Update system, update method, update program, and information processing device.

Abstract

This update system determines whether the data format of moving-body device data is a predetermined data format, and, in cases where it is determined that the data format of the moving-body device data is not the predetermined data format, corrects the data format of the moving-body device data to the predetermined data format. The update system extracts feature information relating to the moving-body device from moving-body device data in the predetermined data format, and estimates the state of the moving-body device using the feature information. The update system calculates an optimized parameter used by each control device on the basis of the moving-body device data and the state information, and updates the parameter.

Description

Technical Field

[0001] The present invention relates to an update system, an update method, an update program, and an information processing device for updating parameters used by a plurality of control devices provided in a mobile device such as a vehicle.

Background Art

[0002] Conventionally, various techniques for collecting diagnostic results from mobile devices such as vehicles have been proposed. As an example of such a technique, the fault diagnosis system disclosed in Patent Document 1 extracts and outputs data of diagnostic results obtained by a diagnostic program that can be used for diagnosing vehicles of a plurality of manufacturers according to a classification selected by a user.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] However, the fault diagnosis system disclosed in Patent Document 1 has a problem that when a mobile device includes a plurality of control devices and the data provided by the mobile device is not in a common data format, it is impossible to update the optimized parameters used by each of these control devices.

[0005] In view of the above problems, one object of the present disclosure is to provide an update system, an update method, an update program, and an information processing device that can update the optimized parameters used by each of a plurality of control devices even when the data provided by the mobile device is not in a common data format.

Means for Solving the Problems

[0006] The update system related to this disclosure is A data format determination means for determining whether the data format of the mobile device data, which is data about the mobile device provided by the mobile device, is a predetermined data format, If it is determined that the data format of the mobile device data is not the default data format, a data format correction means is provided to correct the data format of the mobile device data to the default data format. A feature extraction means for extracting feature information about a mobile device from mobile device data in a predetermined data format, A state estimation means estimates the state of a mobile device using a trained model that takes the feature information extracted by the feature extraction means as input information and outputs state information indicating the state of the mobile device corresponding to the feature information. A parameter calculation means that calculates optimized parameters used by each of the multiple control devices provided by the mobile device based on mobile device data and status information, The system includes a parameter update means that updates the parameters used by each of the multiple control devices using the optimized parameters calculated by the parameter calculation means.

[0007] The method of updating this disclosure is as follows: Computers Determine whether the data format of the mobile device data, which is data about the mobile device provided by the mobile device, is the default data format. If it is determined that the data format of the mobile device data is not the default data format, the data format of the mobile device data will be corrected to the default data format. Extract characteristic information about mobile devices from mobile device data in a default data format. Using a trained model that takes extracted feature information as input and outputs state information indicating the state of the mobile device corresponding to the feature information, the state of the mobile device is estimated. An algorithm is used to optimize the parameters used by each of the multiple control devices installed in the mobile device, and the optimized parameters are calculated using mobile device data and status information. The parameters used by each of the multiple control devices are updated using the calculated optimized parameters.

[0008] The update related to this disclosure is For computers, Determine whether the data format of the mobile device data, which is data about the mobile device provided by the mobile device, is in the default data format. If it is determined that the data format of the mobile device data is not the default data format, the data format of the mobile device data will be corrected to the default data format. Extract characteristic information about mobile devices from mobile device data in a default data format. Using a pre-trained model that takes extracted feature information as input and outputs state information indicating the state of the mobile device corresponding to the feature information, the state of the mobile device is estimated. An algorithm is used to optimize the parameters used by each of the multiple control devices installed in the mobile device, and the optimized parameters are calculated using mobile device data and status information. The calculated optimized parameters are used to update the parameters used by each of the multiple control devices.

