information. Specifically, the server accesses APIs such as the Google Maps API and the Here API to collect traffic information. As input, API requests are sent from the server. As output, traffic information such as the timing of signal changes, railway crossing opening and closing information, traffic congestion status, road construction and accident information is returned to the server.

[0353] Step 6:

[0354] The server temporarily stores the traffic information it acquires in a database. Traffic information is provided to the server as input. The server stores this information in a database (e.g., Redis) so that it can be used in subsequent route calculations.

[0355] Step 7:

[0356] The server applies a route calculation algorithm based on stored traffic information, user settings options, and sentiment information. The server uses route calculation algorithms such as the A algorithm or Dijkstra's algorithm to calculate the optimal route. Traffic information, settings options, and sentiment information are provided to the server as input. Multiple route candidates are generated as output.

[0357] Step 8:

[0358] The server evaluates the generated route candidates and selects the optimal route that best suits the user's configuration options and sentiment information. Multiple route candidates are provided as input. The server evaluates these and selects the optimal route. The optimal route information is generated as output.

[0359] Step 9:

[0360] The server sends optimal route information to the user's terminal. The server receives optimal route information as input. The server sends this information to the terminal, which then receives it. HTTP or WebSocket are used as the communication protocol.

[0361] Step 10:

[0362] The terminal analyzes the route information it receives and displays it on the navigation screen. Furthermore, it initiates voice guidance, providing real-time instructions to the user. The terminal receives optimal route information as input. The terminal analyzes this information and provides visual and audio guidance.

[0363] (Application Example 2)

[0364] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0365] Traditional navigation systems provided optimal routes based on real-time traffic information, but they failed to consider the user's emotional state and lacked route guidance adapted to the user's mental condition. Therefore, they could not address psychological needs, such as when the user was anxious or wanted to relax, potentially leading to a lower satisfaction with the driving experience. Furthermore, there was a need for technology that could efficiently analyze the user's emotional state within a specific vehicle environment and provide appropriate navigation.

[0366] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes an emotion analysis means for recognizing the user's emotions, a means for collecting real-time traffic information based on options specified by the user, and a means for calculating the optimal route using the collected traffic information and emotion information. This makes it possible to provide route guidance that is appropriate to the user's emotional state.

[0367] "Means for users to input their starting point and destination" refers to an interface for users to input their current location and desired destination using electronic devices.

[0368] A "means of emotional analysis that recognizes user emotions" is a system that analyzes a user's facial expressions and voice to determine their emotional state in real time.

[0369] "Means for collecting real-time traffic information based on user-specified options" refers to a system for obtaining traffic conditions and event information from online databases, APIs, etc., according to the conditions selected by the user.

[0370] "Means for calculating the optimal route using collected traffic and sentiment information" refers to a system that uses algorithms to calculate the route that best suits the user's mental and physical needs, based on acquired traffic and sentiment data.

[0371] "Means for transmitting calculated optimal route information to the user's terminal" refers to a communication system for transferring information about the optimal route calculated on a server to the electronic device being used by the user.

[0372] "Means for displaying and guiding users through route information received by their device" refers to interfaces and software for visually and audibly displaying and guiding users through optimal route information on their device.

[0373] This invention relates to a navigation system that analyzes the user's emotional state and provides the optimal route based on real-time traffic information. This navigation system is particularly applicable to autonomous vehicles and enables flexible route guidance that responds to the user's psychological needs.

[0374] 1. System Overview

[0375] This system includes means for emotion analysis to recognize the user's emotions, means for collecting real-time traffic information, means for calculating the optimal route using the collected information, means for transmitting the calculation results to the user's terminal, and means for displaying and guiding the user through the received route information.

[0376] 2. Hardware and software to be used

[0377] hardware

[0378] Camera: Cameras mounted on the autonomous vehicle will be used to capture the user's facial expressions.

[0379] Microphone: The user's voice will be recorded using a microphone installed in the autonomous vehicle.

[0380] Central control terminal: Receives user input via an in-vehicle touchscreen display.

[0381] software

[0382] Emotion analysis engine: Uses Microsoft® Azure® Face API and Google Cloud Vision API to analyze the user's facial expressions and voice.

[0383] Real-time traffic information acquisition module: Uses TomTom and the Google Maps API to collect real-time traffic information.

[0384] Route calculation algorithm: Using algorithms such as Algorithm A, the optimal route is calculated based on collected traffic and sentiment information.

[0385] 3. Data calculation and processing

[0386] Emotion Recognition: The vehicle captures the user's face and voice using an in-car camera and microphone, and an emotion analysis engine performs real-time analysis. For example, if the user is anxious, the system prioritizes a smoother, shorter route to reduce their stress.

[0387] Traffic Information Gathering: Access a real-time traffic database to collect information such as traffic light change timings, railway crossing opening and closing information, traffic congestion status, road construction and accident information.

[0388] Route Calculation: Based on collected traffic information, user sentiment data, and selected options, the system calculates the optimal route. For example, if the user wants to relax, it might suggest a scenic route.

[0389] Route information transmission: The calculated optimal route information is transmitted to the central control terminal to provide information to the user.

[0390] 4. Specific Examples

[0391] The following are specific examples of how this system can be used.

[0392] Example 1:

[0393] The user gets into the self-driving vehicle and enters "park" as their destination. An emotion analysis engine detects impatience from the user's voice, and the system collects real-time traffic information. As a result, the optimal route with minimal traffic lights and congestion is calculated, and the self-driving system begins driving along that route.

[0394] Example 2:

[0395] The user enters "Shopping Mall" as their destination and selects "Prioritize scenic routes" as an option. The emotion analysis engine detects relaxation from the user's facial expressions and acquires traffic information. The system suggests a scenic route, and the vehicle begins driving along that route.

[0396] 5. Example of a prompt statement

[0397] The following is an example of a prompt message to input into a generative AI model.

[0398] Write Python code to calculate the optimal route based on current traffic conditions. Consider the user's sentiment and selection options. Sentiment information will be obtained from facial and speech recognition. Traffic data will be obtained from the Google Maps API. Use the A algorithm for route calculation.

[0399] In this way, an optimal navigation system that takes into account the user's psychological state and actual traffic conditions can be realized. This is expected to significantly improve the driving experience of autonomous vehicles.

[0400] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0401] Step 1:

[0402] The user enters the starting point and destination into the device.

[0403] The input data consists of the starting point (current location) and the destination. This input data is sent from the terminal to the server for use in the next processing step.

[0404] Step 2:

[0405] The device's camera and microphone are activated to recognize the user's emotions.

[0406] The input data used consists of video captured by the camera and audio recorded by the microphone. This data is analyzed in real time by an emotion analysis engine, and the user's emotional state (e.g., relaxed, anxious, stressed) is output. This emotional information is used in the next step.

[0407] Step 3:

[0408] The server collects real-time traffic information based on options specified by the user.

[0409] The input data used includes user-selected options (e.g., shortest travel time, scenic route) and real-time traffic data obtained from a traffic information API. This data includes, for example, traffic signal change timings, railway crossing opening / closing information, and traffic congestion information obtained from the API. This traffic information is used in the next step.

[0410] Step 4:

[0411] The server uses collected traffic and sentiment information to calculate the optimal route.

[0412] The input data used includes acquired traffic information, user sentiment information, and navigation options selected by the user. The server applies route calculation algorithms, such as the A algorithm, to this data to calculate the optimal route. The output is the calculated optimal route information.

[0413] Step 5:

[0414] The server sends the calculated optimal route information to the user's terminal.

[0415] The optimal route information is used as input data. The server sends this information to the terminal, and the information sent to the terminal is used in the next step.

[0416] Step 6:

[0417] The device displays and guides the user through route information it has received.

[0418] The optimal route information transmitted from the server is used as input data. The terminal analyzes this information and initiates visual navigation display and voice guidance. This allows the user to confirm the optimal route information while driving.

[0419] Through the processing steps described above, an optimal navigation system is realized based on the user's emotional state and traffic information. This provides a comfortable driving experience that meets the user's psychological needs.

[0420] 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.

[0421] 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.

[0422] 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.

[0423] [Second Embodiment]

[0424] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0425] 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.

[0426] 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).

[0427] 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.

[0428] 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.

[0429] 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).

[0430] 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.

[0431] 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.

[0432] 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.

[0433] 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.

[0434] 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.

[0435] 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".

[0436] This invention is a navigation system that collects and analyzes traffic information in real time based on options specified by the user and provides the optimal route, and is specifically implemented as follows.

[0437] 1. Accepting user requests

[0438] Terminal: The user opens a navigation application and enters their starting point (current location) and destination. The user also selects options such as "prioritize narrow roads" or "get to destination quickly."

[0439] Terminal: The entered information is sent to the server as a request.

[0440] 2. Collection of real-time traffic information

[0441] Server: Upon receiving a request from a user, it verifies the origin and destination.

[0442] Server: Retrieves real-time traffic information from traffic information providers. This information includes traffic signal timing, railway crossing opening and closing information, traffic congestion, road construction, and accident information.

[0443] Server: The collected traffic information is temporarily stored in a database.

[0444] 3. Calculating square roots

[0445] Server: Applies a route calculation algorithm based on collected traffic information and user-selected options.

[0446] Server: Generates multiple route candidates and evaluates the following elements for each route.

[0447] Duration

[0448] Waiting time at traffic lights

[0449] railroad crossing waiting time

[0450] Server: Compares the evaluation results of each route and selects the optimal route that best suits the user's specified options.

[0451] 4. Route provision

[0452] Server: Generates optimal route information and sends it to the user's terminal.

[0453] Terminal: Analyzes received route information and displays it on the navigation screen. Simultaneously, voice guidance is initiated, providing real-time directions to the user.

[0454] Specific example

[0455] Case 1: Route prioritizing narrow roads

[0456] 1. Terminal: User A enters "City Hall" as the destination and selects the "Prioritize narrow roads" option.

[0457] 2. Server: Receives the request and checks user A's current location and destination.

[0458] 3. Server: Retrieves information such as signal change timing, level crossing opening / closing information, and traffic congestion information from traffic information providers and stores it in a database.

[0459] 4. Server: Calculates the optimal route based on the "Prioritize narrower paths" option. Evaluates multiple candidates and selects the best route for user A.

[0460] 5. Server: Sends the optimal route to user A's terminal.

[0461] 6. Terminal: Displays the received route information and starts voice guidance.

[0462] Case 2: When you want to reach your destination quickly

[0463] 1. Terminal: User B enters "station" as the destination and selects the "I want to get to my destination quickly" option.

[0464] 2. Server: Receives the request and checks user B's current location and destination.

[0465] 3. Server: Retrieves information such as signal change timing, level crossing opening / closing information, and traffic congestion information from traffic information providers and stores it in a database.

[0466] 4. Server: Based on the "I want to reach my destination quickly" option, it calculates the optimal route. It evaluates multiple options and selects the route with the shortest waiting time.

[0467] 5. Server: Sends the optimal route to user B's terminal.

[0468] 6. Terminal: Displays the received route information and starts voice guidance.

[0469] The following describes the processing flow.

[0470] Step 1:

[0471] Terminal: The user launches the navigation application and enters the starting point (current location) and destination. The user can also select options such as "prioritize narrow roads" or "get to destination quickly."

[0472] Step 2:

[0473] Terminal: Sends data regarding the entered departure point, destination, and options as a request to the server.

[0474] Step 3:

[0475] Server: Parses the received request to confirm the user's origin and destination, and the selected options.

[0476] Step 4:

[0477] Server: Accesses traffic information providers to obtain real-time traffic information. This information includes traffic signal timing, railway crossing opening and closing information, traffic congestion status, road construction and accident information, etc.

[0478] Step 5:

[0479] Server: Temporarily stores acquired traffic information in a database.

[0480] Step 6:

[0481] Server: Applies a route calculation algorithm based on stored traffic information and user configuration options.

[0482] Step 7:

[0483] Server: Generates multiple route options based on collected real-time information and evaluates the travel time, signal waiting time, and level crossing waiting time for each route.

[0484] Step 8:

[0485] Server: Compares the evaluation results of each route and selects the optimal route that best suits the user's chosen option.

[0486] Step 9:

[0487] Server: Generates optimal route information and sends it to the user's terminal.

[0488] Step 10:

[0489] Terminal: Analyzes received route information and displays it on the navigation screen.

[0490] Step 11:

[0491] Terminal: Starts voice guidance and provides real-time navigation to the user.

[0492] Step 12:

[0493] Terminal: Until the user reaches their destination, it will re-obtain real-time updated traffic information as needed and reroute and optimize the route.

[0494] (Example 1)

[0495] 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."

[0496] Conventional navigation systems have been unable to fully utilize real-time traffic information, making it difficult to provide the optimal route based on user-specified options. Furthermore, because they could not utilize detailed traffic information such as the timing of traffic light changes and the opening and closing of railway crossings, they could not provide optimal guidance for the user's desired route conditions. The objective of this invention is to solve this problem and provide more accurate route guidance.

[0497] 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.

[0498] In this invention, the server includes means for the user to input a starting point and destination, means for collecting real-time traffic information based on options specified by the user, means for temporarily storing the collected traffic information in a database, means for applying a route calculation algorithm based on the stored data, means for selecting the optimal route based on the evaluation results, means for transmitting the calculated optimal route information to the user's terminal, and means for displaying and guiding the user through the route information received by the user's terminal. This enables highly accurate route guidance based on real-time traffic information, including the timing of signal changes and the opening and closing of railway crossings.

[0499] "A means for users to input their starting point and destination" refers to a mechanism that provides an interface for users to input their current location and destination.

[0500] "Means of collecting real-time traffic information based on user-specified options" refers to a system that acquires real-time traffic conditions according to the route conditions selected by the user (for example, "prioritize narrow roads" or "want to reach the destination quickly").

[0501] "Means for temporarily storing collected traffic information in a database" refers to a mechanism for temporarily storing collected traffic information in a database for use in subsequent processing.

[0502] "A means of applying a route calculation algorithm based on saved data" refers to a mechanism that executes an algorithm that calculates routes using traffic information stored in a database.

[0503] "Method for selecting the optimal route based on evaluation results" refers to a system that selects the route that best suits the user's specified conditions based on the evaluation results of the route calculation algorithm.

[0504] "Means for sending calculated optimal route information to the user's terminal" refers to a mechanism for sending information about the optimal route selected by the server to the user's terminal.

[0505] "Means for displaying and guiding users through route information received by the user's device" refers to a system that displays route information received by the user's device on the screen and provides directions to the user through voice guidance or other means.

[0506] "Information on the timing of traffic signal changes and the opening and closing of level crossings" refers to information regarding the timing of changes in traffic signals and the opening and closing of level crossings.

[0507] A "route that prioritizes narrow roads" refers to a route that prioritizes the use of narrow roads, and includes criteria for selecting a route with many narrow roads.

[0508] A "fastest route to the destination" is a route that prioritizes getting the user to their destination in the shortest possible time.

[0509] This invention is a navigation system that collects and analyzes traffic information in real time based on user-specified options and provides the optimal route. A specific embodiment of this system is described in detail below.

[0510] System Configuration

[0511] This navigation system consists of a user terminal, a server, and a database. The user terminal is a mobile device such as a smartphone, with a navigation application installed. The server collects and stores real-time traffic information and calculates routes. The database temporarily stores the collected traffic information.

[0512] Hardware and software to be used

[0513] User's device:

[0514] These are mobile devices such as smartphones and tablets, which provide the interface for applications.

[0515] server:

[0516] It collects, stores, and calculates routes based on traffic information. The server has software installed that interacts with traffic information providers (e.g., Google Maps API, HERE Technologies).

[0517] Database:

[0518] Relational databases such as MySQL and PostgreSQL are used to temporarily store traffic information.

[0519] System operation

[0520] 1. Accepting user requests:

[0521] The user opens the navigation app and enters their starting point (usually their current location) and destination. They also select options such as "prioritize narrow roads" or "get to destination quickly." This information is sent to the server in JSON format.

