system

Abstract

We provide the system. [Solution] A database system that distributes information on areas with a high incidence of traffic accidents to vehicles, A monitoring means that monitors the surrounding situation using cameras and sensors mounted on the vehicle, A comparison means for matching the current location with information on areas with a high incidence of traffic accidents stored in internal memory, An announcement system to alert the driver when approaching the area, A control means for automatically reducing the speed of a vehicle in a nationally designated deceleration area, 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] 36% of traffic fatalities in 2022 are related to pedestrians, and preventing traffic accidents caused by vehicles is a social issue. Under such circumstances, there is a demand for realizing a system that mounts a high-precision recognition function on a vehicle to arouse attention and automatically decelerate in areas with frequent traffic accidents or areas where deceleration is required.

Means for Solving the Problems

[0005] The present invention includes a database means for distributing information on areas prone to traffic accidents to vehicles, a monitoring means for monitoring the surrounding conditions using cameras and sensors mounted on the vehicle, a comparison means for matching the current location with the information on areas prone to traffic accidents stored in internal memory, an announcement means for alerting the driver when approaching such an area, and a control means for automatically reducing the vehicle's speed in nationally designated deceleration zones. This system can supplement the driver's attention in areas prone to traffic accidents and deceleration zones, thereby preventing traffic accidents.

[0006] "Information on areas with a high incidence of traffic accidents" refers to information that indicates locations in specific areas where accidents frequently occur, based on past traffic accident data.

[0007] A "database means" is a system or device for systematically collecting, storing, retrieving, and providing specific information.

[0008] "Cameras and sensors" are devices used to detect and collect surrounding visual information and physical conditions as data.

[0009] "Monitoring means" refers to a system or device for continuously observing, recording, and analyzing the environment or situation.

[0010] "Internal memory" refers to an electronic storage device used to temporarily or permanently store digital data.

[0011] A "comparison means" is a system or device for comparing two or more pieces of data or information to determine whether they match or not.

[0012] "Current location" refers to the real-time location information of the vehicle obtained using position measurement technologies such as GPS.

[0013] An "announcement system" is a device that a system uses to provide information and instructions to the driver through voice or visual messages.

[0014] The "nationally designated speed reduction area" is an area designated by the nation for the purpose of reducing the speed of vehicles at specific locations for safe traffic.

[0015] The "control means" is a system or device for automatically performing vehicle operations (such as adjusting brakes and accelerators).

Brief Explanation of Drawings

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

Mode for Carrying Out the Invention

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

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

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

[0024] [First Embodiment]

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

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

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

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

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

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

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

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

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

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

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

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

[0037] This invention aims to prevent traffic accidents through a system installed in a vehicle, and a specific embodiment thereof will be described below.

[0038] System Configuration

[0039] server

[0040] 1. The server manages data on areas with a high incidence of traffic accidents and nationally designated speed reduction areas.

[0041] 2. The server collects the latest information from the traffic management center and distributes it to vehicles periodically.

[0042] 3. The server encrypts data using secure communication protocols to ensure security.

[0043] Terminal (car)

[0044] 1. The terminal monitors the surrounding environment in real time through cameras and sensors mounted on the vehicle.

[0045] 2. The device compares its current location with the traffic accident-prone area information stored in its internal memory.

[0046] 3. The terminal will use an announcement system to alert the driver when it approaches a specific area.

[0047] 4. The terminal automatically controls the brakes and accelerator to reduce the vehicle's speed in nationally designated deceleration zones.

[0048] User (driver)

[0049] 1. Users receive system instructions through the in-vehicle display or voice assistant.

[0050] 2. Users should follow the announcements and drive safely.

[0051] 3. The user will monitor the system's deceleration operation and perform appropriate driving maneuvers.

[0052] Program processing

[0053] server

[0054] The server receives the latest accident-prone area information from the traffic management center and distributes it to vehicles in bulk overnight. The distributed data is encrypted and delivered to vehicles securely.

[0055] Terminal (car)

[0056] The terminal stores data received from the server every night in its internal memory. While driving, the vehicle's cameras and sensors monitor the surrounding environment and compare the current location with information on accident-prone areas in real time. When approaching a specific area, the terminal notifies the driver with a voice announcement saying, "This is an area with a high incidence of accidents." Furthermore, if the vehicle enters a nationally designated deceleration zone, it automatically controls the brakes and accelerator to reduce speed.

[0057] User (driver)

[0058] The user checks notifications from the device via the in-car display or audio system. If a warning announcement is made, the user concentrates on driving and drives safely. When entering a nationally designated deceleration zone, the user continues to drive appropriately while monitoring the system's deceleration operation. The user recognizes that the system is automatically adjusting the vehicle's speed and continues driving with confidence.

[0059] Specific example

[0060] Server-side specific example

[0061] The server collects accident-prone area information, updated daily from the traffic management center, and distributes it to vehicles at night. This distribution is performed for all registered vehicles, and security is ensured through multiple security measures.

[0062] Specific examples on the terminal side

[0063] The device monitors the situation ahead using cameras and sensors while driving in urban areas, and notifies the driver via voice message, "This is an area prone to accidents," when approaching an area with a high incidence of traffic accidents. Furthermore, it automatically applies the brakes and slows down the vehicle when entering a government-designated deceleration zone near a highway exit.

[0064] User-side examples

[0065] Users listen to voice announcements from the system and drive with extra caution, especially in areas prone to traffic accidents. When entering a deceleration zone, the system automatically slows down the vehicle, allowing the user to continue driving safely.

[0066] In this way, by implementing the present invention, it is possible to prevent traffic accidents from occurring and to enable safe driving.

[0067] The following describes the processing flow.

[0068] Step 1: The server receives the latest information on areas with a high incidence of traffic accidents from the traffic management center.

[0069] Specifically, the server periodically accesses the traffic management center's database to download the latest information on accident-prone areas and nationally designated speed reduction areas.

[0070] Step 2: The server distributes the received data to the vehicles.

[0071] Specifically, data is encrypted and transmitted to the vehicle's terminal using a secure communication protocol at night.

[0072] Step 3: The terminal receives data delivered from the server and saves it to its internal memory.

[0073] Specifically, data is acquired using the vehicle's communication module and stored in storage.

[0074] Step 4: The device monitors its surroundings using cameras and sensors while in motion.

[0075] Specifically, it captures video of the area ahead and measures the distance to obstacles using sensors.

[0076] Step 5: The device obtains its current location.

[0077] Specifically, it uses a GPS module to acquire real-time location information and compares it with area information stored in internal memory.

[0078] Step 6: The device compares its current location with information on areas prone to traffic accidents.

[0079] Specifically, the system uses a matching algorithm to compare current location information obtained from GPS with a database of accident-prone areas.

[0080] Step 7: The terminal makes an announcement to the driver based on the matching results.

[0081] Specifically, it will notify users via voice announcement that "the area ahead is prone to traffic accidents."

[0082] Step 8: The terminal controls the brakes and accelerator when entering a nationally designated deceleration zone.

[0083] Specifically, it sends a deceleration command to the vehicle's ECU, activating the braking system to adjust the vehicle's speed.

[0084] Step 9: The user checks the announcement from the device and drives safely.

[0085] Specifically, continue driving while paying attention and following voice instructions.

[0086] Step 10: The user monitors the speed adjustment due to automatic deceleration and performs appropriate driving operations.

[0087] Specifically, the system will continue driving while monitoring speed adjustments in the deceleration area.

[0088] (Example 1)

[0089] 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."

[0090] Road accidents remain frequent, particularly in specific locations such as accident-prone areas and government-designated speed-reducing zones. Current systems and methods are insufficient to adequately reduce the risk of accidents. Furthermore, inadequate driver awareness campaigns highlight the need for effective accident prevention approaches.

[0091] 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.

[0092] In this invention, the server includes a database means for distributing information on areas prone to traffic accidents to vehicles, a monitoring means for monitoring the surrounding conditions using cameras and sensors mounted on the vehicle, a storage means for storing information on areas prone to traffic accidents received from the server every night in internal memory, a comparison means for comparing the information on areas prone to traffic accidents stored in internal memory with the current location, an announcement means for alerting the driver when approaching the area in question, and a control means for automatically reducing the vehicle's speed in nationally designated deceleration zones. As a result, warnings and speed adjustments are automatically performed in accident-prone areas and deceleration zones, making it possible to effectively prevent traffic accidents.

[0093] "Information on areas with a high incidence of traffic accidents" refers to data on locations in specific regions or on roads where traffic accidents have frequently occurred in the past.

[0094] A "database means" is a system or device that enables the collection, storage, and distribution of information on areas with a high incidence of traffic accidents to vehicles that require it.

[0095] A "camera" is a device that captures images of the area in front of and around a vehicle in real time, providing surveillance information.

[0096] A "sensor" is a device that measures the physical conditions around a vehicle, such as distance, speed, and position.

[0097] A "monitoring system" is a mechanism that uses cameras and sensors mounted on the vehicle to monitor the area around the vehicle in real time.

[0098] "Storage means" refers to a function or device that stores traffic accident-prone area information received from a server into internal memory.

[0099] The "comparison method" is a technology that compares the vehicle's current location with information on areas prone to traffic accidents stored in internal memory to determine if it is approaching a specific area.

[0100] An "announcement system" is a mechanism that alerts the driver via voice or display when approaching a specific area.

[0101] A "control system" is a mechanism that automatically operates the vehicle's brakes and accelerator to reduce its speed when it enters a nationally designated deceleration zone.

[0102] This invention is a system aimed at preventing traffic accidents, and through the cooperation of a server, a terminal installed in a vehicle, and the user using it, it supports safe driving in areas with a high incidence of traffic accidents and areas designated by the government as speed reduction zones.

[0103] server

[0104] The server collects the latest accident-prone area information from the traffic management center every night. This information includes GPS coordinates, accident frequency, and historical accident data. The collected data is encrypted using strong encryption technologies such as AES-256 and securely stored and transmitted. The server distributes this data to all registered vehicles in bulk. Distribution takes place at night, ensuring security.

[0105] Terminal (vehicle)

[0106] The terminal installed in the vehicle stores information on accident-prone areas received from a server at night in its internal memory. While driving, the terminal monitors the surrounding environment in real time using multiple cameras and sensors. The terminal compares the accident-prone area information stored in its internal memory with the current location and alerts the driver with a voice announcement when approaching a specific area. Furthermore, if the vehicle enters a nationally designated deceleration zone, the terminal automatically controls the brakes and accelerator to reduce the vehicle's speed.

[0107] As a concrete example, the device monitors the situation ahead using cameras and sensors while driving in urban areas, and when approaching an area prone to traffic accidents, it will notify the driver by voice, "This is an area where accidents frequently occur." Furthermore, when entering a deceleration zone near a highway exit, it will automatically apply the brakes to slow down the vehicle.

[0108] User (driver)

[0109] Users check notifications from their devices via the in-car display or audio system. When an announcement is made, they concentrate on driving and drive safely. When entering a nationally designated deceleration zone, they continue to drive appropriately while monitoring the system's deceleration actions. Users can drive with confidence knowing that the system is automatically adjusting the vehicle's speed.

[0110] Examples of prompts for generative AI models

[0111] The following is an example of a prompt message used to have a generative AI model suggest relevant data and new features.

[0112] Based on information on areas with a high incidence of traffic accidents, please propose a more accurate accident prevention alert system.

[0113] Please propose new features or improvements to the vehicle's automatic speed control system.

[0114] Please suggest ways to streamline the data collection process from the traffic management center.

[0115] In this way, the present invention can prevent traffic accidents and improve driving safety.

[0116] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0117] Program processing steps

[0118] Server processing steps

[0119] Step 1:

[0120] The server collects the latest accident-prone area information from the traffic management center at night. This information includes GPS data, accident rates, and historical accident data. The input is data from the traffic management center, and the output is the collected raw data. Data collection involves specific actions such as calling certain APIs to retrieve information.

[0121] Step 2:

[0122] The server encrypts the collected data using strong encryption techniques such as AES-256. The input is collected information on areas with a high incidence of traffic accidents, and the output is encrypted data. The encryption process involves specific actions to apply encryption algorithms to ensure security while maintaining data readability.

[0123] Step 3:

[0124] The server distributes encrypted data to all registered vehicles in a single batch. The input is encrypted data, and the output is the encrypted data sent to each vehicle. The distribution process includes specific actions to send data using the vehicle's network ID.

[0125] Terminal (vehicle) processing steps

[0126] Step 1:

[0127] The terminal stores information about areas prone to traffic accidents, received from the server at night, in its internal memory. The input is encrypted data from the server, and the output is the decrypted data stored in internal memory. This includes the specific actions of the terminal to decrypt the encrypted data and securely store it in internal memory.

[0128] Step 2:

[0129] The terminal monitors the surrounding environment in real time using cameras and sensors mounted on the vehicle while it is in motion. The input is real-time data from each camera and sensor, and the output is the analysis results of the area around the vehicle. The collection and analysis of sensor data specifically includes processing camera images and digitally analyzing sensor values.

[0130] Step 3:

[0131] The device compares its real-time current location with accident-prone area information stored in its internal memory. The input consists of current location data from the GPS module and accident-prone area information in internal memory, while the output is the comparison result. The comparison process involves applying an algorithm that matches the current location data with pre-stored area information.

[0132] Step 4:

[0133] When the vehicle enters a specific area, the terminal alerts the driver with a voice announcement. The input is comparison result data, and the output is a voice announcement. Specifically, the announcement information is generated from an audio file and played back through the vehicle's audio system.

[0134] Step 5:

[0135] When entering a nationally designated deceleration zone, the terminal automatically controls the brakes and accelerator to reduce the vehicle's speed. The input is the comparison result and speed information, and the output is the decelerated vehicle speed. Specifically, this involves sending commands to the engine control unit to perform the necessary braking and engine accelerator control.

[0136] User processing steps

[0137] Step 1:

[0138] Users check notifications from their devices through the in-car display and audio system. The input is the announcement from the device, and the output is the user's awareness and actions. For example, the display might show "Approaching accident-prone area," and this is also announced by voice.

[0139] Step 2:

[0140] When a warning announcement is made, the user concentrates on driving and drives safely. The input is the announcement information, and the output is the user's driving actions. Specifically, this involves performing driving actions such as reducing speed and paying attention to the surrounding conditions.

[0141] Step 3:

[0142] When entering a nationally designated deceleration zone, the user monitors the system's deceleration operation and continues to drive appropriately. Inputs are deceleration operations and information related to deceleration, while outputs are coordinated driving actions. Specifically, this includes actions such as steering and monitoring the surroundings while confirming the system's automatic deceleration.

[0143] (Application Example 1)

[0144] 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."

[0145] There is a need for a system that can promote safe driving and prevent traffic accidents by reliably informing drivers of accident-prone areas and government-designated speed-reducing zones. Conventional systems have limited real-time notification of accident-prone areas and notification functions that can be linked with multiple devices, making it difficult to improve safety for drivers and users of autonomous vehicles.

[0146] 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.

[0147] In this invention, the server includes a database means for distributing accident-prone area information to vehicles; a monitoring means for monitoring the surrounding situation using cameras and sensors mounted on the vehicle; a comparison means for matching the accident-prone area information stored in internal memory with the current location; an announcement means for alerting the driver when approaching the relevant area; a control means for automatically reducing the vehicle's speed in nationally designated deceleration areas; and a notification means for comparing the location information acquired by the monitoring means with the accident-prone area information in real time and providing visual and audible notifications in cooperation with smartphones and head-mounted displays. This enables real-time notification of accident-prone area information and visual and audible notifications on multiple devices.

[0148] A "database means" refers to a system device that has the function of managing and distributing information on areas with a high incidence of traffic accidents to vehicles.

[0149] "Monitoring means" refers to a system device that has the function of monitoring the surrounding situation in real time using cameras and sensors mounted on the vehicle.

[0150] The "comparison means" is a system device that has the function of comparing the current location of a vehicle with information on areas with a high incidence of traffic accidents stored in its internal memory.

[0151] An "announcement device" is a system device that has the function of alerting the driver when approaching the relevant area.

[0152] "Control means" refers to a system device that has the function of automatically reducing the speed of a vehicle in a nationally designated deceleration area.

[0153] The "notification means" is a system device that compares location information acquired by the monitoring means with accident-prone area information in real time and has the function of providing visual and audible notifications in cooperation with smartphones or head-mounted displays.

[0154] This invention aims to prevent traffic accidents through a system installed in a vehicle, and a specific embodiment thereof will be described below.

[0155] System Configuration

[0156] server

[0157] The server manages data on accident-prone areas and nationally designated speed reduction zones. It collects the latest information from traffic management centers and distributes it to vehicles regularly. Furthermore, data is encrypted using secure communication protocols to ensure security.

[0158] Terminal (car)

[0159] The device monitors the surrounding environment in real time through cameras and sensors mounted on the vehicle. It compares the current location with information on accident-prone areas stored in its internal memory and alerts the driver using announcements when approaching such areas. Furthermore, it automatically controls the brakes and accelerator to reduce the vehicle's speed in nationally designated deceleration zones. It also works in conjunction with smartphones and head-mounted displays to provide visual and audible notifications.

[0160] User (driver)

[0161] The user receives system instructions through the in-vehicle display and voice assistant. If alerts are received while driving, the user should drive safely. When entering a nationally designated deceleration zone, the user should monitor the system as it automatically adjusts the vehicle's speed and perform appropriate driving maneuvers.

[0162] Program processing

[0163] server

[0164] The server receives the latest accident-prone area information from the traffic management center and distributes it to vehicles in bulk overnight. The distributed data is encrypted and delivered to vehicles securely.

[0165] Terminal (car)

[0166] The device stores the latest data received from the server every night in its internal memory. While driving, the vehicle's cameras and sensors monitor the surrounding environment and compare the current location with information on accident-prone areas in real time. When approaching a specific area, the device notifies the driver with a voice announcement saying, "This is an area with a high incidence of accidents." In addition, when entering a nationally designated deceleration zone, it automatically applies the brakes and slows down the vehicle. Visual and audible notifications are also provided on smartphones and head-mounted displays.

[0167] User (driver)

[0168] The user checks notifications from the device via the in-car display or audio system. If a warning is issued, the user concentrates on driving and drives safely. When the system performs deceleration, the user monitors the system's operation and continues to drive appropriately.

[0169] Specific example

[0170] For example, if a vehicle's GPS sensor records its current location as "35.6895, 139.6917" while driving in an urban area, this information is compared to a list of accident-prone areas distributed from a server. If this location is within an accident-prone area, the vehicle's display will show "You are in an accident-prone area ahead. Please be careful," and an audio alert will be issued. Similar notifications will also be sent to smartphones and head-mounted displays.

[0171] Examples of prompts to input into a generative AI model

[0172] "Please describe the implementation of a driver alert system in accident-prone areas. Include a function that compares the driver's current location with accident-prone area information obtained from a server in real time and notifies the driver accordingly."

[0173] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0174] Step 1:

[0175] The server receives the latest information on areas with a high incidence of traffic accidents from the traffic management center. At this time, it obtains the data provided by the traffic management center via an API and stores the received data in the server's internal database. The input is the accident-prone area information from the traffic management center, and the output is the information stored in the server's database.

[0176] Step 2:

[0177] The server distributes the latest accident-prone area information to vehicles at a set time every night. It retrieves the latest information from its internal database and transmits it to the vehicles using an encrypted communication protocol. The input is accident-prone area information retrieved from the server's internal database, and the output is encrypted information transmitted to the vehicle's terminal.

[0178] Step 3:

[0179] The terminal stores accident-prone area information received from the server in its internal memory. It stores the received data in its internal memory every night and overrides it. The input is accident-prone area information sent from the server, and the output is the information stored in the terminal's internal memory.

[0180] Step 4:

[0181] The device acquires real-time information about the surrounding environment and current location from the vehicle's GPS sensor and camera. Inputs include data from the GPS sensor and camera, and outputs include current location information and surrounding environment data.

[0182] Step 5:

[0183] The device compares the acquired current location information with accident-prone area information stored in its internal memory in real time. For example, it determines whether the current location is within the radius of a registered accident-prone area. The input consists of real-time current location information and accident-prone area information stored in internal memory, and the output is the result of determining whether the user is approaching the relevant area.

[0184] Step 6:

[0185] The device provides visual and auditory alerts to the driver when approaching a designated area. It works in conjunction with smartphones and head-mounted displays to effectively alert the driver visually and aurally. The input is the detection result of the designated area, and the output is visual and auditory notifications.

[0186] Step 7:

[0187] The terminal automatically controls the brakes and accelerator to reduce the vehicle's speed when it enters a nationally designated deceleration zone. This is achieved in conjunction with the autonomous driving system. The input is the result of the vehicle entering the deceleration zone, and the output is the state in which the vehicle's speed has been reduced.

[0188] Step 8:

[0189] Users receive notifications from their devices via in-vehicle displays, audio systems, smartphones, and head-mounted displays. When alerts are issued, users receive visual and auditory information regarding safe driving and perform driving actions accordingly. The input is notification information from the device, and the output is appropriate driving actions performed with safe driving in mind.

[0190] The above steps will create a system that prevents traffic accidents in accident-prone areas. In addition, visual and audible notifications will alert drivers, enabling safer driving.

[0191] 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.

[0192] This invention aims to prevent traffic accidents through a system installed in a vehicle, and further incorporates an "emotion engine" that monitors the user's emotional state while driving and supports safe driving. Specific embodiments are described below.

[0193] System Configuration

[0194] server

[0195] 1. The server manages data on areas with a high incidence of traffic accidents and nationally designated speed reduction areas.