[0009] The information processing device related to this disclosure is A data format determination means for determining whether the data format of the mobile device data, which is data about the mobile device provided by the mobile device, is a predetermined data format, If it is determined that the data format of the mobile device data is not the default data format, a data format correction means for correcting the data format of the mobile device data to the default data format is provided. A feature extraction means for extracting feature information relating to the mobile device from the mobile device data in the predetermined data format, A state estimation means estimates the state of the mobile device using a trained model that takes the feature information extracted by the feature extraction means as input information and outputs state information indicating the state of the mobile device corresponding to the feature information. An algorithm for optimizing parameters used by each of a plurality of control devices included in the mobile device, and parameter calculation means for calculating the optimized parameters using the mobile device data and the state information. Parameter update instruction means for updating the parameters used by each of the plurality of control devices using the optimized parameters calculated by the parameter calculation means for each of the plurality of control devices.

Effect of the Invention

[0010] According to the present disclosure, when a mobile device includes a plurality of control devices, even when the data provided by the mobile device is not in a common data format, an update system, an update method, an update program, and an information processing device capable of updating the optimized parameters used by each of these control devices can be provided.

Brief Description of the Drawings

[0011] [Figure 1] It is a diagram showing an example of an update system according to the present disclosure. [Figure 2] It is a diagram showing an example of the configuration of a mobile device according to the present disclosure. [Figure 3] It is a diagram showing the functions of an update control device according to the present disclosure. [Figure 4] It is a diagram showing the configuration of a management device according to the present disclosure. [Figure 5] It is a sequence diagram showing an example of a process executed by an update system according to the present disclosure. [Figure 6] It is a conceptual diagram showing a specific example of an update system. [Figure 7] It is a diagram showing the details of the configuration of an ontology. [Figure 8] It is a diagram showing the update procedure of a group of ECUs. [Figure 9] It is a conceptual diagram showing the change in performance due to the optimization of two ECUs manufactured by different manufacturers. [Figure 10] It is a diagram showing the main components of an update system 1 according to the present disclosure. [Modes for carrying out the invention]

[0012] Hereinafter, exemplary embodiments will be described with reference to the drawings. Figure 1 is a diagram showing the update system 1 according to the present disclosure. The update system 1 includes a mobile device 10 and a management device 20. The mobile device 10 and the management device 20 can communicate data with each other via a network 50. The network 50 includes a wide-area network such as the Internet.

[0013] Figure 2 shows the configuration of the mobile device 10 according to this disclosure. Specific examples of the mobile device 10 include vehicles such as automobiles and aircraft such as drones. The mobile device 10 comprises an update control device 11, control devices 12a to 12c, a communication device 13, a storage device 14, and a sensor 15. The update control device 11, control devices 12a to 12c, the communication device 13, the storage device 14, and the sensor 15 can communicate data via a network 17 using CAN (Controller Area Network), SOME / IP (Scalable service-Oriented Middleware over IP), Ethernet, and TSN (Time Sensitive Network), etc. The mobile device 10 may be equipped with any number of control devices.

[0014] The update control device 11 is a device that controls the updating of parameters used by control devices 12a to 12c. Specific examples of the update control device 11 include various processors such as CPUs (Central Processing Units) and MPUs (Micro Processing Units), and integrated circuits such as FPGAs (Field-Programmable Gate Arrays) and ASICs (Application Specific Integrated Circuits).

[0015] Control devices 12a to 12c are devices that control various devices installed in a mobile device. Specific examples of control devices 12a to 12c include ECUs (Electronic Control Units) such as engine control ECUs, motor control ECUs, brake control ECUs, and battery control ECUs.

[0016] The communication device 13 is a device that communicates data with the management device 20 via the network 50. The storage device 14 stores data such as programs executed by the update control device 11 and information processed by the update control device 11.

[0017] Sensor 15 is a device that detects various information related to the mobile device 10. Specific examples of sensor 15 include radar, lidar, imaging sensors, temperature sensors, speed sensors, and acceleration sensors.

[0018] Figure 3 shows the functions of the update control device 11. The update control device 11 includes a mobile device data acquisition means 110, a communication control means 111, and a parameter update means 112. The mobile device data acquisition means 110 is a program that acquires data related to the mobile device (hereinafter referred to as "mobile device data") from the control devices 12a to 12c and / or the sensor 15. The mobile device data includes sensor information acquired by the sensor 15 and data acquired from the control devices 12a to 12c. The data acquired from the control devices 12a to 12c includes, for example, information indicating the type of control device 12a to 12c, information indicating the manufacturer of the control devices 12a to 12c, information indicating the version of the software installed on the control devices 12a to 12c, and bug reports regarding the hardware and / or software of the control devices 12a to 12c. Information indicating the type of control device 12a to 12c refers to, for example, the type of ECU such as engine control ECU, motor control ECU, brake control ECU, battery control ECU, etc.