[0522] 2. Gathering real-time traffic information:

[0523] The server receives requests from users and communicates with traffic information providers to obtain real-time traffic information. This includes information such as traffic light change timings, railway crossing opening and closing information, traffic congestion, road construction, and accident information. This information is temporarily stored in a database.

[0524] 3. Square root calculation:

[0525] The server applies a route calculation algorithm based on traffic information stored in the database and user options. It generates multiple route candidates and evaluates factors such as travel time, traffic light waiting time, and railway crossing waiting time for each route. It then selects the most suitable route.

[0526] 4. Route provision:

[0527] The server generates calculated optimal route information and sends it to the user's device. The user's device analyzes the received route information and displays it on the navigation screen. Simultaneously, voice guidance begins, providing the user with real-time directions.

[0528] Specific example

[0529] For example, if a user enters "City Hall" as their destination in the app and selects the "Prioritize narrow roads" option, the server receives the request, retrieves real-time traffic information, and stores it in the database. Then, based on the "Prioritize narrow roads" option, it calculates the optimal route and sends the result to the user's device. The user's device displays the received route information and begins voice guidance.

[0530] Example of a prompt

[0531] "Please give me directions to the city hall, prioritizing narrower roads."

[0532] "Please tell me the shortest route to the station."

[0533] This invention enables highly accurate route guidance based on real-time, detailed traffic information.

[0534] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0535] Step 1: Accepting user requests

[0536] User: The user launches a navigation app on their smartphone and enters their starting point (usually their current location) and destination. They also select options such as "prioritize narrow roads" or "get to destination quickly."

[0537] Input: Departure point, destination, and optional information.

[0538] Terminal: Converts the entered information into a JSON-formatted request object and sends it to the server as an HTTP POST request.

[0539] Output: Request object in JSON format.

[0540] Step 2: Gathering real-time traffic information

[0541] Server: Receives requests from users and parses the origin, destination, and options.

[0542] Input: Request object in JSON format.

[0543] Server: Communicates with traffic information providers to obtain real-time traffic data. This information includes traffic congestion, traffic light change timing, railway crossing opening / closing information, road construction, and accident information.

[0544] Data processing: The acquired traffic information is formatted into an appropriate format.

[0545] Output: Real-time traffic information.

[0546] Step 3: Temporarily save traffic information

[0547] Server: Temporarily stores the acquired traffic information in a database (e.g., MySQL).

[0548] Input: Real-time traffic information.

[0549] Database: Stores traffic information.

[0550] Output: Success / Failure status.

[0551] Step 4: Calculating square roots

[0552] Server: Applies a route calculation algorithm based on temporarily stored traffic information and user-specified options. The A-search algorithm is commonly used.

[0553] Input: Traffic information, user options.

[0554] Data calculation: Calculate and evaluate the travel time, traffic light waiting time, and railroad crossing waiting time for each route candidate.

[0555] Output: Multiple route candidates evaluated.

[0556] Step 5: Selecting the optimal route

[0557] Server: Selects the optimal route from the evaluated route candidates based on the user's specified options.

[0558] Input: Evaluation results, user options.

[0559] Data processing: Comparison of evaluation scores.

[0560] Output: Optimal route information.

[0561] Step 6: Sending Route Information

[0562] Server: Converts optimal route information into JSON format and sends it to the user's terminal.

[0563] Input: Optimal route information.

[0564] Data processing: Convert to JSON format.

[0565] Output: Route information in JSON format.

[0566] Step 7: Display and guidance of route information

[0567] Terminal: Analyzes received route information and displays it on the navigation screen. Simultaneously, voice guidance begins.

[0568] Input: Route information in JSON format.

[0569] Data processing: Converts data to a format suitable for screen display and audio guidance.

[0570] Output: Navigation screen display and voice guidance.

[0571] Example prompt statements

[0572] "Please give me directions to the city hall, prioritizing narrower roads."

[0573] "Please tell me the shortest route to the station."

[0574] This allows users to receive real-time, optimal route guidance based on specified conditions.

[0575] (Application Example 1)

[0576] 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."

[0577] Conventional navigation systems fail to fully utilize real-time traffic information, making it particularly difficult for autonomous vehicles to select optimal routes that take into account traffic light wait times, railway crossing wait times, and road congestion. Furthermore, flexible route suggestions based on user choices are difficult, resulting in a lack of safety and efficiency. As a result, the operation of autonomous vehicles involves wasted time and energy, leading to a decrease in overall operational efficiency.

[0578] 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.

[0579] In this invention, the server includes means for the user to input a starting point and destination, means for collecting real-time traffic information based on options specified by the user, means for obtaining real-time traffic information from sensors of the autonomous vehicle and an external traffic information provider, means for calculating the optimal route based on the collected traffic information and the user's selection, and means for providing the optimal route as visual and voice guidance. This enables the selection of the optimal route considering real-time traffic conditions, realizes flexible guidance according to the user's selection, and improves the operational efficiency and safety of the autonomous vehicle.

[0580] The "starting point" is the current location or starting point that the user sets when starting navigation.

[0581] A "destination" is the location that the user sets as the target location for the navigation system to guide them to.

[0582] "Options" refer to the conditions and priorities that the user specifies for route selection within the navigation system.

[0583] "Real-time traffic information" refers to the latest traffic condition data obtained from traffic information providers, vehicle sensors, etc.

[0584] An "autonomous vehicle" is a vehicle that operates autonomously using a system, without requiring operation by a human driver.

[0585] A "sensor" is a device used to detect the surrounding conditions of a vehicle and collect data.

[0586] A "traffic information provider" is a service that provides traffic-related data such as road conditions, congestion, and traffic light timings.

[0587] "Methods for calculating routes" refer to algorithms that calculate the optimal travel route based on user input information and collected traffic data.

[0588] "Visual navigation" refers to visual navigation information displayed on digital displays or interfaces.

[0589] "Voice guidance" refers to real-time voice navigation instructions provided through a speaker.

[0590] "User selection" refers to the preferences and conditions that users individually set within the navigation system.

[0591] This invention is a navigation system that collects and analyzes traffic information in real time based on user-specified options and provides the optimal route. It can particularly improve the operational efficiency and safety of autonomous vehicles.

[0592] System Configuration

[0593] This system consists of the following main components:

[0594] 1. User terminal:

[0595] The user enters the starting point and destination.

[0596] Users can set options such as "prioritize narrow roads" or "arrive at destination quickly."

[0597] 2. Server:

[0598] Receives requests from user terminals.

[0599] Real-time traffic information is obtained from sensors in the autonomous vehicle and from external traffic information providers.

[0600] The collected traffic information is stored in a database, and the necessary data is queried in real time.

[0601] Based on the user's selected options, the optimal route is calculated using Dijkstra's algorithm.

[0602] The calculated optimal route is sent to the user's device.

[0603] 3. Autonomous vehicles:

[0604] A central vehicle computer (e.g., a general-purpose GPU-based driving platform) is used.

[0605] Use an infotainment system (e.g., a real-time operating system).

[0606] Environmental recognition is performed using data from various sensors (e.g., cameras, LiDAR, RADAR).

[0607] Flow of operations

[0608] 1. Accepting user requests:

[0609] The user opens the navigation application and enters the starting point, destination, and any options. This information is sent to the server.

[0610] 2. Gathering real-time traffic information:

[0611] The server collects data on current traffic conditions (such as when traffic lights change, when level crossings are open or closed, and how congested the area is) from traffic information providers and vehicle sensors.

[0612] The collected information is stored in a database, enabling fast queries.

[0613] 3. Square root calculation:

[0614] Based on the collected traffic information and the options specified by the user, the server uses Dijkstra's algorithm to calculate multiple routes and select the optimal route.

[0615] 4. Route provision:

[0616] The optimal route information is sent to the user's device, and visual and voice guidance begins. This allows the user to receive guidance in real time.

[0617] Specific example

[0618] As a concrete example, consider a scenario where user A enters "City Hall" as their destination and selects the "Prioritize narrow roads" option. In this case, the server performs the following actions:

[0619] 1. The server checks user A's current location and destination.

[0620] 2. The server retrieves information such as the timing of signal changes, railway crossing opening and closing information, and traffic congestion information from traffic information providers and stores it in a database.

[0621] 3. Based on the "Prioritize narrower paths" option, the server uses Dijkstra's algorithm to calculate the optimal route.

[0622] 4. The server sends the calculated optimal route to user A's terminal, and user A's terminal starts visual and voice guidance.

[0623] Example of a prompt:

[0624] If the user enters "City Hall" as the destination and selects the "Prioritize narrow roads" option:

[0625] By analyzing real-time traffic data obtained from sensors and APIs, Dijkstra's algorithm calculates the optimal route that prioritizes narrow roads.

[0626] The calculated route is evaluated in a database and provided with visual and audio guidance.

[0627] As described above, this invention is a system that makes maximum use of real-time traffic information to provide optimal route guidance for autonomous vehicles.

[0628] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0629] Step 1:

[0630] The user opens the navigation application and enters their starting point, destination, and options. At this stage, the input includes the starting point (GPS location), destination (address or location information), and user-selected options (e.g., "prioritize narrow roads" or "get to destination quickly"). This information is then sent from the application to the server.

[0631] Step 2:

[0632] The server receives a request from the user. The request includes the origin, destination, and options. The server analyzes this information to determine the scope of the traffic information to be collected next. Specifically, it sets the geographical range from the user's current location to their destination.

[0633] Step 3:

[0634] The server acquires real-time traffic information from sensors in autonomous vehicles and from external traffic information providers (e.g., traffic information APIs). Input data includes signal change timings, level crossing opening / closing information, traffic congestion information, and accident information. This data is temporarily stored in a database on the server.

[0635] Step 4:

[0636] The server generates multiple route options based on collected traffic information and user-selected options. Specifically, it uses Dijkstra's algorithm to calculate the optimal route. Input data consists of traffic information and user options, while output is multiple route options and their evaluation results.

[0637] Step 5:

[0638] The server evaluates the generated route candidates and selects the most suitable route. Evaluation criteria include travel time, traffic light waiting times, railway crossing waiting times, and road types. The optimal route is the one that best matches the user's specified options.

[0639] Step 6:

[0640] The server generates optimal route information and sends it to the user's terminal. The input is the evaluated optimal route information, and the output is a data packet for display on the user's terminal.

[0641] Step 7:

[0642] The system analyzes route information received by the user's device and displays it on the navigation screen. Specific actions include displaying visual guidance and initiating voice guidance. Input data is route information transmitted from the server, and output is the display screen and voice guidance. Users can receive real-time navigation guidance.

[0643] 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.

[0644] This invention is a navigation system that collects and analyzes traffic information in real time based on user-specified options and provides the optimal route. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it enables more flexible route guidance tailored to the user's state. Specific embodiments are described below.

[0645] 1. Accepting user requests

[0646] Terminal: The user launches the navigation application and enters the starting point (current location) and destination. The user selects options such as "prioritize narrow roads" or "get to destination quickly."

[0647] Device: Additionally, the emotion engine is activated, recognizing emotions from the user's voice and facial expressions.

[0648] For example, if a user displays expressions of anger or impatience, the emotion engine recognizes this as "stress."

[0649] Terminal: Sends the input data and recognized emotion information as a request to the server.

[0650] 2. Collection of real-time traffic information

[0651] Server: Receives requests from users and verifies the origin and destination, as well as the selected options and sentiment information.

[0652] Server: Accesses traffic information providers to obtain real-time traffic information. This information includes traffic signal timing, railway crossing opening and closing information, traffic congestion status, road construction and accident information, etc.

[0653] Server: The acquired traffic information is temporarily stored in the database.

[0654] 3. Calculating square roots

[0655] Server: Applies a route calculation algorithm based on stored traffic information, user settings options, and sentiment information.

[0656] For example, if the system detects that a user is experiencing stress, it will select a route with smoother traffic flow and shorter waiting times.

[0657] Server: Generates multiple route options and evaluates the travel time, signal waiting time, and level crossing waiting time for each route.

[0658] Server: Compares the evaluation results of each route and selects the optimal route that best suits the user's options and sentiment information.

[0659] 4. Route provision

[0660] Server: Generates optimal route information and sends it to the user's terminal.

[0661] Terminal: Analyzes received route information and displays it on the navigation screen. Simultaneously, voice guidance is initiated, providing real-time directions to the user.

[0662] Specific example

[0663] Case 1: Optimal route selection using an emotion engine

[0664] 1. Terminal: User A enters "City Hall" as the destination and selects the "Prioritize narrow roads" option.

[0665] 2. Terminal: The emotion engine detects anxiety from user A's voice.

[0666] 3. Terminal: Sends the input data and recognized emotion information to the server.

[0667] 4. Server: Receives the request and verifies the origin and destination, options, and sentiment information.

[0668] 5. Server: Retrieves information such as signal change timing, level crossing opening / closing information, and traffic congestion information from traffic information providers and stores it in a database.

[0669] 6. Server: Calculates the optimal route based on the "Prioritize narrower paths" option and the server's emotional state (emotional information indicating anxiety).

[0670] 7. Server: Evaluate each route candidate and select the optimal route for user A.

[0671] 8. Server: Sends the optimal route to user A's terminal.

[0672] 9. Terminal: Displays the received route information and starts voice guidance.

[0673] Case 2: Route reselection based on an emotion engine

[0674] 1. Terminal: User B enters "station" as the destination and selects the "I want to get to my destination quickly" option.

[0675] 2. Device: The emotion engine detects stress from user B's facial expressions.

[0676] 3. Terminal: Sends the input data and recognized emotion information to the server.

[0677] 4. Server: Receives the request and verifies the origin and destination, options, and sentiment information.

[0678] 5. Server: Retrieves information such as signal change timing, level crossing opening / closing information, and traffic congestion information from traffic information providers and stores it in a database.

[0679] 6. Server: Calculates the optimal route based on the "I want to get to my destination quickly" option and stress levels.

[0680] 7. Server: Evaluates each route candidate and allows user B to select the optimal route.

[0681] 8. Server: Sends the optimal route to user B's terminal.

[0682] 9. Terminal: Displays the received route information and starts voice guidance.

[0683] The following describes the processing flow.

[0684] Step 1:

[0685] Terminal: The user launches the navigation application and enters the starting point (current location) and destination. The user selects options such as "prioritize narrow roads" or "get to destination quickly."

[0686] Step 2:

[0687] Device: The emotion engine is activated and recognizes emotions from the user's voice and facial expressions. For example, it captures the user's facial expressions through the camera and performs voice analysis using speech recognition technology.

[0688] Step 3:

[0689] Device: The emotion engine analyzes the emotional information it recognizes to determine whether the user is feeling "anxiety" or "stress."

[0690] Step 4:

[0691] Terminal: Sends the origin, destination, user-selected options, and sentiment information as a request to the server.

[0692] Step 5:

[0693] Server: Analyzes incoming requests to determine the user's origin, destination, options, and sentiment information.

[0694] Step 6:

[0695] Server: Accesses traffic information providers to obtain real-time traffic information such as signal change timing, level crossing opening and closing information, traffic congestion status, road construction and accident information.

[0696] Step 7:

[0697] Server: Temporarily stores acquired traffic information in a database.

[0698] Step 8:

[0699] Server: Applies route calculation algorithms based on stored traffic information, user selection options, and sentiment information.

[0700] Step 9:

[0701] Server: Generates multiple route options and evaluates the travel time, signal waiting time, and level crossing waiting time for each route.

[0702] Step 10:

[0703] Server: Compares the evaluation results of each route and selects the optimal route, taking into account the "prioritize narrow roads" option and the user's sense of urgency.

[0704] Step 11:

[0705] Server: Creates optimal route information and sends it to the user's terminal.

[0706] Step 12:

[0707] Terminal: Analyzes received route information and displays it on the navigation screen. Also initiates corresponding voice guidance.

[0708] Step 13:

[0709] Terminal: The user begins moving towards their destination.

[0710] Step 14:

[0711] Terminal: While on the move, it continuously monitors the user's emotional information and sends updates to the server as needed.