[0196] 2. The server collects the latest information from the traffic management center and distributes it to vehicles periodically.

[0197] 3. The server encrypts data using secure communication protocols to ensure security.

[0198] Terminal (car)

[0199] 1. The terminal monitors the surrounding environment in real time through cameras and sensors mounted on the vehicle.

[0200] 2. The device compares its current location with the traffic accident-prone area information stored in its internal memory.

[0201] 3. The terminal will use an announcement system to alert the driver when it approaches a specific area.

[0202] 4. The terminal automatically controls the brakes and accelerator to reduce the vehicle's speed in nationally designated deceleration zones.

[0203] 5. The device is equipped with an emotion engine that recognizes the user's emotions and analyzes the user's facial expressions and voice.

[0204] Emotional Engine

[0205] 1. The emotion engine collects the user's facial expressions and voice in real time through the camera and microphone.

[0206] 2. The emotion engine analyzes the collected data to identify the user's emotional state (e.g., tension, stress, relaxation).

[0207] 3. If necessary, the emotion engine sends emotion data to the device, and the device performs the corresponding action.

[0208] User (driver)

[0209] 1. Users receive system instructions through the in-vehicle display or voice assistant.

[0210] 2. Users should follow the announcements and drive safely.

[0211] 3. Based on notifications from the emotion engine, users will utilize relaxation content if necessary.

[0212] Program processing

[0213] server

[0214] The server receives the latest accident-prone area information from the traffic management center and distributes it to vehicles in bulk overnight. The distributed data is encrypted and delivered to vehicles securely.

[0215] Terminal (car)

[0216] The device stores data received from the server in its internal memory every night. While driving, the vehicle's cameras and sensors monitor the surrounding environment and compare the current location with information on accident-prone areas in real time. When approaching a specific area, the device notifies the driver with a voice announcement saying, "This is an area with a high incidence of accidents." Furthermore, if the vehicle enters a nationally designated deceleration zone, it automatically controls the brakes and accelerator to reduce speed. In addition, if the emotion engine detects that the user is feeling tense or stressed, it notifies the device to provide relaxation content.

[0217] Emotional Engine

[0218] The emotion engine collects the user's facial expressions and voice using the camera and microphone and analyzes them in real time. If it detects tension or stress, it sends the emotion data to the device and provides relaxation content.

[0219] User (driver)

[0220] Users check notifications from their devices via the in-car display and audio system. If a warning announcement is made, they concentrate on driving and drive safely. Furthermore, if relaxation content is provided by the emotional engine, they can use it to maintain an appropriate mental state.

[0221] Specific example

[0222] Server-side specific example

[0223] The server collects accident-prone area information, updated daily from the traffic management center, and distributes it to vehicles at night. This distribution is performed for all registered vehicles, and security is ensured through multiple security measures.

[0224] Specific examples on the terminal side

[0225] The device monitors the situation ahead using cameras and sensors while driving in urban areas, and notifies the driver via voice, "This is an area prone to accidents," when approaching an area with a high incidence of traffic accidents. Furthermore, it automatically applies the brakes and slows down the vehicle when entering a government-designated deceleration zone near a highway exit. Additionally, if the user is experiencing high levels of stress, a relaxation engine plays soothing music.

[0226] User-side examples

[0227] Users listen to voice announcements from the system and drive with extra caution, especially in areas with a high incidence of traffic accidents. Notifications from the emotion engine allow users to relax using relaxation content, enabling them to continue driving safely.

[0228] In this way, by implementing the present invention, it is possible not only to prevent traffic accidents and enable safe driving, but also to appropriately manage the user's mental state.

[0229] The following describes the processing flow.

[0230] Step 1: The server receives the latest information on areas with a high incidence of traffic accidents from the traffic management center.

[0231] Specifically, the server periodically accesses the traffic management center's database to download the latest information on accident-prone areas and nationally designated speed reduction areas.

[0232] Step 2: The server distributes the received data to the vehicles.

[0233] Specifically, data is encrypted and transmitted to the vehicle's terminal using a secure communication protocol at night.

[0234] Step 3: The terminal receives data delivered from the server and saves it to its internal memory.

[0235] Specifically, data is acquired using the vehicle's communication module and stored in storage.

[0236] Step 4: The terminal uses the vehicle's cameras and sensors to monitor the surrounding environment in real time.

[0237] Specifically, it captures video of the area ahead and measures the distance to obstacles using sensors.

[0238] Step 5: The device obtains its current location.

[0239] Specifically, it uses a GPS module to acquire real-time location information and compares it with area information stored in internal memory.

[0240] Step 6: The device compares its current location with information on areas prone to traffic accidents.

[0241] Specifically, the system uses a matching algorithm to compare current location information obtained from GPS with a database of accident-prone areas.

[0242] Step 7: The terminal makes an announcement to the driver based on the matching results.

[0243] Specifically, it will notify users via voice announcement that "the area ahead is prone to traffic accidents."

[0244] Step 8: The terminal controls the brakes and accelerator when entering a nationally designated deceleration zone.

[0245] Specifically, it sends a deceleration command to the vehicle's ECU, activating the braking system to adjust the vehicle's speed.

[0246] Step 9: The device monitors the user's emotions using an emotion engine.

[0247] Specifically, it collects and analyzes the user's facial expressions and voice through a camera and microphone.

[0248] Step 10: The emotion engine identifies the user's emotional state.

[0249] Specifically, the collected data is used to determine whether the user is tense, stressed, or relaxed.

[0250] Step 11: The device takes appropriate action based on the emotional data sent from the emotion engine.

[0251] Specifically, if a user is feeling tense or stressed, relaxation content (such as music or audio guides) will be provided.

[0252] Step 12: The user receives announcements and relaxation content from the device and is encouraged to drive safely.

[0253] Specifically, this involves continuing to drive while paying attention and following voice instructions, and using relaxation content to maintain an appropriate mental state.

[0254] (Example 2)

[0255] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0256] Traffic accidents are a serious problem in daily life, and effective measures to prevent them are needed. However, current traffic information systems have difficulty providing real-time information on road conditions and accident-prone areas, and accident prevention measures are not functioning adequately. Furthermore, technologies to appropriately manage drivers' emotional states and support safe driving are not yet fully established. The challenge is to improve this situation, reduce the occurrence of traffic accidents, and appropriately manage drivers' mental states.

[0257] The identification processing by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a database means for distributing traffic accident-prone area information to the vehicle, a monitoring means for monitoring the surrounding situation using a camera and detection device mounted on the vehicle, a comparison means for comparing the traffic accident-prone area information stored in the internal storage device with the current location, a notification means for alerting the driver when approaching the relevant area, a control means for automatically reducing the vehicle's speed in government-designated deceleration areas, and an emotion analysis means for monitoring the user's emotional state and providing relaxation content as needed. This reduces the risk of accidents in traffic accident-prone areas and government-designated deceleration areas, and enables safe driving by appropriately managing the driver's emotional state.

[0258] "Information on areas with a high incidence of traffic accidents" refers to information on areas where traffic accidents frequently occur, identified based on past statistical data and information from traffic management organizations.

[0259] "Database means" refers to a system or device for organizing, storing, and managing specific data, and in this invention, it has the function of distributing information on areas with a high incidence of traffic accidents and areas where speed reduction is required to vehicles.

[0260] A "shooting device" refers to hardware for capturing images, such as a camera or video camera, and in this invention, it is a device mounted on a vehicle and used to monitor the surrounding environment.

[0261] A "detection device" is hardware such as a sensor or radar that detects specific physical changes or situations, and in this invention, it is a device mounted on a vehicle and used to monitor the surrounding conditions.

[0262] "Monitoring means" refers to a system or function that uses imaging devices and detection devices to observe and record the surrounding situation in real time.

[0263] "Internal memory" refers to hardware used to permanently or temporarily store data in a computer or electronic device, and in this invention, it is a device for storing information such as traffic accident-prone areas.

[0264] "Comparison means" refers to a system or function for comparing current location information with data stored in internal memory.

[0265] "Notification means" refers to a system or function that provides drivers with specific information or warnings via voice or visual means.

[0266] "Control means" refers to functions or systems for automatically adjusting the vehicle's speed, particularly those that reduce the vehicle's speed in deceleration areas.

[0267] "Emotional analysis means" refers to a system or function that collects and analyzes the user's facial expressions and voice to identify their emotional state, and provides relaxation content as needed.

[0268] This invention aims to prevent traffic accidents through a system installed in a vehicle, and also incorporates an emotion analysis function that monitors the user's emotional state while driving and supports safe driving. A specific embodiment of this invention is described below.

[0269] System Configuration

[0270] server:

[0271] The server acquires data in real time from traffic management agencies and manages information on accident-prone areas and government-designated speed-reducing areas. Since the server encrypts this information at night before distributing it to vehicles, a high-performance server and encryption software are required. Typical hardware used would be a standard high-performance server (e.g., a high-performance server series). Software used would include data collection and encryption software (e.g., an encryption library).

[0272] Terminal (in-vehicle system):

[0273] The terminal is installed in the vehicle and monitors the surrounding environment in real time through cameras and sensors. Based on this, it compares the current location with information on areas with a high incidence of traffic accidents and alerts the driver with a voice announcement when approaching a specific area. The terminal also has a function to automatically control the brakes and accelerator to reduce speed when entering a government-designated deceleration zone. Furthermore, it collects the user's facial expressions and voice and transmits them to an emotion analysis engine. The hardware required includes an in-vehicle camera, sensors (e.g., a series of detection devices), and an in-vehicle computer (e.g., an in-vehicle computer series). The software used includes real-time data analysis software and voice announcement software (e.g., voice announcement software).

[0274] Emotion analysis engine:

[0275] The emotion analysis engine collects the user's facial expressions and voice in real time through the in-vehicle camera and microphone, and identifies the user's emotional state by analyzing this data. For example, it can detect tension and stress by analyzing facial muscle movements and voice tone, and transmit this information to the terminal to provide relaxation content. The hardware used includes a camera, microphone (e.g., a series of imaging devices), and an in-vehicle computer. Software required includes facial expression analysis software and voice analysis software (e.g., a voice analysis API).

[0276] User (driver):

[0277] Users receive instructions and notifications from their devices through the in-vehicle display and voice assistant. For example, they may receive notifications such as "This area is prone to accidents" or the playback of relaxation music, allowing them to concentrate on driving and drive safely.

[0278] Specific example

[0279] Server-side specific example:

[0280] The server obtains the accident-prone area information updated daily by the traffic management agency at night and securely distributes it to vehicles through AES-256 encryption. As a result, the vehicles can always receive the latest traffic information.

[0281] Terminal-side specific example:

[0282] While driving in the urban area, the terminal monitors the front situation with a camera and sensors, and when approaching an accident-prone area, it notifies with voice "There is an area with frequent accidents ahead". Also, when entering a government-designated deceleration area near the highway exit, it automatically brakes to decelerate the vehicle. Furthermore, when the user is feeling strong tension, relaxation music is played by the emotion analysis engine.

[0283] User-side specific example:

[0284] The user drives while paying special attention in the accident-prone area after listening to the voice announcement from the system. Based on the notification from the emotion analysis engine, the user can continue safe driving by using relaxation content to relax.

[0285] By implementing the present invention in this way, not only can the occurrence of traffic accidents be prevented in advance and safe driving be made possible, but also the mental state of the user can be appropriately managed.

[0286] The flow of the specific process in Example 2 will be described using FIG. 13.

[0287] Step 1: Receiving data from the traffic management agency

[0288] The server receives the latest accident-prone area information and government-designated deceleration area information from the traffic management agency. This data is usually provided in XML or JSON format.

[0289] Input: Latest data from traffic management authorities

[0290] Data processing: Parsing (analysis) XML / JSON data and extracting necessary information.

[0291] Output: Extracted information on areas with a high incidence of traffic accidents and areas where speed reduction is required.

[0292] Step 2: Encrypt and store data

[0293] The server stores the received data in an internal database and encrypts the data using AES-256 encryption.

[0294] Input: Extracted information on areas with a high incidence of traffic accidents and areas where speed reduction is required.

[0295] Data processing: Data encryption

[0296] Output: Encrypted information on areas with a high incidence of traffic accidents and areas requiring reduced speed is stored in an internal database.

[0297] Step 3: Data distribution to the vehicle

[0298] The server delivers encrypted data to vehicles overnight. A secure communication protocol (e.g., HTTPS) is used during delivery.

[0299] Input: Encrypted traffic accident-prone area information and speed reduction area information

[0300] Data processing: None

[0301] Output: Encrypted data delivered to the vehicle

[0302] Step 4: Receiving and storing data by the vehicle

[0303] The terminal receives the encrypted data sent from the server at night and stores it in the internal memory. It verifies the integrity of the data to check for any reception omissions or data corruption.

[0304] Input: Encrypted data distributed from the server

[0305] Data processing: Data integrity check and decryption

[0306] Output: Data stored in the internal memory

[0307] Step 5: Real-time monitoring of the surrounding situation

[0308] The terminal uses the cameras and sensors installed in the vehicle to monitor the surrounding situation in real time. Data is collected every second to measure the distance to the vehicles and obstacles ahead.

[0309] Input: Real-time data from the cameras and sensors

[0310] Data processing: Analysis of image and sensor data

[0311] Output: Analysis results of the surrounding situation

[0312] Step 6: Notification of accident-prone areas

[0313] The terminal compares the current position with the data in the internal memory and, when approaching an accident-prone area or a deceleration area, notifies the driver with an audio announcement "Ahead, there is an area with frequent accidents".

[0314] Input: Current position data, accident-prone area information in the internal memory

[0315] Data processing: Comparison of the current position and area information

[0316] Output: Audio notification to the driver

[0317] Step 7: Automatic deceleration control

[0318] The device automatically controls the brakes and accelerator when entering a government-designated deceleration zone, safely reducing the vehicle's speed.

[0319] Input: Current location data, internal memory deceleration area information

[0320] Data processing: Deceleration area detection and control signal generation.

[0321] Output: Vehicle deceleration control signal

[0322] Step 8: Monitoring the user's emotional state

[0323] The device uses an in-car camera and microphone to collect the user's facial expressions and voice in real time and transmit them to an emotion analysis engine.

[0324] Input: Real-time data from camera and microphone

[0325] Data processing: Collection and transmission of facial expression and voice data.

[0326] Output: Data sent to the emotion analysis engine

[0327] Step 9: Emotion Analysis

[0328] The emotion analysis engine analyzes the received data to identify the user's emotional state. For example, it analyzes facial muscle movements and voice tone.

[0329] Input: Facial expressions and audio data from the device.

[0330] Data processing: Data analysis

[0331] Output: Identified emotional state (e.g., tension, stress, relaxation)

[0332] Step 10: Determine the necessary actions

[0333] The emotion analysis engine determines the necessary action (e.g., playing relaxation music) based on the identified emotional state and notifies the device.

[0334] Input: Emotional state data from the analysis results

[0335] Data processing: Action decision algorithm

[0336] Output: Action instructions for the terminal

[0337] Step 11: System notifications and driving operations

[0338] Users receive notifications from their devices via the in-car display and audio system, enabling them to drive safely.

[0339] Input: Notifications from the device

[0340] Data processing: None

[0341] Output: Implementation of safe driving

[0342] Step 12: Use relaxation content

[0343] Based on notifications from the emotion analysis engine, users utilize relaxation content as needed to maintain an appropriate mental state.

[0344] Input: Relaxation content playback notification from emotion analysis engine

[0345] Data processing: None

[0346] Output: Use of relaxation content and stabilization of mental state

[0347] This clarifies the specific actions, inputs, and outputs performed at each processing step, making the overall system process easier to understand.

[0348] (Application Example 2)

[0349] 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".

[0350] Conventional autonomous driving and driver assistance systems primarily aimed to ensure safety in accident-prone areas and speed-reducing zones, but they lacked sufficient measures to address the driver's emotional state. Despite the known fact that tension and stress negatively impact driving, there was a lack of methods to address these emotions. As a result, the risk of accidents increased, hindering safe driving. This invention aims to solve these problems and improve driver safety and comfort.

[0351] In Application Example 2, the identification processing by the identification processing unit 290 of the data processing device 12 is realized by the following means. In this invention, the server includes a database means for distributing traffic accident-prone area information to the vehicle, a monitoring means for monitoring the surrounding situation using cameras and sensors mounted on the vehicle, a comparison means for comparing the traffic accident-prone area information stored in internal memory with the current location, an announcement means for alerting the driver when approaching the relevant area, a control means for automatically reducing the vehicle's speed in nationally designated deceleration areas, an emotion engine for collecting and analyzing the user's facial expressions and voice in real time, and a means for providing relaxation content when it is detected that the user's emotional state is tension or stress. This not only prevents traffic accidents but also reduces the driver's mental stress, enabling safer and more comfortable driving.

[0352] "Information on areas with a high incidence of traffic accidents" refers to data on areas where traffic accidents have occurred frequently in the past.

[0353] A "database system" is a system that organizes and stores information, making it available for retrieval as needed.

[0354] "Cameras and sensors" are devices that acquire visual information and environmental data from the surroundings.

[0355] "Monitoring means" refers to the function of checking the surrounding situation in real time using cameras and sensors.

[0356] The "comparison means" is a function that compares the current location of the vehicle with information stored in advance.

[0357] An "announcement system" is a device that uses voice to convey important information to the driver.

[0358] A "control system" is a function that automatically adjusts the vehicle's speed and operation under specific conditions.

[0359] An "emotion engine" is a system that analyzes a user's emotional state based on their facial expressions and voice.

[0360] "Relaxation content" refers to content such as music and videos provided to reduce users' tension and stress.

[0361] System Configuration

[0362] Server side

[0363] The server manages information on areas with a high incidence of traffic accidents and receives the latest information from the traffic management center. This information is periodically distributed to connected vehicles using an encrypted and secure communication protocol. The server works in conjunction with the traffic information database to collect and distribute data.

[0364] Vehicle terminal side

[0365] The vehicle terminal monitors the surrounding environment through cameras and various sensors built into the vehicle. Its internal memory stores information on accident-prone areas and nationally designated deceleration zones received from the server, and it compares this information with the vehicle's current location.

[0366] When approaching a specific area, the system alerts the driver via the in-car display and voice assistant. Furthermore, it includes a function that automatically controls the vehicle's speed when entering a deceleration zone.

[0367] Emotional Engine

[0368] The emotion engine collects and analyzes the driver's facial expressions and voice in real time through cameras and microphones installed in the vehicle. If the system determines that the driver is experiencing tension or stress, the emotion engine sends emotional data to the device, and relaxation content is provided. This relaxation content, including music and videos, is designed to stabilize the driver's mental state.

[0369] Specific example

[0370] For example, if a vehicle is driving through an urban area and approaches an area prone to frequent traffic accidents, the terminal will announce, "This is an area where accidents frequently occur." Also, when entering a government-designated deceleration zone near a highway exit, the terminal will automatically apply the brakes and reduce the vehicle's speed.

[0371] Furthermore, if the emotional engine detects that the driver is feeling tense or stressed, relaxation music will automatically play. In this way, the driver can relax while maintaining a focus on safe driving.

[0372] Example of a prompt

[0373] Please generate an audio announcement for when a driver approaches an area with a high incidence of traffic accidents. For example, it should include the following: "Warning: You are approaching an accident-prone area."

[0374] Additionally, if tension is detected from the driver's facial expressions captured by the camera, display the message "User stress detected. Relaxation content will be provided," and generate a prompt to play relaxation music.

[0375] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0376] Step 1:

[0377] The server receives information on accident-prone areas and nationally designated speed reduction areas from the traffic management center. The received data is encrypted and distributed to vehicles using a secure communication protocol. The input is data from the traffic management center, and the output is encrypted traffic information data.

[0378] Step 2:

[0379] The terminal receives traffic information data distributed from the server and stores it in its internal memory. The input is encrypted traffic information data from the server, and the output is the state of the data stored in the terminal's internal memory. Specifically, the terminal automatically connects to the server at night to download and store the data.

[0380] Step 3:

[0381] The camera and sensors mounted on the device monitor the surrounding environment in real time. Input is raw data from the camera and sensors, and output is analyzed data of the surrounding environment. Specifically, the camera captures image data, and the sensors collect environmental data.

[0382] Step 4:

[0383] The device compares the current location with accident-prone area information stored in its internal memory and alerts the driver with a voice announcement when approaching a specific area. Inputs are current location data from the built-in GPS and accident-prone area information from internal memory; output is a voice announcement. Specifically, it periodically compares the current location with the accident-prone area information.

[0384] Step 5:

[0385] When the terminal enters a nationally designated deceleration zone, it automatically controls the brakes and accelerator to reduce the vehicle's speed. Inputs include current location data from the built-in GPS and deceleration zone information stored in internal memory, while output is the decelerated vehicle status. Specifically, when the vehicle enters a deceleration zone, the speed control system activates.

[0386] Step 6:

[0387] The emotion engine collects the driver's facial expressions and voice in real time through cameras and microphones inside the vehicle and analyzes their emotional state. The input is facial and voice data from the cameras and microphones, and the output is the analyzed emotional state of the driver. Specifically, the collected data is analyzed using an algorithm to detect tension and stress.

[0388] Step 7:

[0389] When the emotion engine detects the driver's tension or stress, it notifies the device and provides relaxation content. The input is emotional state data from the emotion engine, and the output is the relaxation content to be played. Specifically, when stress is detected, the device plays pre-set relaxation music or video.

[0390] Step 8:

[0391] The user checks notifications from their device via the in-car display and audio system. Input is notification data from the device, and output is the user's actions (e.g., driving operations or relaxation). Specifically, the user performs driving operations according to voice announcements and uses relaxation content as needed.