[0019] Furthermore, the mobile device data includes information indicating the energy consumed by the mobile device 10, such as gasoline, diesel fuel, biomass fuel, electricity, hydrogen, etc.; information indicating the emissions of exhaust gases from the mobile device 10, such as nitrogen oxides and carbon dioxide; information indicating the cruising range of the mobile device 10; and information indicating the performance of the power source equipped in the mobile device 10, such as an engine or motor. This information can be obtained from the sensor 15 or the control devices 12a to 12c.

[0020] The communication control means 111 is a program that controls the communication device 13 to control data communication between the mobile device 10 and the management device 20. The communication control means 111 transmits mobile device data acquired from the control devices 12a to 12c to the management device 20. The communication control means 111 also provides parameters received from the management device 20 to the control devices 12a to 12c.

[0021] The parameter update means 112 is a program that updates the parameters used by the control devices 12a to 12c using parameters received from the management device 20. The parameter update means 112 updates the parameters used by the control devices 12a to 12c at specific timings in accordance with safety and security policies. For example, the parameter update means 112 updates the parameters used by the control devices 12a to 12c when the mobile device 10 is idling or parked.

[0022] Figure 4 shows the configuration of the management device 20 according to this disclosure. An example of the management device 20 is an information processing device such as a server. The management device 20 comprises a computing device 21, a communication interface (I / F) 22, and a storage device 23.

[0023] The arithmetic unit 21 is a device that performs overall control of the management device 20. Specific examples of the arithmetic unit 21 include integrated circuits such as CPUs and MPUs. Alternatively, the program executed by the arithmetic unit 21 may be executed by integrated circuits such as FPGAs and ASICs.

[0024] The communication interface 22 is a device that communicates data with the mobile device 10 via the network 50. The storage device 23 stores data such as programs executed by the arithmetic unit 21 and information processed by the arithmetic unit 21.

[0025] The computing unit 21 performs the following: data format determination means 210, data format correction means 211, feature extraction means 212, state estimation means 213, parameter calculation means 214, and update instruction means 215.

[0026] The data format determination means 210 is a program that determines whether the data format of the mobile device data received from the mobile device 10 is a default data format. Examples of default data formats include data formats that conform to the Vehicle Signal Specification (VSS) or the Vehicle Signal Specification Ontology (VSSO).

[0027] The data format correction means 211 is a program that corrects the data format of the mobile device data received from the mobile device 10 to a default data format. Examples of default data formats include data formats that conform to vehicle signal specifications or vehicle signal reference ontology.

[0028] The feature extraction means 212 is a program that extracts feature information about the mobile device 10 from mobile device data in a predetermined data format. The feature information includes information indicating the energy consumption of the mobile device 10, information indicating the exhaust gas emissions of the mobile device 10, information indicating the cruising range of the mobile device 10, information indicating the performance of the power source of the mobile device 10, and so on. The feature extraction means 212 can extract this feature information from the payload of the mobile device data.

[0029] The state estimation means 213 is a program that estimates the state of the mobile device 10 using the characteristic information of the extracted mobile device data. The state estimation means 213 can estimate the state of the mobile device 10 from the characteristic information of the extracted mobile device data using a trained model trained by machine learning. This trained model can be trained to take mobile device data as input information and output information indicating the state of the mobile device corresponding to the mobile device data. By inputting the mobile device data received from the mobile device 10 into this trained model, the state estimation means 213 can obtain state information indicating the state of the mobile device 10 corresponding to the mobile device data. The state information indicating the state of the mobile device 10 includes, for example, information showing the time-series change in energy consumption by the mobile device 10, information showing the time-series change in exhaust gas emissions by the mobile device 10, information showing the cruising range of the mobile device 10, and information showing the time-series change in the performance of the power source of the mobile device 10.

