Data processing device, data processing method, and data processing program

Abstract

To provide a data processing device capable of utilizing event data recorder information more easily compared to conventional technologies, a data processing method, and a data processing program.SOLUTION: A data processing device comprises: an input unit 292 which acquires user data; and a processing unit 294 which performs specific processing using a data generation model which generates predetermined inference results according to the user data. The input unit 292, as the user data, acquires event data recorder information recorded by an event data recorder installed in a vehicle when an accident occurs in the vehicle on which the user rides. The processing unit 294, as specific processing, performs processing for generating analysis support information for assisting the analysis of event recorder information using the output of the data generation model when at least a part of the event data recorder information is input.SELECTED DRAWING: Figure 4

Description

[Technical Field]

[0001] The technology of the present disclosure relates to a data processing device, a data processing method, and a data processing program. [Background technology]

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description of the chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] However, the conventional technology has room for improvement in terms of easily using event data recorder information, which is information recorded in an EDR (Event Data Recorder, hereinafter also referred to as "event data recorder") installed in a user's vehicle. [Means for solving the problem]

[0005] A first aspect of the technology disclosed herein is a data processing device that includes an input unit that acquires user data, and a processing unit that performs specific processing using a data generation model that generates a predetermined inference result according to the user data, wherein the input unit acquires, as the user data, event data recorder information recorded by an event data recorder installed in a vehicle in which a user is riding when an accident occurs, and the processing unit performs, as the specific processing, a process of generating analysis support information for assisting in analysis of the event data recorder information, using the output of the data generation model when at least a portion of the event data recorder information is input.

[0006] A second aspect of the technology of the present disclosure is a data processing method that acquires user data and performs specific processing using a data generation model that generates a predetermined inference result according to the user data, wherein when an accident occurs in a vehicle in which a user is riding, event data recorder information recorded by an event data recorder installed in the vehicle is acquired as the user data, and the specific processing is performed by using the output of the data generation model when at least a portion of the event data recorder information is input to generate analysis support information for assisting in the analysis of the event data recorder information.

[0007] A third aspect of the technology of the present disclosure is a data processing program that causes a computer to execute a process of acquiring user data and performing specific processing using a data generation model that generates a predetermined inference result according to the user data, wherein when an accident occurs in a vehicle in which a user is riding, event data recorder information recorded by an event data recorder installed in the vehicle is acquired as the user data, and analysis support information for assisting in analysis of the event data recorder information is generated using the output of the data generation model when at least a portion of the event data recorder information is input. [Brief explanation of the drawings]

[0008] [Figure 1] FIG. 1 is a conceptual diagram illustrating an example of a configuration of a data processing system. [Figure 2] FIG. 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device. [Figure 3] FIG. 10 is a schematic diagram illustrating an outline of a specific process. [Figure 4] 2 is a block diagram illustrating a schematic functional configuration of a specific processing unit of the data processing device. FIG. [Figure 5] 10 is a flowchart illustrating an example of an operation flow of a specific process performed by a data processing device. [Figure 6] FIG. 10 is a diagram showing an example of a display screen for analysis support information. [Figure 7] FIG. 10 is a diagram showing an example of a display screen for analysis support information. [Figure 8] FIG. 10 is a diagram showing an example of a display screen of three-dimensional trace information. DETAILED DESCRIPTION OF THE INVENTION

[0009] Hereinafter, exemplary embodiments of a data processing device, a data processing method, and a data processing program according to the techniques of the present disclosure will be described with reference to the accompanying drawings.

[0010] First, the terms used in the following description will be explained.

[0011] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, the processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), or a TPU (Tensor Processing Unit).

[0012] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0013] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0014] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0015] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0016] FIG. 1 shows an example of the configuration of a data processing system 10 according to the embodiment.

[0017] As shown in FIG. 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a cloud server. An example of the smart device 14 is a smartphone. In this embodiment, the data processing device 12 is an example of a "data processing device" according to the technology of the present disclosure. The smart device 14 according to this embodiment is owned by a user.