[0392] 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.

[0393] 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.

[0394] 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.

[0395] [Second Embodiment]

[0396] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0397] 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.

[0398] 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).

[0399] 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.

[0400] 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.

[0401] 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).

[0402] 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.

[0403] 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.

[0404] 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.

[0405] 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.

[0406] 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.

[0407] 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".

[0408] This invention aims to prevent traffic accidents through a system installed in a vehicle, and a specific embodiment thereof will be described below.

[0409] System Configuration

[0410] server

[0411] 1. The server manages data on areas with a high incidence of traffic accidents and nationally designated speed reduction areas.

[0412] 2. The server collects the latest information from the traffic management center and distributes it to vehicles periodically.

[0413] 3. The server encrypts data using secure communication protocols to ensure security.

[0414] Terminal (car)

[0415] 1. The terminal monitors the surrounding environment in real time through cameras and sensors mounted on the vehicle.

[0416] 2. The device compares its current location with the traffic accident-prone area information stored in its internal memory.

[0417] 3. The terminal will use an announcement system to alert the driver when it approaches a specific area.

[0418] 4. The terminal automatically controls the brakes and accelerator to reduce the vehicle's speed in nationally designated deceleration zones.

[0419] User (driver)

[0420] 1. Users receive system instructions through the in-vehicle display or voice assistant.

[0421] 2. Users should follow the announcements and drive safely.

[0422] 3. The user will monitor the system's deceleration operation and perform appropriate driving maneuvers.

[0423] Program processing

[0424] server

[0425] The server receives the latest accident-prone area information from the traffic management center and distributes it to vehicles in bulk overnight. The distributed data is encrypted and delivered to vehicles securely.

[0426] Terminal (car)

[0427] The terminal stores data received from the server every night in its internal memory. While driving, the vehicle's cameras and sensors monitor the surrounding environment and compare the current location with information on accident-prone areas in real time. When approaching a specific area, the terminal notifies the driver with a voice announcement saying, "This is an area with a high incidence of accidents." Furthermore, if the vehicle enters a nationally designated deceleration zone, it automatically controls the brakes and accelerator to reduce speed.

[0428] User (driver)

[0429] The user checks notifications from the device via the in-car display or audio system. If a warning announcement is made, the user concentrates on driving and drives safely. When entering a nationally designated deceleration zone, the user continues to drive appropriately while monitoring the system's deceleration operation. The user recognizes that the system is automatically adjusting the vehicle's speed and continues driving with confidence.

[0430] Specific example

[0431] Server-side specific example

[0432] The server collects accident-prone area information, updated daily from the traffic management center, and distributes it to vehicles at night. This distribution is performed for all registered vehicles, and security is ensured through multiple security measures.

[0433] Specific examples on the terminal side

[0434] The device monitors the situation ahead using cameras and sensors while driving in urban areas, and notifies the driver via voice message, "This is an area prone to accidents," when approaching an area with a high incidence of traffic accidents. Furthermore, it automatically applies the brakes and slows down the vehicle when entering a government-designated deceleration zone near a highway exit.

[0435] User-side examples

[0436] Users listen to voice announcements from the system and drive with extra caution, especially in areas prone to traffic accidents. When entering a deceleration zone, the system automatically slows down the vehicle, allowing the user to continue driving safely.

[0437] In this way, by implementing the present invention, it is possible to prevent traffic accidents from occurring and to enable safe driving.

[0438] The following describes the processing flow.

[0439] Step 1: The server receives the latest information on areas with a high incidence of traffic accidents from the traffic management center.

[0440] Specifically, the server periodically accesses the traffic management center's database to download the latest information on accident-prone areas and nationally designated speed reduction areas.

[0441] Step 2: The server distributes the received data to the vehicles.

[0442] Specifically, data is encrypted and transmitted to the vehicle's terminal using a secure communication protocol at night.

[0443] Step 3: The terminal receives data delivered from the server and saves it to its internal memory.

[0444] Specifically, data is acquired using the vehicle's communication module and stored in storage.

[0445] Step 4: The device monitors its surroundings using cameras and sensors while in motion.

[0446] Specifically, it captures video of the area ahead and measures the distance to obstacles using sensors.

[0447] Step 5: The device obtains its current location.

[0448] Specifically, it uses a GPS module to acquire real-time location information and compares it with area information stored in internal memory.

[0449] Step 6: The device compares its current location with information on areas prone to traffic accidents.

[0450] Specifically, the system uses a matching algorithm to compare current location information obtained from GPS with a database of accident-prone areas.

[0451] Step 7: The terminal makes an announcement to the driver based on the matching results.

[0452] Specifically, it will notify users via voice announcement that "the area ahead is prone to traffic accidents."

[0453] Step 8: The terminal controls the brakes and accelerator when entering a nationally designated deceleration zone.

[0454] Specifically, it sends a deceleration command to the vehicle's ECU, activating the braking system to adjust the vehicle's speed.

[0455] Step 9: The user checks the announcement from the device and drives safely.

[0456] Specifically, continue driving while paying attention and following voice instructions.

[0457] Step 10: The user monitors the speed adjustment due to automatic deceleration and performs appropriate driving operations.

[0458] Specifically, the system will continue driving while monitoring speed adjustments in the deceleration area.

[0459] (Example 1)

[0460] 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".

[0461] Road accidents remain frequent, particularly in specific locations such as accident-prone areas and government-designated speed-reducing zones. Current systems and methods are insufficient to adequately reduce the risk of accidents. Furthermore, inadequate driver awareness campaigns highlight the need for effective accident prevention approaches.

[0462] 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.

[0463] In this invention, the server includes a database means for distributing information on areas prone to traffic accidents to vehicles, a monitoring means for monitoring the surrounding conditions using cameras and sensors mounted on the vehicle, a storage means for storing information on areas prone to traffic accidents received from the server every night in internal memory, a comparison means for comparing the information on areas prone to traffic accidents stored in internal memory with the current location, an announcement means for alerting the driver when approaching the area in question, and a control means for automatically reducing the vehicle's speed in nationally designated deceleration zones. As a result, warnings and speed adjustments are automatically performed in accident-prone areas and deceleration zones, making it possible to effectively prevent traffic accidents.

[0464] "Information on areas with a high incidence of traffic accidents" refers to data on locations in specific regions or on roads where traffic accidents have frequently occurred in the past.

[0465] A "database means" is a system or device that enables the collection, storage, and distribution of information on areas with a high incidence of traffic accidents to vehicles that require it.

[0466] A "camera" is a device that captures images of the area in front of and around a vehicle in real time, providing surveillance information.

[0467] A "sensor" is a device that measures the physical conditions around a vehicle, such as distance, speed, and position.

[0468] A "monitoring system" is a mechanism that uses cameras and sensors mounted on the vehicle to monitor the area around the vehicle in real time.

[0469] "Storage means" refers to a function or device that stores traffic accident-prone area information received from a server into internal memory.

[0470] The "comparison method" is a technology that compares the vehicle's current location with information on areas prone to traffic accidents stored in internal memory to determine if it is approaching a specific area.

[0471] An "announcement system" is a mechanism that alerts the driver via voice or display when approaching a specific area.

[0472] A "control system" is a mechanism that automatically operates the vehicle's brakes and accelerator to reduce its speed when it enters a nationally designated deceleration zone.

[0473] This invention is a system aimed at preventing traffic accidents, and through the cooperation of a server, a terminal installed in a vehicle, and the user using it, it supports safe driving in areas with a high incidence of traffic accidents and areas designated by the government as speed reduction zones.

[0474] server

[0475] The server collects the latest accident-prone area information from the traffic management center every night. This information includes GPS coordinates, accident frequency, and historical accident data. The collected data is encrypted using strong encryption technologies such as AES-256 and securely stored and transmitted. The server distributes this data to all registered vehicles in bulk. Distribution takes place at night, ensuring security.

[0476] Terminal (vehicle)

[0477] The terminal installed in the vehicle stores information on accident-prone areas received from a server at night in its internal memory. While driving, the terminal monitors the surrounding environment in real time using multiple cameras and sensors. The terminal compares the accident-prone area information stored in its internal memory with the current location and alerts the driver with a voice announcement when approaching a specific area. Furthermore, if the vehicle enters a nationally designated deceleration zone, the terminal automatically controls the brakes and accelerator to reduce the vehicle's speed.

[0478] As a concrete example, the device monitors the situation ahead using cameras and sensors while driving in urban areas, and when approaching an area prone to traffic accidents, it will notify the driver by voice, "This is an area where accidents frequently occur." Furthermore, when entering a deceleration zone near a highway exit, it will automatically apply the brakes to slow down the vehicle.

[0479] User (driver)

[0480] Users check notifications from their devices via the in-car display or audio system. When an announcement is made, they concentrate on driving and drive safely. When entering a nationally designated deceleration zone, they continue to drive appropriately while monitoring the system's deceleration actions. Users can drive with confidence knowing that the system is automatically adjusting the vehicle's speed.

[0481] Examples of prompts for generative AI models

[0482] The following is an example of a prompt message used to have a generative AI model suggest relevant data and new features.

[0483] Based on information on areas with a high incidence of traffic accidents, please propose a more accurate accident prevention alert system.

[0484] Please propose new features or improvements to the vehicle's automatic speed control system.

[0485] Please suggest ways to streamline the data collection process from the traffic management center.

[0486] In this way, the present invention can prevent traffic accidents and improve driving safety.

[0487] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0488] Program processing steps

[0489] Server processing steps

[0490] Step 1:

[0491] The server collects the latest accident-prone area information from the traffic management center at night. This information includes GPS data, accident rates, and historical accident data. The input is data from the traffic management center, and the output is the collected raw data. Data collection involves specific actions such as calling certain APIs to retrieve information.

[0492] Step 2:

[0493] The server encrypts the collected data using strong encryption techniques such as AES-256. The input is collected information on areas with a high incidence of traffic accidents, and the output is encrypted data. The encryption process involves specific actions to apply encryption algorithms to ensure security while maintaining data readability.

[0494] Step 3:

[0495] The server distributes encrypted data to all registered vehicles in a single batch. The input is encrypted data, and the output is the encrypted data sent to each vehicle. The distribution process includes specific actions to send data using the vehicle's network ID.

[0496] Terminal (vehicle) processing steps

[0497] Step 1:

[0498] The terminal stores information about areas prone to traffic accidents, received from the server at night, in its internal memory. The input is encrypted data from the server, and the output is the decrypted data stored in internal memory. This includes the specific actions of the terminal to decrypt the encrypted data and securely store it in internal memory.

[0499] Step 2:

[0500] The terminal monitors the surrounding environment in real time using cameras and sensors mounted on the vehicle while it is in motion. The input is real-time data from each camera and sensor, and the output is the analysis results of the area around the vehicle. The collection and analysis of sensor data specifically includes processing camera images and digitally analyzing sensor values.

[0501] Step 3:

[0502] The device compares its real-time current location with accident-prone area information stored in its internal memory. The input consists of current location data from the GPS module and accident-prone area information in internal memory, while the output is the comparison result. The comparison process involves applying an algorithm that matches the current location data with pre-stored area information.

[0503] Step 4:

[0504] When the vehicle enters a specific area, the terminal alerts the driver with a voice announcement. The input is comparison result data, and the output is a voice announcement. Specifically, the announcement information is generated from an audio file and played back through the vehicle's audio system.

[0505] Step 5:

[0506] When entering a nationally designated deceleration zone, the terminal automatically controls the brakes and accelerator to reduce the vehicle's speed. The input is the comparison result and speed information, and the output is the decelerated vehicle speed. Specifically, this involves sending commands to the engine control unit to perform the necessary braking and engine accelerator control.

[0507] User processing steps

[0508] Step 1:

[0509] Users check notifications from their devices through the in-car display and audio system. The input is the announcement from the device, and the output is the user's awareness and actions. For example, the display might show "Approaching accident-prone area," and this is also announced by voice.

[0510] Step 2:

[0511] When a warning announcement is made, the user concentrates on driving and drives safely. The input is the announcement information, and the output is the user's driving actions. Specifically, this involves performing driving actions such as reducing speed and paying attention to the surrounding conditions.

[0512] Step 3:

[0513] When entering a nationally designated deceleration zone, the user monitors the system's deceleration operation and continues to drive appropriately. Inputs are deceleration operations and information related to deceleration, while outputs are coordinated driving actions. Specifically, this includes actions such as steering and monitoring the surroundings while confirming the system's automatic deceleration.

[0514] (Application Example 1)

[0515] 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."

[0516] There is a need for a system that can promote safe driving and prevent traffic accidents by reliably informing drivers of accident-prone areas and government-designated speed-reducing zones. Conventional systems have limited real-time notification of accident-prone areas and notification functions that can be linked with multiple devices, making it difficult to improve safety for drivers and users of autonomous vehicles.

[0517] 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.

[0518] In this invention, the server includes a database means for distributing accident-prone area information to vehicles; a monitoring means for monitoring the surrounding situation using cameras and sensors mounted on the vehicle; a comparison means for matching the accident-prone area information stored in internal memory with the current location; an announcement means for alerting the driver when approaching the relevant area; a control means for automatically reducing the vehicle's speed in nationally designated deceleration areas; and a notification means for comparing the location information acquired by the monitoring means with the accident-prone area information in real time and providing visual and audible notifications in cooperation with smartphones and head-mounted displays. This enables real-time notification of accident-prone area information and visual and audible notifications on multiple devices.

[0519] A "database means" refers to a system device that has the function of managing and distributing information on areas with a high incidence of traffic accidents to vehicles.

[0520] "Monitoring means" refers to a system device that has the function of monitoring the surrounding situation in real time using cameras and sensors mounted on the vehicle.

[0521] The "comparison means" is a system device that has the function of comparing the current location of a vehicle with information on areas with a high incidence of traffic accidents stored in its internal memory.

[0522] An "announcement device" is a system device that has the function of alerting the driver when approaching the relevant area.

[0523] "Control means" refers to a system device that has the function of automatically reducing the speed of a vehicle in a nationally designated deceleration area.

[0524] The "notification means" is a system device that compares location information acquired by the monitoring means with accident-prone area information in real time and has the function of providing visual and audible notifications in cooperation with smartphones or head-mounted displays.

[0525] This invention aims to prevent traffic accidents through a system installed in a vehicle, and a specific embodiment thereof will be described below.

[0526] System Configuration

[0527] server

[0528] The server manages data on accident-prone areas and nationally designated speed reduction zones. It collects the latest information from traffic management centers and distributes it to vehicles regularly. Furthermore, data is encrypted using secure communication protocols to ensure security.

[0529] Terminal (car)

[0530] The device monitors the surrounding environment in real time through cameras and sensors mounted on the vehicle. It compares the current location with information on accident-prone areas stored in its internal memory and alerts the driver using announcements when approaching such areas. Furthermore, it automatically controls the brakes and accelerator to reduce the vehicle's speed in nationally designated deceleration zones. It also works in conjunction with smartphones and head-mounted displays to provide visual and audible notifications.

[0531] User (driver)

[0532] The user receives system instructions through the in-vehicle display and voice assistant. If alerts are received while driving, the user should drive safely. When entering a nationally designated deceleration zone, the user should monitor the system as it automatically adjusts the vehicle's speed and perform appropriate driving maneuvers.

[0533] Program processing

[0534] server

[0535] The server receives the latest accident-prone area information from the traffic management center and distributes it to vehicles in bulk overnight. The distributed data is encrypted and delivered to vehicles securely.

[0536] Terminal (car)

[0537] The device stores the latest data received from the server every night in its internal memory. While driving, the vehicle's cameras and sensors monitor the surrounding environment and compare the current location with information on accident-prone areas in real time. When approaching a specific area, the device notifies the driver with a voice announcement saying, "This is an area with a high incidence of accidents." In addition, when entering a nationally designated deceleration zone, it automatically applies the brakes and slows down the vehicle. Visual and audible notifications are also provided on smartphones and head-mounted displays.

[0538] User (driver)

[0539] The user checks notifications from the device via the in-car display or audio system. If a warning is issued, the user concentrates on driving and drives safely. When the system performs deceleration, the user monitors the system's operation and continues to drive appropriately.

[0540] Specific example

[0541] For example, if a vehicle's GPS sensor records its current location as "35.6895, 139.6917" while driving in an urban area, this information is compared to a list of accident-prone areas distributed from a server. If this location is within an accident-prone area, the vehicle's display will show "You are in an accident-prone area ahead. Please be careful," and an audio alert will be issued. Similar notifications will also be sent to smartphones and head-mounted displays.

[0542] Examples of prompts to input into a generative AI model

[0543] "Please describe the implementation of a driver alert system in accident-prone areas. Include a function that compares the driver's current location with accident-prone area information obtained from a server in real time and notifies the driver accordingly."

[0544] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0545] Step 1:

[0546] The server receives the latest information on areas with a high incidence of traffic accidents from the traffic management center. At this time, it obtains the data provided by the traffic management center via an API and stores the received data in the server's internal database. The input is the accident-prone area information from the traffic management center, and the output is the information stored in the server's database.

[0547] Step 2:

[0548] The server distributes the latest accident-prone area information to vehicles at a set time every night. It retrieves the latest information from its internal database and transmits it to the vehicles using an encrypted communication protocol. The input is accident-prone area information retrieved from the server's internal database, and the output is encrypted information transmitted to the vehicle's terminal.

[0549] Step 3:

[0550] The terminal stores accident-prone area information received from the server in its internal memory. It stores the received data in its internal memory every night and overrides it. The input is accident-prone area information sent from the server, and the output is the information stored in the terminal's internal memory.

[0551] Step 4:

[0552] The device acquires real-time information about the surrounding environment and current location from the vehicle's GPS sensor and camera. Inputs include data from the GPS sensor and camera, and outputs include current location information and surrounding environment data.

[0553] Step 5:

[0554] The device compares the acquired current location information with accident-prone area information stored in its internal memory in real time. For example, it determines whether the current location is within the radius of a registered accident-prone area. The input consists of real-time current location information and accident-prone area information stored in internal memory, and the output is the result of determining whether the user is approaching the relevant area.

[0555] Step 6:

[0556] The device provides visual and auditory alerts to the driver when approaching a designated area. It works in conjunction with smartphones and head-mounted displays to effectively alert the driver visually and aurally. The input is the detection result of the designated area, and the output is visual and auditory notifications.

[0557] Step 7:

[0558] The terminal automatically controls the brakes and accelerator to reduce the vehicle's speed when it enters a nationally designated deceleration zone. This is achieved in conjunction with the autonomous driving system. The input is the result of the vehicle entering the deceleration zone, and the output is the state in which the vehicle's speed has been reduced.

[0559] Step 8:

[0560] Users receive notifications from their devices via in-vehicle displays, audio systems, smartphones, and head-mounted displays. When alerts are issued, users receive visual and auditory information regarding safe driving and perform driving actions accordingly. The input is notification information from the device, and the output is appropriate driving actions performed with safe driving in mind.

[0561] The above steps will create a system that prevents traffic accidents in accident-prone areas. In addition, visual and audible notifications will alert drivers, enabling safer driving.

[0562] 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.

[0563] This invention aims to prevent traffic accidents through a system installed in a vehicle, and further incorporates an "emotion engine" that monitors the user's emotional state while driving and supports safe driving. Specific embodiments are described below.

[0564] System Configuration

[0565] server

[0566] 1. The server manages data on areas with a high incidence of traffic accidents and nationally designated speed reduction areas.

[0567] 2. The server collects the latest information from the traffic management center and distributes it to vehicles periodically.

[0568] 3. The server encrypts data using secure communication protocols to ensure security.

[0569] Terminal (car)

[0570] 1. The terminal monitors the surrounding environment in real time through cameras and sensors mounted on the vehicle.

[0571] 2. The device compares its current location with the traffic accident-prone area information stored in its internal memory.

[0572] 3. The terminal will use an announcement system to alert the driver when it approaches a specific area.

[0573] 4. The terminal automatically controls the brakes and accelerator to reduce the vehicle's speed in nationally designated deceleration zones.

[0574] 5. The device is equipped with an emotion engine that recognizes the user's emotions and analyzes the user's facial expressions and voice.

[0575] Emotional Engine

[0576] 1. The emotion engine collects the user's facial expressions and voice in real time through the camera and microphone.

[0577] 2. The emotion engine analyzes the collected data to identify the user's emotional state (e.g., tension, stress, relaxation).

[0578] 3. If necessary, the emotion engine sends emotion data to the device, and the device performs the corresponding action.

[0579] User (driver)

[0580] 1. Users receive system instructions through the in-vehicle display or voice assistant.

[0581] 2. Users should follow the announcements and drive safely.

[0582] 3. Based on notifications from the emotion engine, users will utilize relaxation content if necessary.

[0583] Program processing

[0584] server

[0585] The server receives the latest accident-prone area information from the traffic management center and distributes it to vehicles in bulk overnight. The distributed data is encrypted and delivered to vehicles securely.

[0586] Terminal (car)

[0587] The device stores data received from the server in its internal memory every night. While driving, the vehicle's cameras and sensors monitor the surrounding environment and compare the current location with information on accident-prone areas in real time. When approaching a specific area, the device notifies the driver with a voice announcement saying, "This is an area with a high incidence of accidents." Furthermore, if the vehicle enters a nationally designated deceleration zone, it automatically controls the brakes and accelerator to reduce speed. In addition, if the emotion engine detects that the user is feeling tense or stressed, it notifies the device to provide relaxation content.