[0030] The parameter calculation means 214 is a program that calculates an optimized parameter set using an optimization algorithm that optimizes the parameters used by each of the multiple control devices 12a to 12c provided by the mobile device 10, mobile device data provided by the mobile device 10, and state information of the mobile device 10. The parameter set includes parameters related to energy consumption used by the mobile device 10, parameters related to exhaust gas emissions, parameters related to cruising range, and parameters related to power source performance. Optimization of parameters related to energy consumption means deriving parameters that reduce energy consumption. Optimization of parameters related to exhaust gas emissions means deriving parameters that reduce exhaust gas emissions. Optimization of parameters related to cruising range means deriving parameters that increase cruising range. Optimization of parameters related to power source performance means deriving parameters that improve the performance of the power source, such as the output of the power source.

[0031] The parameter calculation means 214 can optimize these parameters using various optimization algorithms corresponding to different types of mobile devices 10, such as vehicle models. Specific examples of optimization algorithms include algorithms using weighted averaging, genetic algorithms, and machine learning algorithms such as deep learning.

[0032] For example, when optimizing parameters using machine learning, the parameter calculation means 214 can obtain optimized parameters for each control device using a model that takes mobile device data provided by the mobile device 10 and state information of the mobile device 10 calculated by the state estimation means 213 as input information, and outputs an optimized parameter set. This model can be trained using mobile device data and state information derived from said mobile device data as input information, and an optimized parameter set corresponding to this mobile device data and state information as output information. The mobile device data used to train this model includes information indicating the type of control device 12a to 12c, information indicating the manufacturer of the control devices 12a to 12c, information indicating the version of the software installed on the control device, bug reports regarding the hardware and / or software of the control devices 12a to 12c, information indicating energy consumption, information indicating exhaust gas emissions, information indicating cruising range, information indicating power source performance, etc. The parameter calculation means 214 can also calculate the optimized parameter set using quantum computing.

[0033] The update instruction means 215 is a program that transmits the calculated parameter set to the mobile device 10, causing the control devices 12a to 12c provided by the mobile device 10 to update the parameters used by them.

[0034] Figure 5 is a sequence diagram showing an example of the processing performed by the update system 1 related to this disclosure.

[0035] In step S1, the mobile device data acquisition means 110 of the mobile device 10 acquires mobile device data from each of the control devices 12a to 12c of the mobile device 10. In step S2, the communication control means 111 of the mobile device 10 transmits the acquired mobile device data to the management device 20 via the network 50.

[0036] When the management device 20 receives mobile device data from the mobile device 10, in step S3, the data format determination means 210 determines whether the data format of the mobile device data received from the mobile device 10 is a predetermined data format.

[0037] If the data format of the mobile device data received from the mobile device 10 is not the default data format, in step S4 the data format correction means 211 corrects the data format of the mobile device data received from the mobile device 10 to the default data format. If the data format of the mobile device data received from the mobile device 10 is already the default data format, the process in step S4 is not executed.

[0038] In step S5, the feature extraction means 212 extracts feature information from the mobile device data received from the mobile device 10.

[0039] In step S6, the state estimation means 213 estimates the state of the mobile device 10 using the feature information of the extracted mobile device data. The state estimation means 213 can estimate the state of the mobile device 10 from the feature information of the extracted mobile device data using a trained model trained by machine learning. This trained model can be trained to take mobile device data as input information and output information indicating the state of the mobile device corresponding to the mobile device data. By inputting the mobile device data received from the mobile device 10 into this trained model, the state estimation means 213 can obtain state information indicating the state of the mobile device 10 corresponding to the mobile device data.

[0040] In step S7, the parameter calculation means 214 calculates a set of parameters to be used by the multiple control devices 12a to 12c of the mobile device 10, using the mobile device data received from the mobile device 10 and the status information of the mobile device 10. The parameter calculation means 214 adds identification information of the control devices 12a to 12c that use each parameter included in the calculated parameter set.

[0041] In step S8, the update instruction means 215 transmits the calculated parameter set to the mobile device 10.