[0712] Step 15:

[0713] Server: Based on real-time traffic information and updated user sentiment data, it recalculates the optimal route and reroutes as needed.

[0714] Step 16:

[0715] Terminal: Receives new route information and updates the navigation screen. Performs a series of operations continuously until the user reaches their destination.

[0716] (Example 2)

[0717] 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".

[0718] Conventional navigation systems have the problem of failing to alleviate user stress and anxiety because they provide route guidance without considering the user's emotional state. Furthermore, route calculations based solely on real-time traffic information have the challenge of not being able to flexibly respond to individual user needs (for example, wanting to choose a quiet route or wanting to reach the destination quickly).

[0719] 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.

[0720] In this invention, the server includes means for the user to input a starting point and destination, means for collecting real-time traffic information based on options specified by the user, means for calculating an optimal route using the collected traffic information and the user's emotional information, means for transmitting the calculated optimal route information to the user's terminal, and means for displaying and guiding the user's terminal to the route information received. This enables the provision of an optimal route according to the user's emotional state and flexible route guidance that reflects real-time traffic information and the user's individual needs.

[0721] The "starting point" refers to the location where the user begins their route to their current location or destination.

[0722] "Destination" refers to the place the user ultimately wants to reach.

[0723] "Options" refer to the conditions and settings that users prioritize in route guidance. For example, these include "I want to get to my destination quickly" or "Prioritize narrow roads."

[0724] "Real-time traffic information" refers to the most up-to-date information in time, such as current traffic conditions, traffic light change timings, railway crossing opening and closing information, traffic congestion status, road construction and accident information.

[0725] "Emotional information" refers to the emotional state analyzed from the user's voice, facial expressions, and other behaviors. Examples include stress, anxiety, and anger.

[0726] A "route calculation algorithm" refers to a method for calculating the optimal route based on collected traffic information, user settings, and sentiment information. Examples include the A algorithm and Dijkstra's algorithm.

[0727] "Terminal" refers to devices used by users, such as mobile phones, tablets, and car navigation systems.

[0728] A "server" refers to a central processing unit that processes requests sent by users, collects and analyzes necessary information, and sends the results to the user's terminal.

[0729] "Route information" refers to detailed data about the calculated route. This includes the route itself, estimated travel time, traffic light waiting times, railway crossing waiting times, etc.

[0730] This invention is a navigation system that collects and analyzes traffic information in real time based on user-specified options and emotional information, and provides the optimal route. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it enables more flexible route guidance tailored to the user's state.

[0731] First, the user launches the navigation application and enters their starting point (current location) and destination. The user can select options such as "prioritize narrow roads" or "get to destination quickly." The device has a built-in emotion engine that recognizes the user's emotions in real time from their voice and facial expressions. For example, if the user shows signs of anger or impatience, the emotion engine recognizes this as "stress."

[0732] Next, the terminal sends the entered data and recognized sentiment information as a request to the server. The server receives the request from the user and verifies the origin and destination, as well as the selected options and sentiment information. The server then accesses a traffic information provider (e.g., Google Maps API or Here API) to obtain real-time traffic information. This information includes traffic light change timings, railway crossing opening and closing information, traffic congestion, road construction and accident information, etc. The retrieved traffic information is temporarily stored in a database.

[0733] The server applies a route calculation algorithm based on stored traffic information, user settings options, and emotional information. For example, if the server detects that the user is stressed, it selects a route with smooth traffic flow and minimal waiting times. The server generates multiple route options and evaluates the travel time, traffic light waiting times, and railway crossing waiting times for each route. It compares the evaluation results of each route and selects the optimal route that best suits the user's options and emotional information.

[0734] Once the optimal route information is generated, the server sends it to the user's terminal. The terminal analyzes the received route information and displays it on the navigation screen. Simultaneously, voice guidance begins, providing instructions to the user in real time.

[0735] For example, suppose user A enters "City Hall" as their destination and selects the "Prioritize narrow roads" option. If the emotion engine detects impatience from user A's voice, the device sends this information to the server. The server receives the request and retrieves information such as traffic light timings, railway crossing opening / closing information, and traffic congestion information from a traffic information provider. Then, based on the "Prioritize narrow roads" option and the impatient emotion information, it calculates the optimal route and sends it to user A's device. The device displays the received route information and starts voice guidance.

[0736] As another example, suppose user B enters "station" as their destination and selects the "I want to get to my destination quickly" option. If the emotion engine detects stress from user B's facial expression, the terminal sends the entered data and the recognized emotion information to the server. The server receives the request and retrieves information such as traffic signal timing, level crossing opening / closing information, and traffic congestion information from a traffic information provider. It then calculates the optimal route based on the "I want to get to my destination quickly" option and stress emotion, and sends it to user B's terminal. The terminal displays the received route information and starts voice guidance.

[0737] (Example of a prompt message)

[0738] "Explain how, after the user enters their starting point and destination and selects an option, the emotion engine recognizes the user's emotions and calculates the optimal route."

[0739] "Please describe, in natural language, the processing flow of a navigation system that collects real-time traffic information and takes user sentiment into consideration."

[0740] This invention enables the provision of optimal routes according to the user's emotional state, allowing for flexible route guidance that reflects real-time traffic information and the user's individual needs. Furthermore, by combining it with an emotion engine, an improvement in the user experience can be expected.

[0741] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0742] Step 1:

[0743] The terminal launches the navigation application, and the user enters the starting point and destination. The user selects options such as "I want to get to the destination quickly" or "Prioritize narrow roads." The terminal receives the starting point, destination, and options as input. The terminal receives this input data and proceeds to the next step.

[0744] Step 2:

[0745] The device activates an emotion engine to recognize emotional information from the user's voice and facial expressions. Specifically, it uses the device's camera and microphone to capture facial expressions and voice, and a generative AI model analyzes this data. The user's voice and image data are provided to the emotion engine as input. The emotion engine analyzes this data and outputs emotional information, such as whether the user is feeling stressed.

[0746] Step 3:

[0747] The terminal sends collected origin, destination, options, and sentiment information to the server. As input, request data containing origin, destination, options, and sentiment information is sent from the terminal to the server. This data is transmitted via communication protocols such as HTTP or WebSocket.

[0748] Step 4:

[0749] The server analyzes the request data received from the terminal to confirm the origin and destination, as well as the selected options and sentiment information. The request data is provided to the server as input. The server analyzes this data and extracts the information necessary for route calculation.

[0750] Step 5:

[0751] The server sends API requests to traffic information providers to obtain real-time traffic information. Specifically, the server accesses APIs such as the Google Maps API and the Here API to collect traffic information. As input, API requests are sent from the server. As output, traffic information such as the timing of signal changes, railway crossing opening and closing information, traffic congestion status, road construction and accident information is returned to the server.

[0752] Step 6:

[0753] The server temporarily stores the traffic information it acquires in a database. Traffic information is provided to the server as input. The server stores this information in a database (e.g., Redis) so that it can be used in subsequent route calculations.

[0754] Step 7:

[0755] The server applies a route calculation algorithm based on stored traffic information, user settings options, and sentiment information. The server uses route calculation algorithms such as the A algorithm or Dijkstra's algorithm to calculate the optimal route. Traffic information, settings options, and sentiment information are provided to the server as input. Multiple route candidates are generated as output.

[0756] Step 8:

[0757] The server evaluates the generated route candidates and selects the optimal route that best suits the user's configuration options and sentiment information. Multiple route candidates are provided as input. The server evaluates these and selects the optimal route. The optimal route information is generated as output.

[0758] Step 9:

[0759] The server sends optimal route information to the user's terminal. The server receives optimal route information as input. The server sends this information to the terminal, which then receives it. HTTP or WebSocket are used as the communication protocol.

[0760] Step 10:

[0761] The terminal analyzes the route information it receives and displays it on the navigation screen. Furthermore, it initiates voice guidance, providing real-time instructions to the user. The terminal receives optimal route information as input. The terminal analyzes this information and provides visual and audio guidance.

[0762] (Application Example 2)

[0763] 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."

[0764] Traditional navigation systems provided optimal routes based on real-time traffic information, but they failed to consider the user's emotional state and lacked route guidance adapted to the user's mental condition. Therefore, they could not address psychological needs, such as when the user was anxious or wanted to relax, potentially leading to a lower satisfaction with the driving experience. Furthermore, there was a need for technology that could efficiently analyze the user's emotional state within a specific vehicle environment and provide appropriate navigation.

[0765] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes an emotion analysis means for recognizing the user's emotions, a means for collecting real-time traffic information based on options specified by the user, and a means for calculating the optimal route using the collected traffic information and emotion information. This makes it possible to provide route guidance that is appropriate to the user's emotional state.

[0766] "Means for users to input their starting point and destination" refers to an interface for users to input their current location and desired destination using electronic devices.

[0767] A "means of emotional analysis that recognizes user emotions" is a system that analyzes a user's facial expressions and voice to determine their emotional state in real time.

[0768] "Means for collecting real-time traffic information based on user-specified options" refers to a system for obtaining traffic conditions and event information from online databases, APIs, etc., according to the conditions selected by the user.

[0769] "Means for calculating the optimal route using collected traffic and sentiment information" refers to a system that uses algorithms to calculate the route that best suits the user's mental and physical needs, based on acquired traffic and sentiment data.

[0770] "Means for transmitting calculated optimal route information to the user's terminal" refers to a communication system for transferring information about the optimal route calculated on a server to the electronic device being used by the user.

[0771] "Means for displaying and guiding users through route information received by their device" refers to interfaces and software for visually and audibly displaying and guiding users through optimal route information on their device.

[0772] This invention relates to a navigation system that analyzes the user's emotional state and provides the optimal route based on real-time traffic information. This navigation system is particularly applicable to autonomous vehicles and enables flexible route guidance that responds to the user's psychological needs.

[0773] 1. System Overview

[0774] This system includes means for emotion analysis to recognize the user's emotions, means for collecting real-time traffic information, means for calculating the optimal route using the collected information, means for transmitting the calculation results to the user's terminal, and means for displaying and guiding the user through the received route information.

[0775] 2. Hardware and software to be used

[0776] hardware

[0777] Camera: Cameras mounted on the autonomous vehicle will be used to capture the user's facial expressions.

[0778] Microphone: The user's voice will be recorded using a microphone installed in the autonomous vehicle.

[0779] Central control terminal: Receives user input via an in-vehicle touchscreen display.

[0780] software

[0781] Emotion analysis engine: Uses Microsoft Azure's Face API and Google's Cloud Vision API to analyze the user's facial expressions and voice.

[0782] Real-time traffic information acquisition module: Uses TomTom and the Google Maps API to collect real-time traffic information.

[0783] Route calculation algorithm: Using algorithms such as Algorithm A, the optimal route is calculated based on collected traffic and sentiment information.

[0784] 3. Data calculation and processing

[0785] Emotion Recognition: The vehicle captures the user's face and voice using an in-car camera and microphone, and an emotion analysis engine performs real-time analysis. For example, if the user is anxious, the system prioritizes a smoother, shorter route to reduce their stress.

[0786] Traffic Information Gathering: Access a real-time traffic database to collect information such as traffic light change timings, railway crossing opening and closing information, traffic congestion status, road construction and accident information.

[0787] Route Calculation: Based on collected traffic information, user sentiment data, and selected options, the system calculates the optimal route. For example, if the user wants to relax, it might suggest a scenic route.

[0788] Route information transmission: The calculated optimal route information is transmitted to the central control terminal to provide information to the user.

[0789] 4. Specific Examples

[0790] The following are specific examples of how this system can be used.

[0791] Example 1:

[0792] The user gets into the self-driving vehicle and enters "park" as their destination. An emotion analysis engine detects impatience from the user's voice, and the system collects real-time traffic information. As a result, the optimal route with minimal traffic lights and congestion is calculated, and the self-driving system begins driving along that route.

[0793] Example 2:

[0794] The user enters "Shopping Mall" as their destination and selects "Prioritize scenic routes" as an option. The emotion analysis engine detects relaxation from the user's facial expressions and acquires traffic information. The system suggests a scenic route, and the vehicle begins driving along that route.

[0795] 5. Example of a prompt statement

[0796] The following is an example of a prompt message to input into a generative AI model.

[0797] Write Python code to calculate the optimal route based on current traffic conditions. Consider the user's sentiment and selection options. Sentiment information will be obtained from facial and speech recognition. Traffic data will be obtained from the Google Maps API. Use the A algorithm for route calculation.

[0798] In this way, an optimal navigation system that takes into account the user's psychological state and actual traffic conditions can be realized. This is expected to significantly improve the driving experience of autonomous vehicles.

[0799] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0800] Step 1:

[0801] The user enters the starting point and destination into the device.

[0802] The input data consists of the starting point (current location) and the destination. This input data is sent from the terminal to the server for use in the next processing step.

[0803] Step 2:

[0804] The device's camera and microphone are activated to recognize the user's emotions.

[0805] The input data used consists of video captured by the camera and audio recorded by the microphone. This data is analyzed in real time by an emotion analysis engine, and the user's emotional state (e.g., relaxed, anxious, stressed) is output. This emotional information is used in the next step.

[0806] Step 3:

[0807] The server collects real-time traffic information based on options specified by the user.

[0808] The input data used includes user-selected options (e.g., shortest travel time, scenic route) and real-time traffic data obtained from a traffic information API. This data includes, for example, traffic signal change timings, railway crossing opening / closing information, and traffic congestion information obtained from the API. This traffic information is used in the next step.

[0809] Step 4:

[0810] The server uses collected traffic and sentiment information to calculate the optimal route.

[0811] The input data used includes acquired traffic information, user sentiment information, and navigation options selected by the user. The server applies route calculation algorithms, such as the A algorithm, to this data to calculate the optimal route. The output is the calculated optimal route information.

[0812] Step 5:

[0813] The server sends the calculated optimal route information to the user's terminal.

[0814] The optimal route information is used as input data. The server sends this information to the terminal, and the information sent to the terminal is used in the next step.

[0815] Step 6:

[0816] The device displays and guides the user through route information it has received.

[0817] The optimal route information transmitted from the server is used as input data. The terminal analyzes this information and initiates visual navigation display and voice guidance. This allows the user to confirm the optimal route information while driving.

[0818] Through the processing steps described above, an optimal navigation system is realized based on the user's emotional state and traffic information. This provides a comfortable driving experience that meets the user's psychological needs.

[0819] 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.

[0820] 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.

[0821] 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.

[0822] [Third Embodiment]

[0823] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0824] 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.

[0825] 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).

[0826] 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.

[0827] 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.

[0828] 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).

[0829] 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.

[0830] 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.

[0831] 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.

[0832] 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.

[0833] 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.

[0834] 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".

[0835] This invention is a navigation system that collects and analyzes traffic information in real time based on options specified by the user and provides the optimal route, and is specifically implemented as follows.

[0836] 1. Accepting user requests

[0837] Terminal: The user opens a navigation application and enters their starting point (current location) and destination. The user also selects options such as "prioritize narrow roads" or "get to destination quickly."

[0838] Terminal: The entered information is sent to the server as a request.

[0839] 2. Collection of real-time traffic information

[0840] Server: Upon receiving a request from a user, it verifies the origin and destination.

[0841] Server: Retrieves real-time traffic information from traffic information providers. This information includes traffic signal timing, railway crossing opening and closing information, traffic congestion, road construction, and accident information.

[0842] Server: The collected traffic information is temporarily stored in a database.

[0843] 3. Calculating square roots

[0844] Server: Applies a route calculation algorithm based on collected traffic information and user-selected options.

[0845] Server: Generates multiple route candidates and evaluates the following elements for each route.

[0846] Duration

[0847] Waiting time at traffic lights

[0848] railroad crossing waiting time

[0849] Server: Compares the evaluation results of each route and selects the optimal route that best suits the user's specified options.

[0850] 4. Route provision

[0851] Server: Generates optimal route information and sends it to the user's terminal.

[0852] Terminal: Analyzes received route information and displays it on the navigation screen. Simultaneously, voice guidance is initiated, providing real-time directions to the user.