[0588] Emotional Engine

[0589] The emotion engine collects the user's facial expressions and voice using the camera and microphone and analyzes them in real time. If it detects tension or stress, it sends the emotion data to the device and provides relaxation content.

[0590] User (driver)

[0591] Users check notifications from their devices via the in-car display and audio system. If a warning announcement is made, they concentrate on driving and drive safely. Furthermore, if relaxation content is provided by the emotional engine, they can use it to maintain an appropriate mental state.

[0592] Specific example

[0593] Server-side specific example

[0594] The server collects accident-prone area information, updated daily from the traffic management center, and distributes it to vehicles at night. This distribution is performed for all registered vehicles, and security is ensured through multiple security measures.

[0595] Specific examples on the terminal side

[0596] The device monitors the situation ahead using cameras and sensors while driving in urban areas, and notifies the driver via voice, "This is an area prone to accidents," when approaching an area with a high incidence of traffic accidents. Furthermore, it automatically applies the brakes and slows down the vehicle when entering a government-designated deceleration zone near a highway exit. Additionally, if the user is experiencing high levels of stress, a relaxation engine plays soothing music.

[0597] User-side examples

[0598] Users listen to voice announcements from the system and drive with extra caution, especially in areas with a high incidence of traffic accidents. Notifications from the emotion engine allow users to relax using relaxation content, enabling them to continue driving safely.

[0599] In this way, by implementing the present invention, it is possible not only to prevent traffic accidents and enable safe driving, but also to appropriately manage the user's mental state.

[0600] The following describes the processing flow.

[0601] Step 1: The server receives the latest information on areas with a high incidence of traffic accidents from the traffic management center.

[0602] Specifically, the server periodically accesses the traffic management center's database to download the latest information on accident-prone areas and nationally designated speed reduction areas.

[0603] Step 2: The server distributes the received data to the vehicles.

[0604] Specifically, data is encrypted and transmitted to the vehicle's terminal using a secure communication protocol at night.

[0605] Step 3: The terminal receives data delivered from the server and saves it to its internal memory.

[0606] Specifically, data is acquired using the vehicle's communication module and stored in storage.

[0607] Step 4: The terminal uses the vehicle's cameras and sensors to monitor the surrounding environment in real time.

[0608] Specifically, it captures video of the area ahead and measures the distance to obstacles using sensors.

[0609] Step 5: The device obtains its current location.

[0610] Specifically, it uses a GPS module to acquire real-time location information and compares it with area information stored in internal memory.

[0611] Step 6: The device compares its current location with information on areas prone to traffic accidents.

[0612] Specifically, the system uses a matching algorithm to compare current location information obtained from GPS with a database of accident-prone areas.

[0613] Step 7: The terminal makes an announcement to the driver based on the matching results.

[0614] Specifically, it will notify users via voice announcement that "the area ahead is prone to traffic accidents."

[0615] Step 8: The terminal controls the brakes and accelerator when entering a nationally designated deceleration zone.

[0616] Specifically, it sends a deceleration command to the vehicle's ECU, activating the braking system to adjust the vehicle's speed.

[0617] Step 9: The device monitors the user's emotions using an emotion engine.

[0618] Specifically, it collects and analyzes the user's facial expressions and voice through a camera and microphone.

[0619] Step 10: The emotion engine identifies the user's emotional state.

[0620] Specifically, the collected data is used to determine whether the user is tense, stressed, or relaxed.

[0621] Step 11: The device takes appropriate action based on the emotional data sent from the emotion engine.

[0622] Specifically, if a user is feeling tense or stressed, relaxation content (such as music or audio guides) will be provided.

[0623] Step 12: The user receives announcements and relaxation content from the device and is encouraged to drive safely.

[0624] Specifically, this involves continuing to drive while paying attention and following voice instructions, and using relaxation content to maintain an appropriate mental state.

[0625] (Example 2)

[0626] 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".

[0627] Traffic accidents are a serious problem in daily life, and effective measures to prevent them are needed. However, current traffic information systems have difficulty providing real-time information on road conditions and accident-prone areas, and accident prevention measures are not functioning adequately. Furthermore, technologies to appropriately manage drivers' emotional states and support safe driving are not yet fully established. The challenge is to improve this situation, reduce the occurrence of traffic accidents, and appropriately manage drivers' mental states.

[0628] The identification processing by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a database means for distributing traffic accident-prone area information to the vehicle, a monitoring means for monitoring the surrounding situation using a camera and detection device mounted on the vehicle, a comparison means for comparing the traffic accident-prone area information stored in the internal storage device with the current location, a notification means for alerting the driver when approaching the relevant area, a control means for automatically reducing the vehicle's speed in government-designated deceleration areas, and an emotion analysis means for monitoring the user's emotional state and providing relaxation content as needed. This reduces the risk of accidents in traffic accident-prone areas and government-designated deceleration areas, and enables safe driving by appropriately managing the driver's emotional state.

[0629] "Information on areas with a high incidence of traffic accidents" refers to information on areas where traffic accidents frequently occur, identified based on past statistical data and information from traffic management organizations.

[0630] "Database means" refers to a system or device for organizing, storing, and managing specific data, and in this invention, it has the function of distributing information on areas with a high incidence of traffic accidents and areas where speed reduction is required to vehicles.

[0631] A "shooting device" refers to hardware for capturing images, such as a camera or video camera, and in this invention, it is a device mounted on a vehicle and used to monitor the surrounding environment.

[0632] A "detection device" is hardware such as a sensor or radar that detects specific physical changes or situations, and in this invention, it is a device mounted on a vehicle and used to monitor the surrounding conditions.

[0633] "Monitoring means" refers to a system or function that uses imaging devices and detection devices to observe and record the surrounding situation in real time.

[0634] "Internal memory" refers to hardware used to permanently or temporarily store data in a computer or electronic device, and in this invention, it is a device for storing information such as traffic accident-prone areas.

[0635] "Comparison means" refers to a system or function for comparing current location information with data stored in internal memory.

[0636] "Notification means" refers to a system or function that provides drivers with specific information or warnings via voice or visual means.

[0637] "Control means" refers to functions or systems for automatically adjusting the vehicle's speed, particularly those that reduce the vehicle's speed in deceleration areas.

[0638] "Emotional analysis means" refers to a system or function that collects and analyzes the user's facial expressions and voice to identify their emotional state, and provides relaxation content as needed.

[0639] This invention aims to prevent traffic accidents through a system installed in a vehicle, and also incorporates an emotion analysis function that monitors the user's emotional state while driving and supports safe driving. A specific embodiment of this invention is described below.

[0640] System Configuration

[0641] server:

[0642] The server acquires data in real time from traffic management agencies and manages information on accident-prone areas and government-designated speed-reducing areas. Since the server encrypts this information at night before distributing it to vehicles, a high-performance server and encryption software are required. Typical hardware used would be a standard high-performance server (e.g., a high-performance server series). Software used would include data collection and encryption software (e.g., an encryption library).

[0643] Terminal (in-vehicle system):

[0644] The terminal is installed in the vehicle and monitors the surrounding environment in real time through cameras and sensors. Based on this, it compares the current location with information on areas with a high incidence of traffic accidents and alerts the driver with a voice announcement when approaching a specific area. The terminal also has a function to automatically control the brakes and accelerator to reduce speed when entering a government-designated deceleration zone. Furthermore, it collects the user's facial expressions and voice and transmits them to an emotion analysis engine. The hardware required includes an in-vehicle camera, sensors (e.g., a series of detection devices), and an in-vehicle computer (e.g., an in-vehicle computer series). The software used includes real-time data analysis software and voice announcement software (e.g., voice announcement software).

[0645] Emotion analysis engine:

[0646] The emotion analysis engine collects the user's facial expressions and voice in real time through the in-vehicle camera and microphone, and identifies the user's emotional state by analyzing this data. For example, it can detect tension and stress by analyzing facial muscle movements and voice tone, and transmit this information to the terminal to provide relaxation content. The hardware used includes a camera, microphone (e.g., a series of imaging devices), and an in-vehicle computer. Software required includes facial expression analysis software and voice analysis software (e.g., a voice analysis API).

[0647] User (driver):

[0648] Users receive instructions and notifications from their devices through the in-vehicle display and voice assistant. For example, they may receive notifications such as "This area is prone to accidents" or the playback of relaxation music, allowing them to concentrate on driving and drive safely.

[0649] Specific example

[0650] Server-side example:

[0651] The server retrieves daily updated information on accident-prone areas from traffic management agencies at night and securely distributes it to vehicles using AES-256 encryption. This ensures that vehicles always receive the latest traffic information.

[0652] Specific examples on the terminal side:

[0653] The device monitors the situation ahead using cameras and sensors while driving in urban areas, and notifies the driver via voice message, "This is an area prone to accidents," when approaching an area with a high incidence of traffic accidents. Furthermore, it automatically applies the brakes and slows down the vehicle when entering a government-designated deceleration zone near a highway exit. Additionally, if the user is experiencing high levels of stress, a mood analysis engine plays relaxation music.

[0654] User-side examples:

[0655] Users listen to voice announcements from the system and drive with extra caution, especially in areas with a high incidence of traffic accidents. Based on notifications from the emotion analysis engine, users can continue to drive safely by using relaxation content to relax.

[0656] In this way, by implementing the present invention, it is possible not only to prevent traffic accidents and enable safe driving, but also to appropriately manage the user's mental state.

[0657] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0658] Step 1: Receive data from traffic management authorities.

[0659] The server receives the latest information on accident-prone areas and government-designated speed-reducing areas from traffic management agencies. This data is usually provided in XML or JSON format.

[0660] Input: Latest data from traffic management authorities

[0661] Data processing: Parsing (analysis) XML / JSON data and extracting necessary information.

[0662] Output: Extracted information on areas with a high incidence of traffic accidents and areas where speed reduction is required.

[0663] Step 2: Encrypt and store data

[0664] The server stores the received data in an internal database and encrypts the data using AES-256 encryption.

[0665] Input: Extracted information on areas with a high incidence of traffic accidents and areas where speed reduction is required.

[0666] Data processing: Data encryption

[0667] Output: Encrypted information on areas with a high incidence of traffic accidents and areas requiring reduced speed is stored in an internal database.

[0668] Step 3: Data distribution to the vehicle

[0669] The server delivers encrypted data to vehicles overnight. A secure communication protocol (e.g., HTTPS) is used during delivery.

[0670] Input: Encrypted traffic accident-prone area information and speed reduction area information

[0671] Data processing: None

[0672] Output: Encrypted data delivered to the vehicle

[0673] Step 4: Receiving and storing data by the vehicle

[0674] The terminal receives encrypted data sent from the server overnight and stores it in its internal memory. It then verifies the integrity of the data and checks for any missed data or data corruption.

[0675] Input: Encrypted data delivered from the server

[0676] Data processing: Data integrity check and decryption

[0677] Output: Data stored in internal memory

[0678] Step 5: Real-time monitoring of the surrounding environment

[0679] The terminal uses cameras and sensors mounted on the vehicle to monitor the surrounding environment in real time. Data is collected every second to measure the distance to vehicles and obstacles ahead.

[0680] Input: Real-time data from cameras and sensors

[0681] Data processing: Analysis of image and sensor data

[0682] Output: Analysis results of the surrounding environment

[0683] Step 6: Notification of areas with a high incidence of traffic accidents

[0684] The device compares the current location with data in its internal memory, and if it approaches an area prone to traffic accidents or a slow-down zone, it notifies the driver with a voice announcement saying, "You are in an area prone to accidents ahead."

[0685] Input: Current location data, information on areas with a high incidence of traffic accidents stored in internal memory.

[0686] Data processing: Comparison of current location and area information

[0687] Output: Voice notification to the driver

[0688] Step 7: Automatic deceleration control

[0689] The device automatically controls the brakes and accelerator when entering a government-designated deceleration zone, safely reducing the vehicle's speed.

[0690] Input: Current location data, internal memory deceleration area information

[0691] Data processing: Deceleration area detection and control signal generation.

[0692] Output: Vehicle deceleration control signal

[0693] Step 8: Monitoring the user's emotional state

[0694] The device uses an in-car camera and microphone to collect the user's facial expressions and voice in real time and transmit them to an emotion analysis engine.

[0695] Input: Real-time data from camera and microphone

[0696] Data processing: Collection and transmission of facial expression and voice data.

[0697] Output: Data sent to the emotion analysis engine

[0698] Step 9: Emotion Analysis

[0699] The emotion analysis engine analyzes the received data to identify the user's emotional state. For example, it analyzes facial muscle movements and voice tone.

[0700] Input: Facial expressions and audio data from the device.

[0701] Data processing: Data analysis

[0702] Output: Identified emotional state (e.g., tension, stress, relaxation)

[0703] Step 10: Determine the necessary actions

[0704] The emotion analysis engine determines the necessary action (e.g., playing relaxation music) based on the identified emotional state and notifies the device.

[0705] Input: Emotional state data from the analysis results

[0706] Data processing: Action decision algorithm

[0707] Output: Action instructions for the terminal

[0708] Step 11: System notifications and driving operations

[0709] Users receive notifications from their devices via the in-car display and audio system, enabling them to drive safely.

[0710] Input: Notifications from the device

[0711] Data processing: None

[0712] Output: Implementation of safe driving

[0713] Step 12: Use relaxation content

[0714] Based on notifications from the emotion analysis engine, users utilize relaxation content as needed to maintain an appropriate mental state.

[0715] Input: Relaxation content playback notification from emotion analysis engine

[0716] Data processing: None

[0717] Output: Use of relaxation content and stabilization of mental state

[0718] This clarifies the specific actions, inputs, and outputs performed at each processing step, making the overall system process easier to understand.

[0719] (Application Example 2)

[0720] 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."

[0721] Conventional autonomous driving and driver assistance systems primarily aimed to ensure safety in accident-prone areas and speed-reducing zones, but they lacked sufficient measures to address the driver's emotional state. Despite the known fact that tension and stress negatively impact driving, there was a lack of methods to address these emotions. As a result, the risk of accidents increased, hindering safe driving. This invention aims to solve these problems and improve driver safety and comfort.

[0722] In Application Example 2, the identification processing by the identification processing unit 290 of the data processing device 12 is realized by the following means. In this invention, the server includes a database means for distributing traffic accident-prone area information to the vehicle, a monitoring means for monitoring the surrounding situation using cameras and sensors mounted on the vehicle, a comparison means for comparing the traffic accident-prone area information stored in internal memory with the current location, an announcement means for alerting the driver when approaching the relevant area, a control means for automatically reducing the vehicle's speed in nationally designated deceleration areas, an emotion engine for collecting and analyzing the user's facial expressions and voice in real time, and a means for providing relaxation content when it is detected that the user's emotional state is tension or stress. This not only prevents traffic accidents but also reduces the driver's mental stress, enabling safer and more comfortable driving.

[0723] "Information on areas with a high incidence of traffic accidents" refers to data on areas where traffic accidents have occurred frequently in the past.

[0724] A "database system" is a system that organizes and stores information, making it available for retrieval as needed.

[0725] "Cameras and sensors" are devices that acquire visual information and environmental data from the surroundings.

[0726] "Monitoring means" refers to the function of checking the surrounding situation in real time using cameras and sensors.

[0727] The "comparison means" is a function that compares the current location of the vehicle with information stored in advance.

[0728] An "announcement system" is a device that uses voice to convey important information to the driver.

[0729] A "control system" is a function that automatically adjusts the vehicle's speed and operation under specific conditions.

[0730] An "emotion engine" is a system that analyzes a user's emotional state based on their facial expressions and voice.

[0731] "Relaxation content" refers to content such as music and videos provided to reduce users' tension and stress.

[0732] System Configuration

[0733] Server side

[0734] The server manages information on areas with a high incidence of traffic accidents and receives the latest information from the traffic management center. This information is periodically distributed to connected vehicles using an encrypted and secure communication protocol. The server works in conjunction with the traffic information database to collect and distribute data.

[0735] Vehicle terminal side

[0736] The vehicle terminal monitors the surrounding environment through cameras and various sensors built into the vehicle. Its internal memory stores information on accident-prone areas and nationally designated deceleration areas received from the server, and it compares this information with the vehicle's current location.

[0737] When approaching a specific area, the system alerts the driver via the in-car display and voice assistant. Furthermore, it includes a function that automatically controls the vehicle's speed when entering a deceleration zone.

[0738] Emotional Engine

[0739] The emotion engine collects and analyzes the driver's facial expressions and voice in real time through cameras and microphones installed in the vehicle. If the system determines that the driver is experiencing tension or stress, the emotion engine sends emotional data to the device, and relaxation content is provided. This relaxation content, including music and videos, is designed to stabilize the driver's mental state.

[0740] Specific example

[0741] For example, if a vehicle is driving through an urban area and approaches an area prone to frequent traffic accidents, the terminal will announce, "This is an area where accidents frequently occur." Also, when entering a government-designated deceleration zone near a highway exit, the terminal will automatically apply the brakes and reduce the vehicle's speed.

[0742] Furthermore, if the emotional engine detects that the driver is feeling tense or stressed, relaxation music will automatically play. In this way, the driver can relax while maintaining a focus on safe driving.

[0743] Example of a prompt

[0744] Please generate an audio announcement for when a driver approaches an area with a high incidence of traffic accidents. For example, it should include the following: "Warning: You are approaching an accident-prone area."

[0745] Additionally, if tension is detected from the driver's facial expressions captured by the camera, display the message "User stress detected. Relaxation content will be provided," and generate a prompt to play relaxation music.

[0746] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0747] Step 1:

[0748] The server receives information on accident-prone areas and nationally designated speed reduction areas from the traffic management center. The received data is encrypted and distributed to vehicles using a secure communication protocol. The input is data from the traffic management center, and the output is encrypted traffic information data.

[0749] Step 2:

[0750] The terminal receives traffic information data distributed from the server and stores it in its internal memory. The input is encrypted traffic information data from the server, and the output is the state of the data stored in the terminal's internal memory. Specifically, the terminal automatically connects to the server at night to download and store the data.

[0751] Step 3:

[0752] The camera and sensors mounted on the device monitor the surrounding environment in real time. Input is raw data from the camera and sensors, and output is analyzed data of the surrounding environment. Specifically, the camera captures image data, and the sensors collect environmental data.

[0753] Step 4:

[0754] The device compares the current location with accident-prone area information stored in its internal memory and alerts the driver with a voice announcement when approaching a specific area. Inputs are current location data from the built-in GPS and accident-prone area information from internal memory; output is a voice announcement. Specifically, it periodically compares the current location with the accident-prone area information.

[0755] Step 5:

[0756] When the terminal enters a nationally designated deceleration zone, it automatically controls the brakes and accelerator to reduce the vehicle's speed. Inputs include current location data from the built-in GPS and deceleration zone information stored in internal memory, while output is the decelerated vehicle status. Specifically, when the vehicle enters a deceleration zone, the speed control system activates.

[0757] Step 6:

[0758] The emotion engine collects the driver's facial expressions and voice in real time through cameras and microphones inside the vehicle and analyzes their emotional state. The input is facial and voice data from the cameras and microphones, and the output is the analyzed emotional state of the driver. Specifically, the collected data is analyzed using an algorithm to detect tension and stress.

[0759] Step 7:

[0760] When the emotion engine detects the driver's tension or stress, it notifies the device and provides relaxation content. The input is emotional state data from the emotion engine, and the output is the relaxation content to be played. Specifically, when stress is detected, the device plays pre-set relaxation music or video.

[0761] Step 8:

[0762] The user checks notifications from their device via the in-car display and audio system. Input is notification data from the device, and output is the user's actions (e.g., driving operations or relaxation). Specifically, the user performs driving operations according to voice announcements and uses relaxation content as needed.

[0763] 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.

[0764] 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.

[0765] 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.

[0766] [Third Embodiment]

[0767] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0768] 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.

[0769] 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).

[0770] 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.

[0771] 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.

[0772] 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).

[0773] 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.

[0774] 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.

[0775] 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.

[0776] 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.

[0777] 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.

[0778] 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".

[0779] This invention aims to prevent traffic accidents through a system installed in a vehicle, and a specific embodiment thereof will be described below.

[0780] System Configuration

[0781] server

[0782] 1. The server manages data on areas with a high incidence of traffic accidents and nationally designated speed reduction areas.

[0783] 2. The server collects the latest information from the traffic management center and distributes it to vehicles periodically.

[0784] 3. The server encrypts data using secure communication protocols to ensure security.

[0785] Terminal (car)

[0786] 1. The terminal monitors the surrounding environment in real time through cameras and sensors mounted on the vehicle.

[0787] 2. The device compares its current location with the traffic accident-prone area information stored in its internal memory.

[0788] 3. The terminal will use an announcement system to alert the driver when it approaches a specific area.

[0789] 4. The terminal automatically controls the brakes and accelerator to reduce the vehicle's speed in nationally designated deceleration zones.

[0790] User (driver)

[0791] 1. Users receive system instructions through the in-vehicle display or voice assistant.

[0792] 2. Users should follow the announcements and drive safely.

[0793] 3. The user will monitor the system's deceleration operation and perform appropriate driving maneuvers.

[0794] Program processing

[0795] server

[0796] The server receives the latest accident-prone area information from the traffic management center and distributes it to vehicles in bulk overnight. The distributed data is encrypted and delivered to vehicles securely.

[0797] Terminal (car)

[0798] The terminal stores data received from the server every night in its internal memory. While driving, the vehicle's cameras and sensors monitor the surrounding environment and compare the current location with information on accident-prone areas in real time. When approaching a specific area, the terminal notifies the driver with a voice announcement saying, "This is an area with a high incidence of accidents." Furthermore, if the vehicle enters a nationally designated deceleration zone, it automatically controls the brakes and accelerator to reduce speed.