[0042] When the mobile device 10 receives a parameter set from the management device 20, in step S9, the parameter update means 112 of the mobile device 10 updates the parameters of each of the multiple control devices provided by the mobile device 10. Specifically, the parameter update means 112 identifies the control device to which the parameter should be provided based on the identification information of the control devices 12a to 12c attached to the parameter. Then, the parameter update means 112 provides and updates the parameter to the identified control device.

[0043] Figure 6 is a conceptual diagram showing a specific example of the update system described above. In the example shown in Figure 6, a vehicle is used as the mobile device 10. The update system 1 corresponds to the knowledge acquisition system.

[0044] The business infrastructure 60 provides access to the ontology verification means 61 and the ontology synthesis means 62.

[0045] The ontology verification means 61, which corresponds to the data format determination means, determines whether the data provided to the ML (Machine Learning) / AI (Artificial Intelligence) optimization processing means 63, which corresponds to the parameter calculation means 214, conforms to default data definitions such as vehicle signal specifications and vehicle signal reference ontology. The ontology verification means 61 also exchanges related vehicle data with the digital twin 64, which includes a vehicle twin, etc. The dataset used by the digital twin 64 must conform to default datasets and data definitions.

[0046] In the example shown in Figure 6, the vehicle diagnostic means 65 performs vehicle diagnostic processing based on vehicle data. The vehicle diagnostic processing determines whether the condition of the target vehicle conforms to the manufacturer's guidelines regarding maximum power, energy consumption, functional safety, security, etc. Data sets and parameters related to vehicle condition estimation are stored in a dedicated data server 66.

[0047] The ML / AI optimization processing means 63 performs ML / AI optimization processing on the parameter set of the control device. The ML / AI optimization processing means 63 discovers new parameter sets and provides a dataset for the updated parameter set for the firmware of the control device.

[0048] The backend server 67 transmits the updated parameter set of the ECU 68 to multiple target ECU 68s installed in the vehicle via the network 69. The multiple ECU 68s are then updated with this updated parameter set of the ECU 68.

[0049] Figure 7 shows the details of the ontology configuration. The ontology synthesis means 62 is connected to the operational infrastructure 60 and the digital twin 64, and provides them with the synthesis results. These results relate to a new dataset for additional result data. Such result data relates to the digital twin.

[0050] The ontology synthesis means 62 combines multiple related ontologaries via the ontology hub 70. The ontology hub 70 provides access to the multiple related ontologaries. These multiple related ontologaries include the driver ontology 71, the maintenance service ontology 72, the telematics ontology 73, and other related ontologaries 74. Each ontology 71-74 includes a data definition, data relationships including a data hierarchy, and data. The data definition and data relationships can be stored in files based on, for example, JSON or other XML. The data itself can be stored in JSON files or other related files, such as XML files or CSV files. This data is readable, compressible, and encrypted. If the data is encrypted, the system ensures that the correct data definitions and relationships are supported.

[0051] Figure 8 shows the update procedure for a group of ECUs. Manufacturer A81 accesses only the ECUs 801-802 that it manufactured via network 82 and updates the parameter sets as needed.

[0052] Meanwhile, the vehicle maintenance service provider 80 accesses all ECUs 801-803, 811-813, 821-823 of the vehicle 10 via the network 82 and optimizes these ECUs simultaneously as needed. Here, the VSS and VSSO interfaces 800, 810, and 820 support a simple method for updating each ECU manufactured by different manufacturers.

[0053] Figure 9 is a conceptual diagram showing the performance change due to optimization of two ECUs manufactured by different manufacturers. The left side of Figure 9 shows the change in performance over time when each ECU manufactured by a different manufacturer is updated using an optimized parameter set. In this disclosure, since ECUs manufactured by different manufacturers can be updated, the overall performance of two ECUs manufactured by different manufacturers can be improved, as shown on the right side of Figure 9.