[0853] Specific example

[0854] Case 1: Route prioritizing narrow roads

[0855] 1. Terminal: User A enters "City Hall" as the destination and selects the "Prioritize narrow roads" option.

[0856] 2. Server: Receives the request and checks user A's current location and destination.

[0857] 3. Server: Retrieves information such as signal change timing, level crossing opening / closing information, and traffic congestion information from traffic information providers and stores it in a database.

[0858] 4. Server: Calculates the optimal route based on the "Prioritize narrower paths" option. Evaluates multiple candidates and selects the best route for user A.

[0859] 5. Server: Sends the optimal route to user A's terminal.

[0860] 6. Terminal: Displays the received route information and starts voice guidance.

[0861] Case 2: When you want to reach your destination quickly

[0862] 1. Terminal: User B enters "station" as the destination and selects the "I want to get to my destination quickly" option.

[0863] 2. Server: Receives the request and checks user B's current location and destination.

[0864] 3. Server: Retrieves information such as signal change timing, level crossing opening / closing information, and traffic congestion information from traffic information providers and stores it in a database.

[0865] 4. Server: Based on the "I want to reach my destination quickly" option, it calculates the optimal route. It evaluates multiple options and selects the route with the shortest waiting time.

[0866] 5. Server: Sends the optimal route to user B's terminal.

[0867] 6. Terminal: Displays the received route information and starts voice guidance.

[0868] The following describes the processing flow.

[0869] Step 1:

[0870] Terminal: The user launches the navigation application and enters the starting point (current location) and destination. The user can also select options such as "prioritize narrow roads" or "get to destination quickly."

[0871] Step 2:

[0872] Terminal: Sends data regarding the entered departure point, destination, and options as a request to the server.

[0873] Step 3:

[0874] Server: Parses the received request to confirm the user's origin and destination, and the selected options.

[0875] Step 4:

[0876] Server: Accesses traffic information providers to obtain real-time traffic information. This information includes traffic signal timing, railway crossing opening and closing information, traffic congestion status, road construction and accident information, etc.

[0877] Step 5:

[0878] Server: Temporarily stores acquired traffic information in a database.

[0879] Step 6:

[0880] Server: Applies a route calculation algorithm based on stored traffic information and user configuration options.

[0881] Step 7:

[0882] Server: Generates multiple route options based on collected real-time information and evaluates the travel time, signal waiting time, and level crossing waiting time for each route.

[0883] Step 8:

[0884] Server: Compares the evaluation results of each route and selects the optimal route that best suits the user's chosen option.

[0885] Step 9:

[0886] Server: Generates optimal route information and sends it to the user's terminal.

[0887] Step 10:

[0888] Terminal: Analyzes received route information and displays it on the navigation screen.

[0889] Step 11:

[0890] Terminal: Starts voice guidance and provides real-time navigation to the user.

[0891] Step 12:

[0892] Terminal: Until the user reaches their destination, it will re-obtain real-time updated traffic information as needed and reroute and optimize the route.

[0893] (Example 1)

[0894] 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."

[0895] Conventional navigation systems have been unable to fully utilize real-time traffic information, making it difficult to provide the optimal route based on user-specified options. Furthermore, because they could not utilize detailed traffic information such as the timing of traffic light changes and the opening and closing of railway crossings, they could not provide optimal guidance for the user's desired route conditions. The objective of this invention is to solve this problem and provide more accurate route guidance.

[0896] 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.

[0897] In this invention, the server includes means for the user to input a starting point and destination, means for collecting real-time traffic information based on options specified by the user, means for temporarily storing the collected traffic information in a database, means for applying a route calculation algorithm based on the stored data, means for selecting the optimal route based on the evaluation results, means for transmitting the calculated optimal route information to the user's terminal, and means for displaying and guiding the user through the route information received by the user's terminal. This enables highly accurate route guidance based on real-time traffic information, including the timing of signal changes and the opening and closing of railway crossings.

[0898] "A means for users to input their starting point and destination" refers to a mechanism that provides an interface for users to input their current location and destination.

[0899] "Means of collecting real-time traffic information based on user-specified options" refers to a system that acquires real-time traffic conditions according to the route conditions selected by the user (for example, "prioritize narrow roads" or "want to reach the destination quickly").

[0900] "Means for temporarily storing collected traffic information in a database" refers to a mechanism for temporarily storing collected traffic information in a database for use in subsequent processing.

[0901] "A means of applying a route calculation algorithm based on saved data" refers to a mechanism that executes an algorithm that calculates routes using traffic information stored in a database.

[0902] "Method for selecting the optimal route based on evaluation results" refers to a system that selects the route that best suits the user's specified conditions based on the evaluation results of the route calculation algorithm.

[0903] "Means for sending calculated optimal route information to the user's terminal" refers to a mechanism for sending information about the optimal route selected by the server to the user's terminal.

[0904] "Means for displaying and guiding users through route information received by the user's device" refers to a system that displays route information received by the user's device on the screen and provides directions to the user through voice guidance or other means.

[0905] "Information on the timing of traffic signal changes and the opening and closing of level crossings" refers to information regarding the timing of changes in traffic signals and the opening and closing of level crossings.

[0906] A "route that prioritizes narrow roads" refers to a route that prioritizes the use of narrow roads, and includes criteria for selecting a route with many narrow roads.

[0907] A "fastest route to the destination" is a route that prioritizes getting the user to their destination in the shortest possible time.

[0908] This invention is a navigation system that collects and analyzes traffic information in real time based on user-specified options and provides the optimal route. A specific embodiment of this system is described in detail below.

[0909] System Configuration

[0910] This navigation system consists of a user terminal, a server, and a database. The user terminal is a mobile device such as a smartphone, with a navigation application installed. The server collects and stores real-time traffic information and calculates routes. The database temporarily stores the collected traffic information.

[0911] Hardware and software to be used

[0912] User's device:

[0913] These are mobile devices such as smartphones and tablets, which provide the interface for applications.

[0914] server:

[0915] It collects, stores, and calculates routes based on traffic information. The server has software installed that interacts with traffic information providers (e.g., Google Maps API, HERE Technologies).

[0916] Database:

[0917] Relational databases such as MySQL and PostgreSQL are used to temporarily store traffic information.

[0918] System operation

[0919] 1. Accepting user requests:

[0920] The user opens the navigation app and enters their starting point (usually their current location) and destination. They also select options such as "prioritize narrow roads" or "get to destination quickly." This information is sent to the server in JSON format.

[0921] 2. Gathering real-time traffic information:

[0922] The server receives requests from users and communicates with traffic information providers to obtain real-time traffic information. This includes information such as traffic light change timings, railway crossing opening and closing information, traffic congestion, road construction, and accident information. This information is temporarily stored in a database.

[0923] 3. Square root calculation:

[0924] The server applies a route calculation algorithm based on traffic information stored in the database and user options. It generates multiple route candidates and evaluates factors such as travel time, traffic light waiting time, and railway crossing waiting time for each route. It then selects the most suitable route.

[0925] 4. Route provision:

[0926] The server generates calculated optimal route information and sends it to the user's device. The user's device analyzes the received route information and displays it on the navigation screen. Simultaneously, voice guidance begins, providing the user with real-time directions.

[0927] Specific example

[0928] For example, if a user enters "City Hall" as their destination in the app and selects the "Prioritize narrow roads" option, the server receives the request, retrieves real-time traffic information, and stores it in the database. Then, based on the "Prioritize narrow roads" option, it calculates the optimal route and sends the result to the user's device. The user's device displays the received route information and begins voice guidance.

[0929] Example of a prompt

[0930] "Please give me directions to the city hall, prioritizing narrower roads."

[0931] "Please tell me the shortest route to the station."

[0932] This invention enables highly accurate route guidance based on real-time, detailed traffic information.

[0933] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0934] Step 1: Accepting user requests

[0935] User: The user launches a navigation app on their smartphone and enters their starting point (usually their current location) and destination. They also select options such as "prioritize narrow roads" or "get to destination quickly."

[0936] Input: Departure point, destination, and optional information.

[0937] Terminal: Converts the entered information into a JSON-formatted request object and sends it to the server as an HTTP POST request.

[0938] Output: Request object in JSON format.

[0939] Step 2: Gathering real-time traffic information

[0940] Server: Receives requests from users and parses the origin, destination, and options.

[0941] Input: Request object in JSON format.

[0942] Server: Communicates with traffic information providers to obtain real-time traffic data. This information includes traffic congestion, traffic light change timing, railway crossing opening / closing information, road construction, and accident information.

[0943] Data processing: The acquired traffic information is formatted into an appropriate format.

[0944] Output: Real-time traffic information.

[0945] Step 3: Temporarily save traffic information

[0946] Server: Temporarily stores the acquired traffic information in a database (e.g., MySQL).

[0947] Input: Real-time traffic information.

[0948] Database: Stores traffic information.

[0949] Output: Success / Failure status.

[0950] Step 4: Calculating square roots

[0951] Server: Applies a route calculation algorithm based on temporarily stored traffic information and user-specified options. The A-search algorithm is commonly used.

[0952] Input: Traffic information, user options.

[0953] Data calculation: Calculate and evaluate the travel time, traffic light waiting time, and railroad crossing waiting time for each route candidate.

[0954] Output: Multiple route candidates evaluated.

[0955] Step 5: Selecting the optimal route

[0956] Server: Selects the optimal route from the evaluated route candidates based on the user's specified options.

[0957] Input: Evaluation results, user options.

[0958] Data processing: Comparison of evaluation scores.

[0959] Output: Optimal route information.

[0960] Step 6: Sending Route Information

[0961] Server: Converts optimal route information into JSON format and sends it to the user's terminal.

[0962] Input: Optimal route information.

[0963] Data processing: Convert to JSON format.

[0964] Output: Route information in JSON format.

[0965] Step 7: Display and guidance of route information

[0966] Terminal: Analyzes received route information and displays it on the navigation screen. Simultaneously, voice guidance begins.

[0967] Input: Route information in JSON format.

[0968] Data processing: Converts data to a format suitable for screen display and audio guidance.

[0969] Output: Navigation screen display and voice guidance.

[0970] Example prompt statements

[0971] "Please give me directions to the city hall, prioritizing narrower roads."

[0972] "Please tell me the shortest route to the station."

[0973] This allows users to receive real-time, optimal route guidance based on specified conditions.

[0974] (Application Example 1)

[0975] 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."

[0976] Conventional navigation systems fail to fully utilize real-time traffic information, making it particularly difficult for autonomous vehicles to select optimal routes that take into account traffic light wait times, railway crossing wait times, and road congestion. Furthermore, flexible route suggestions based on user choices are difficult, resulting in a lack of safety and efficiency. As a result, the operation of autonomous vehicles involves wasted time and energy, leading to a decrease in overall operational efficiency.

[0977] 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.

[0978] In this invention, the server includes means for the user to input a starting point and destination, means for collecting real-time traffic information based on options specified by the user, means for obtaining real-time traffic information from sensors of the autonomous vehicle and an external traffic information provider, means for calculating the optimal route based on the collected traffic information and the user's selection, and means for providing the optimal route as visual and voice guidance. This enables the selection of the optimal route considering real-time traffic conditions, realizes flexible guidance according to the user's selection, and improves the operational efficiency and safety of the autonomous vehicle.

[0979] The "starting point" is the current location or starting point that the user sets when starting navigation.

[0980] A "destination" is the location that the user sets as the target location for the navigation system to guide them to.

[0981] "Options" refer to the conditions and priorities that the user specifies for route selection within the navigation system.

[0982] "Real-time traffic information" refers to the latest traffic condition data obtained from traffic information providers, vehicle sensors, etc.

[0983] An "autonomous vehicle" is a vehicle that operates autonomously using a system, without requiring operation by a human driver.

[0984] A "sensor" is a device used to detect the surrounding conditions of a vehicle and collect data.

[0985] A "traffic information provider" is a service that provides traffic-related data such as road conditions, congestion, and traffic light timings.

[0986] "Methods for calculating routes" refer to algorithms that calculate the optimal travel route based on user input information and collected traffic data.

[0987] "Visual navigation" refers to visual navigation information displayed on digital displays or interfaces.

[0988] "Voice guidance" refers to real-time voice navigation instructions provided through a speaker.

[0989] "User selection" refers to the preferences and conditions that users individually set within the navigation system.

[0990] This invention is a navigation system that collects and analyzes traffic information in real time based on user-specified options and provides the optimal route. It can particularly improve the operational efficiency and safety of autonomous vehicles.

[0991] System Configuration

[0992] This system consists of the following main components:

[0993] 1. User terminal:

[0994] The user enters the starting point and destination.

[0995] Users can set options such as "prioritize narrow roads" or "arrive at destination quickly."

[0996] 2. Server:

[0997] Receives requests from user terminals.

[0998] Real-time traffic information is obtained from sensors in the autonomous vehicle and from external traffic information providers.

[0999] The collected traffic information is stored in a database, and the necessary data is queried in real time.

[1000] Based on the user's selected options, the optimal route is calculated using Dijkstra's algorithm.

[1001] The calculated optimal route is sent to the user's device.

[1002] 3. Autonomous vehicles:

[1003] A central vehicle computer (e.g., a general-purpose GPU-based driving platform) is used.

[1004] Use an infotainment system (e.g., a real-time operating system).

[1005] Environmental recognition is performed using data from various sensors (e.g., cameras, LiDAR, RADAR).

[1006] Flow of operations

[1007] 1. Accepting user requests:

[1008] The user opens the navigation application and enters the starting point, destination, and any options. This information is sent to the server.

[1009] 2. Gathering real-time traffic information:

[1010] The server collects data on current traffic conditions (such as when traffic lights change, when level crossings are open or closed, and how congested the area is) from traffic information providers and vehicle sensors.

[1011] The collected information is stored in a database, enabling fast queries.

[1012] 3. Square root calculation:

[1013] Based on the collected traffic information and the options specified by the user, the server uses Dijkstra's algorithm to calculate multiple routes and select the optimal route.

[1014] 4. Route provision:

[1015] The optimal route information is sent to the user's device, and visual and voice guidance begins. This allows the user to receive guidance in real time.

[1016] Specific example

[1017] As a concrete example, consider a scenario where user A enters "City Hall" as their destination and selects the "Prioritize narrow roads" option. In this case, the server performs the following actions:

[1018] 1. The server checks user A's current location and destination.

[1019] 2. The server retrieves information such as the timing of signal changes, railway crossing opening and closing information, and traffic congestion information from traffic information providers and stores it in a database.

[1020] 3. Based on the "Prioritize narrower paths" option, the server uses Dijkstra's algorithm to calculate the optimal route.

[1021] 4. The server sends the calculated optimal route to user A's terminal, and user A's terminal starts visual and voice guidance.

[1022] Example of a prompt:

[1023] If the user enters "City Hall" as the destination and selects the "Prioritize narrow roads" option:

[1024] By analyzing real-time traffic data obtained from sensors and APIs, Dijkstra's algorithm calculates the optimal route that prioritizes narrow roads.

[1025] The calculated route is evaluated in a database and provided with visual and audio guidance.

[1026] As described above, this invention is a system that makes maximum use of real-time traffic information to provide optimal route guidance for autonomous vehicles.

[1027] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1028] Step 1:

[1029] The user opens the navigation application and enters their starting point, destination, and options. At this stage, the input includes the starting point (GPS location), destination (address or location information), and user-selected options (e.g., "prioritize narrow roads" or "get to destination quickly"). This information is then sent from the application to the server.

[1030] Step 2:

[1031] The server receives a request from the user. The request includes the origin, destination, and options. The server analyzes this information to determine the scope of the traffic information to be collected next. Specifically, it sets the geographical range from the user's current location to their destination.

[1032] Step 3:

[1033] The server acquires real-time traffic information from sensors in autonomous vehicles and from external traffic information providers (e.g., traffic information APIs). Input data includes signal change timings, level crossing opening / closing information, traffic congestion information, and accident information. This data is temporarily stored in a database on the server.

[1034] Step 4:

[1035] The server generates multiple route options based on collected traffic information and user-selected options. Specifically, it uses Dijkstra's algorithm to calculate the optimal route. Input data consists of traffic information and user options, while output is multiple route options and their evaluation results.