[0799] User (driver)

[0800] The user checks notifications from the device via the in-car display or audio system. If a warning announcement is made, the user concentrates on driving and drives safely. When entering a nationally designated deceleration zone, the user continues to drive appropriately while monitoring the system's deceleration operation. The user recognizes that the system is automatically adjusting the vehicle's speed and continues driving with confidence.

[0801] Specific example

[0802] Server-side specific example

[0803] The server collects accident-prone area information, updated daily from the traffic management center, and distributes it to vehicles at night. This distribution is performed for all registered vehicles, and security is ensured through multiple security measures.

[0804] Specific examples on the terminal side

[0805] The device monitors the situation ahead using cameras and sensors while driving in urban areas, and notifies the driver via voice message, "This is an area prone to accidents," when approaching an area with a high incidence of traffic accidents. Furthermore, it automatically applies the brakes and slows down the vehicle when entering a government-designated deceleration zone near a highway exit.

[0806] User-side examples

[0807] Users listen to voice announcements from the system and drive with extra caution, especially in areas prone to traffic accidents. When entering a deceleration zone, the system automatically slows down the vehicle, allowing the user to continue driving safely.

[0808] In this way, by implementing the present invention, it is possible to prevent traffic accidents from occurring and to enable safe driving.

[0809] The following describes the processing flow.

[0810] Step 1: The server receives the latest information on areas with a high incidence of traffic accidents from the traffic management center.

[0811] Specifically, the server periodically accesses the traffic management center's database to download the latest information on accident-prone areas and nationally designated speed reduction areas.

[0812] Step 2: The server distributes the received data to the vehicles.

[0813] Specifically, data is encrypted and transmitted to the vehicle's terminal using a secure communication protocol at night.

[0814] Step 3: The terminal receives data delivered from the server and saves it to its internal memory.

[0815] Specifically, data is acquired using the vehicle's communication module and stored in storage.

[0816] Step 4: The device monitors its surroundings using cameras and sensors while in motion.

[0817] Specifically, it captures video of the area ahead and measures the distance to obstacles using sensors.

[0818] Step 5: The device obtains its current location.

[0819] Specifically, it uses a GPS module to acquire real-time location information and compares it with area information stored in internal memory.

[0820] Step 6: The device compares its current location with information on areas prone to traffic accidents.

[0821] Specifically, the system uses a matching algorithm to compare current location information obtained from GPS with a database of accident-prone areas.

[0822] Step 7: The terminal makes an announcement to the driver based on the matching results.

[0823] Specifically, it will notify users via voice announcement that "the area ahead is prone to traffic accidents."

[0824] Step 8: The terminal controls the brakes and accelerator when entering a nationally designated deceleration zone.

[0825] Specifically, it sends a deceleration command to the vehicle's ECU, activating the braking system to adjust the vehicle's speed.

[0826] Step 9: The user checks the announcement from the device and drives safely.

[0827] Specifically, continue driving while paying attention and following voice instructions.

[0828] Step 10: The user monitors the speed adjustment due to automatic deceleration and performs appropriate driving operations.

[0829] Specifically, the system will continue driving while monitoring speed adjustments in the deceleration area.

[0830] (Example 1)

[0831] 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."

[0832] Road accidents remain frequent, particularly in specific locations such as accident-prone areas and government-designated speed-reducing zones. Current systems and methods are insufficient to adequately reduce the risk of accidents. Furthermore, inadequate driver awareness campaigns highlight the need for effective accident prevention approaches.

[0833] 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.

[0834] In this invention, the server includes a database means for distributing information on areas prone to traffic accidents to vehicles, a monitoring means for monitoring the surrounding conditions using cameras and sensors mounted on the vehicle, a storage means for storing information on areas prone to traffic accidents received from the server every night in internal memory, a comparison means for comparing the information on areas prone to traffic accidents stored in internal memory with the current location, an announcement means for alerting the driver when approaching the area in question, and a control means for automatically reducing the vehicle's speed in nationally designated deceleration zones. As a result, warnings and speed adjustments are automatically performed in accident-prone areas and deceleration zones, making it possible to effectively prevent traffic accidents.

[0835] "Information on areas with a high incidence of traffic accidents" refers to data on locations in specific regions or on roads where traffic accidents have frequently occurred in the past.

[0836] A "database means" is a system or device that enables the collection, storage, and distribution of information on areas with a high incidence of traffic accidents to vehicles that require it.

[0837] A "camera" is a device that captures images of the area in front of and around a vehicle in real time, providing surveillance information.

[0838] A "sensor" is a device that measures the physical conditions around a vehicle, such as distance, speed, and position.

[0839] A "monitoring system" is a mechanism that uses cameras and sensors mounted on the vehicle to monitor the area around the vehicle in real time.

[0840] "Storage means" refers to a function or device that stores traffic accident-prone area information received from a server into internal memory.

[0841] The "comparison method" is a technology that compares the vehicle's current location with information on areas prone to traffic accidents stored in internal memory to determine if it is approaching a specific area.

[0842] An "announcement system" is a mechanism that alerts the driver via voice or display when approaching a specific area.

[0843] A "control system" is a mechanism that automatically operates the vehicle's brakes and accelerator to reduce its speed when it enters a nationally designated deceleration zone.

[0844] This invention is a system aimed at preventing traffic accidents, and through the cooperation of a server, a terminal installed in a vehicle, and the user using it, it supports safe driving in areas with a high incidence of traffic accidents and areas designated by the government as speed reduction zones.

[0845] server

[0846] The server collects the latest accident-prone area information from the traffic management center every night. This information includes GPS coordinates, accident frequency, and historical accident data. The collected data is encrypted using strong encryption technologies such as AES-256 and securely stored and transmitted. The server distributes this data to all registered vehicles in bulk. Distribution takes place at night, ensuring security.

[0847] Terminal (vehicle)

[0848] The terminal installed in the vehicle stores information on accident-prone areas received from a server at night in its internal memory. While driving, the terminal monitors the surrounding environment in real time using multiple cameras and sensors. The terminal compares the accident-prone area information stored in its internal memory with the current location and alerts the driver with a voice announcement when approaching a specific area. Furthermore, if the vehicle enters a nationally designated deceleration zone, the terminal automatically controls the brakes and accelerator to reduce the vehicle's speed.

[0849] As a concrete example, the device monitors the situation ahead using cameras and sensors while driving in urban areas, and when approaching an area prone to traffic accidents, it will notify the driver by voice, "This is an area where accidents frequently occur." Furthermore, when entering a deceleration zone near a highway exit, it will automatically apply the brakes to slow down the vehicle.

[0850] User (driver)

[0851] Users check notifications from their devices via the in-car display or audio system. When an announcement is made, they concentrate on driving and drive safely. When entering a nationally designated deceleration zone, they continue to drive appropriately while monitoring the system's deceleration actions. Users can drive with confidence knowing that the system is automatically adjusting the vehicle's speed.

[0852] Examples of prompts for generative AI models

[0853] The following is an example of a prompt message used to have a generative AI model suggest relevant data and new features.

[0854] Based on information on areas with a high incidence of traffic accidents, please propose a more accurate accident prevention alert system.

[0855] Please propose new features or improvements to the vehicle's automatic speed control system.

[0856] Please suggest ways to streamline the data collection process from the traffic management center.

[0857] In this way, the present invention can prevent traffic accidents and improve driving safety.

[0858] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0859] Program processing steps

[0860] Server processing steps

[0861] Step 1:

[0862] The server collects the latest accident-prone area information from the traffic management center at night. This information includes GPS data, accident rates, and historical accident data. The input is data from the traffic management center, and the output is the collected raw data. Data collection involves specific actions such as calling certain APIs to retrieve information.

[0863] Step 2:

[0864] The server encrypts the collected data using strong encryption techniques such as AES-256. The input is collected information on areas with a high incidence of traffic accidents, and the output is encrypted data. The encryption process involves specific actions to apply encryption algorithms to ensure security while maintaining data readability.

[0865] Step 3:

[0866] The server distributes encrypted data to all registered vehicles in a single batch. The input is encrypted data, and the output is the encrypted data sent to each vehicle. The distribution process includes specific actions to send data using the vehicle's network ID.

[0867] Terminal (vehicle) processing steps

[0868] Step 1:

[0869] The terminal stores information about areas prone to traffic accidents, received from the server at night, in its internal memory. The input is encrypted data from the server, and the output is the decrypted data stored in internal memory. This includes the specific actions of the terminal to decrypt the encrypted data and securely store it in internal memory.

[0870] Step 2:

[0871] The terminal monitors the surrounding environment in real time using cameras and sensors mounted on the vehicle while it is in motion. The input is real-time data from each camera and sensor, and the output is the analysis results of the area around the vehicle. The collection and analysis of sensor data specifically includes processing camera images and digitally analyzing sensor values.

[0872] Step 3:

[0873] The device compares its real-time current location with accident-prone area information stored in its internal memory. The input consists of current location data from the GPS module and accident-prone area information in internal memory, while the output is the comparison result. The comparison process involves applying an algorithm that matches the current location data with pre-stored area information.

[0874] Step 4:

[0875] When the vehicle enters a specific area, the terminal alerts the driver with a voice announcement. The input is comparison result data, and the output is a voice announcement. Specifically, the announcement information is generated from an audio file and played back through the vehicle's audio system.

[0876] Step 5:

[0877] When entering a nationally designated deceleration zone, the terminal automatically controls the brakes and accelerator to reduce the vehicle's speed. The input is the comparison result and speed information, and the output is the decelerated vehicle speed. Specifically, this involves sending commands to the engine control unit to perform the necessary braking and engine accelerator control.

[0878] User processing steps

[0879] Step 1:

[0880] Users check notifications from their devices through the in-car display and audio system. The input is the announcement from the device, and the output is the user's awareness and actions. For example, the display might show "Approaching accident-prone area," and this is also announced by voice.

[0881] Step 2:

[0882] When a warning announcement is made, the user concentrates on driving and drives safely. The input is the announcement information, and the output is the user's driving actions. Specifically, this involves performing driving actions such as reducing speed and paying attention to the surrounding conditions.

[0883] Step 3:

[0884] When entering a nationally designated deceleration zone, the user monitors the system's deceleration operation and continues to drive appropriately. Inputs are deceleration operations and information related to deceleration, while outputs are coordinated driving actions. Specifically, this includes actions such as steering and monitoring the surroundings while confirming the system's automatic deceleration.

[0885] (Application Example 1)

[0886] 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."

[0887] There is a need for a system that can promote safe driving and prevent traffic accidents by reliably informing drivers of accident-prone areas and government-designated speed-reducing zones. Conventional systems have limited real-time notification of accident-prone areas and notification functions that can be linked with multiple devices, making it difficult to improve safety for drivers and users of autonomous vehicles.

[0888] 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.

[0889] In this invention, the server includes a database means for distributing accident-prone area information to vehicles; a monitoring means for monitoring the surrounding situation using cameras and sensors mounted on the vehicle; a comparison means for matching the accident-prone area information stored in internal memory with the current location; an announcement means for alerting the driver when approaching the relevant area; a control means for automatically reducing the vehicle's speed in nationally designated deceleration areas; and a notification means for comparing the location information acquired by the monitoring means with the accident-prone area information in real time and providing visual and audible notifications in cooperation with smartphones and head-mounted displays. This enables real-time notification of accident-prone area information and visual and audible notifications on multiple devices.

[0890] A "database means" refers to a system device that has the function of managing and distributing information on areas with a high incidence of traffic accidents to vehicles.

[0891] "Monitoring means" refers to a system device that has the function of monitoring the surrounding situation in real time using cameras and sensors mounted on the vehicle.

[0892] The "comparison means" is a system device that has the function of comparing the current location of a vehicle with information on areas with a high incidence of traffic accidents stored in its internal memory.

[0893] An "announcement device" is a system device that has the function of alerting the driver when approaching the relevant area.

[0894] "Control means" refers to a system device that has the function of automatically reducing the speed of a vehicle in a nationally designated deceleration area.

[0895] The "notification means" is a system device that compares location information acquired by the monitoring means with accident-prone area information in real time and has the function of providing visual and audible notifications in cooperation with smartphones or head-mounted displays.

[0896] This invention aims to prevent traffic accidents through a system installed in a vehicle, and a specific embodiment thereof will be described below.

[0897] System Configuration

[0898] server

[0899] The server manages data on accident-prone areas and nationally designated speed reduction zones. It collects the latest information from traffic management centers and distributes it to vehicles regularly. Furthermore, data is encrypted using secure communication protocols to ensure security.

[0900] Terminal (car)

[0901] The device monitors the surrounding environment in real time through cameras and sensors mounted on the vehicle. It compares the current location with information on accident-prone areas stored in its internal memory and alerts the driver using announcements when approaching such areas. Furthermore, it automatically controls the brakes and accelerator to reduce the vehicle's speed in nationally designated deceleration zones. It also works in conjunction with smartphones and head-mounted displays to provide visual and audible notifications.

[0902] User (driver)

[0903] The user receives system instructions through the in-vehicle display and voice assistant. If alerts are received while driving, the user should drive safely. When entering a nationally designated deceleration zone, the user should monitor the system as it automatically adjusts the vehicle's speed and perform appropriate driving maneuvers.

[0904] Program processing

[0905] server

[0906] The server receives the latest accident-prone area information from the traffic management center and distributes it to vehicles in bulk overnight. The distributed data is encrypted and delivered to vehicles securely.

[0907] Terminal (car)

[0908] The device stores the latest data received from the server every night in its internal memory. While driving, the vehicle's cameras and sensors monitor the surrounding environment and compare the current location with information on accident-prone areas in real time. When approaching a specific area, the device notifies the driver with a voice announcement saying, "This is an area with a high incidence of accidents." In addition, when entering a nationally designated deceleration zone, it automatically applies the brakes and slows down the vehicle. Visual and audible notifications are also provided on smartphones and head-mounted displays.

[0909] User (driver)

[0910] The user checks notifications from the device via the in-car display or audio system. If a warning is issued, the user concentrates on driving and drives safely. When the system performs deceleration, the user monitors the system's operation and continues to drive appropriately.

[0911] Specific example

[0912] For example, if a vehicle's GPS sensor records its current location as "35.6895, 139.6917" while driving in an urban area, this information is compared to a list of accident-prone areas distributed from a server. If this location is within an accident-prone area, the vehicle's display will show "You are in an accident-prone area ahead. Please be careful," and an audio alert will be issued. Similar notifications will also be sent to smartphones and head-mounted displays.

[0913] Examples of prompts to input into a generative AI model

[0914] "Please describe the implementation of a driver alert system in accident-prone areas. Include a function that compares the driver's current location with accident-prone area information obtained from a server in real time and notifies the driver accordingly."

[0915] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0916] Step 1:

[0917] The server receives the latest information on areas with a high incidence of traffic accidents from the traffic management center. At this time, it obtains the data provided by the traffic management center via an API and stores the received data in the server's internal database. The input is the accident-prone area information from the traffic management center, and the output is the information stored in the server's database.

[0918] Step 2:

[0919] The server distributes the latest accident-prone area information to vehicles at a set time every night. It retrieves the latest information from its internal database and transmits it to the vehicles using an encrypted communication protocol. The input is accident-prone area information retrieved from the server's internal database, and the output is encrypted information transmitted to the vehicle's terminal.

[0920] Step 3:

[0921] The terminal stores accident-prone area information received from the server in its internal memory. It stores the received data in its internal memory every night and overrides it. The input is accident-prone area information sent from the server, and the output is the information stored in the terminal's internal memory.

[0922] Step 4:

[0923] The device acquires real-time information about the surrounding environment and current location from the vehicle's GPS sensor and camera. Inputs include data from the GPS sensor and camera, and outputs include current location information and surrounding environment data.

[0924] Step 5:

[0925] The device compares the acquired current location information with accident-prone area information stored in its internal memory in real time. For example, it determines whether the current location is within the radius of a registered accident-prone area. The input consists of real-time current location information and accident-prone area information stored in internal memory, and the output is the result of determining whether the user is approaching the relevant area.

[0926] Step 6:

[0927] The device provides visual and auditory alerts to the driver when approaching a designated area. It works in conjunction with smartphones and head-mounted displays to effectively alert the driver visually and aurally. The input is the detection result of the designated area, and the output is visual and auditory notifications.

[0928] Step 7:

[0929] The terminal automatically controls the brakes and accelerator to reduce the vehicle's speed when it enters a nationally designated deceleration zone. This is achieved in conjunction with the autonomous driving system. The input is the result of the vehicle entering the deceleration zone, and the output is the state in which the vehicle's speed has been reduced.

[0930] Step 8:

[0931] Users receive notifications from their devices via in-vehicle displays, audio systems, smartphones, and head-mounted displays. When alerts are issued, users receive visual and auditory information regarding safe driving and perform driving actions accordingly. The input is notification information from the device, and the output is appropriate driving actions performed with safe driving in mind.

[0932] The above steps will create a system that prevents traffic accidents in accident-prone areas. In addition, visual and audible notifications will alert drivers, enabling safer driving.

[0933] 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.

[0934] This invention aims to prevent traffic accidents through a system installed in a vehicle, and further incorporates an "emotion engine" that monitors the user's emotional state while driving and supports safe driving. Specific embodiments are described below.

[0935] System Configuration

[0936] server

[0937] 1. The server manages data on areas with a high incidence of traffic accidents and nationally designated speed reduction areas.

[0938] 2. The server collects the latest information from the traffic management center and distributes it to vehicles periodically.

[0939] 3. The server encrypts data using secure communication protocols to ensure security.

[0940] Terminal (car)

[0941] 1. The terminal monitors the surrounding environment in real time through cameras and sensors mounted on the vehicle.

[0942] 2. The device compares its current location with the traffic accident-prone area information stored in its internal memory.

[0943] 3. The terminal will use an announcement system to alert the driver when it approaches a specific area.

[0944] 4. The terminal automatically controls the brakes and accelerator to reduce the vehicle's speed in nationally designated deceleration zones.

[0945] 5. The device is equipped with an emotion engine that recognizes the user's emotions and analyzes the user's facial expressions and voice.

[0946] Emotional Engine

[0947] 1. The emotion engine collects the user's facial expressions and voice in real time through the camera and microphone.

[0948] 2. The emotion engine analyzes the collected data to identify the user's emotional state (e.g., tension, stress, relaxation).

[0949] 3. If necessary, the emotion engine sends emotion data to the device, and the device performs the corresponding action.

[0950] User (driver)

[0951] 1. Users receive system instructions through the in-vehicle display or voice assistant.

[0952] 2. Users should follow the announcements and drive safely.

[0953] 3. Based on notifications from the emotion engine, users will utilize relaxation content if necessary.

[0954] Program processing

[0955] server

[0956] The server receives the latest accident-prone area information from the traffic management center and distributes it to vehicles in bulk overnight. The distributed data is encrypted and delivered to vehicles securely.

[0957] Terminal (car)

[0958] The device stores data received from the server in its internal memory every night. While driving, the vehicle's cameras and sensors monitor the surrounding environment and compare the current location with information on accident-prone areas in real time. When approaching a specific area, the device notifies the driver with a voice announcement saying, "This is an area with a high incidence of accidents." Furthermore, if the vehicle enters a nationally designated deceleration zone, it automatically controls the brakes and accelerator to reduce speed. In addition, if the emotion engine detects that the user is feeling tense or stressed, it notifies the device to provide relaxation content.

[0959] Emotional Engine

[0960] The emotion engine collects the user's facial expressions and voice using the camera and microphone and analyzes them in real time. If it detects tension or stress, it sends the emotion data to the device and provides relaxation content.

[0961] User (driver)

[0962] Users check notifications from their devices via the in-car display and audio system. If a warning announcement is made, they concentrate on driving and drive safely. Furthermore, if relaxation content is provided by the emotional engine, they can use it to maintain an appropriate mental state.

[0963] Specific example

[0964] Server-side specific example

[0965] The server collects accident-prone area information, updated daily from the traffic management center, and distributes it to vehicles at night. This distribution is performed for all registered vehicles, and security is ensured through multiple security measures.

[0966] Specific examples on the terminal side

[0967] The device monitors the situation ahead using cameras and sensors while driving in urban areas, and notifies the driver via voice, "This is an area prone to accidents," when approaching an area with a high incidence of traffic accidents. Furthermore, it automatically applies the brakes and slows down the vehicle when entering a government-designated deceleration zone near a highway exit. Additionally, if the user is experiencing high levels of stress, a relaxation engine plays soothing music.

[0968] User-side examples

[0969] Users listen to voice announcements from the system and drive with extra caution, especially in areas with a high incidence of traffic accidents. Notifications from the emotion engine allow users to relax using relaxation content, enabling them to continue driving safely.

[0970] In this way, by implementing the present invention, it is possible not only to prevent traffic accidents and enable safe driving, but also to appropriately manage the user's mental state.

[0971] The following describes the processing flow.

[0972] Step 1: The server receives the latest information on areas with a high incidence of traffic accidents from the traffic management center.

[0973] Specifically, the server periodically accesses the traffic management center's database to download the latest information on accident-prone areas and nationally designated speed reduction areas.

[0974] Step 2: The server distributes the received data to the vehicles.

[0975] Specifically, data is encrypted and transmitted to the vehicle's terminal using a secure communication protocol at night.

[0976] Step 3: The terminal receives data delivered from the server and saves it to its internal memory.

[0977] Specifically, data is acquired using the vehicle's communication module and stored in storage.