[0018] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0019] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0020] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. A control unit 46A, which will be described later, transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, a specific processing unit 290, which will be described later, acquires the data indicating the user input.

[0021] The output device 40 is equipped with a display 40A, a speaker 40B, etc., and presents data to the user by outputting the data in a form of expression that the user can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0022] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0023] The smart device 14 according to this embodiment is capable of wireless communication with an event data recorder 80 and a drive recorder 82 mounted in a vehicle in which a user is riding. In this embodiment, Wi-Fi (registered trademark) is used as the wireless communication method, but other short-range communication methods such as Bluetooth (registered trademark) may also be used. The control unit 46A of the smart device 14 according to this embodiment transmits various pieces of information received from the event data recorder 80 and the drive recorder 82 to the data processing device 12.

[0024] The event data recorder 80 records information that cannot be recorded by a drive recorder, and in Japan, it will be mandatory for all new vehicles to be equipped with such a recorder from July 2022. The event data recorder information recorded by the event data recorder 80 includes information such as the acceleration, speed, seat belt status (driver), brake on / off status, accelerator open / close status, engine RPM, yaw rate, seat position, etc. of the vehicle in which it is installed.

[0025] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0026] As shown in FIG. 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "data processing program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0027] Two data generation models, a first data generation model 58A and a second data generation model 58B, are stored in the storage 32. The first data generation model 58A and the second data generation model 58B are used by the specification processing unit 290.

[0028] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0029] Next, the processing of the specific processing unit 290 when the data processing device 12 performs specific processing that enables the event data recorder information recorded by the event data recorder 80 to be easily used will be described.

[0030] A schematic diagram showing an overview of the identification process according to this embodiment is shown in Fig. 3. As shown in Fig. 3, the identification process according to this embodiment is roughly divided into two stages of processing.

[0031] When an accident occurs in a vehicle to be processed (hereinafter referred to as the "processing target vehicle"), the control unit 46A of the smart device 14 carried by the user riding in the processing target vehicle receives event data recorder information from the event data recorder 80 mounted on the processing target vehicle as the above-mentioned reception and output process, and outputs (uploads) the information to the data processing device 12. At this time, the control unit 46A of the smart device 14 acquires location information from the drive recorder 82, and also uploads the acquired location information to the data processing device 12 together with the event data recorder information.

[0032] Therefore, in the first stage of the identification process executed by the data processing device 12, the event data recorder information and location information are received and acquired from the smart device 14, and the event data recorder information is converted into a format for a CDR (Crash Data Retrieval) tool. Then, in the first stage of the identification process, analysis support information for supporting analysis of the event data recorder information is generated using at least a portion of the converted event data recorder information (in this embodiment, all of the information), the location information, and the first data generation model 58A.

[0033] In addition, in the second stage of the identification process, at least a portion of the converted event data recorder information (in this embodiment, all of the information), the location information, and the second data generation model 58B are used to generate three-dimensional trace information that reproduces the movement of the vehicle being processed in an accident that occurred to the vehicle being processed as three-dimensional movement in an image.

[0034] In the data processing device 12 according to this embodiment, by using 2D map data in the first stage of identification processing, the first data generation model 58A generates 2D image information, which represents the situation of an accident that occurred in the processing target vehicle as a 2D image, as analysis support information. In addition, in the data processing device 12 according to this embodiment, by using 3D map data in the second stage of identification processing, the second data generation model 58B generates the above-mentioned 3D trace information. In this embodiment, the 2D map data and 3D map data are acquired via the network 54 from data publicly available on the Internet.

[0035] In the data processing device 12 according to the present embodiment, both image information and text information are applied as the analysis support information, but the present invention is not limited to this. For example, only either image information or text information may be applied as the analysis support information, or audio information may be applied as the analysis support information in addition to or instead of the image information or text information.