[1036] Step 5:

[1037] The server evaluates the generated route candidates and selects the most suitable route. Evaluation criteria include travel time, traffic light waiting times, railway crossing waiting times, and road types. The optimal route is the one that best matches the user's specified options.

[1038] Step 6:

[1039] The server generates optimal route information and sends it to the user's terminal. The input is the evaluated optimal route information, and the output is a data packet for display on the user's terminal.

[1040] Step 7:

[1041] The system analyzes route information received by the user's device and displays it on the navigation screen. Specific actions include displaying visual guidance and initiating voice guidance. Input data is route information transmitted from the server, and output is the display screen and voice guidance. Users can receive real-time navigation guidance.

[1042] 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.

[1043] This invention is a navigation system that collects and analyzes traffic information in real time based on user-specified options and provides the optimal route. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it enables more flexible route guidance tailored to the user's state. Specific embodiments are described below.

[1044] 1. Accepting user requests

[1045] Terminal: The user launches the navigation application and enters the starting point (current location) and destination. The user selects options such as "prioritize narrow roads" or "get to destination quickly."

[1046] Device: Additionally, the emotion engine is activated, recognizing emotions from the user's voice and facial expressions.

[1047] For example, if a user displays expressions of anger or impatience, the emotion engine recognizes this as "stress."

[1048] Terminal: Sends the input data and recognized emotion information as a request to the server.

[1049] 2. Collection of real-time traffic information

[1050] Server: Receives requests from users and verifies the origin and destination, as well as the selected options and sentiment information.

[1051] Server: Accesses traffic information providers to obtain real-time traffic information. This information includes traffic signal timing, railway crossing opening and closing information, traffic congestion status, road construction and accident information, etc.

[1052] Server: The acquired traffic information is temporarily stored in the database.

[1053] 3. Calculating square roots

[1054] Server: Applies a route calculation algorithm based on stored traffic information, user settings options, and sentiment information.

[1055] For example, if the system detects that a user is experiencing stress, it will select a route with smoother traffic flow and shorter waiting times.

[1056] Server: Generates multiple route options and evaluates the travel time, signal waiting time, and level crossing waiting time for each route.

[1057] Server: Compares the evaluation results of each route and selects the optimal route that best suits the user's options and sentiment information.

[1058] 4. Route provision

[1059] Server: Generates optimal route information and sends it to the user's terminal.

[1060] Terminal: Analyzes received route information and displays it on the navigation screen. Simultaneously, voice guidance is initiated, providing real-time directions to the user.

[1061] Specific example

[1062] Case 1: Optimal route selection using an emotion engine

[1063] 1. Terminal: User A enters "City Hall" as the destination and selects the "Prioritize narrow roads" option.

[1064] 2. Terminal: The emotion engine detects anxiety from user A's voice.

[1065] 3. Terminal: Sends the input data and recognized emotion information to the server.

[1066] 4. Server: Receives the request and verifies the origin and destination, options, and sentiment information.

[1067] 5. Server: Retrieves information such as signal change timing, level crossing opening / closing information, and traffic congestion information from traffic information providers and stores it in a database.

[1068] 6. Server: Calculates the optimal route based on the "Prioritize narrower paths" option and the server's emotional state (emotional information indicating anxiety).

[1069] 7. Server: Evaluate each route candidate and select the optimal route for user A.

[1070] 8. Server: Sends the optimal route to user A's terminal.

[1071] 9. Terminal: Displays the received route information and starts voice guidance.

[1072] Case 2: Route reselection based on an emotion engine

[1073] 1. Terminal: User B enters "station" as the destination and selects the "I want to get to my destination quickly" option.

[1074] 2. Device: The emotion engine detects stress from user B's facial expressions.

[1075] 3. Terminal: Sends the input data and recognized emotion information to the server.

[1076] 4. Server: Receives the request and verifies the origin and destination, options, and sentiment information.

[1077] 5. Server: Retrieves information such as signal change timing, level crossing opening / closing information, and traffic congestion information from traffic information providers and stores it in a database.

[1078] 6. Server: Calculates the optimal route based on the "I want to get to my destination quickly" option and stress levels.

[1079] 7. Server: Evaluates each route candidate and allows user B to select the optimal route.

[1080] 8. Server: Sends the optimal route to user B's terminal.

[1081] 9. Terminal: Displays the received route information and starts voice guidance.

[1082] The following describes the processing flow.

[1083] Step 1:

[1084] Terminal: The user launches the navigation application and enters the starting point (current location) and destination. The user selects options such as "prioritize narrow roads" or "get to destination quickly."

[1085] Step 2:

[1086] Device: The emotion engine is activated and recognizes emotions from the user's voice and facial expressions. For example, it captures the user's facial expressions through the camera and performs voice analysis using speech recognition technology.

[1087] Step 3:

[1088] Device: The emotion engine analyzes the emotional information it recognizes to determine whether the user is feeling "anxiety" or "stress."

[1089] Step 4:

[1090] Terminal: Sends the origin, destination, user-selected options, and sentiment information as a request to the server.

[1091] Step 5:

[1092] Server: Analyzes incoming requests to determine the user's origin, destination, options, and sentiment information.

[1093] Step 6:

[1094] Server: Accesses traffic information providers to obtain real-time traffic information such as signal change timing, level crossing opening and closing information, traffic congestion status, road construction and accident information.

[1095] Step 7:

[1096] Server: Temporarily stores acquired traffic information in a database.

[1097] Step 8:

[1098] Server: Applies route calculation algorithms based on stored traffic information, user selection options, and sentiment information.

[1099] Step 9:

[1100] Server: Generates multiple route options and evaluates the travel time, signal waiting time, and level crossing waiting time for each route.

[1101] Step 10:

[1102] Server: Compares the evaluation results of each route and selects the optimal route, taking into account the "prioritize narrow roads" option and the user's sense of urgency.

[1103] Step 11:

[1104] Server: Creates optimal route information and sends it to the user's terminal.

[1105] Step 12:

[1106] Terminal: Analyzes received route information and displays it on the navigation screen. Also initiates corresponding voice guidance.

[1107] Step 13:

[1108] Terminal: The user begins moving towards their destination.

[1109] Step 14:

[1110] Terminal: While on the move, it continuously monitors the user's emotional information and sends updates to the server as needed.

[1111] Step 15:

[1112] Server: Based on real-time traffic information and updated user sentiment data, it recalculates the optimal route and reroutes as needed.

[1113] Step 16:

[1114] Terminal: Receives new route information and updates the navigation screen. Performs a series of operations continuously until the user reaches their destination.

[1115] (Example 2)

[1116] 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."

[1117] Conventional navigation systems have the problem of failing to alleviate user stress and anxiety because they provide route guidance without considering the user's emotional state. Furthermore, route calculations based solely on real-time traffic information have the challenge of not being able to flexibly respond to individual user needs (for example, wanting to choose a quiet route or wanting to reach the destination quickly).

[1118] 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.

[1119] In this invention, the server includes means for the user to input a starting point and destination, means for collecting real-time traffic information based on options specified by the user, means for calculating an optimal route using the collected traffic information and the user's emotional information, means for transmitting the calculated optimal route information to the user's terminal, and means for displaying and guiding the user's terminal to the route information received. This enables the provision of an optimal route according to the user's emotional state and flexible route guidance that reflects real-time traffic information and the user's individual needs.

[1120] The "starting point" refers to the location where the user begins their route to their current location or destination.

[1121] "Destination" refers to the place the user ultimately wants to reach.

[1122] "Options" refer to the conditions and settings that users prioritize in route guidance. For example, these include "I want to get to my destination quickly" or "Prioritize narrow roads."

[1123] "Real-time traffic information" refers to the most up-to-date information in time, such as current traffic conditions, traffic light change timings, railway crossing opening and closing information, traffic congestion status, road construction and accident information.

[1124] "Emotional information" refers to the emotional state analyzed from the user's voice, facial expressions, and other behaviors. Examples include stress, anxiety, and anger.

[1125] A "route calculation algorithm" refers to a method for calculating the optimal route based on collected traffic information, user settings, and sentiment information. Examples include the A algorithm and Dijkstra's algorithm.

[1126] "Terminal" refers to devices used by users, such as mobile phones, tablets, and car navigation systems.

[1127] A "server" refers to a central processing unit that processes requests sent by users, collects and analyzes necessary information, and sends the results to the user's terminal.

[1128] "Route information" refers to detailed data about the calculated route. This includes the route itself, estimated travel time, traffic light waiting times, railway crossing waiting times, etc.

[1129] This invention is a navigation system that collects and analyzes traffic information in real time based on user-specified options and emotional information, and provides the optimal route. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it enables more flexible route guidance tailored to the user's state.

[1130] First, the user launches the navigation application and enters their starting point (current location) and destination. The user can select options such as "prioritize narrow roads" or "get to destination quickly." The device has a built-in emotion engine that recognizes the user's emotions in real time from their voice and facial expressions. For example, if the user shows signs of anger or impatience, the emotion engine recognizes this as "stress."

[1131] Next, the terminal sends the entered data and recognized sentiment information as a request to the server. The server receives the request from the user and verifies the origin and destination, as well as the selected options and sentiment information. The server then accesses a traffic information provider (e.g., Google Maps API or Here API) to obtain real-time traffic information. This information includes traffic light change timings, railway crossing opening and closing information, traffic congestion, road construction and accident information, etc. The retrieved traffic information is temporarily stored in a database.

[1132] The server applies a route calculation algorithm based on stored traffic information, user settings options, and emotional information. For example, if the server detects that the user is stressed, it selects a route with smooth traffic flow and minimal waiting times. The server generates multiple route options and evaluates the travel time, traffic light waiting times, and railway crossing waiting times for each route. It compares the evaluation results of each route and selects the optimal route that best suits the user's options and emotional information.

[1133] Once the optimal route information is generated, the server sends it to the user's terminal. The terminal analyzes the received route information and displays it on the navigation screen. Simultaneously, voice guidance begins, providing instructions to the user in real time.

[1134] For example, suppose user A enters "City Hall" as their destination and selects the "Prioritize narrow roads" option. If the emotion engine detects impatience from user A's voice, the device sends this information to the server. The server receives the request and retrieves information such as traffic light timings, railway crossing opening / closing information, and traffic congestion information from a traffic information provider. Then, based on the "Prioritize narrow roads" option and the impatient emotion information, it calculates the optimal route and sends it to user A's device. The device displays the received route information and starts voice guidance.

[1135] As another example, suppose user B enters "station" as their destination and selects the "I want to get to my destination quickly" option. If the emotion engine detects stress from user B's facial expression, the terminal sends the entered data and the recognized emotion information to the server. The server receives the request and retrieves information such as traffic signal timing, level crossing opening / closing information, and traffic congestion information from a traffic information provider. It then calculates the optimal route based on the "I want to get to my destination quickly" option and stress emotion, and sends it to user B's terminal. The terminal displays the received route information and starts voice guidance.

[1136] (Example of a prompt message)

[1137] "Explain how, after the user enters their starting point and destination and selects an option, the emotion engine recognizes the user's emotions and calculates the optimal route."

[1138] "Please describe, in natural language, the processing flow of a navigation system that collects real-time traffic information and takes user sentiment into consideration."

[1139] This invention enables the provision of optimal routes according to the user's emotional state, allowing for flexible route guidance that reflects real-time traffic information and the user's individual needs. Furthermore, by combining it with an emotion engine, an improvement in the user experience can be expected.

[1140] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1141] Step 1:

[1142] The terminal launches the navigation application, and the user enters the starting point and destination. The user selects options such as "I want to get to the destination quickly" or "Prioritize narrow roads." The terminal receives the starting point, destination, and options as input. The terminal receives this input data and proceeds to the next step.

[1143] Step 2:

[1144] The device activates an emotion engine to recognize emotional information from the user's voice and facial expressions. Specifically, it uses the device's camera and microphone to capture facial expressions and voice, and a generative AI model analyzes this data. The user's voice and image data are provided to the emotion engine as input. The emotion engine analyzes this data and outputs emotional information, such as whether the user is feeling stressed.

[1145] Step 3:

[1146] The terminal sends collected origin, destination, options, and sentiment information to the server. As input, request data containing origin, destination, options, and sentiment information is sent from the terminal to the server. This data is transmitted via communication protocols such as HTTP or WebSocket.

[1147] Step 4:

[1148] The server analyzes the request data received from the terminal to confirm the origin and destination, as well as the selected options and sentiment information. The request data is provided to the server as input. The server analyzes this data and extracts the information necessary for route calculation.

[1149] Step 5:

[1150] The server sends API requests to traffic information providers to obtain real-time traffic information. Specifically, the server accesses APIs such as the Google Maps API and the Here API to collect traffic information. As input, API requests are sent from the server. As output, traffic information such as the timing of signal changes, railway crossing opening and closing information, traffic congestion status, road construction and accident information is returned to the server.

[1151] Step 6:

[1152] The server temporarily stores the traffic information it acquires in a database. Traffic information is provided to the server as input. The server stores this information in a database (e.g., Redis) so that it can be used in subsequent route calculations.

[1153] Step 7:

[1154] The server applies a route calculation algorithm based on stored traffic information, user settings options, and sentiment information. The server uses route calculation algorithms such as the A algorithm or Dijkstra's algorithm to calculate the optimal route. Traffic information, settings options, and sentiment information are provided to the server as input. Multiple route candidates are generated as output.

[1155] Step 8:

[1156] The server evaluates the generated route candidates and selects the optimal route that best suits the user's configuration options and sentiment information. Multiple route candidates are provided as input. The server evaluates these and selects the optimal route. The optimal route information is generated as output.

[1157] Step 9:

[1158] The server sends optimal route information to the user's terminal. The server receives optimal route information as input. The server sends this information to the terminal, which then receives it. HTTP or WebSocket are used as the communication protocol.

[1159] Step 10:

[1160] The terminal analyzes the route information it receives and displays it on the navigation screen. Furthermore, it initiates voice guidance, providing real-time instructions to the user. The terminal receives optimal route information as input. The terminal analyzes this information and provides visual and audio guidance.

[1161] (Application Example 2)

[1162] 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."

[1163] Traditional navigation systems provided optimal routes based on real-time traffic information, but they failed to consider the user's emotional state and lacked route guidance adapted to the user's mental condition. Therefore, they could not address psychological needs, such as when the user was anxious or wanted to relax, potentially leading to a lower satisfaction with the driving experience. Furthermore, there was a need for technology that could efficiently analyze the user's emotional state within a specific vehicle environment and provide appropriate navigation.

[1164] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes an emotion analysis means for recognizing the user's emotions, a means for collecting real-time traffic information based on options specified by the user, and a means for calculating the optimal route using the collected traffic information and emotion information. This makes it possible to provide route guidance that is appropriate to the user's emotional state.

[1165] "Means for users to input their starting point and destination" refers to an interface for users to input their current location and desired destination using electronic devices.

[1166] A "means of emotional analysis that recognizes user emotions" is a system that analyzes a user's facial expressions and voice to determine their emotional state in real time.

[1167] "Means for collecting real-time traffic information based on user-specified options" refers to a system for obtaining traffic conditions and event information from online databases, APIs, etc., according to the conditions selected by the user.

[1168] "Means for calculating the optimal route using collected traffic and sentiment information" refers to a system that uses algorithms to calculate the route that best suits the user's mental and physical needs, based on acquired traffic and sentiment data.

[1169] "Means for transmitting calculated optimal route information to the user's terminal" refers to a communication system for transferring information about the optimal route calculated on a server to the electronic device being used by the user.

[1170] "Means for displaying and guiding users through route information received by their device" refers to interfaces and software for visually and audibly displaying and guiding users through optimal route information on their device.

[1171] This invention relates to a navigation system that analyzes the user's emotional state and provides the optimal route based on real-time traffic information. This navigation system is particularly applicable to autonomous vehicles and enables flexible route guidance that responds to the user's psychological needs.