[0054] Figure 10 is a diagram showing the main components of the update system 1 according to this disclosure. The update system 1 includes a data format determination means 210, a data format correction means 211, a feature extraction means 212, a state estimation means 213, a parameter calculation means 214, and a parameter update means 112. The data format determination means 210 determines whether the data format of the mobile device data provided from the mobile device 10 is a default data format. If the data format correction means 211 determines that the data format of the mobile device data is not a default data format, it corrects the data format of the mobile device data to the default data format. The feature extraction means 212 extracts feature information about the mobile device from the mobile device data in the default data format. The state estimation means 213 takes the feature information extracted by the feature extraction means 212 as input information and estimates the state of the mobile device 10 using a trained model that outputs state information indicating the state of the mobile device 10 corresponding to the feature information. The parameter calculation means 214 calculates optimized parameters based on an algorithm that optimizes the parameters used by each of the multiple control devices 12a to 12c provided by the mobile device 10, as well as mobile device data and status information. The parameter update means 112 updates the parameters used by each of the multiple control devices 12a to 12c using the optimized parameters calculated by the parameter calculation means 214.

[0055] By adopting this configuration, even when the mobile device 10 is equipped with multiple control devices 12a to 12c, and the data provided by the mobile device is not in a common data format, optimized parameters can be calculated based on a common data format. Then, using these optimized parameters, the parameters used by each of the multiple control devices 12a to 12c can be updated. For example, if the mobile device 10 is equipped with multiple control devices 12a to 12c manufactured by different manufacturers, the data formats provided by the control devices 12a to 12c may differ. Even in such cases, the update system 1 can optimize the parameters used by each of the multiple control devices 12a to 12c.

[0056] In the examples described above, the program includes a set of instructions (or software code) that, when loaded into a computer, cause the computer to perform one or more of the functions described in the embodiments. The program may be stored on a non-temporary computer-readable medium or a physical storage medium. Examples, but not limited to, include random-access memory (RAM), read-only memory (ROM), flash memory, solid-state drive (SSD) or other memory technologies, CD-ROM, digital versatile disk (DVD), Blu-ray® disc or other optical disc storage, magnetic cassette, magnetic tape, magnetic disk storage or other magnetic storage devices. The program may be transmitted over a temporary computer-readable medium or a communication medium. Examples, but not limited to, include transmitting signals of electrical, optical, acoustic or other forms. Processors and servers correspond to computers.

[0057] This disclosure is not limited to the embodiments described above, and can be modified as appropriate without departing from the spirit of this disclosure. For example, in the embodiments described above, the management device 20 determines and corrects the data format of the mobile device data, but in other embodiments, the mobile device 10 may be equipped with data format determination means and data format correction means.

[0058] Each drawing is merely illustrative to illustrate one or more embodiments. Each drawing may be associated with one or more other embodiments rather than with only one specific embodiment. As those skilled in the art will understand, various features or steps described with reference to any one drawing can be combined with features or steps shown in one or more other drawings, for example, to create embodiments not explicitly shown or described. Not all features or steps shown in any one drawing to illustrate an exemplary embodiment are necessarily required, and some features or steps may be omitted. The order of steps shown in any of the drawings may be changed as appropriate.