[0036] Furthermore, in the data processing device 12 according to the present embodiment, the image information is applied in the form of both first image information (the above-mentioned two-dimensional image information) that shows the accident situation by superimposing it on an image showing the road on which the accident occurred, and second image information that shows at least part of the event data recorder information in the form of a graph, but this is not limitative. For example, only one of the first image information and the second image information may be applied as the image information, or in addition to or instead of this information, information that shows the event data recorder information as a schematic diagram may be applied as the image information.

[0037] Furthermore, in the data processing device 12 according to the present embodiment, information expressing the accident situation in text form is used as the text information, but the present invention is not limited to this. For example, information expressing in text form the events that can be grasped from the graphs described above may be used as the text information.

[0038] As shown in FIG. 4, the specific processing unit 290 includes an input unit 292 and a processing unit 294.

[0039] The input unit 292 acquires user data transmitted from the smart device 14. Specifically, the input unit 292 acquires data including event data recorder information and location information transmitted from the smart device 14.

[0040] The processing unit 294 performs identification processing using the first data generation model 58A and the second data generation model 58B. Specifically, the processing unit 294 inputs at least a portion of the event data recorder information, location information, and two-dimensional map data into the first data generation model 58A, and obtains analysis support information including the above-mentioned two-dimensional image information as a generation result. Also, the processing unit 294 inputs at least a portion of the event data recorder information, location information, and three-dimensional map data into the second data generation model 58B, and obtains the above-mentioned three-dimensional trace information as a generation result.

[0041] Incidentally, vehicle accidents may involve only one vehicle, such as collisions with guardrails or signs, or collisions with pedestrians, but in many cases multiple vehicles are involved, such as collisions between vehicles or rear-end collisions.

[0042] Therefore, when the accident involves another vehicle other than the processing target vehicle, the input unit 292 according to this embodiment further acquires event data recorder information and location information of the other vehicle. Then, the processing unit 294 according to this embodiment performs identification processing using the output of the first data generation model 58A when at least a portion of the event data recorder information acquired from the other vehicle is further input. Furthermore, the processing unit 294 according to this embodiment performs identification processing by generating three-dimensional trace information using the output of the second data generation model 58B when at least a portion of the event data recorder information acquired from the other vehicle and location information are further input.

[0043] The first data generation model 58A and the second data generation model 58B are so-called generative AI (Artificial Intelligence). An example of these data generation models 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ) and other generation AIs. The first data generation model 58A and the second data generation model 58B are obtained by performing deep learning on a neural network. A prompt including an instruction is input to the first data generation model 58A and the second data generation model 58B, and inference data such as text data indicating text or image data indicating an image is also input. The first data generation model 58A and the second data generation model 58B perform inference on the input inference data in accordance with the instruction indicated by the prompt, and output the inference result in a data format such as image data or text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0044] Next, the operation of the data processing system 10 will be described.

[0045] An example of the flow of the identification process will be described with reference to FIG. 5. The flow of the identification process shown in FIG. 5 is an example of a "data processing method" according to the technology of the present disclosure. The identification process according to this embodiment is executed when the input unit 292 in the data processing device 12 receives event data recorder information and location information from at least one vehicle (corresponding to the "processing target vehicle" described above). To avoid confusion, the following description will be given assuming that different accidents do not occur simultaneously in multiple locations. In other words, when event data recorder information and location information are received simultaneously from multiple vehicles, it is assumed that a single accident involving those multiple vehicles has occurred.

[0046] In step S300, the processing unit 294 converts the received event data recorder information into a CDR tool format. At this time, if there are multiple target vehicles, the processing unit 294 assumes that an accident involving these multiple target vehicles has occurred. In this case, the processing unit 294 converts the event data recorder information received from the multiple target vehicles into a CDR tool format.