[1172] 1. System Overview

[1173] This system includes means for emotion analysis to recognize the user's emotions, means for collecting real-time traffic information, means for calculating the optimal route using the collected information, means for transmitting the calculation results to the user's terminal, and means for displaying and guiding the user through the received route information.

[1174] 2. Hardware and software to be used

[1175] hardware

[1176] Camera: Cameras mounted on the autonomous vehicle will be used to capture the user's facial expressions.

[1177] Microphone: The user's voice will be recorded using a microphone installed in the autonomous vehicle.

[1178] Central control terminal: Receives user input via an in-vehicle touchscreen display.

[1179] software

[1180] Emotion analysis engine: Uses Microsoft Azure's Face API and Google's Cloud Vision API to analyze the user's facial expressions and voice.

[1181] Real-time traffic information acquisition module: Uses TomTom and the Google Maps API to collect real-time traffic information.

[1182] Route calculation algorithm: Using algorithms such as Algorithm A, the optimal route is calculated based on collected traffic and sentiment information.

[1183] 3. Data calculation and processing

[1184] Emotion Recognition: The vehicle captures the user's face and voice using an in-car camera and microphone, and an emotion analysis engine performs real-time analysis. For example, if the user is anxious, the system prioritizes a smoother, shorter route to reduce their stress.

[1185] Traffic Information Gathering: Access a real-time traffic database to collect information such as traffic light change timings, railway crossing opening and closing information, traffic congestion status, road construction and accident information.

[1186] Route Calculation: Based on collected traffic information, user sentiment data, and selected options, the system calculates the optimal route. For example, if the user wants to relax, it might suggest a scenic route.

[1187] Route information transmission: The calculated optimal route information is transmitted to the central control terminal to provide information to the user.

[1188] 4. Specific Examples

[1189] The following are specific examples of how this system can be used.

[1190] Example 1:

[1191] The user gets into the self-driving vehicle and enters "park" as their destination. An emotion analysis engine detects impatience from the user's voice, and the system collects real-time traffic information. As a result, the optimal route with minimal traffic lights and congestion is calculated, and the self-driving system begins driving along that route.

[1192] Example 2:

[1193] The user enters "Shopping Mall" as their destination and selects "Prioritize scenic routes" as an option. The emotion analysis engine detects relaxation from the user's facial expressions and acquires traffic information. The system suggests a scenic route, and the vehicle begins driving along that route.

[1194] 5. Example of a prompt statement

[1195] The following is an example of a prompt message to input into a generative AI model.

[1196] Write Python code to calculate the optimal route based on current traffic conditions. Consider the user's sentiment and selection options. Sentiment information will be obtained from facial and speech recognition. Traffic data will be obtained from the Google Maps API. Use the A algorithm for route calculation.

[1197] In this way, an optimal navigation system that takes into account the user's psychological state and actual traffic conditions can be realized. This is expected to significantly improve the driving experience of autonomous vehicles.

[1198] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1199] Step 1:

[1200] The user enters the starting point and destination into the device.

[1201] The input data consists of the starting point (current location) and the destination. This input data is sent from the terminal to the server for use in the next processing step.

[1202] Step 2:

[1203] The device's camera and microphone are activated to recognize the user's emotions.

[1204] The input data used consists of video captured by the camera and audio recorded by the microphone. This data is analyzed in real time by an emotion analysis engine, and the user's emotional state (e.g., relaxed, anxious, stressed) is output. This emotional information is used in the next step.

[1205] Step 3:

[1206] The server collects real-time traffic information based on options specified by the user.

[1207] The input data used includes user-selected options (e.g., shortest travel time, scenic route) and real-time traffic data obtained from a traffic information API. This data includes, for example, traffic signal change timings, railway crossing opening / closing information, and traffic congestion information obtained from the API. This traffic information is used in the next step.

[1208] Step 4:

[1209] The server uses collected traffic and sentiment information to calculate the optimal route.

[1210] The input data used includes acquired traffic information, user sentiment information, and navigation options selected by the user. The server applies route calculation algorithms, such as the A algorithm, to this data to calculate the optimal route. The output is the calculated optimal route information.

[1211] Step 5:

[1212] The server sends the calculated optimal route information to the user's terminal.

[1213] The optimal route information is used as input data. The server sends this information to the terminal, and the information sent to the terminal is used in the next step.

[1214] Step 6:

[1215] The device displays and guides the user through route information it has received.

[1216] The optimal route information transmitted from the server is used as input data. The terminal analyzes this information and initiates visual navigation display and voice guidance. This allows the user to confirm the optimal route information while driving.

[1217] Through the processing steps described above, an optimal navigation system is realized based on the user's emotional state and traffic information. This provides a comfortable driving experience that meets the user's psychological needs.

[1218] 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.

[1219] 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.

[1220] 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.

[1221] [Fourth Embodiment]

[1222] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[1223] 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.

[1224] 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).

[1225] 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.

[1226] 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.

[1227] 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).

[1228] 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.

[1229] 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.

[1230] 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.

[1231] 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.

[1232] 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.

[1233] 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.

[1234] 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".

[1235] This invention is a navigation system that collects and analyzes traffic information in real time based on options specified by the user and provides the optimal route, and is specifically implemented as follows.

[1236] 1. Accepting user requests

[1237] Terminal: The user opens a navigation application and enters their starting point (current location) and destination. The user also selects options such as "prioritize narrow roads" or "get to destination quickly."

[1238] Terminal: The entered information is sent to the server as a request.

[1239] 2. Collection of real-time traffic information

[1240] Server: Upon receiving a request from a user, it verifies the origin and destination.

[1241] Server: Retrieves real-time traffic information from traffic information providers. This information includes traffic signal timing, railway crossing opening and closing information, traffic congestion, road construction, and accident information.

[1242] Server: The collected traffic information is temporarily stored in a database.

[1243] 3. Calculating square roots

[1244] Server: Applies a route calculation algorithm based on collected traffic information and user-selected options.

[1245] Server: Generates multiple route candidates and evaluates the following elements for each route.

[1246] Duration

[1247] Waiting time at traffic lights

[1248] railroad crossing waiting time

[1249] Server: Compares the evaluation results of each route and selects the optimal route that best suits the user's specified options.

[1250] 4. Route provision

[1251] Server: Generates optimal route information and sends it to the user's terminal.

[1252] Terminal: Analyzes received route information and displays it on the navigation screen. Simultaneously, voice guidance is initiated, providing real-time directions to the user.

[1253] Specific example

[1254] Case 1: Route prioritizing narrow roads

[1255] 1. Terminal: User A enters "City Hall" as the destination and selects the "Prioritize narrow roads" option.

[1256] 2. Server: Receives the request and checks user A's current location and destination.

[1257] 3. Server: Retrieves information such as signal change timing, level crossing opening / closing information, and traffic congestion information from traffic information providers and stores it in a database.

[1258] 4. Server: Calculates the optimal route based on the "Prioritize narrower paths" option. Evaluates multiple candidates and selects the best route for user A.

[1259] 5. Server: Sends the optimal route to user A's terminal.

[1260] 6. Terminal: Displays the received route information and starts voice guidance.

[1261] Case 2: When you want to reach your destination quickly

[1262] 1. Terminal: User B enters "station" as the destination and selects the "I want to get to my destination quickly" option.

[1263] 2. Server: Receives the request and checks user B's current location and destination.

[1264] 3. Server: Retrieves information such as signal change timing, level crossing opening / closing information, and traffic congestion information from traffic information providers and stores it in a database.

[1265] 4. Server: Based on the "I want to reach my destination quickly" option, it calculates the optimal route. It evaluates multiple options and selects the route with the shortest waiting time.

[1266] 5. Server: Sends the optimal route to user B's terminal.

[1267] 6. Terminal: Displays the received route information and starts voice guidance.

[1268] The following describes the processing flow.

[1269] Step 1:

[1270] Terminal: The user launches the navigation application and enters the starting point (current location) and destination. The user can also select options such as "prioritize narrow roads" or "get to destination quickly."

[1271] Step 2:

[1272] Terminal: Sends data regarding the entered departure point, destination, and options as a request to the server.

[1273] Step 3:

[1274] Server: Parses the received request to confirm the user's origin and destination, and the selected options.

[1275] Step 4:

[1276] Server: Accesses traffic information providers to obtain real-time traffic information. This information includes traffic signal timing, railway crossing opening and closing information, traffic congestion status, road construction and accident information, etc.

[1277] Step 5:

[1278] Server: Temporarily stores acquired traffic information in a database.

[1279] Step 6:

[1280] Server: Applies a route calculation algorithm based on stored traffic information and user configuration options.

[1281] Step 7:

[1282] Server: Generates multiple route options based on collected real-time information and evaluates the travel time, signal waiting time, and level crossing waiting time for each route.

[1283] Step 8:

[1284] Server: Compares the evaluation results of each route and selects the optimal route that best suits the user's chosen option.

[1285] Step 9:

[1286] Server: Generates optimal route information and sends it to the user's terminal.

[1287] Step 10:

[1288] Terminal: Analyzes received route information and displays it on the navigation screen.

[1289] Step 11:

[1290] Terminal: Starts voice guidance and provides real-time navigation to the user.

[1291] Step 12:

[1292] Terminal: Until the user reaches their destination, it will re-obtain real-time updated traffic information as needed and reroute and optimize the route.

[1293] (Example 1)

[1294] 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".

[1295] Conventional navigation systems have been unable to fully utilize real-time traffic information, making it difficult to provide the optimal route based on user-specified options. Furthermore, because they could not utilize detailed traffic information such as the timing of traffic light changes and the opening and closing of railway crossings, they could not provide optimal guidance for the user's desired route conditions. The objective of this invention is to solve this problem and provide more accurate route guidance.

[1296] 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.

[1297] In this invention, the server includes means for the user to input a starting point and destination, means for collecting real-time traffic information based on options specified by the user, means for temporarily storing the collected traffic information in a database, means for applying a route calculation algorithm based on the stored data, means for selecting the optimal route based on the evaluation results, means for transmitting the calculated optimal route information to the user's terminal, and means for displaying and guiding the user through the route information received by the user's terminal. This enables highly accurate route guidance based on real-time traffic information, including the timing of signal changes and the opening and closing of railway crossings.

[1298] "A means for users to input their starting point and destination" refers to a mechanism that provides an interface for users to input their current location and destination.

[1299] "Means of collecting real-time traffic information based on user-specified options" refers to a system that acquires real-time traffic conditions according to the route conditions selected by the user (for example, "prioritize narrow roads" or "want to reach the destination quickly").

[1300] "Means for temporarily storing collected traffic information in a database" refers to a mechanism for temporarily storing collected traffic information in a database for use in subsequent processing.

[1301] "A means of applying a route calculation algorithm based on saved data" refers to a mechanism that executes an algorithm that calculates routes using traffic information stored in a database.

[1302] "Method for selecting the optimal route based on evaluation results" refers to a system that selects the route that best suits the user's specified conditions based on the evaluation results of the route calculation algorithm.

[1303] "Means for sending calculated optimal route information to the user's terminal" refers to a mechanism for sending information about the optimal route selected by the server to the user's terminal.

[1304] "Means for displaying and guiding users through route information received by the user's device" refers to a system that displays route information received by the user's device on the screen and provides directions to the user through voice guidance or other means.

[1305] "Information on the timing of traffic signal changes and the opening and closing of level crossings" refers to information regarding the timing of changes in traffic signals and the opening and closing of level crossings.

[1306] A "route that prioritizes narrow roads" refers to a route that prioritizes the use of narrow roads, and includes criteria for selecting a route with many narrow roads.

[1307] A "fastest route to the destination" is a route that prioritizes getting the user to their destination in the shortest possible time.

[1308] This invention is a navigation system that collects and analyzes traffic information in real time based on user-specified options and provides the optimal route. A specific embodiment of this system is described in detail below.

[1309] System Configuration

[1310] This navigation system consists of a user terminal, a server, and a database. The user terminal is a mobile device such as a smartphone, with a navigation application installed. The server collects and stores real-time traffic information and calculates routes. The database temporarily stores the collected traffic information.

[1311] Hardware and software to be used

[1312] User's device:

[1313] These are mobile devices such as smartphones and tablets, which provide the interface for applications.

[1314] server:

[1315] It collects, stores, and calculates routes based on traffic information. The server has software installed that interacts with traffic information providers (e.g., Google Maps API, HERE Technologies).

[1316] Database:

[1317] Relational databases such as MySQL and PostgreSQL are used to temporarily store traffic information.

[1318] System operation

[1319] 1. Accepting user requests:

[1320] The user opens the navigation app and enters their starting point (usually their current location) and destination. They also select options such as "prioritize narrow roads" or "get to destination quickly." This information is sent to the server in JSON format.

[1321] 2. Gathering real-time traffic information:

[1322] The server receives requests from users and communicates with traffic information providers to obtain real-time traffic information. This includes information such as traffic light change timings, railway crossing opening and closing information, traffic congestion, road construction, and accident information. This information is temporarily stored in a database.

[1323] 3. Square root calculation:

[1324] The server applies a route calculation algorithm based on traffic information stored in the database and user options. It generates multiple route candidates and evaluates factors such as travel time, traffic light waiting time, and railway crossing waiting time for each route. It then selects the most suitable route.

[1325] 4. Route provision:

[1326] The server generates calculated optimal route information and sends it to the user's device. The user's device analyzes the received route information and displays it on the navigation screen. Simultaneously, voice guidance begins, providing the user with real-time directions.

[1327] Specific example

[1328] For example, if a user enters "City Hall" as their destination in the app and selects the "Prioritize narrow roads" option, the server receives the request, retrieves real-time traffic information, and stores it in the database. Then, based on the "Prioritize narrow roads" option, it calculates the optimal route and sends the result to the user's device. The user's device displays the received route information and begins voice guidance.

[1329] Example of a prompt

[1330] "Please give me directions to the city hall, prioritizing narrower roads."

[1331] "Please tell me the shortest route to the station."

[1332] This invention enables highly accurate route guidance based on real-time, detailed traffic information.

[1333] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1334] Step 1: Accepting user requests

[1335] User: The user launches a navigation app on their smartphone and enters their starting point (usually their current location) and destination. They also select options such as "prioritize narrow roads" or "get to destination quickly."

[1336] Input: Departure point, destination, and optional information.

[1337] Terminal: Converts the entered information into a JSON-formatted request object and sends it to the server as an HTTP POST request.

[1338] Output: Request object in JSON format.

[1339] Step 2: Gathering real-time traffic information

[1340] Server: Receives requests from users and parses the origin, destination, and options.

[1341] Input: Request object in JSON format.

[1342] Server: Communicates with traffic information providers to obtain real-time traffic data. This information includes traffic congestion, traffic light change timing, railway crossing opening / closing information, road construction, and accident information.

[1343] Data processing: The acquired traffic information is formatted into an appropriate format.

[1344] Output: Real-time traffic information.

[1345] Step 3: Temporarily save traffic information

[1346] Server: Temporarily stores the acquired traffic information in a database (e.g., MySQL).

[1347] Input: Real-time traffic information.

[1348] Database: Stores traffic information.

[1349] Output: Success / Failure status.

[1350] Step 4: Calculating square roots

[1351] Server: Applies a route calculation algorithm based on temporarily stored traffic information and user-specified options. The A-search algorithm is commonly used.

[1352] Input: Traffic information, user options.

[1353] Data calculation: Calculate and evaluate the travel time, traffic light waiting time, and railroad crossing waiting time for each route candidate.

[1354] Output: Multiple route candidates evaluated.

[1355] Step 5: Selecting the optimal route

[1356] Server: Selects the optimal route from the evaluated route candidates based on the user's specified options.

[1357] Input: Evaluation results, user options.

[1358] Data processing: Comparison of evaluation scores.

[1359] Output: Optimal route information.

[1360] Step 6: Sending Route Information

[1361] Server: Converts optimal route information into JSON format and sends it to the user's terminal.

[1362] Input: Optimal route information.

[1363] Data processing: Convert to JSON format.

[1364] Output: Route information in JSON format.