[0059] Some or all of the above embodiments may also be described as follows, but are not limited to the following: (Note 1) A data format determination means for determining whether the data format of the mobile device data, which is data about the mobile device provided by the mobile device, is a predetermined data format, If it is determined that the data format of the mobile device data is not the default data format, a data format correction means for correcting the data format of the mobile device data to the default data format is provided. A feature extraction means for extracting feature information relating to the mobile device from the mobile device data in the predetermined data format, A state estimation means estimates the state of the mobile device using a trained model that takes the feature information extracted by the feature extraction means as input information and outputs state information indicating the state of the mobile device corresponding to the feature information. An algorithm for optimizing the parameters used by each of the multiple control devices provided in the mobile device, and a parameter calculation means for calculating the optimized parameters using the mobile device data and the state information. A parameter update means updates the parameters used by each of the plurality of control devices using the optimized parameters calculated by the parameter calculation means. An update system, including the update system. (Note 2) The aforementioned default data format is a data format that conforms to the vehicle signal specifications and vehicle signal reference ontology, as described in Appendix 1 of the update system. (Note 3) The update system as described in Appendix 1 or 2, wherein the characteristic information includes information indicating the energy consumption by the mobile device, information indicating the exhaust gas emissions by the mobile device, information indicating the cruising range of the mobile device, and information indicating the performance of the power source provided by the mobile device. (Note 4) The parameter calculation means is an update system according to any one of the appendices 1 to 3, which calculates the optimized parameters using a trained model that takes the mobile device data and the state information as input information and the optimized parameters as output information. (Note 5) The update system described in any one of the appendices 1 to 4, wherein the mobile device data includes information indicating the type of control device, information indicating the manufacturer of the control device, information indicating the version of the software installed on the control device, a bug report of the control device, and the characteristic information. (Note 6) Computers Determine whether the data format of the mobile device data, which is data about the mobile device provided by the mobile device, is the default data format. If it is determined that the data format of the mobile device data is not the default data format, the data format of the mobile device data is corrected to the default data format. Characteristic information relating to the mobile device is extracted from the mobile device data in the predetermined data format. Using a trained model that takes extracted feature information as input and outputs state information indicating the state of the mobile device corresponding to the feature information, the state of the mobile device is estimated. An algorithm for optimizing the parameters used by each of the multiple control devices provided in the mobile device, and the optimized parameters calculated using the mobile device data and the state information, The parameters used by each of the multiple control devices are updated using the calculated optimized parameters. How to update. (Note 7) The aforementioned default data format is a data format that conforms to the vehicle signal specifications or the vehicle signal reference ontology, as described in Appendix 6 regarding the update method. (Note 8) The update method described in Appendix 6 or 7, wherein the characteristic information includes information indicating the energy consumption by the mobile device, information indicating the exhaust gas emissions by the mobile device, information indicating the cruising range of the mobile device, and information indicating the performance of the power source provided by the mobile device. (Note 9) The update method described in Appendix 8, wherein the computer calculates the update using a trained model that takes the mobile device data and the state information as input information and the optimized parameters as output information. (Note 10) The update method described in Appendix 9 includes, in addition to the mobile device data, information indicating the type of control device, information indicating the manufacturer of the control device, information indicating the version of the software installed on the control device, a bug report of the control device, and the characteristic information. (Note 11) For computers, Determine whether the data format of the mobile device data, which is data about the mobile device provided by the mobile device, is in the default data format. If it is determined that the data format of the mobile device data is not the default data format, the data format of the mobile device data will be modified to the default data format. Characteristic information relating to the mobile device is extracted from the mobile device data in the predetermined data format. Using a trained model that takes extracted feature information as input and outputs state information indicating the state of the mobile device corresponding to the feature information, the state of the mobile device is estimated. An algorithm for optimizing the parameters used by each of the multiple control devices provided in the mobile device, and the calculation of the optimized parameters using the mobile device data and the state information, The parameters used by each of the multiple control devices are updated using the calculated optimized parameters. Update. (Note 12) The aforementioned default data format is a data format that conforms to the vehicle signaling specifications and vehicle signaling reference ontology, as described in the update program in Appendix 11. (Note 13) The update program described in Appendix 11 or 12 includes, for the feature information, information indicating the energy consumption of the mobile device, information indicating the exhaust gas emissions of the mobile device, information indicating the cruising range of the mobile device, and information indicating the performance of the power source provided by the mobile device. (Note 14) The update program described in Appendix 13 causes the computer to calculate the optimized parameters using a trained model that takes the mobile device data and the state information as input information and the optimized parameters as output information. (Note 15) The update program described in Appendix 14 includes information indicating the type of control device, information indicating the manufacturer of the control device, information indicating the version of the software installed on the control device, a bug report of the control device, and the characteristic information. (Note 16) A data format determination means for determining whether the data format of the mobile device data, which is data about the mobile device provided by the mobile device, is a predetermined data format, If it is determined that the data format of the mobile device data is not the default data format, a data format correction means for correcting the data format of the mobile device data to the default data format is provided. A feature extraction means for extracting feature information relating to the mobile device from the mobile device data in the predetermined data format, A state estimation means estimates the state of the mobile device using a trained model that takes the feature information extracted by the feature extraction means as input information and outputs state information indicating the state of the mobile device corresponding to the feature information. An algorithm for optimizing the parameters used by each of the multiple control devices provided in the mobile device, and a parameter calculation means for calculating the optimized parameters using the mobile device data and the state information. A parameter update instruction means provides each of the plurality of control devices with a parameter update instruction means that causes each of the plurality of control devices to update the parameters it uses using the optimized parameters calculated by the parameter calculation means. Equipped with, information processing device. (Note 17) The aforementioned default data format is a data format that conforms to the vehicle signal specifications or the vehicle signal reference ontology, as described in Appendix 16 of the information processing device. (Note 18) The information processing device according to Appendix 16 or 17, wherein the characteristic information includes information indicating the energy consumption by the mobile device, information indicating the exhaust gas emissions by the mobile device, information indicating the cruising range of the mobile device, and information indicating the performance of the power source provided by the mobile device. (Note 19) The parameter calculation means is an information processing device as described in Appendix 18, which calculates the optimized parameters using a trained model that takes the mobile device data and the state information as input information and the optimized parameters as output information. (Note 20) The information processing device described in Appendix 19 includes, in addition to the mobile device data, information indicating the type of control device, information indicating the manufacturer of the control device, information indicating the version of the software installed on the control device, a bug report of the control device, and the characteristic information.