[0047] In step S302, the input unit 292 acquires, via the network 54, two-dimensional map data and three-dimensional map data corresponding to the position indicated by the received position information. At this time, even if there are multiple vehicles to be processed, the position information indicates approximately the same position. Therefore, the two-dimensional map data and three-dimensional map data acquired here are for the same location.

[0048] In step S304, the processing unit 294 generates a prompt including an instruction statement instructing the generation of the above-mentioned analysis support information.

[0049] In step S306, the processing unit 294 generates the above-mentioned analysis support information by inputting the generated prompt into the first data generation model 58A together with at least a portion of the converted event data recorder information, location information, and two-dimensional map data.

[0050] In step S308, the processing unit 294 outputs (registers) the generated analysis support information to a predetermined device (in this embodiment, the storage 32).

[0051] In step S310, the processing unit 294 generates a prompt including an instruction sentence instructing the generation of the above-mentioned three-dimensional trace information.

[0052] In step S312, the processing unit 294 generates the above-mentioned three-dimensional trace information by inputting the generated prompt into the second data generation model 58B together with at least a portion of the converted event data recorder information, location information, and three-dimensional map data.

[0053] In step S314, the processing unit 294 outputs (registers) the generated three-dimensional trace information to a predetermined device (the storage 32 in this embodiment), and ends the identification process.

[0054] The analysis support information and three-dimensional trace information obtained by this identification process are referenced by non-life insurance companies that provide compensation for the accident that has occurred, and by courts and other organizations in the event of a lawsuit regarding the accident.

[0055] An example of a display screen of the analysis support information registered by the processing of step S308 is shown in Fig. 6. Note that the example shown in Fig. 6 is a display example of a two-dimensional image indicated by the first image information.

[0056] As shown in Fig. 6, this display screen displays a plan view of a situation in which two vehicles, vehicle A and vehicle B, collide with each other while vehicle A is turning right and vehicle B is traveling straight ahead. Therefore, by referring to the display screen, the situation of the accident that has occurred can be intuitively grasped.

[0057] In this case, the first data generation model 58A may be configured to also generate text that describes the circumstances of the accident, and the text may also be displayed, as shown in Fig. 6. In this manner, the circumstances of the accident that occurred can be objectively grasped as the circumstances indicated by the event data recorder information.

[0058] 7 shows an example of a display screen of the analysis support information registered by the processing of step S308. The example shown in Fig. 7 is a display example of a graph showing multiple types of information such as vehicle speed, braking operation, etc. in the event data recorder information as the second image information.

[0059] As shown in Figure 7, this display screen displays chronological graphs of multiple types of information from the event data recorder information on the same time axis, all the way up to the time of the collision. Therefore, by referring to this display screen, it is possible to understand the progression of various data leading up to the occurrence of the accident.

[0060] Furthermore, Fig. 8 shows an example of a display screen of the three-dimensional trace information registered by the processing of step S314. Note that for convenience, Fig. 8 only shows the target vehicle, road, and crosswalk, but in reality, other things that exist at the location are also displayed. Also, in the example shown in Fig. 8, the vehicles are displayed as line drawings, but each vehicle may also be displayed as a three-dimensional image that imitates the actual model of the target vehicle.

[0061] As shown in Fig. 8, on this display screen, multiple vehicles involved in the accident (two vehicles, vehicle A and vehicle B, in the example shown in Fig. 8) are displayed as a three-dimensional video, including the surrounding situation. Therefore, by referring to this display screen, the situation of the accident can be grasped more realistically than when it is displayed as a two-dimensional trace.

[0062] As described above, the data processing system 10 according to this embodiment includes an input unit 292 that acquires user data, and a processing unit 294 that performs identification processing using a first data generation model 58A and a second data generation model 58B that generate a predetermined inference result according to the user data. The input unit 292 acquires, as user data, event data recorder information recorded by an event data recorder installed in a vehicle in which a user is riding when an accident occurs. The processing unit 294 performs the identification processing by using the output of the first data generation model 58A when at least a portion of the event data recorder information is input to generate analysis support information for supporting analysis of the event data recorder information. Therefore, the event data recorder information can be used more easily than with conventional techniques.