[1365] Step 7: Display and guidance of route information

[1366] Terminal: Analyzes received route information and displays it on the navigation screen. Simultaneously, voice guidance begins.

[1367] Input: Route information in JSON format.

[1368] Data processing: Converts data to a format suitable for screen display and audio guidance.

[1369] Output: Navigation screen display and voice guidance.

[1370] Example prompt statements

[1371] "Please give me directions to the city hall, prioritizing narrower roads."

[1372] "Please tell me the shortest route to the station."

[1373] This allows users to receive real-time, optimal route guidance based on specified conditions.

[1374] (Application Example 1)

[1375] 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".

[1376] Conventional navigation systems fail to fully utilize real-time traffic information, making it particularly difficult for autonomous vehicles to select optimal routes that take into account traffic light wait times, railway crossing wait times, and road congestion. Furthermore, flexible route suggestions based on user choices are difficult, resulting in a lack of safety and efficiency. As a result, the operation of autonomous vehicles involves wasted time and energy, leading to a decrease in overall operational efficiency.

[1377] 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.

[1378] In this invention, the server includes means for the user to input a starting point and destination, means for collecting real-time traffic information based on options specified by the user, means for obtaining real-time traffic information from sensors of the autonomous vehicle and an external traffic information provider, means for calculating the optimal route based on the collected traffic information and the user's selection, and means for providing the optimal route as visual and voice guidance. This enables the selection of the optimal route considering real-time traffic conditions, realizes flexible guidance according to the user's selection, and improves the operational efficiency and safety of the autonomous vehicle.

[1379] The "starting point" is the current location or starting point that the user sets when starting navigation.

[1380] A "destination" is the location that the user sets as the target location for the navigation system to guide them to.

[1381] "Options" refer to the conditions and priorities that the user specifies for route selection within the navigation system.

[1382] "Real-time traffic information" refers to the latest traffic condition data obtained from traffic information providers, vehicle sensors, etc.

[1383] An "autonomous vehicle" is a vehicle that operates autonomously using a system, without requiring operation by a human driver.

[1384] A "sensor" is a device used to detect the surrounding conditions of a vehicle and collect data.

[1385] A "traffic information provider" is a service that provides traffic-related data such as road conditions, congestion, and traffic light timings.

[1386] "Methods for calculating routes" refer to algorithms that calculate the optimal travel route based on user input information and collected traffic data.

[1387] "Visual navigation" refers to visual navigation information displayed on digital displays or interfaces.

[1388] "Voice guidance" refers to real-time voice navigation instructions provided through a speaker.

[1389] "User selection" refers to the preferences and conditions that users individually set within the navigation system.

[1390] This invention is a navigation system that collects and analyzes traffic information in real time based on user-specified options and provides the optimal route. It can particularly improve the operational efficiency and safety of autonomous vehicles.

[1391] System Configuration

[1392] This system consists of the following main components:

[1393] 1. User terminal:

[1394] The user enters the starting point and destination.

[1395] Users can set options such as "prioritize narrow roads" or "arrive at destination quickly."

[1396] 2. Server:

[1397] Receives requests from user terminals.

[1398] Real-time traffic information is obtained from sensors in the autonomous vehicle and from external traffic information providers.

[1399] The collected traffic information is stored in a database, and the necessary data is queried in real time.

[1400] Based on the user's selected options, the optimal route is calculated using Dijkstra's algorithm.

[1401] The calculated optimal route is sent to the user's device.

[1402] 3. Autonomous vehicles:

[1403] A central vehicle computer (e.g., a general-purpose GPU-based driving platform) is used.

[1404] Use an infotainment system (e.g., a real-time operating system).

[1405] Environmental recognition is performed using data from various sensors (e.g., cameras, LiDAR, RADAR).

[1406] Flow of operations

[1407] 1. Accepting user requests:

[1408] The user opens the navigation application and enters the starting point, destination, and any options. This information is sent to the server.

[1409] 2. Gathering real-time traffic information:

[1410] The server collects data on current traffic conditions (such as when traffic lights change, when level crossings are open or closed, and how congested the area is) from traffic information providers and vehicle sensors.

[1411] The collected information is stored in a database, enabling fast queries.

[1412] 3. Square root calculation:

[1413] Based on the collected traffic information and the options specified by the user, the server uses Dijkstra's algorithm to calculate multiple routes and select the optimal route.

[1414] 4. Route provision:

[1415] The optimal route information is sent to the user's device, and visual and voice guidance begins. This allows the user to receive guidance in real time.

[1416] Specific example

[1417] As a concrete example, consider a scenario where user A enters "City Hall" as their destination and selects the "Prioritize narrow roads" option. In this case, the server performs the following actions:

[1418] 1. The server checks user A's current location and destination.

[1419] 2. The server retrieves information such as the timing of signal changes, railway crossing opening and closing information, and traffic congestion information from traffic information providers and stores it in a database.

[1420] 3. Based on the "Prioritize narrower paths" option, the server uses Dijkstra's algorithm to calculate the optimal route.

[1421] 4. The server sends the calculated optimal route to user A's terminal, and user A's terminal starts visual and voice guidance.

[1422] Example of a prompt:

[1423] If the user enters "City Hall" as the destination and selects the "Prioritize narrow roads" option:

[1424] By analyzing real-time traffic data obtained from sensors and APIs, Dijkstra's algorithm calculates the optimal route that prioritizes narrow roads.

[1425] The calculated route is evaluated in a database and provided with visual and audio guidance.

[1426] As described above, this invention is a system that makes maximum use of real-time traffic information to provide optimal route guidance for autonomous vehicles.

[1427] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1428] Step 1:

[1429] The user opens the navigation application and enters their starting point, destination, and options. At this stage, the input includes the starting point (GPS location), destination (address or location information), and user-selected options (e.g., "prioritize narrow roads" or "get to destination quickly"). This information is then sent from the application to the server.

[1430] Step 2:

[1431] The server receives a request from the user. The request includes the origin, destination, and options. The server analyzes this information to determine the scope of the traffic information to be collected next. Specifically, it sets the geographical range from the user's current location to their destination.

[1432] Step 3:

[1433] The server acquires real-time traffic information from sensors in autonomous vehicles and from external traffic information providers (e.g., traffic information APIs). Input data includes signal change timings, level crossing opening / closing information, traffic congestion information, and accident information. This data is temporarily stored in a database on the server.

[1434] Step 4:

[1435] The server generates multiple route options based on collected traffic information and user-selected options. Specifically, it uses Dijkstra's algorithm to calculate the optimal route. Input data consists of traffic information and user options, while output is multiple route options and their evaluation results.

[1436] Step 5:

[1437] The server evaluates the generated route candidates and selects the most suitable route. Evaluation criteria include travel time, traffic light waiting times, railway crossing waiting times, and road types. The optimal route is the one that best matches the user's specified options.

[1438] Step 6:

[1439] The server generates optimal route information and sends it to the user's terminal. The input is the evaluated optimal route information, and the output is a data packet for display on the user's terminal.

[1440] Step 7:

[1441] The system analyzes route information received by the user's device and displays it on the navigation screen. Specific actions include displaying visual guidance and initiating voice guidance. Input data is route information transmitted from the server, and output is the display screen and voice guidance. Users can receive real-time navigation guidance.

[1442] 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.

[1443] This invention is a navigation system that collects and analyzes traffic information in real time based on user-specified options and provides the optimal route. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it enables more flexible route guidance tailored to the user's state. Specific embodiments are described below.

[1444] 1. Accepting user requests

[1445] Terminal: The user launches the navigation application and enters the starting point (current location) and destination. The user selects options such as "prioritize narrow roads" or "get to destination quickly."

[1446] Device: Additionally, the emotion engine is activated, recognizing emotions from the user's voice and facial expressions.

[1447] For example, if a user displays expressions of anger or impatience, the emotion engine recognizes this as "stress."

[1448] Terminal: Sends the input data and recognized emotion information as a request to the server.

[1449] 2. Collection of real-time traffic information

[1450] Server: Receives requests from users and verifies the origin and destination, as well as the selected options and sentiment information.

[1451] Server: Accesses traffic information providers to obtain real-time traffic information. This information includes traffic signal timing, railway crossing opening and closing information, traffic congestion status, road construction and accident information, etc.

[1452] Server: The acquired traffic information is temporarily stored in the database.

[1453] 3. Calculating square roots

[1454] Server: Applies a route calculation algorithm based on stored traffic information, user settings options, and sentiment information.

[1455] For example, if the system detects that a user is experiencing stress, it will select a route with smoother traffic flow and shorter waiting times.

[1456] Server: Generates multiple route options and evaluates the travel time, signal waiting time, and level crossing waiting time for each route.

[1457] Server: Compares the evaluation results of each route and selects the optimal route that best suits the user's options and sentiment information.

[1458] 4. Route provision

[1459] Server: Generates optimal route information and sends it to the user's terminal.

[1460] Terminal: Analyzes received route information and displays it on the navigation screen. Simultaneously, voice guidance is initiated, providing real-time directions to the user.

[1461] Specific example

[1462] Case 1: Optimal route selection using an emotion engine

[1463] 1. Terminal: User A enters "City Hall" as the destination and selects the "Prioritize narrow roads" option.

[1464] 2. Terminal: The emotion engine detects anxiety from user A's voice.

[1465] 3. Terminal: Sends the input data and recognized emotion information to the server.

[1466] 4. Server: Receives the request and verifies the origin and destination, options, and sentiment information.

[1467] 5. Server: Retrieves information such as signal change timing, level crossing opening / closing information, and traffic congestion information from traffic information providers and stores it in a database.

[1468] 6. Server: Calculates the optimal route based on the "Prioritize narrower paths" option and the server's emotional state (emotional information indicating anxiety).

[1469] 7. Server: Evaluate each route candidate and select the optimal route for user A.

[1470] 8. Server: Sends the optimal route to user A's terminal.

[1471] 9. Terminal: Displays the received route information and starts voice guidance.

[1472] Case 2: Route reselection based on an emotion engine

[1473] 1. Terminal: User B enters "station" as the destination and selects the "I want to get to my destination quickly" option.

[1474] 2. Device: The emotion engine detects stress from user B's facial expressions.

[1475] 3. Terminal: Sends the input data and recognized emotion information to the server.

[1476] 4. Server: Receives the request and verifies the origin and destination, options, and sentiment information.

[1477] 5. Server: Retrieves information such as signal change timing, level crossing opening / closing information, and traffic congestion information from traffic information providers and stores it in a database.

[1478] 6. Server: Calculates the optimal route based on the "I want to get to my destination quickly" option and stress levels.

[1479] 7. Server: Evaluates each route candidate and allows user B to select the optimal route.

[1480] 8. Server: Sends the optimal route to user B's terminal.

[1481] 9. Terminal: Displays the received route information and starts voice guidance.

[1482] The following describes the processing flow.

[1483] Step 1:

[1484] Terminal: The user launches the navigation application and enters the starting point (current location) and destination. The user selects options such as "prioritize narrow roads" or "get to destination quickly."

[1485] Step 2:

[1486] Device: The emotion engine is activated and recognizes emotions from the user's voice and facial expressions. For example, it captures the user's facial expressions through the camera and performs voice analysis using speech recognition technology.

[1487] Step 3:

[1488] Device: The emotion engine analyzes the emotional information it recognizes to determine whether the user is feeling "anxiety" or "stress."

[1489] Step 4:

[1490] Terminal: Sends the origin, destination, user-selected options, and sentiment information as a request to the server.

[1491] Step 5:

[1492] Server: Analyzes incoming requests to determine the user's origin, destination, options, and sentiment information.

[1493] Step 6:

[1494] Server: Accesses traffic information providers to obtain real-time traffic information such as signal change timing, level crossing opening and closing information, traffic congestion status, road construction and accident information.

[1495] Step 7:

[1496] Server: Temporarily stores acquired traffic information in a database.

[1497] Step 8:

[1498] Server: Applies route calculation algorithms based on stored traffic information, user selection options, and sentiment information.

[1499] Step 9:

[1500] Server: Generates multiple route options and evaluates the travel time, signal waiting time, and level crossing waiting time for each route.

[1501] Step 10:

[1502] Server: Compares the evaluation results of each route and selects the optimal route, taking into account the "prioritize narrow roads" option and the user's sense of urgency.

[1503] Step 11:

[1504] Server: Creates optimal route information and sends it to the user's terminal.

[1505] Step 12:

[1506] Terminal: Analyzes received route information and displays it on the navigation screen. Also initiates corresponding voice guidance.

[1507] Step 13:

[1508] Terminal: The user begins moving towards their destination.

[1509] Step 14:

[1510] Terminal: While on the move, it continuously monitors the user's emotional information and sends updates to the server as needed.

[1511] Step 15:

[1512] Server: Based on real-time traffic information and updated user sentiment data, it recalculates the optimal route and reroutes as needed.

[1513] Step 16:

[1514] Terminal: Receives new route information and updates the navigation screen. Performs a series of operations continuously until the user reaches their destination.

[1515] (Example 2)

[1516] 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".

[1517] Conventional navigation systems have the problem of failing to alleviate user stress and anxiety because they provide route guidance without considering the user's emotional state. Furthermore, route calculations based solely on real-time traffic information have the challenge of not being able to flexibly respond to individual user needs (for example, wanting to choose a quiet route or wanting to reach the destination quickly).

[1518] 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.

[1519] In this invention, the server includes means for the user to input a starting point and destination, means for collecting real-time traffic information based on options specified by the user, means for calculating an optimal route using the collected traffic information and the user's emotional information, means for transmitting the calculated optimal route information to the user's terminal, and means for displaying and guiding the user's terminal to the route information received. This enables the provision of an optimal route according to the user's emotional state and flexible route guidance that reflects real-time traffic information and the user's individual needs.

[1520] The "starting point" refers to the location where the user begins their route to their current location or destination.

[1521] "Destination" refers to the place the user ultimately wants to reach.

[1522] "Options" refer to the conditions and settings that users prioritize in route guidance. For example, these include "I want to get to my destination quickly" or "Prioritize narrow roads."

[1523] "Real-time traffic information" refers to the most up-to-date information in time, such as current traffic conditions, traffic light change timings, railway crossing opening and closing information, traffic congestion status, road construction and accident information.

[1524] "Emotional information" refers to the emotional state analyzed from the user's voice, facial expressions, and other behaviors. Examples include stress, anxiety, and anger.

[1525] A "route calculation algorithm" refers to a method for calculating the optimal route based on collected traffic information, user settings, and sentiment information. Examples include the A algorithm and Dijkstra's algorithm.

[1526] "Terminal" refers to devices used by users, such as mobile phones, tablets, and car navigation systems.

[1527] A "server" refers to a central processing unit that processes requests sent by users, collects and analyzes necessary information, and sends the results to the user's terminal.

[1528] "Route information" refers to detailed data about the calculated route. This includes the route itself, estimated travel time, traffic light waiting times, railway crossing waiting times, etc.

[1529] This invention is a navigation system that collects and analyzes traffic information in real time based on user-specified options and emotional information, and provides the optimal route. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it enables more flexible route guidance tailored to the user's state.

[1530] First, the user launches the navigation application and enters their starting point (current location) and destination. The user can select options such as "prioritize narrow roads" or "get to destination quickly." The device has a built-in emotion engine that recognizes the user's emotions in real time from their voice and facial expressions. For example, if the user shows signs of anger or impatience, the emotion engine recognizes this as "stress."

[1531] Next, the terminal sends the entered data and recognized sentiment information as a request to the server. The server receives the request from the user and verifies the origin and destination, as well as the selected options and sentiment information. The server then accesses a traffic information provider (e.g., Google Maps API or Here API) to obtain real-time traffic information. This information includes traffic light change timings, railway crossing opening and closing information, traffic congestion, road construction and accident information, etc. The retrieved traffic information is temporarily stored in a database.

[1532] The server applies a route calculation algorithm based on stored traffic information, user settings options, and emotional information. For example, if the server detects that the user is stressed, it selects a route with smooth traffic flow and minimal waiting times. The server generates multiple route options and evaluates the travel time, traffic light waiting times, and railway crossing waiting times for each route. It compares the evaluation results of each route and selects the optimal route that best suits the user's options and emotional information.