[0978] Step 4: The terminal uses the vehicle's cameras and sensors to monitor the surrounding environment in real time.

[0979] Specifically, it captures video of the area ahead and measures the distance to obstacles using sensors.

[0980] Step 5: The device obtains its current location.

[0981] Specifically, it uses a GPS module to acquire real-time location information and compares it with area information stored in internal memory.

[0982] Step 6: The device compares its current location with information on areas prone to traffic accidents.

[0983] Specifically, the system uses a matching algorithm to compare current location information obtained from GPS with a database of accident-prone areas.

[0984] Step 7: The terminal makes an announcement to the driver based on the matching results.

[0985] Specifically, it will notify users via voice announcement that "the area ahead is prone to traffic accidents."

[0986] Step 8: The terminal controls the brakes and accelerator when entering a nationally designated deceleration zone.

[0987] Specifically, it sends a deceleration command to the vehicle's ECU, activating the braking system to adjust the vehicle's speed.

[0988] Step 9: The device monitors the user's emotions using an emotion engine.

[0989] Specifically, it collects and analyzes the user's facial expressions and voice through a camera and microphone.

[0990] Step 10: The emotion engine identifies the user's emotional state.

[0991] Specifically, the collected data is used to determine whether the user is tense, stressed, or relaxed.

[0992] Step 11: The device takes appropriate action based on the emotional data sent from the emotion engine.

[0993] Specifically, if a user is feeling tense or stressed, relaxation content (such as music or audio guides) will be provided.

[0994] Step 12: The user receives announcements and relaxation content from the device and is encouraged to drive safely.

[0995] Specifically, this involves continuing to drive while paying attention and following voice instructions, and using relaxation content to maintain an appropriate mental state.

[0996] (Example 2)

[0997] 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."

[0998] Traffic accidents are a serious problem in daily life, and effective measures to prevent them are needed. However, current traffic information systems have difficulty providing real-time information on road conditions and accident-prone areas, and accident prevention measures are not functioning adequately. Furthermore, technologies to appropriately manage drivers' emotional states and support safe driving are not yet fully established. The challenge is to improve this situation, reduce the occurrence of traffic accidents, and appropriately manage drivers' mental states.

[0999] The identification processing by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a database means for distributing traffic accident-prone area information to the vehicle, a monitoring means for monitoring the surrounding situation using a camera and detection device mounted on the vehicle, a comparison means for comparing the traffic accident-prone area information stored in the internal storage device with the current location, a notification means for alerting the driver when approaching the relevant area, a control means for automatically reducing the vehicle's speed in government-designated deceleration areas, and an emotion analysis means for monitoring the user's emotional state and providing relaxation content as needed. This reduces the risk of accidents in traffic accident-prone areas and government-designated deceleration areas, and enables safe driving by appropriately managing the driver's emotional state.

[1000] "Information on areas with a high incidence of traffic accidents" refers to information on areas where traffic accidents frequently occur, identified based on past statistical data and information from traffic management organizations.

[1001] "Database means" refers to a system or device for organizing, storing, and managing specific data, and in this invention, it has the function of distributing information on areas with a high incidence of traffic accidents and areas where speed reduction is required to vehicles.

[1002] A "shooting device" refers to hardware for capturing images, such as a camera or video camera, and in this invention, it is a device mounted on a vehicle and used to monitor the surrounding environment.

[1003] A "detection device" is hardware such as a sensor or radar that detects specific physical changes or situations, and in this invention, it is a device mounted on a vehicle and used to monitor the surrounding conditions.

[1004] "Monitoring means" refers to a system or function that uses imaging devices and detection devices to observe and record the surrounding situation in real time.

[1005] "Internal memory" refers to hardware used to permanently or temporarily store data in a computer or electronic device, and in this invention, it is a device for storing information such as traffic accident-prone areas.

[1006] "Comparison means" refers to a system or function for comparing current location information with data stored in internal memory.

[1007] "Notification means" refers to a system or function that provides drivers with specific information or warnings via voice or visual means.

[1008] "Control means" refers to functions or systems for automatically adjusting the vehicle's speed, particularly those that reduce the vehicle's speed in deceleration areas.

[1009] "Emotional analysis means" refers to a system or function that collects and analyzes the user's facial expressions and voice to identify their emotional state, and provides relaxation content as needed.

[1010] This invention aims to prevent traffic accidents through a system installed in a vehicle, and also incorporates an emotion analysis function that monitors the user's emotional state while driving and supports safe driving. A specific embodiment of this invention is described below.

[1011] System Configuration

[1012] server:

[1013] The server acquires data in real time from traffic management agencies and manages information on accident-prone areas and government-designated speed-reducing areas. Since the server encrypts this information at night before distributing it to vehicles, a high-performance server and encryption software are required. Typical hardware used would be a standard high-performance server (e.g., a high-performance server series). Software used would include data collection and encryption software (e.g., an encryption library).

[1014] Terminal (in-vehicle system):

[1015] The terminal is installed in the vehicle and monitors the surrounding environment in real time through cameras and sensors. Based on this, it compares the current location with information on areas with a high incidence of traffic accidents and alerts the driver with a voice announcement when approaching a specific area. The terminal also has a function to automatically control the brakes and accelerator to reduce speed when entering a government-designated deceleration zone. Furthermore, it collects the user's facial expressions and voice and transmits them to an emotion analysis engine. The hardware required includes an in-vehicle camera, sensors (e.g., a series of detection devices), and an in-vehicle computer (e.g., an in-vehicle computer series). The software used includes real-time data analysis software and voice announcement software (e.g., voice announcement software).

[1016] Emotion analysis engine:

[1017] The emotion analysis engine collects the user's facial expressions and voice in real time through the in-vehicle camera and microphone, and identifies the user's emotional state by analyzing this data. For example, it can detect tension and stress by analyzing facial muscle movements and voice tone, and transmit this information to the terminal to provide relaxation content. The hardware used includes a camera, microphone (e.g., a series of imaging devices), and an in-vehicle computer. Software required includes facial expression analysis software and voice analysis software (e.g., a voice analysis API).

[1018] User (driver):

[1019] Users receive instructions and notifications from their devices through the in-vehicle display and voice assistant. For example, they may receive notifications such as "This area is prone to accidents" or the playback of relaxation music, allowing them to concentrate on driving and drive safely.

[1020] Specific example

[1021] Server-side example:

[1022] The server retrieves daily updated information on accident-prone areas from traffic management agencies at night and securely distributes it to vehicles using AES-256 encryption. This ensures that vehicles always receive the latest traffic information.

[1023] Specific examples on the terminal side:

[1024] The device monitors the situation ahead using cameras and sensors while driving in urban areas, and notifies the driver via voice message, "This is an area prone to accidents," when approaching an area with a high incidence of traffic accidents. Furthermore, it automatically applies the brakes and slows down the vehicle when entering a government-designated deceleration zone near a highway exit. Additionally, if the user is experiencing high levels of stress, a mood analysis engine plays relaxation music.

[1025] User-side examples:

[1026] Users listen to voice announcements from the system and drive with extra caution, especially in areas with a high incidence of traffic accidents. Based on notifications from the emotion analysis engine, users can continue to drive safely by using relaxation content to relax.

[1027] In this way, by implementing the present invention, it is possible not only to prevent traffic accidents and enable safe driving, but also to appropriately manage the user's mental state.

[1028] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1029] Step 1: Receive data from traffic management authorities.

[1030] The server receives the latest information on accident-prone areas and government-designated speed-reducing areas from traffic management agencies. This data is usually provided in XML or JSON format.

[1031] Input: Latest data from traffic management authorities

[1032] Data processing: Parsing (analysis) XML / JSON data and extracting necessary information.

[1033] Output: Extracted information on areas with a high incidence of traffic accidents and areas where speed reduction is required.

[1034] Step 2: Encrypt and store data

[1035] The server stores the received data in an internal database and encrypts the data using AES-256 encryption.

[1036] Input: Extracted information on areas with a high incidence of traffic accidents and areas where speed reduction is required.

[1037] Data processing: Data encryption

[1038] Output: Encrypted information on areas with a high incidence of traffic accidents and areas requiring reduced speed is stored in an internal database.

[1039] Step 3: Data distribution to the vehicle

[1040] The server delivers encrypted data to vehicles overnight. A secure communication protocol (e.g., HTTPS) is used during delivery.

[1041] Input: Encrypted traffic accident-prone area information and speed reduction area information

[1042] Data processing: None

[1043] Output: Encrypted data delivered to the vehicle

[1044] Step 4: Receiving and storing data by the vehicle

[1045] The terminal receives encrypted data sent from the server overnight and stores it in its internal memory. It then verifies the integrity of the data and checks for any missed data or data corruption.

[1046] Input: Encrypted data delivered from the server

[1047] Data processing: Data integrity check and decryption

[1048] Output: Data stored in internal memory

[1049] Step 5: Real-time monitoring of the surrounding environment

[1050] The terminal uses cameras and sensors mounted on the vehicle to monitor the surrounding environment in real time. Data is collected every second to measure the distance to vehicles and obstacles ahead.

[1051] Input: Real-time data from cameras and sensors

[1052] Data processing: Analysis of image and sensor data

[1053] Output: Analysis results of the surrounding environment

[1054] Step 6: Notification of areas with a high incidence of traffic accidents

[1055] The device compares the current location with data in its internal memory, and if it approaches an area prone to traffic accidents or a slow-down zone, it notifies the driver with a voice announcement saying, "You are in an area prone to accidents ahead."

[1056] Input: Current location data, information on areas with a high incidence of traffic accidents stored in internal memory.

[1057] Data processing: Comparison of current location and area information

[1058] Output: Voice notification to the driver

[1059] Step 7: Automatic deceleration control

[1060] The device automatically controls the brakes and accelerator when entering a government-designated deceleration zone, safely reducing the vehicle's speed.

[1061] Input: Current location data, internal memory deceleration area information

[1062] Data processing: Deceleration area detection and control signal generation.

[1063] Output: Vehicle deceleration control signal

[1064] Step 8: Monitoring the user's emotional state

[1065] The device uses an in-car camera and microphone to collect the user's facial expressions and voice in real time and transmit them to an emotion analysis engine.

[1066] Input: Real-time data from camera and microphone

[1067] Data processing: Collection and transmission of facial expression and voice data.

[1068] Output: Data sent to the emotion analysis engine

[1069] Step 9: Emotion Analysis

[1070] The emotion analysis engine analyzes the received data to identify the user's emotional state. For example, it analyzes facial muscle movements and voice tone.

[1071] Input: Facial expressions and audio data from the device.

[1072] Data processing: Data analysis

[1073] Output: Identified emotional state (e.g., tension, stress, relaxation)

[1074] Step 10: Determine the necessary actions

[1075] The emotion analysis engine determines the necessary action (e.g., playing relaxation music) based on the identified emotional state and notifies the device.

[1076] Input: Emotional state data from the analysis results

[1077] Data processing: Action decision algorithm

[1078] Output: Action instructions for the terminal

[1079] Step 11: System notifications and driving operations

[1080] Users receive notifications from their devices via the in-car display and audio system, enabling them to drive safely.

[1081] Input: Notifications from the device

[1082] Data processing: None

[1083] Output: Implementation of safe driving

[1084] Step 12: Use relaxation content

[1085] Based on notifications from the emotion analysis engine, users utilize relaxation content as needed to maintain an appropriate mental state.

[1086] Input: Relaxation content playback notification from emotion analysis engine

[1087] Data processing: None

[1088] Output: Use of relaxation content and stabilization of mental state

[1089] This clarifies the specific actions, inputs, and outputs performed at each processing step, making the overall system process easier to understand.

[1090] (Application Example 2)

[1091] 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."

[1092] Conventional autonomous driving and driver assistance systems primarily aimed to ensure safety in accident-prone areas and speed-reducing zones, but they lacked sufficient measures to address the driver's emotional state. Despite the known fact that tension and stress negatively impact driving, there was a lack of methods to address these emotions. As a result, the risk of accidents increased, hindering safe driving. This invention aims to solve these problems and improve driver safety and comfort.

[1093] In Application Example 2, the identification processing by the identification processing unit 290 of the data processing device 12 is realized by the following means. In this invention, the server includes a database means for distributing traffic accident-prone area information to the vehicle, a monitoring means for monitoring the surrounding situation using cameras and sensors mounted on the vehicle, a comparison means for comparing the traffic accident-prone area information stored in internal memory with the current location, an announcement means for alerting the driver when approaching the relevant area, a control means for automatically reducing the vehicle's speed in nationally designated deceleration areas, an emotion engine for collecting and analyzing the user's facial expressions and voice in real time, and a means for providing relaxation content when it is detected that the user's emotional state is tension or stress. This not only prevents traffic accidents but also reduces the driver's mental stress, enabling safer and more comfortable driving.

[1094] "Information on areas with a high incidence of traffic accidents" refers to data on areas where traffic accidents have occurred frequently in the past.

[1095] A "database system" is a system that organizes and stores information, making it available for retrieval as needed.

[1096] "Cameras and sensors" are devices that acquire visual information and environmental data from the surroundings.

[1097] "Monitoring means" refers to the function of checking the surrounding situation in real time using cameras and sensors.

[1098] The "comparison means" is a function that compares the current location of the vehicle with information stored in advance.

[1099] An "announcement system" is a device that uses voice to convey important information to the driver.

[1100] A "control system" is a function that automatically adjusts the vehicle's speed and operation under specific conditions.

[1101] An "emotion engine" is a system that analyzes a user's emotional state based on their facial expressions and voice.

[1102] "Relaxation content" refers to content such as music and videos provided to reduce users' tension and stress.

[1103] System Configuration

[1104] Server side

[1105] The server manages information on areas with a high incidence of traffic accidents and receives the latest information from the traffic management center. This information is periodically distributed to connected vehicles using an encrypted and secure communication protocol. The server works in conjunction with the traffic information database to collect and distribute data.

[1106] Vehicle terminal side

[1107] The vehicle terminal monitors the surrounding environment through cameras and various sensors built into the vehicle. Its internal memory stores information on accident-prone areas and nationally designated deceleration areas received from the server, and it compares this information with the vehicle's current location.

[1108] When approaching a specific area, the system alerts the driver via the in-car display and voice assistant. Furthermore, it includes a function that automatically controls the vehicle's speed when entering a deceleration zone.

[1109] Emotional Engine

[1110] The emotion engine collects and analyzes the driver's facial expressions and voice in real time through cameras and microphones installed in the vehicle. If the system determines that the driver is experiencing tension or stress, the emotion engine sends emotional data to the device, and relaxation content is provided. This relaxation content, including music and videos, is designed to stabilize the driver's mental state.

[1111] Specific example

[1112] For example, if a vehicle is driving through an urban area and approaches an area prone to frequent traffic accidents, the terminal will announce, "This is an area where accidents frequently occur." Also, when entering a government-designated deceleration zone near a highway exit, the terminal will automatically apply the brakes and reduce the vehicle's speed.

[1113] Furthermore, if the emotional engine detects that the driver is feeling tense or stressed, relaxation music will automatically play. In this way, the driver can relax while maintaining a focus on safe driving.

[1114] Example of a prompt

[1115] Please generate an audio announcement for when a driver approaches an area with a high incidence of traffic accidents. For example, it should include the following: "Warning: You are approaching an accident-prone area."

[1116] Additionally, if tension is detected from the driver's facial expressions captured by the camera, display the message "User stress detected. Relaxation content will be provided," and generate a prompt to play relaxation music.

[1117] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1118] Step 1:

[1119] The server receives information on accident-prone areas and nationally designated speed reduction areas from the traffic management center. The received data is encrypted and distributed to vehicles using a secure communication protocol. The input is data from the traffic management center, and the output is encrypted traffic information data.

[1120] Step 2:

[1121] The terminal receives traffic information data distributed from the server and stores it in its internal memory. The input is encrypted traffic information data from the server, and the output is the state of the data stored in the terminal's internal memory. Specifically, the terminal automatically connects to the server at night to download and store the data.

[1122] Step 3:

[1123] The camera and sensors mounted on the device monitor the surrounding environment in real time. Input is raw data from the camera and sensors, and output is analyzed data of the surrounding environment. Specifically, the camera captures image data, and the sensors collect environmental data.

[1124] Step 4:

[1125] The device compares the current location with accident-prone area information stored in its internal memory and alerts the driver with a voice announcement when approaching a specific area. Inputs are current location data from the built-in GPS and accident-prone area information from internal memory; output is a voice announcement. Specifically, it periodically compares the current location with the accident-prone area information.

[1126] Step 5:

[1127] When the terminal enters a nationally designated deceleration zone, it automatically controls the brakes and accelerator to reduce the vehicle's speed. Inputs include current location data from the built-in GPS and deceleration zone information stored in internal memory, while output is the decelerated vehicle status. Specifically, when the vehicle enters a deceleration zone, the speed control system activates.

[1128] Step 6:

[1129] The emotion engine collects the driver's facial expressions and voice in real time through cameras and microphones inside the vehicle and analyzes their emotional state. The input is facial and voice data from the cameras and microphones, and the output is the analyzed emotional state of the driver. Specifically, the collected data is analyzed using an algorithm to detect tension and stress.

[1130] Step 7:

[1131] When the emotion engine detects the driver's tension or stress, it notifies the device and provides relaxation content. The input is emotional state data from the emotion engine, and the output is the relaxation content to be played. Specifically, when stress is detected, the device plays pre-set relaxation music or video.

[1132] Step 8:

[1133] The user checks notifications from their device via the in-car display and audio system. Input is notification data from the device, and output is the user's actions (e.g., driving operations or relaxation). Specifically, the user performs driving operations according to voice announcements and uses relaxation content as needed.

[1134] 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.

[1135] 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.

[1136] 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.

[1137] [Fourth Embodiment]

[1138] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[1139] 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.

[1140] 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).

[1141] 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.

[1142] 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.

[1143] 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).

[1144] 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.

[1145] 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.

[1146] 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.

[1147] 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.

[1148] 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.

[1149] 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.

[1150] 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".

[1151] This invention aims to prevent traffic accidents through a system installed in a vehicle, and a specific embodiment thereof will be described below.

[1152] System Configuration

[1153] server

[1154] 1. The server manages data on areas with a high incidence of traffic accidents and nationally designated speed reduction areas.

[1155] 2. The server collects the latest information from the traffic management center and distributes it to vehicles periodically.

[1156] 3. The server encrypts data using secure communication protocols to ensure security.

[1157] Terminal (car)

[1158] 1. The terminal monitors the surrounding environment in real time through cameras and sensors mounted on the vehicle.

[1159] 2. The device compares its current location with the traffic accident-prone area information stored in its internal memory.

[1160] 3. The terminal will use an announcement system to alert the driver when it approaches a specific area.

[1161] 4. The terminal automatically controls the brakes and accelerator to reduce the vehicle's speed in nationally designated deceleration zones.

[1162] User (driver)

[1163] 1. Users receive system instructions through the in-vehicle display or voice assistant.

[1164] 2. Users should follow the announcements and drive safely.

[1165] 3. The user will monitor the system's deceleration operation and perform appropriate driving maneuvers.

[1166] Program processing

[1167] server

[1168] The server receives the latest accident-prone area information from the traffic management center and distributes it to vehicles in bulk overnight. The distributed data is encrypted and delivered to vehicles securely.

[1169] Terminal (car)

[1170] The terminal stores data received from the server every night in its internal memory. While driving, the vehicle's cameras and sensors monitor the surrounding environment and compare the current location with information on accident-prone areas in real time. When approaching a specific area, the terminal notifies the driver with a voice announcement saying, "This is an area with a high incidence of accidents." Furthermore, if the vehicle enters a nationally designated deceleration zone, it automatically controls the brakes and accelerator to reduce speed.

[1171] User (driver)

[1172] The user checks notifications from the device via the in-car display or audio system. If a warning announcement is made, the user concentrates on driving and drives safely. When entering a nationally designated deceleration zone, the user continues to drive appropriately while monitoring the system's deceleration operation. The user recognizes that the system is automatically adjusting the vehicle's speed and continues driving with confidence.

[1173] Specific example

[1174] Server-side specific example

[1175] The server collects accident-prone area information, updated daily from the traffic management center, and distributes it to vehicles at night. This distribution is performed for all registered vehicles, and security is ensured through multiple security measures.

[1176] Specific examples on the terminal side

[1177] The device monitors the situation ahead using cameras and sensors while driving in urban areas, and notifies the driver via voice message, "This is an area prone to accidents," when approaching an area with a high incidence of traffic accidents. Furthermore, it automatically applies the brakes and slows down the vehicle when entering a government-designated deceleration zone near a highway exit.

[1178] User-side examples

[1179] Users listen to voice announcements from the system and drive with extra caution, especially in areas prone to traffic accidents. When entering a deceleration zone, the system automatically slows down the vehicle, allowing the user to continue driving safely.

[1180] In this way, by implementing the present invention, it is possible to prevent traffic accidents from occurring and to enable safe driving.

[1181] The following describes the processing flow.

[1182] Step 1: The server receives the latest information on areas with a high incidence of traffic accidents from the traffic management center.

[1183] Specifically, the server periodically accesses the traffic management center's database to download the latest information on accident-prone areas and nationally designated speed reduction areas.

[1184] Step 2: The server distributes the received data to the vehicles.

[1185] Specifically, data is encrypted and transmitted to the vehicle's terminal using a secure communication protocol at night.

[1186] Step 3: The terminal receives data delivered from the server and saves it to its internal memory.

[1187] Specifically, data is acquired using the vehicle's communication module and stored in storage.

[1188] Step 4: The device monitors its surroundings using cameras and sensors while in motion.