[0063] Furthermore, in the data processing system 10 according to this embodiment, the input unit 292 further acquires position information indicating the position of the vehicle during a predetermined period including the time when the accident occurred (in this embodiment, the time when the accident occurred), and the processing unit 294 further traces the movement of the vehicle using at least a part of the event data recorder information and the output of the second data generation model 58B when the position information was input. Therefore, the situation of the accident that occurred can be grasped more realistically.

[0064] Furthermore, in the data processing system 10 according to this embodiment, the processing unit 294 performs tracing by further using geographical data, thereby making it possible to recreate the situation in which an accident occurred in a more realistic manner.

[0065] Furthermore, in the data processing system 10 according to this embodiment, the input unit 292 acquires geographic data from data publicly available on the Internet. Therefore, the effects of the disclosed technology can be enjoyed at a lower cost.

[0066] Furthermore, in the data processing system 10 according to this embodiment, if the accident involves another vehicle other than the vehicle, the input unit 292 further acquires event data recorder information and position information of the other vehicle, and the processing unit 294 traces the movements of the vehicle and the other vehicle using the output of the second data generation model 58B when at least a portion of the event data recorder information acquired from the other vehicle and the position information are further input. Therefore, the circumstances of the accident that has occurred can be grasped more realistically.

[0067] Furthermore, in the data processing system 10 according to this embodiment, at least one of image information and text information is used as the analysis support information. Therefore, the situation of the accident that has occurred can be understood by at least one of the image and the text.

[0068] Furthermore, in the data processing system 10 according to the present embodiment, at least one of first image information that shows the situation of the accident by superimposing it on an image showing the road on which the accident occurred, and second image information that shows at least part of the event data recorder information in the form of a graph is applied as the image information. Therefore, the situation of the accident that has occurred can be grasped by referring to the applied first image information and second image information.

[0069] Furthermore, in the data processing system 10 according to this embodiment, if the accident involves another vehicle other than the vehicle, the input unit 292 further acquires event data recorder information of the other vehicle, and the processing unit 294 performs identification processing using the output of the first data generation model 58A when at least a portion of the event data recorder information acquired from the other vehicle is further input. Therefore, the situation of the accident that has occurred can be intuitively grasped, including the situation of the other vehicle.

[0070] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[0071] In the above embodiment, an example was given in which a specific process is performed by one computer 22, but the technology disclosed herein is not limited to this, and distributed processing of the specific process may be performed by multiple computers including computer 22.

[0072] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[0073] 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.

[0074] It is not necessary to store all 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 all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[0075] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[0076] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with 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). Also, the hardware resource that executes the specific processing may be a single processor.

[0077] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[0078] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[0079] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[0080] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[0081] For example, in the above embodiment, the data processing device of the present disclosure is described as being applied to the data processing device 12 configured as a cloud server, but the present disclosure is not limited to this. For example, the data processing device of the present disclosure may be applied to a smart device 14. Furthermore, the data processing device of the present disclosure may be applied to various devices mounted on a vehicle, such as an event data recorder 80 and a drive recorder 82.

[0082] In the above embodiment, the case where the event data recorder information is uploaded to the data processing device 12 via the smart device 14 has been described, but the present invention is not limited to this. For example, the event data recorder information may be uploaded directly from the event data recorder 80 to the data processing device 12, or may be uploaded to the data processing device 12 via another in-vehicle device such as the drive recorder 82.

[0083] In the above embodiment, the image indicated by the analysis support information and the image indicated by the 3D trace information are generated using map data provided free of charge on the Internet, but the present invention is not limited to this. For example, map data created specifically for this system may be used, or if a camera such as a surveillance camera or an AI camera is installed at the location where the accident occurred, images captured by the camera may be used.