[1533] Once the optimal route information is generated, the server sends it to the user's terminal. The terminal analyzes the received route information and displays it on the navigation screen. Simultaneously, voice guidance begins, providing instructions to the user in real time.

[1534] For example, suppose user A enters "City Hall" as their destination and selects the "Prioritize narrow roads" option. If the emotion engine detects impatience from user A's voice, the device sends this information to the server. The server receives the request and retrieves information such as traffic light timings, railway crossing opening / closing information, and traffic congestion information from a traffic information provider. Then, based on the "Prioritize narrow roads" option and the impatient emotion information, it calculates the optimal route and sends it to user A's device. The device displays the received route information and starts voice guidance.

[1535] As another example, suppose user B enters "station" as their destination and selects the "I want to get to my destination quickly" option. If the emotion engine detects stress from user B's facial expression, the terminal sends the entered data and the recognized emotion information to the server. The server receives the request and retrieves information such as traffic signal timing, level crossing opening / closing information, and traffic congestion information from a traffic information provider. It then calculates the optimal route based on the "I want to get to my destination quickly" option and stress emotion, and sends it to user B's terminal. The terminal displays the received route information and starts voice guidance.

[1536] (Example of a prompt message)

[1537] "Explain how, after the user enters their starting point and destination and selects an option, the emotion engine recognizes the user's emotions and calculates the optimal route."

[1538] "Please describe, in natural language, the processing flow of a navigation system that collects real-time traffic information and takes user sentiment into consideration."

[1539] This invention enables the provision of optimal routes according to the user's emotional state, allowing for flexible route guidance that reflects real-time traffic information and the user's individual needs. Furthermore, by combining it with an emotion engine, an improvement in the user experience can be expected.

[1540] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1541] Step 1:

[1542] The terminal launches the navigation application, and the user enters the starting point and destination. The user selects options such as "I want to get to the destination quickly" or "Prioritize narrow roads." The terminal receives the starting point, destination, and options as input. The terminal receives this input data and proceeds to the next step.

[1543] Step 2:

[1544] The device activates an emotion engine to recognize emotional information from the user's voice and facial expressions. Specifically, it uses the device's camera and microphone to capture facial expressions and voice, and a generative AI model analyzes this data. The user's voice and image data are provided to the emotion engine as input. The emotion engine analyzes this data and outputs emotional information, such as whether the user is feeling stressed.

[1545] Step 3:

[1546] The terminal sends collected origin, destination, options, and sentiment information to the server. As input, request data containing origin, destination, options, and sentiment information is sent from the terminal to the server. This data is transmitted via communication protocols such as HTTP or WebSocket.

[1547] Step 4:

[1548] The server analyzes the request data received from the terminal to confirm the origin and destination, as well as the selected options and sentiment information. The request data is provided to the server as input. The server analyzes this data and extracts the information necessary for route calculation.

[1549] Step 5:

[1550] The server sends API requests to traffic information providers to obtain real-time traffic information. Specifically, the server accesses APIs such as the Google Maps API and the Here API to collect traffic information. As input, API requests are sent from the server. As output, traffic information such as the timing of signal changes, railway crossing opening and closing information, traffic congestion status, road construction and accident information is returned to the server.

[1551] Step 6:

[1552] The server temporarily stores the traffic information it acquires in a database. Traffic information is provided to the server as input. The server stores this information in a database (e.g., Redis) so that it can be used in subsequent route calculations.

[1553] Step 7:

[1554] The server applies a route calculation algorithm based on stored traffic information, user settings options, and sentiment information. The server uses route calculation algorithms such as the A algorithm or Dijkstra's algorithm to calculate the optimal route. Traffic information, settings options, and sentiment information are provided to the server as input. Multiple route candidates are generated as output.

[1555] Step 8:

[1556] The server evaluates the generated route candidates and selects the optimal route that best suits the user's configuration options and sentiment information. Multiple route candidates are provided as input. The server evaluates these and selects the optimal route. The optimal route information is generated as output.

[1557] Step 9:

[1558] The server sends optimal route information to the user's terminal. The server receives optimal route information as input. The server sends this information to the terminal, which then receives it. HTTP or WebSocket are used as the communication protocol.

[1559] Step 10:

[1560] The terminal analyzes the route information it receives and displays it on the navigation screen. Furthermore, it initiates voice guidance, providing real-time instructions to the user. The terminal receives optimal route information as input. The terminal analyzes this information and provides visual and audio guidance.

[1561] (Application Example 2)

[1562] 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".

[1563] Traditional navigation systems provided optimal routes based on real-time traffic information, but they failed to consider the user's emotional state and lacked route guidance adapted to the user's mental condition. Therefore, they could not address psychological needs, such as when the user was anxious or wanted to relax, potentially leading to a lower satisfaction with the driving experience. Furthermore, there was a need for technology that could efficiently analyze the user's emotional state within a specific vehicle environment and provide appropriate navigation.

[1564] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes an emotion analysis means for recognizing the user's emotions, a means for collecting real-time traffic information based on options specified by the user, and a means for calculating the optimal route using the collected traffic information and emotion information. This makes it possible to provide route guidance that is appropriate to the user's emotional state.

[1565] "Means for users to input their starting point and destination" refers to an interface for users to input their current location and desired destination using electronic devices.

[1566] A "means of emotional analysis that recognizes user emotions" is a system that analyzes a user's facial expressions and voice to determine their emotional state in real time.

[1567] "Means for collecting real-time traffic information based on user-specified options" refers to a system for obtaining traffic conditions and event information from online databases, APIs, etc., according to the conditions selected by the user.

[1568] "Means for calculating the optimal route using collected traffic and sentiment information" refers to a system that uses algorithms to calculate the route that best suits the user's mental and physical needs, based on acquired traffic and sentiment data.

[1569] "Means for transmitting calculated optimal route information to the user's terminal" refers to a communication system for transferring information about the optimal route calculated on a server to the electronic device being used by the user.

[1570] "Means for displaying and guiding users through route information received by their device" refers to interfaces and software for visually and audibly displaying and guiding users through optimal route information on their device.

[1571] This invention relates to a navigation system that analyzes the user's emotional state and provides the optimal route based on real-time traffic information. This navigation system is particularly applicable to autonomous vehicles and enables flexible route guidance that responds to the user's psychological needs.

[1572] 1. System Overview

[1573] This system includes means for emotion analysis to recognize the user's emotions, means for collecting real-time traffic information, means for calculating the optimal route using the collected information, means for transmitting the calculation results to the user's terminal, and means for displaying and guiding the user through the received route information.

[1574] 2. Hardware and software to be used

[1575] hardware

[1576] Camera: Cameras mounted on the autonomous vehicle will be used to capture the user's facial expressions.

[1577] Microphone: The user's voice will be recorded using a microphone installed in the autonomous vehicle.

[1578] Central control terminal: Receives user input via an in-vehicle touchscreen display.

[1579] software

[1580] Emotion analysis engine: Uses Microsoft Azure's Face API and Google's Cloud Vision API to analyze the user's facial expressions and voice.

[1581] Real-time traffic information acquisition module: Uses TomTom and the Google Maps API to collect real-time traffic information.

[1582] Route calculation algorithm: Using algorithms such as Algorithm A, the optimal route is calculated based on collected traffic and sentiment information.

[1583] 3. Data calculation and processing

[1584] Emotion Recognition: The vehicle captures the user's face and voice using an in-car camera and microphone, and an emotion analysis engine performs real-time analysis. For example, if the user is anxious, the system prioritizes a smoother, shorter route to reduce their stress.

[1585] Traffic Information Gathering: Access a real-time traffic database to collect information such as traffic light change timings, railway crossing opening and closing information, traffic congestion status, road construction and accident information.

[1586] Route Calculation: Based on collected traffic information, user sentiment data, and selected options, the system calculates the optimal route. For example, if the user wants to relax, it might suggest a scenic route.

[1587] Route information transmission: The calculated optimal route information is transmitted to the central control terminal to provide information to the user.

[1588] 4. Specific Examples

[1589] The following are specific examples of how this system can be used.

[1590] Example 1:

[1591] The user gets into the self-driving vehicle and enters "park" as their destination. An emotion analysis engine detects impatience from the user's voice, and the system collects real-time traffic information. As a result, the optimal route with minimal traffic lights and congestion is calculated, and the self-driving system begins driving along that route.

[1592] Example 2:

[1593] The user enters "Shopping Mall" as their destination and selects "Prioritize scenic routes" as an option. The emotion analysis engine detects relaxation from the user's facial expressions and acquires traffic information. The system suggests a scenic route, and the vehicle begins driving along that route.

[1594] 5. Example of a prompt statement

[1595] The following is an example of a prompt message to input into a generative AI model.

[1596] Write Python code to calculate the optimal route based on current traffic conditions. Consider the user's sentiment and selection options. Sentiment information will be obtained from facial and speech recognition. Traffic data will be obtained from the Google Maps API. Use the A algorithm for route calculation.

[1597] In this way, an optimal navigation system that takes into account the user's psychological state and actual traffic conditions can be realized. This is expected to significantly improve the driving experience of autonomous vehicles.

[1598] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1599] Step 1:

[1600] The user enters the starting point and destination into the device.

[1601] The input data consists of the starting point (current location) and the destination. This input data is sent from the terminal to the server for use in the next processing step.

[1602] Step 2:

[1603] The device's camera and microphone are activated to recognize the user's emotions.

[1604] The input data used consists of video captured by the camera and audio recorded by the microphone. This data is analyzed in real time by an emotion analysis engine, and the user's emotional state (e.g., relaxed, anxious, stressed) is output. This emotional information is used in the next step.

[1605] Step 3:

[1606] The server collects real-time traffic information based on options specified by the user.

[1607] The input data used includes user-selected options (e.g., shortest travel time, scenic route) and real-time traffic data obtained from a traffic information API. This data includes, for example, traffic signal change timings, railway crossing opening / closing information, and traffic congestion information obtained from the API. This traffic information is used in the next step.

[1608] Step 4:

[1609] The server uses collected traffic and sentiment information to calculate the optimal route.

[1610] The input data used includes acquired traffic information, user sentiment information, and navigation options selected by the user. The server applies route calculation algorithms, such as the A algorithm, to this data to calculate the optimal route. The output is the calculated optimal route information.

[1611] Step 5:

[1612] The server sends the calculated optimal route information to the user's terminal.

[1613] The optimal route information is used as input data. The server sends this information to the terminal, and the information sent to the terminal is used in the next step.

[1614] Step 6:

[1615] The device displays and guides the user through route information it has received.

[1616] The optimal route information transmitted from the server is used as input data. The terminal analyzes this information and initiates visual navigation display and voice guidance. This allows the user to confirm the optimal route information while driving.

[1617] Through the processing steps described above, an optimal navigation system is realized based on the user's emotional state and traffic information. This provides a comfortable driving experience that meets the user's psychological needs.

[1618] 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.

[1619] 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.

[1620] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[1621] 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.

[1622] 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. In the upper and lower directions of the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. Also, the upper side of the concentric circles is where "pleasant" emotions are located, and the lower side is where "unpleasant" emotions are located. In this way, 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.

[1623] 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.

[1624] 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.

[1625] 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.

[1626] 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."

[1627] 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.

[1628] 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.

[1629] 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.

[1630] 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.

[1631] 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.

[1632] 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.

[1633] 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.

[1634] 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.

[1635] 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.

[1636] 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.

[1637] 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.

[1638] 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.

[1639] The following is further disclosed regarding the embodiments described above.

[1640] (Claim 1)

[1641] A means for the user to input the starting point and destination,

[1642] A means of collecting real-time traffic information based on options specified by the user,

[1643] A means of calculating the optimal route using collected traffic information,

[1644] A means of sending calculated optimal route information to the user's terminal,

[1645] A means for displaying and guiding the user through route information received by the user's device,

[1646] A system that includes this.

[1647] (Claim 2)

[1648] The system according to claim 1, which collects information on the timing of signal changes and the opening and closing of railroad crossings.

[1649] (Claim 3)

[1650] The system according to claim 1, which calculates a route that prioritizes narrow roads or a route that gets to the destination faster, based on the user's choice.

[1651] "Example 1"

[1652] (Claim 1)

[1653] A means for the user to input the starting point and destination,

[1654] A means of collecting real-time traffic information based on options specified by the user,

[1655] A means of calculating the optimal route using collected traffic information,

[1656] A means of sending calculated optimal route information to the user's terminal,

[1657] A means for displaying and guiding the user through route information received by the user's device,

[1658] A system that includes this.

[1659] (Claim 2)

[1660] The system according to claim 1, which collects information on the timing of signal changes and the opening and closing of railroad crossings.

[1661] (Claim 3)

[1662] The system according to claim 1, which calculates a route that prioritizes narrow roads or a route that gets to the destination faster, based on the user's choice.

[1663] (Claim 4)

[1664] A means of temporarily storing collected traffic information in a database,

[1665] A means of applying a root calculation algorithm based on saved data,

[1666] A means of selecting the optimal route based on the evaluation results,

[1667] The system according to claim 1, including the following:

[1668] "Application Example 1"

[1669] (Claim 1)

[1670] A means for the user to input the starting point and destination,

[1671] A means of collecting real-time traffic information based on options specified by the user,

[1672] A means for acquiring real-time traffic information from sensors in autonomous vehicles and from external traffic information providers,

[1673] A means for calculating the optimal route based on collected traffic information and user selection,

[1674] A means of providing the optimal route as visual and audio guidance,

[1675] A system that includes this.

[1676] (Claim 2)

[1677] The system according to claim 1, which collects information on the timing of signal changes and the opening and closing of railroad crossings.

[1678] (Claim 3)

[1679] The system according to claim 1, which calculates a route that prioritizes narrow roads or a route that gets to the destination faster, based on the user's choice.

[1680] "Example 2 of combining an emotion engine"

[1681] (Claim 1)

[1682] A means for the user to input the starting point and destination,

[1683] A means of collecting real-time traffic information based on options specified by the user,

[1684] A means for calculating the optimal route using collected traffic information and user sentiment information,

[1685] A means of sending calculated optimal route information to the user's terminal,

[1686] A means for displaying and guiding the user through route information received by the user's device,

[1687] A system that includes this.

[1688] (Claim 2)

[1689] The system according to claim 1, which collects information on the timing of signal changes and the opening and closing of railroad crossings.

[1690] (Claim 3)

[1691] The system according to claim 1, which calculates a route that prioritizes narrow roads or a route that gets to the destination faster, based on the user's choice.

[1692] (Claim 4)

[1693] The system according to claim 1, which analyzes the user's emotional information and selects the optimal route according to the user's emotional state.

[1694] "Application example 2 when combining with an emotional engine"

[1695] (Claim 1)

[1696] A means for the user to input the starting point and destination,

[1697] A means of analyzing user emotions,

[1698] A means of collecting real-time traffic information based on options specified by the user,

[1699] A means for calculating the optimal route using collected traffic and sentiment information,

[1700] A means of sending calculated optimal route information to the user's terminal,

[1701] A means for displaying and guiding the user through route information received by the user's device,

[1702] A system that includes this.

[1703] (Claim 2)

[1704] The system according to claim 1, which collects information on the timing of signal changes and the opening and closing of railroad crossings.

[1705] (Claim 3)

[1706] The system according to claim 1, which calculates a route that prioritizes narrow roads or a route that gets to the destination faster, based on the user's choice. [Explanation of symbols]

[1707] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for the user to input the starting point and destination, A means of collecting real-time traffic information based on options specified by the user, A means of calculating the optimal route using collected traffic information, A means of sending calculated optimal route information to the user's terminal, A means for displaying and guiding the user through route information received by the user's device, A system that includes this.

2. The system according to claim 1, which collects information on the timing of signal changes and the opening and closing of railroad crossings.

3. The system according to claim 1, which calculates a route that prioritizes narrow roads or a route that gets to the destination faster, based on the user's choice.

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