[1189] Specifically, it captures video of the area ahead and measures the distance to obstacles using sensors.

[1190] Step 5: The device obtains its current location.

[1191] Specifically, it uses a GPS module to acquire real-time location information and compares it with area information stored in internal memory.

[1192] Step 6: The device compares its current location with information on areas prone to traffic accidents.

[1193] Specifically, the system uses a matching algorithm to compare current location information obtained from GPS with a database of accident-prone areas.

[1194] Step 7: The terminal makes an announcement to the driver based on the matching results.

[1195] Specifically, it will notify users via voice announcement that "the area ahead is prone to traffic accidents."

[1196] Step 8: The terminal controls the brakes and accelerator when entering a nationally designated deceleration zone.

[1197] Specifically, it sends a deceleration command to the vehicle's ECU, activating the braking system to adjust the vehicle's speed.

[1198] Step 9: The user checks the announcement from the device and drives safely.

[1199] Specifically, continue driving while paying attention and following voice instructions.

[1200] Step 10: The user monitors the speed adjustment due to automatic deceleration and performs appropriate driving operations.

[1201] Specifically, the system will continue driving while monitoring speed adjustments in the deceleration area.

[1202] (Example 1)

[1203] 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".

[1204] Road accidents remain frequent, particularly in specific locations such as accident-prone areas and government-designated speed-reducing zones. Current systems and methods are insufficient to adequately reduce the risk of accidents. Furthermore, inadequate driver awareness campaigns highlight the need for effective accident prevention approaches.

[1205] 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.

[1206] In this invention, the server includes a database means for distributing information on areas prone to traffic accidents to vehicles, a monitoring means for monitoring the surrounding conditions using cameras and sensors mounted on the vehicle, a storage means for storing information on areas prone to traffic accidents received from the server every night in internal memory, a comparison means for comparing the information on areas prone to traffic accidents stored in internal memory with the current location, an announcement means for alerting the driver when approaching the area in question, and a control means for automatically reducing the vehicle's speed in nationally designated deceleration zones. As a result, warnings and speed adjustments are automatically performed in accident-prone areas and deceleration zones, making it possible to effectively prevent traffic accidents.

[1207] "Information on areas with a high incidence of traffic accidents" refers to data on locations in specific regions or on roads where traffic accidents have frequently occurred in the past.

[1208] A "database means" is a system or device that enables the collection, storage, and distribution of information on areas with a high incidence of traffic accidents to vehicles that require it.

[1209] A "camera" is a device that captures images of the area in front of and around a vehicle in real time, providing surveillance information.

[1210] A "sensor" is a device that measures the physical conditions around a vehicle, such as distance, speed, and position.

[1211] A "monitoring system" is a mechanism that uses cameras and sensors mounted on the vehicle to monitor the area around the vehicle in real time.

[1212] "Storage means" refers to a function or device that stores traffic accident-prone area information received from a server into internal memory.

[1213] The "comparison method" is a technology that compares the vehicle's current location with information on areas prone to traffic accidents stored in internal memory to determine if it is approaching a specific area.

[1214] An "announcement system" is a mechanism that alerts the driver via voice or display when approaching a specific area.

[1215] A "control system" is a mechanism that automatically operates the vehicle's brakes and accelerator to reduce its speed when it enters a nationally designated deceleration zone.

[1216] This invention is a system aimed at preventing traffic accidents, and through the cooperation of a server, a terminal installed in a vehicle, and the user using it, it supports safe driving in areas with a high incidence of traffic accidents and areas designated by the government as speed reduction zones.

[1217] server

[1218] The server collects the latest accident-prone area information from the traffic management center every night. This information includes GPS coordinates, accident frequency, and historical accident data. The collected data is encrypted using strong encryption technologies such as AES-256 and securely stored and transmitted. The server distributes this data to all registered vehicles in bulk. Distribution takes place at night, ensuring security.

[1219] Terminal (vehicle)

[1220] The terminal installed in the vehicle stores information on accident-prone areas received from a server at night in its internal memory. While driving, the terminal monitors the surrounding environment in real time using multiple cameras and sensors. The terminal compares the accident-prone area information stored in its internal memory with the current location and alerts the driver with a voice announcement when approaching a specific area. Furthermore, if the vehicle enters a nationally designated deceleration zone, the terminal automatically controls the brakes and accelerator to reduce the vehicle's speed.

[1221] As a concrete example, the device monitors the situation ahead using cameras and sensors while driving in urban areas, and when approaching an area prone to traffic accidents, it will notify the driver by voice, "This is an area where accidents frequently occur." Furthermore, when entering a deceleration zone near a highway exit, it will automatically apply the brakes to slow down the vehicle.

[1222] User (driver)

[1223] Users check notifications from their devices via the in-car display or audio system. When an announcement is made, they concentrate on driving and drive safely. When entering a nationally designated deceleration zone, they continue to drive appropriately while monitoring the system's deceleration actions. Users can drive with confidence knowing that the system is automatically adjusting the vehicle's speed.

[1224] Examples of prompts for generative AI models

[1225] The following is an example of a prompt message used to have a generative AI model suggest relevant data and new features.

[1226] Based on information on areas with a high incidence of traffic accidents, please propose a more accurate accident prevention alert system.

[1227] Please propose new features or improvements to the vehicle's automatic speed control system.

[1228] Please suggest ways to streamline the data collection process from the traffic management center.

[1229] In this way, the present invention can prevent traffic accidents and improve driving safety.

[1230] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1231] Program processing steps

[1232] Server processing steps

[1233] Step 1:

[1234] The server collects the latest accident-prone area information from the traffic management center at night. This information includes GPS data, accident rates, and historical accident data. The input is data from the traffic management center, and the output is the collected raw data. Data collection involves specific actions such as calling certain APIs to retrieve information.

[1235] Step 2:

[1236] The server encrypts the collected data using strong encryption techniques such as AES-256. The input is collected information on areas with a high incidence of traffic accidents, and the output is encrypted data. The encryption process involves specific actions to apply encryption algorithms to ensure security while maintaining data readability.

[1237] Step 3:

[1238] The server distributes encrypted data to all registered vehicles in a single batch. The input is encrypted data, and the output is the encrypted data sent to each vehicle. The distribution process includes specific actions to send data using the vehicle's network ID.

[1239] Terminal (vehicle) processing steps

[1240] Step 1:

[1241] The terminal stores information about areas prone to traffic accidents, received from the server at night, in its internal memory. The input is encrypted data from the server, and the output is the decrypted data stored in internal memory. This includes the specific actions of the terminal to decrypt the encrypted data and securely store it in internal memory.

[1242] Step 2:

[1243] The terminal monitors the surrounding environment in real time using cameras and sensors mounted on the vehicle while it is in motion. The input is real-time data from each camera and sensor, and the output is the analysis results of the area around the vehicle. The collection and analysis of sensor data specifically includes processing camera images and digitally analyzing sensor values.

[1244] Step 3:

[1245] The device compares its real-time current location with accident-prone area information stored in its internal memory. The input consists of current location data from the GPS module and accident-prone area information in internal memory, while the output is the comparison result. The comparison process involves applying an algorithm that matches the current location data with pre-stored area information.

[1246] Step 4:

[1247] When the vehicle enters a specific area, the terminal alerts the driver with a voice announcement. The input is comparison result data, and the output is a voice announcement. Specifically, the announcement information is generated from an audio file and played back through the vehicle's audio system.

[1248] Step 5:

[1249] When entering a nationally designated deceleration zone, the terminal automatically controls the brakes and accelerator to reduce the vehicle's speed. The input is the comparison result and speed information, and the output is the decelerated vehicle speed. Specifically, this involves sending commands to the engine control unit to perform the necessary braking and engine accelerator control.

[1250] User processing steps

[1251] Step 1:

[1252] Users check notifications from their devices through the in-car display and audio system. The input is the announcement from the device, and the output is the user's awareness and actions. For example, the display might show "Approaching accident-prone area," and this is also announced by voice.

[1253] Step 2:

[1254] When a warning announcement is made, the user concentrates on driving and drives safely. The input is the announcement information, and the output is the user's driving actions. Specifically, this involves performing driving actions such as reducing speed and paying attention to the surrounding conditions.

[1255] Step 3:

[1256] When entering a nationally designated deceleration zone, the user monitors the system's deceleration operation and continues to drive appropriately. Inputs are deceleration operations and information related to deceleration, while outputs are coordinated driving actions. Specifically, this includes actions such as steering and monitoring the surroundings while confirming the system's automatic deceleration.

[1257] (Application Example 1)

[1258] 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".

[1259] There is a need for a system that can promote safe driving and prevent traffic accidents by reliably informing drivers of accident-prone areas and government-designated speed-reducing zones. Conventional systems have limited real-time notification of accident-prone areas and notification functions that can be linked with multiple devices, making it difficult to improve safety for drivers and users of autonomous vehicles.

[1260] 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.

[1261] In this invention, the server includes a database means for distributing accident-prone area information to vehicles; a monitoring means for monitoring the surrounding situation using cameras and sensors mounted on the vehicle; a comparison means for matching the accident-prone area information stored in internal memory with the current location; an announcement means for alerting the driver when approaching the relevant area; a control means for automatically reducing the vehicle's speed in nationally designated deceleration areas; and a notification means for comparing the location information acquired by the monitoring means with the accident-prone area information in real time and providing visual and audible notifications in cooperation with smartphones and head-mounted displays. This enables real-time notification of accident-prone area information and visual and audible notifications on multiple devices.

[1262] A "database means" refers to a system device that has the function of managing and distributing information on areas with a high incidence of traffic accidents to vehicles.

[1263] "Monitoring means" refers to a system device that has the function of monitoring the surrounding situation in real time using cameras and sensors mounted on the vehicle.

[1264] The "comparison means" is a system device that has the function of comparing the current location of a vehicle with information on areas with a high incidence of traffic accidents stored in its internal memory.

[1265] An "announcement device" is a system device that has the function of alerting the driver when approaching the relevant area.

[1266] "Control means" refers to a system device that has the function of automatically reducing the speed of a vehicle in a nationally designated deceleration area.

[1267] The "notification means" is a system device that compares location information acquired by the monitoring means with accident-prone area information in real time and has the function of providing visual and audible notifications in cooperation with smartphones or head-mounted displays.

[1268] This invention aims to prevent traffic accidents through a system installed in a vehicle, and a specific embodiment thereof will be described below.

[1269] System Configuration

[1270] server

[1271] The server manages data on accident-prone areas and nationally designated speed reduction zones. It collects the latest information from traffic management centers and distributes it to vehicles regularly. Furthermore, data is encrypted using secure communication protocols to ensure security.

[1272] Terminal (car)

[1273] The device monitors the surrounding environment in real time through cameras and sensors mounted on the vehicle. It compares the current location with information on accident-prone areas stored in its internal memory and alerts the driver using announcements when approaching such areas. Furthermore, it automatically controls the brakes and accelerator to reduce the vehicle's speed in nationally designated deceleration zones. It also works in conjunction with smartphones and head-mounted displays to provide visual and audible notifications.

[1274] User (driver)

[1275] The user receives system instructions through the in-vehicle display and voice assistant. If alerts are received while driving, the user should drive safely. When entering a nationally designated deceleration zone, the user should monitor the system as it automatically adjusts the vehicle's speed and perform appropriate driving maneuvers.

[1276] Program processing

[1277] server

[1278] The server receives the latest accident-prone area information from the traffic management center and distributes it to vehicles in bulk overnight. The distributed data is encrypted and delivered to vehicles securely.

[1279] Terminal (car)

[1280] The device stores the latest data received from the server every night in its internal memory. While driving, the vehicle's cameras and sensors monitor the surrounding environment and compare the current location with information on accident-prone areas in real time. When approaching a specific area, the device notifies the driver with a voice announcement saying, "This is an area with a high incidence of accidents." In addition, when entering a nationally designated deceleration zone, it automatically applies the brakes and slows down the vehicle. Visual and audible notifications are also provided on smartphones and head-mounted displays.

[1281] User (driver)

[1282] The user checks notifications from the device via the in-car display or audio system. If a warning is issued, the user concentrates on driving and drives safely. When the system performs deceleration, the user monitors the system's operation and continues to drive appropriately.

[1283] Specific example

[1284] For example, if a vehicle's GPS sensor records its current location as "35.6895, 139.6917" while driving in an urban area, this information is compared to a list of accident-prone areas distributed from a server. If this location is within an accident-prone area, the vehicle's display will show "You are in an accident-prone area ahead. Please be careful," and an audio alert will be issued. Similar notifications will also be sent to smartphones and head-mounted displays.

[1285] Examples of prompts to input into a generative AI model

[1286] "Please describe the implementation of a driver alert system in accident-prone areas. Include a function that compares the driver's current location with accident-prone area information obtained from a server in real time and notifies the driver accordingly."

[1287] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1288] Step 1:

[1289] The server receives the latest information on areas with a high incidence of traffic accidents from the traffic management center. At this time, it obtains the data provided by the traffic management center via an API and stores the received data in the server's internal database. The input is the accident-prone area information from the traffic management center, and the output is the information stored in the server's database.

[1290] Step 2:

[1291] The server distributes the latest accident-prone area information to vehicles at a set time every night. It retrieves the latest information from its internal database and transmits it to the vehicles using an encrypted communication protocol. The input is accident-prone area information retrieved from the server's internal database, and the output is encrypted information transmitted to the vehicle's terminal.

[1292] Step 3:

[1293] The terminal stores accident-prone area information received from the server in its internal memory. It stores the received data in its internal memory every night and overrides it. The input is accident-prone area information sent from the server, and the output is the information stored in the terminal's internal memory.

[1294] Step 4:

[1295] The device acquires real-time information about the surrounding environment and current location from the vehicle's GPS sensor and camera. Inputs include data from the GPS sensor and camera, and outputs include current location information and surrounding environment data.

[1296] Step 5:

[1297] The device compares the acquired current location information with accident-prone area information stored in its internal memory in real time. For example, it determines whether the current location is within the radius of a registered accident-prone area. The input consists of real-time current location information and accident-prone area information stored in internal memory, and the output is the result of determining whether the user is approaching the relevant area.

[1298] Step 6:

[1299] The device provides visual and auditory alerts to the driver when approaching a designated area. It works in conjunction with smartphones and head-mounted displays to effectively alert the driver visually and aurally. The input is the detection result of the designated area, and the output is visual and auditory notifications.

[1300] Step 7:

[1301] The terminal automatically controls the brakes and accelerator to reduce the vehicle's speed when it enters a nationally designated deceleration zone. This is achieved in conjunction with the autonomous driving system. The input is the result of the vehicle entering the deceleration zone, and the output is the state in which the vehicle's speed has been reduced.

[1302] Step 8:

[1303] Users receive notifications from their devices via in-vehicle displays, audio systems, smartphones, and head-mounted displays. When alerts are issued, users receive visual and auditory information regarding safe driving and perform driving actions accordingly. The input is notification information from the device, and the output is appropriate driving actions performed with safe driving in mind.

[1304] The above steps will create a system that prevents traffic accidents in accident-prone areas. In addition, visual and audible notifications will alert drivers, enabling safer driving.

[1305] 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.

[1306] This invention aims to prevent traffic accidents through a system installed in a vehicle, and further incorporates an "emotion engine" that monitors the user's emotional state while driving and supports safe driving. Specific embodiments are described below.

[1307] System Configuration

[1308] server

[1309] 1. The server manages data on areas with a high incidence of traffic accidents and nationally designated speed reduction areas.

[1310] 2. The server collects the latest information from the traffic management center and distributes it to vehicles periodically.

[1311] 3. The server encrypts data using secure communication protocols to ensure security.

[1312] Terminal (car)

[1313] 1. The terminal monitors the surrounding environment in real time through cameras and sensors mounted on the vehicle.

[1314] 2. The device compares its current location with the traffic accident-prone area information stored in its internal memory.

[1315] 3. The terminal will use an announcement system to alert the driver when it approaches a specific area.

[1316] 4. The terminal automatically controls the brakes and accelerator to reduce the vehicle's speed in nationally designated deceleration zones.

[1317] 5. The device is equipped with an emotion engine that recognizes the user's emotions and analyzes the user's facial expressions and voice.

[1318] Emotional Engine

[1319] 1. The emotion engine collects the user's facial expressions and voice in real time through the camera and microphone.

[1320] 2. The emotion engine analyzes the collected data to identify the user's emotional state (e.g., tension, stress, relaxation).

[1321] 3. If necessary, the emotion engine sends emotion data to the device, and the device performs the corresponding action.

[1322] User (driver)

[1323] 1. Users receive system instructions through the in-vehicle display or voice assistant.

[1324] 2. Users should follow the announcements and drive safely.

[1325] 3. Based on notifications from the emotion engine, users will utilize relaxation content if necessary.

[1326] Program processing

[1327] server

[1328] The server receives the latest accident-prone area information from the traffic management center and distributes it to vehicles in bulk overnight. The distributed data is encrypted and delivered to vehicles securely.

[1329] Terminal (car)

[1330] The device stores data received from the server in its internal memory every night. While driving, the vehicle's cameras and sensors monitor the surrounding environment and compare the current location with information on accident-prone areas in real time. When approaching a specific area, the device notifies the driver with a voice announcement saying, "This is an area with a high incidence of accidents." Furthermore, if the vehicle enters a nationally designated deceleration zone, it automatically controls the brakes and accelerator to reduce speed. In addition, if the emotion engine detects that the user is feeling tense or stressed, it notifies the device to provide relaxation content.

[1331] Emotional Engine

[1332] The emotion engine collects the user's facial expressions and voice using the camera and microphone and analyzes them in real time. If it detects tension or stress, it sends the emotion data to the device and provides relaxation content.

[1333] User (driver)

[1334] Users check notifications from their devices via the in-car display and audio system. If a warning announcement is made, they concentrate on driving and drive safely. Furthermore, if relaxation content is provided by the emotional engine, they can use it to maintain an appropriate mental state.

[1335] Specific example

[1336] Server-side specific example

[1337] The server collects accident-prone area information, updated daily from the traffic management center, and distributes it to vehicles at night. This distribution is performed for all registered vehicles, and security is ensured through multiple security measures.

[1338] Specific examples on the terminal side

[1339] The device monitors the situation ahead using cameras and sensors while driving in urban areas, and notifies the driver via voice, "This is an area prone to accidents," when approaching an area with a high incidence of traffic accidents. Furthermore, it automatically applies the brakes and slows down the vehicle when entering a government-designated deceleration zone near a highway exit. Additionally, if the user is experiencing high levels of stress, a relaxation engine plays soothing music.

[1340] User-side examples

[1341] Users listen to voice announcements from the system and drive with extra caution, especially in areas with a high incidence of traffic accidents. Notifications from the emotion engine allow users to relax using relaxation content, enabling them to continue driving safely.

[1342] In this way, by implementing the present invention, it is possible not only to prevent traffic accidents and enable safe driving, but also to appropriately manage the user's mental state.

[1343] The following describes the processing flow.

[1344] Step 1: The server receives the latest information on areas with a high incidence of traffic accidents from the traffic management center.

[1345] Specifically, the server periodically accesses the traffic management center's database to download the latest information on accident-prone areas and nationally designated speed reduction areas.

[1346] Step 2: The server distributes the received data to the vehicles.

[1347] Specifically, data is encrypted and transmitted to the vehicle's terminal using a secure communication protocol at night.

[1348] Step 3: The terminal receives data delivered from the server and saves it to its internal memory.

[1349] Specifically, data is acquired using the vehicle's communication module and stored in storage.

[1350] Step 4: The terminal uses the vehicle's cameras and sensors to monitor the surrounding environment in real time.

[1351] Specifically, it captures video of the area ahead and measures the distance to obstacles using sensors.

[1352] Step 5: The device obtains its current location.

[1353] Specifically, it uses a GPS module to acquire real-time location information and compares it with area information stored in internal memory.

[1354] Step 6: The device compares its current location with information on areas prone to traffic accidents.

[1355] Specifically, the system uses a matching algorithm to compare current location information obtained from GPS with a database of accident-prone areas.

[1356] Step 7: The terminal makes an announcement to the driver based on the matching results.

[1357] Specifically, it will notify users via voice announcement that "the area ahead is prone to traffic accidents."

[1358] Step 8: The terminal controls the brakes and accelerator when entering a nationally designated deceleration zone.

[1359] Specifically, it sends a deceleration command to the vehicle's ECU, activating the braking system to adjust the vehicle's speed.

[1360] Step 9: The device monitors the user's emotions using an emotion engine.

[1361] Specifically, it collects and analyzes the user's facial expressions and voice through a camera and microphone.

[1362] Step 10: The emotion engine identifies the user's emotional state.

[1363] Specifically, the collected data is used to determine whether the user is tense, stressed, or relaxed.

[1364] Step 11: The device takes appropriate action based on the emotional data sent from the emotion engine.

[1365] Specifically, if a user is feeling tense or stressed, relaxation content (such as music or audio guides) will be provided.

[1366] Step 12: The user receives announcements and relaxation content from the device and is encouraged to drive safely.

[1367] Specifically, this involves continuing to drive while paying attention and following voice instructions, and using relaxation content to maintain an appropriate mental state.

[1368] (Example 2)

[1369] 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".

[1370] Traffic accidents are a serious problem in daily life, and effective measures to prevent them are needed. However, current traffic information systems have difficulty providing real-time information on road conditions and accident-prone areas, and accident prevention measures are not functioning adequately. Furthermore, technologies to appropriately manage drivers' emotional states and support safe driving are not yet fully established. The challenge is to improve this situation, reduce the occurrence of traffic accidents, and appropriately manage drivers' mental states.