[0084] In the above embodiment, the location information indicating the location of the vehicle is obtained from the drive recorder 82. However, the present invention is not limited to this. For example, if the smart device 14 is equipped with a GPS (Global Positioning System) function, the location information may be obtained using the GPS function. Alternatively, if another in-vehicle device is equipped with a GPS function, the location information may be obtained using the GPS function. Furthermore, instead of obtaining the location information using the GPS function, the location information may be obtained using a beacon.

[0085] In the above embodiment, the analysis support information and the three-dimensional trace information are generated using two data generation models, the first data generation model 58A and the second data generation model 58B, but the present invention is not limited to this. For example, the first data generation model 58A may be configured to also output the three-dimensional trace information generated by the second data generation model 58B, thereby combining these two models into a single data generation model.

[0086] In the above embodiment, the first data generation model 58A uses position information indicating the vehicle's position, but the present invention is not limited to this. For example, if the analysis support information does not include the first image information and only the second image information, i.e., the graph described above, is generated, the position information may not be used. Furthermore, if the map indicated by the two-dimensional map data or three-dimensional map data is not superimposed on the two-dimensional image information or three-dimensional trace information, the position information is not necessarily required.

[0087] In the above embodiment, various processes are performed after the event data recorder information is converted into the CDR tool format, but the present invention is not limited to this. For example, various processes may be performed without converting the event data recorder information into the CDR tool format.

[0088] In the above embodiment, the data processing device of the present disclosure is described as being applied to a case where different accidents do not occur simultaneously in multiple locations, but the present disclosure is not limited to this case. For example, it goes without saying that the data processing device of the present disclosure may be applied to a case where different accidents occur simultaneously in multiple locations.

[0089] In the above embodiment, three-dimensional trace information indicating a three-dimensional trace is used as information for tracing the movement of a vehicle, but the present invention is not limited to this. For example, two-dimensional trace information indicating a two-dimensional trace may be used as information for tracing the movement of a vehicle.

[0090] Furthermore, in the above embodiment, the case where the event data recorder information is uploaded to the data processing device 12 when an accident occurs to the vehicle has been described, but the present invention is not limited to this. For example, the event data recorder information may be uploaded to the data processing device 12 immediately before the accident occurs or when a predetermined period of time has elapsed since the accident occurred.

[0091] In relation to the above, the following additional notes are further disclosed.

[0092] <Appendix 1> an input unit for acquiring user data; a processing unit that performs a specific process using a data generation model that generates a predetermined inference result according to the user data, the input unit acquires, as the user data, event data recorder information recorded by an event data recorder mounted on a vehicle in which the user is riding when an accident occurs; the processing unit performs, as the identification process, a process of generating analysis support information for supporting analysis of the event data recorder information, using an output of the data generation model when at least a part of the event data recorder information is input. Data processing device. <Appendix 2> the input unit further acquires location information indicating a location of the vehicle during a predetermined period including a time point when the accident occurred; the processing unit further traces the movement of the vehicle using an output of the data generation model when at least a part of the event data recorder information and the position information are input. 2. A data processing device according to claim 1. <Appendix 3> the processing unit further uses geographic data to perform the tracing. 3. A data processing device according to claim 2. <Appendix 4> the input unit acquires the geographic data from data publicly available on the Internet; 4. A data processing device according to claim 3. <Appendix 5> When the accident is an accident involving another vehicle other than the vehicle, the input unit further acquires the event data recorder information and the location information of the other vehicle; the processing unit traces movements of the vehicle and the other vehicle using an output of the data generation model when at least a part of the event data recorder information acquired from the other vehicle and the position information are further input. 5. A data processing device according to any one of claims 2 to 4. <Appendix 6> The analysis support information is at least one of image information and text information. 6. A data processing device according to any one of claims 1 to 5. <Appendix 7> The image information is at least one of first image information that shows the situation of the accident by superimposing it on an image showing the road on which the accident occurred, and second image information that shows at least part of the information of the event data recorder information in a graph. 7. A data processing device according to claim 6. <Appendix 8> When the accident is an accident involving another vehicle other than the vehicle, the input unit further acquires the event data recorder information of the other vehicle; the processing unit performs the identification process using an output of the data generation model when at least a part of the event data recorder information acquired from the other vehicle is further input. 2. A data processing device according to claim 1. [Explanation of symbols]

[0093] 10 Data Processing System 12 Data Processing Device 14 Smart Devices 22 Computer 24 databases 26 Communication I / F 28 processors 30 RAM 32 Storage 34 Bus 36 Computer 38 Reception device 38A Touch Panel 38B Microphone 40 Output Devices 40A Display 40B speaker 42 Camera 44 Communication I / F 46 processors 46A Control Unit 48 RAM 50 Storage 52 Bus 54 Network 56 Specific Processing Program 58A First Data Generation Model 58B Second Data Generation Model 60 Reception Output Program 80 Event Data Recorder 82 Drive Recorder 290 Special Processing Department 292 Input section 294 Processing Section Vehicles A and B

Claims

1. an input unit for acquiring user data; a processing unit that performs a specific process using a data generation model that generates a predetermined inference result according to the user data, the input unit acquires, as the user data, event data recorder information recorded by an event data recorder mounted on a vehicle in which the user is riding when an accident occurs; the processing unit performs, as the identification process, a process of generating analysis support information for supporting analysis of the event data recorder information, using an output of the data generation model when at least a part of the event data recorder information is input. Data processing device.

2. the input unit further acquires location information indicating a location of the vehicle during a predetermined period including a time point when the accident occurred; the processing unit further traces the movement of the vehicle using an output of the data generation model when at least a part of the event data recorder information and the position information are input.

2. The data processing device according to claim 1.

3. the processing unit further uses geographic data to perform the tracing.

3. The data processing device according to claim 2.

4. the input unit acquires the geographic data from data publicly available on the Internet; 4. The data processing device according to claim 3.

5. When the accident is an accident involving another vehicle other than the vehicle, the input unit further acquires the event data recorder information and the location information of the other vehicle; the processing unit traces movements of the vehicle and the other vehicle using an output of the data generation model when at least a part of the event data recorder information acquired from the other vehicle and the position information are further input.

5. The data processing device according to claim 2.

6. The analysis support information is at least one of image information and text information.

2. The data processing device according to claim 1.

7. The image information is at least one of first image information that shows the situation of the accident by superimposing it on an image showing the road on which the accident occurred, and second image information that shows at least a part of the event data recorder information in a graph.

7. The data processing device according to claim 6.

8. When the accident is an accident involving another vehicle other than the vehicle, the input unit further acquires the event data recorder information of the other vehicle; the processing unit performs the identification process using an output of the data generation model when at least a part of the event data recorder information acquired from the other vehicle is further input.

2. The data processing device according to claim 1.

9. Get user data, A data processing method comprising: performing specific processing using a data generation model that generates a predetermined inference result according to the user data; As the user data, when an accident occurs in a vehicle in which the user is riding, event data recorder information recorded by an event data recorder mounted on the vehicle is acquired; performing, as the specifying process, a process of generating analysis support information for supporting analysis of the event data recorder information by using an output of the data generation model when at least a part of the event data recorder information is input; Data processing methods.

10. Get user data, A process of performing a specific process using a data generation model that generates a predetermined inference result according to the user data, As the user data, when an accident occurs in a vehicle in which the user is riding, event data recorder information recorded by an event data recorder mounted on the vehicle is acquired; performing, as the specifying process, a process of generating analysis support information for supporting analysis of the event data recorder information by using an output of the data generation model when at least a part of the event data recorder information is input; A data processing program that causes a computer to perform processing.

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