[1371] The identification processing by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a database means for distributing traffic accident-prone area information to the vehicle, a monitoring means for monitoring the surrounding situation using a camera and detection device mounted on the vehicle, a comparison means for comparing the traffic accident-prone area information stored in the internal storage device with the current location, a notification means for alerting the driver when approaching the relevant area, a control means for automatically reducing the vehicle's speed in government-designated deceleration areas, and an emotion analysis means for monitoring the user's emotional state and providing relaxation content as needed. This reduces the risk of accidents in traffic accident-prone areas and government-designated deceleration areas, and enables safe driving by appropriately managing the driver's emotional state.

[1372] "Information on areas with a high incidence of traffic accidents" refers to information on areas where traffic accidents frequently occur, identified based on past statistical data and information from traffic management organizations.

[1373] "Database means" refers to a system or device for organizing, storing, and managing specific data, and in this invention, it has the function of distributing information on areas with a high incidence of traffic accidents and areas where speed reduction is required to vehicles.

[1374] A "shooting device" refers to hardware for capturing images, such as a camera or video camera, and in this invention, it is a device mounted on a vehicle and used to monitor the surrounding environment.

[1375] A "detection device" is hardware such as a sensor or radar that detects specific physical changes or situations, and in this invention, it is a device mounted on a vehicle and used to monitor the surrounding conditions.

[1376] "Monitoring means" refers to a system or function that uses imaging devices and detection devices to observe and record the surrounding situation in real time.

[1377] "Internal memory" refers to hardware used to permanently or temporarily store data in a computer or electronic device, and in this invention, it is a device for storing information such as traffic accident-prone areas.

[1378] "Comparison means" refers to a system or function for comparing current location information with data stored in internal memory.

[1379] "Notification means" refers to a system or function that provides drivers with specific information or warnings via voice or visual means.

[1380] "Control means" refers to functions or systems for automatically adjusting the vehicle's speed, particularly those that reduce the vehicle's speed in deceleration areas.

[1381] "Emotional analysis means" refers to a system or function that collects and analyzes the user's facial expressions and voice to identify their emotional state, and provides relaxation content as needed.

[1382] This invention aims to prevent traffic accidents through a system installed in a vehicle, and also incorporates an emotion analysis function that monitors the user's emotional state while driving and supports safe driving. A specific embodiment of this invention is described below.

[1383] System Configuration

[1384] server:

[1385] The server acquires data in real time from traffic management agencies and manages information on accident-prone areas and government-designated speed-reducing areas. Since the server encrypts this information at night before distributing it to vehicles, a high-performance server and encryption software are required. Typical hardware used would be a standard high-performance server (e.g., a high-performance server series). Software used would include data collection and encryption software (e.g., an encryption library).

[1386] Terminal (in-vehicle system):

[1387] The terminal is installed in the vehicle and monitors the surrounding environment in real time through cameras and sensors. Based on this, it compares the current location with information on areas with a high incidence of traffic accidents and alerts the driver with a voice announcement when approaching a specific area. The terminal also has a function to automatically control the brakes and accelerator to reduce speed when entering a government-designated deceleration zone. Furthermore, it collects the user's facial expressions and voice and transmits them to an emotion analysis engine. The hardware required includes an in-vehicle camera, sensors (e.g., a series of detection devices), and an in-vehicle computer (e.g., an in-vehicle computer series). The software used includes real-time data analysis software and voice announcement software (e.g., voice announcement software).

[1388] Emotion analysis engine:

[1389] The emotion analysis engine collects the user's facial expressions and voice in real time through the in-vehicle camera and microphone, and identifies the user's emotional state by analyzing this data. For example, it can detect tension and stress by analyzing facial muscle movements and voice tone, and transmit this information to the terminal to provide relaxation content. The hardware used includes a camera, microphone (e.g., a series of imaging devices), and an in-vehicle computer. Software required includes facial expression analysis software and voice analysis software (e.g., a voice analysis API).

[1390] User (driver):

[1391] Users receive instructions and notifications from their devices through the in-vehicle display and voice assistant. For example, they may receive notifications such as "This area is prone to accidents" or the playback of relaxation music, allowing them to concentrate on driving and drive safely.

[1392] Specific example

[1393] Server-side example:

[1394] The server retrieves daily updated information on accident-prone areas from traffic management agencies at night and securely distributes it to vehicles using AES-256 encryption. This ensures that vehicles always receive the latest traffic information.

[1395] Specific examples on the terminal side:

[1396] The device monitors the situation ahead using cameras and sensors while driving in urban areas, and notifies the driver via voice message, "This is an area prone to accidents," when approaching an area with a high incidence of traffic accidents. Furthermore, it automatically applies the brakes and slows down the vehicle when entering a government-designated deceleration zone near a highway exit. Additionally, if the user is experiencing high levels of stress, a mood analysis engine plays relaxation music.

[1397] User-side examples:

[1398] Users listen to voice announcements from the system and drive with extra caution, especially in areas with a high incidence of traffic accidents. Based on notifications from the emotion analysis engine, users can continue to drive safely by using relaxation content to relax.

[1399] In this way, by implementing the present invention, it is possible not only to prevent traffic accidents and enable safe driving, but also to appropriately manage the user's mental state.

[1400] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1401] Step 1: Receive data from traffic management authorities.

[1402] The server receives the latest information on accident-prone areas and government-designated speed-reducing areas from traffic management agencies. This data is usually provided in XML or JSON format.

[1403] Input: Latest data from traffic management authorities

[1404] Data processing: Parsing (analysis) XML / JSON data and extracting necessary information.

[1405] Output: Extracted information on areas with a high incidence of traffic accidents and areas where speed reduction is required.

[1406] Step 2: Encrypt and store data

[1407] The server stores the received data in an internal database and encrypts the data using AES-256 encryption.

[1408] Input: Extracted information on areas with a high incidence of traffic accidents and areas where speed reduction is required.

[1409] Data processing: Data encryption

[1410] Output: Encrypted information on areas with a high incidence of traffic accidents and areas requiring reduced speed is stored in an internal database.

[1411] Step 3: Data distribution to the vehicle

[1412] The server delivers encrypted data to vehicles overnight. A secure communication protocol (e.g., HTTPS) is used during delivery.

[1413] Input: Encrypted traffic accident-prone area information and speed reduction area information

[1414] Data processing: None

[1415] Output: Encrypted data delivered to the vehicle

[1416] Step 4: Receiving and storing data by the vehicle

[1417] The terminal receives encrypted data sent from the server overnight and stores it in its internal memory. It then verifies the integrity of the data and checks for any missed data or data corruption.

[1418] Input: Encrypted data delivered from the server

[1419] Data processing: Data integrity check and decryption

[1420] Output: Data stored in internal memory

[1421] Step 5: Real-time monitoring of the surrounding environment

[1422] The terminal uses cameras and sensors mounted on the vehicle to monitor the surrounding environment in real time. Data is collected every second to measure the distance to vehicles and obstacles ahead.

[1423] Input: Real-time data from cameras and sensors

[1424] Data processing: Analysis of image and sensor data

[1425] Output: Analysis results of the surrounding environment

[1426] Step 6: Notification of areas with a high incidence of traffic accidents

[1427] The device compares the current location with data in its internal memory, and if it approaches an area prone to traffic accidents or a slow-down zone, it notifies the driver with a voice announcement saying, "You are in an area prone to accidents ahead."

[1428] Input: Current location data, information on areas with a high incidence of traffic accidents stored in internal memory.

[1429] Data processing: Comparison of current location and area information

[1430] Output: Voice notification to the driver

[1431] Step 7: Automatic deceleration control

[1432] The device automatically controls the brakes and accelerator when entering a government-designated deceleration zone, safely reducing the vehicle's speed.

[1433] Input: Current location data, internal memory deceleration area information

[1434] Data processing: Deceleration area detection and control signal generation.

[1435] Output: Vehicle deceleration control signal

[1436] Step 8: Monitoring the user's emotional state

[1437] The device uses an in-car camera and microphone to collect the user's facial expressions and voice in real time and transmit them to an emotion analysis engine.

[1438] Input: Real-time data from camera and microphone

[1439] Data processing: Collection and transmission of facial expression and voice data.

[1440] Output: Data sent to the emotion analysis engine

[1441] Step 9: Emotion Analysis

[1442] The emotion analysis engine analyzes the received data to identify the user's emotional state. For example, it analyzes facial muscle movements and voice tone.

[1443] Input: Facial expressions and audio data from the device.

[1444] Data processing: Data analysis

[1445] Output: Identified emotional state (e.g., tension, stress, relaxation)

[1446] Step 10: Determine the necessary actions

[1447] The emotion analysis engine determines the necessary action (e.g., playing relaxation music) based on the identified emotional state and notifies the device.

[1448] Input: Emotional state data from the analysis results

[1449] Data processing: Action decision algorithm

[1450] Output: Action instructions for the terminal

[1451] Step 11: System notifications and driving operations

[1452] Users receive notifications from their devices via the in-car display and audio system, enabling them to drive safely.

[1453] Input: Notifications from the device

[1454] Data processing: None

[1455] Output: Implementation of safe driving

[1456] Step 12: Use relaxation content

[1457] Based on notifications from the emotion analysis engine, users utilize relaxation content as needed to maintain an appropriate mental state.

[1458] Input: Relaxation content playback notification from emotion analysis engine

[1459] Data processing: None

[1460] Output: Use of relaxation content and stabilization of mental state

[1461] This clarifies the specific actions, inputs, and outputs performed at each processing step, making the overall system process easier to understand.

[1462] (Application Example 2)

[1463] 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".

[1464] Conventional autonomous driving and driver assistance systems primarily aimed to ensure safety in accident-prone areas and speed-reducing zones, but they lacked sufficient measures to address the driver's emotional state. Despite the known fact that tension and stress negatively impact driving, there was a lack of methods to address these emotions. As a result, the risk of accidents increased, hindering safe driving. This invention aims to solve these problems and improve driver safety and comfort.

[1465] In Application Example 2, the identification processing by the identification processing unit 290 of the data processing device 12 is realized by the following means. In this invention, the server includes a database means for distributing traffic accident-prone area information to the vehicle, a monitoring means for monitoring the surrounding situation using cameras and sensors mounted on the vehicle, a comparison means for comparing the traffic accident-prone area information stored in internal memory with the current location, an announcement means for alerting the driver when approaching the relevant area, a control means for automatically reducing the vehicle's speed in nationally designated deceleration areas, an emotion engine for collecting and analyzing the user's facial expressions and voice in real time, and a means for providing relaxation content when it is detected that the user's emotional state is tension or stress. This not only prevents traffic accidents but also reduces the driver's mental stress, enabling safer and more comfortable driving.

[1466] "Information on areas with a high incidence of traffic accidents" refers to data on areas where traffic accidents have occurred frequently in the past.

[1467] A "database system" is a system that organizes and stores information, making it available for retrieval as needed.

[1468] "Cameras and sensors" are devices that acquire visual information and environmental data from the surroundings.

[1469] "Monitoring means" refers to the function of checking the surrounding situation in real time using cameras and sensors.

[1470] The "comparison means" is a function that compares the current location of the vehicle with information stored in advance.

[1471] An "announcement system" is a device that uses voice to convey important information to the driver.

[1472] A "control system" is a function that automatically adjusts the vehicle's speed and operation under specific conditions.

[1473] An "emotion engine" is a system that analyzes a user's emotional state based on their facial expressions and voice.

[1474] "Relaxation content" refers to content such as music and videos provided to reduce users' tension and stress.

[1475] System Configuration

[1476] Server side

[1477] The server manages information on areas with a high incidence of traffic accidents and receives the latest information from the traffic management center. This information is periodically distributed to connected vehicles using an encrypted and secure communication protocol. The server works in conjunction with the traffic information database to collect and distribute data.

[1478] Vehicle terminal side

[1479] The vehicle terminal monitors the surrounding environment through cameras and various sensors built into the vehicle. Its internal memory stores information on accident-prone areas and nationally designated deceleration areas received from the server, and it compares this information with the vehicle's current location.

[1480] When approaching a specific area, the system alerts the driver via the in-car display and voice assistant. Furthermore, it includes a function that automatically controls the vehicle's speed when entering a deceleration zone.

[1481] Emotional Engine

[1482] The emotion engine collects and analyzes the driver's facial expressions and voice in real time through cameras and microphones installed in the vehicle. If the system determines that the driver is experiencing tension or stress, the emotion engine sends emotional data to the device, and relaxation content is provided. This relaxation content, including music and videos, is designed to stabilize the driver's mental state.

[1483] Specific example

[1484] For example, if a vehicle is driving through an urban area and approaches an area prone to frequent traffic accidents, the terminal will announce, "This is an area where accidents frequently occur." Also, when entering a government-designated deceleration zone near a highway exit, the terminal will automatically apply the brakes and reduce the vehicle's speed.

[1485] Furthermore, if the emotional engine detects that the driver is feeling tense or stressed, relaxation music will automatically play. In this way, the driver can relax while maintaining a focus on safe driving.

[1486] Example of a prompt

[1487] Please generate an audio announcement for when a driver approaches an area with a high incidence of traffic accidents. For example, it should include the following: "Warning: You are approaching an accident-prone area."

[1488] Additionally, if tension is detected from the driver's facial expressions captured by the camera, display the message "User stress detected. Relaxation content will be provided," and generate a prompt to play relaxation music.

[1489] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1490] Step 1:

[1491] The server receives information on accident-prone areas and nationally designated speed reduction areas from the traffic management center. The received data is encrypted and distributed to vehicles using a secure communication protocol. The input is data from the traffic management center, and the output is encrypted traffic information data.

[1492] Step 2:

[1493] The terminal receives traffic information data distributed from the server and stores it in its internal memory. The input is encrypted traffic information data from the server, and the output is the state of the data stored in the terminal's internal memory. Specifically, the terminal automatically connects to the server at night to download and store the data.

[1494] Step 3:

[1495] The camera and sensors mounted on the device monitor the surrounding environment in real time. Input is raw data from the camera and sensors, and output is analyzed data of the surrounding environment. Specifically, the camera captures image data, and the sensors collect environmental data.

[1496] Step 4:

[1497] The device compares the current location with accident-prone area information stored in its internal memory and alerts the driver with a voice announcement when approaching a specific area. Inputs are current location data from the built-in GPS and accident-prone area information from internal memory; output is a voice announcement. Specifically, it periodically compares the current location with the accident-prone area information.

[1498] Step 5:

[1499] When the terminal enters a nationally designated deceleration zone, it automatically controls the brakes and accelerator to reduce the vehicle's speed. Inputs include current location data from the built-in GPS and deceleration zone information stored in internal memory, while output is the decelerated vehicle status. Specifically, when the vehicle enters a deceleration zone, the speed control system activates.

[1500] Step 6:

[1501] The emotion engine collects the driver's facial expressions and voice in real time through cameras and microphones inside the vehicle and analyzes their emotional state. The input is facial and voice data from the cameras and microphones, and the output is the analyzed emotional state of the driver. Specifically, the collected data is analyzed using an algorithm to detect tension and stress.

[1502] Step 7:

[1503] When the emotion engine detects the driver's tension or stress, it notifies the device and provides relaxation content. The input is emotional state data from the emotion engine, and the output is the relaxation content to be played. Specifically, when stress is detected, the device plays pre-set relaxation music or video.

[1504] Step 8:

[1505] The user checks notifications from their device via the in-car display and audio system. Input is notification data from the device, and output is the user's actions (e.g., driving operations or relaxation). Specifically, the user performs driving operations according to voice announcements and uses relaxation content as needed.

[1506] 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.

[1507] 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.

[1508] 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.

[1509] 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.

[1510] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[1511] 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.

[1512] 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.

[1513] 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.

[1514] 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."

[1515] 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.

[1516] 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.

[1517] 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.

[1518] 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.

[1519] 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.

[1520] 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.

[1521] 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.

[1522] 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.

[1523] 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.

[1524] 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.

[1525] 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.

[1526] 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 to be incorporated by reference.

[1527] The following is further disclosed regarding the embodiments described above.

[1528] (Claim 1)

[1529] A database system that distributes information on areas with a high incidence of traffic accidents to vehicles,

[1530] A monitoring means that monitors the surrounding situation using cameras and sensors mounted on the vehicle,

[1531] A comparison means for matching the current location with information on areas with a high incidence of traffic accidents stored in internal memory,

[1532] An announcement system to alert the driver when approaching the area,

[1533] A control means for automatically reducing the speed of a vehicle in a nationally designated deceleration area,

[1534] A system that includes this.

[1535] (Claim 2)

[1536] The system according to claim 1, wherein the database means is a server that receives data from a traffic management center and distributes it to vehicles.

[1537] (Claim 3)

[1538] The system according to claim 1, wherein the monitoring means monitors the surrounding conditions in real time using a plurality of cameras and sensors mounted on the vehicle.

[1539]

[1540] "Example 1"

[1541] (Claim 1)

[1542] A database system that distributes information on areas with a high incidence of traffic accidents to vehicles,

[1543] A monitoring means that monitors the surrounding situation using cameras and sensors mounted on the vehicle,

[1544] A storage method that saves traffic accident-prone area information received from a server every night into internal memory,

[1545] A comparison means for matching the current location with information on areas with a high incidence of traffic accidents stored in internal memory,

[1546] An announcement system to alert the driver when approaching the area,

[1547] A control means for automatically reducing the speed of a vehicle in a nationally designated deceleration area,

[1548] A system that includes this.

[1549] (Claim 2)

[1550] The system according to claim 1, wherein the database means is a server that receives data from a traffic management center and distributes it to vehicles.

[1551] (Claim 3)

[1552] The system according to claim 1, wherein the monitoring means monitors the surrounding conditions in real time using a plurality of cameras and sensors mounted on the vehicle.

[1553] "Application Example 1"

[1554] (Claim 1)

[1555] A database system that distributes information on areas with a high incidence of traffic accidents to vehicles,

[1556] A monitoring means that monitors the surrounding situation using cameras and sensors mounted on the vehicle,

[1557] A comparison means for matching the current location with information on areas with a high incidence of traffic accidents stored in internal memory,

[1558] An announcement system to alert the driver when approaching the area,

[1559] A control means for automatically reducing the speed of a vehicle in a nationally designated deceleration area,

[1560] A notification means that compares location information acquired by the aforementioned monitoring means with accident-prone area information in real time and provides visual and audible notifications in cooperation with a smartphone or head-mounted display,

[1561] A system that includes this.

[1562] (Claim 2)

[1563] The system according to claim 1, wherein the database means is a server that receives data from a traffic management center and distributes it to vehicles.

[1564] (Claim 3)

[1565] The system according to claim 1, wherein the monitoring means monitors the surrounding situation in real time using a plurality of cameras and sensors mounted on the vehicle, and the notification means generates a prompt message regarding areas with a high incidence of traffic accidents using a generation AI model and provides it to the driver.

[1566] "Example 2 of combining an emotion engine"

[1567] (Claim 1)

[1568] A database system that distributes information on areas with a high incidence of traffic accidents to vehicles,

[1569] A monitoring means that monitors the surrounding situation using a camera and detection device mounted on the vehicle,

[1570] A comparison means for matching the current location with information on areas with a high incidence of traffic accidents stored in an internal memory device,

[1571] A notification system to alert the driver when approaching the area,

[1572] A control means for automatically reducing the speed of a vehicle in a government-designated deceleration area,

[1573] An emotion analysis means that monitors the user's emotional state and provides relaxation content as needed,

[1574] A system that includes this.

[1575] (Claim 2)

[1576] The system according to claim 1, wherein the database means is a server that receives data from a traffic management organization and distributes it to vehicles.

[1577] (Claim 3)

[1578] The system according to claim 1, wherein the monitoring means monitors the surrounding conditions in real time using a plurality of camera and detection devices mounted on the vehicle.

[1579] "Application example 2 when combining with an emotional engine"

[1580] (Claim 1)

[1581] A database system that distributes information on areas with a high incidence of traffic accidents to vehicles,

[1582] A monitoring means that monitors the surrounding situation using cameras and sensors mounted on the vehicle,

[1583] A comparison means for matching the current location with information on areas with a high incidence of traffic accidents stored in internal memory,

[1584] An announcement system to alert the driver when approaching the area,

[1585] A control means for automatically reducing the speed of a vehicle in a nationally designated deceleration area,

[1586] An emotion engine that collects and analyzes the user's facial expressions and voice in real time,

[1587] A means of providing relaxation content when it is detected that the user's emotional state is one of tension or stress,

[1588] A system that includes this.

[1589] (Claim 2)

[1590] The system according to claim 1, wherein the database means is a server that receives data from a traffic management center and distributes it to vehicles.

[1591] (Claim 3)

[1592] The system according to claim 1, wherein the monitoring means monitors the surrounding conditions in real time using a plurality of cameras and sensors mounted on the vehicle. [Explanation of symbols]

[1593] 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 database system that distributes information on areas with a high incidence of traffic accidents to vehicles, A monitoring means that monitors the surrounding situation using cameras and sensors mounted on the vehicle, A comparison means for matching the current location with information on areas with a high incidence of traffic accidents stored in internal memory, An announcement system to alert the driver when approaching the area, A control means for automatically reducing the speed of a vehicle in a nationally designated deceleration area, A system that includes this.

2. The system according to claim 1, wherein the database means is a server that receives data from a traffic management center and distributes it to vehicles.

3. The system according to claim 1, wherein the monitoring means monitors the surrounding conditions in real time using a plurality of cameras and sensors mounted on the vehicle.

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