[0060] This application claims priority based on Japanese Patent Application No. 2023-59771, filed on 3 April 2023, and incorporates all of its disclosures herein. [Explanation of Symbols]

[0061] 1. Update System 10 Mobile devices, vehicles 11. Update control device 12a Control device 12b Control device 12c control unit 13. Communication equipment 14 Storage device 15 sensors 17 Network 20 Management device 21 Arithmetic unit 22 Communication Interfaces 23 Storage device 110 Mobile object data acquisition means 111 Communication control means 112 Parameter update means 210 Data format determination means 211 Data format modification means 212 Feature extraction means 213 State Estimation Means 214 Parameter calculation means 215 Update instruction means

Claims

1. A data format determination means for determining whether the data format of the mobile device data, which is data about the mobile device provided by the mobile device, is a predetermined data format, If it is determined that the data format of the mobile device data is not the default data format, a data format correction means for correcting the data format of the mobile device data to the default data format is provided. A feature extraction means for extracting feature information relating to the mobile device from the mobile device data in the predetermined data format, A state estimation means estimates the state of the mobile device using a trained model that takes the feature information extracted by the feature extraction means as input information and outputs state information indicating the state of the mobile device corresponding to the feature information. An algorithm for optimizing the parameters used by each of the multiple control devices provided in the mobile device, and a parameter calculation means for calculating the optimized parameters using the mobile device data and the state information. A parameter update means updates the parameters used by each of the plurality of control devices using the optimized parameters calculated by the parameter calculation means. An update system, including the update system.

2. The update system according to claim 1, wherein the predetermined data format is a data format that conforms to vehicle signal specifications or vehicle signal reference ontology.

3. The update system according to claim 1 or 2, wherein the characteristic information includes information indicating the energy consumption by the mobile device, information indicating the exhaust gas emissions by the mobile device, information indicating the cruising range of the mobile device, and information indicating the performance of the power source provided by the mobile device.

4. The update system according to claim 3, wherein the parameter calculation means calculates the optimized parameters using a trained model that takes the mobile device data and the state information as input information and the optimized parameters as output information.

5. The update system according to claim 4, wherein the mobile device data includes information indicating the type of control device, information indicating the manufacturer of the control device, information indicating the version of the software installed on the control device, a bug report of the control device, and the feature information.

6. Computers Determine whether the data format of the mobile device data, which is data about the mobile device provided by the mobile device, is the default data format. If it is determined that the data format of the mobile device data is not the default data format, the data format of the mobile device data is corrected to the default data format. Characteristic information relating to the mobile device is extracted from the mobile device data in the predetermined data format. Using a trained model that takes extracted feature information as input and outputs state information indicating the state of the mobile device corresponding to the feature information, the state of the mobile device is estimated. An algorithm for optimizing the parameters used by each of the multiple control devices provided in the mobile device, and the optimized parameters calculated using the mobile device data and the state information, The parameters used by each of the multiple control devices are updated using the calculated optimized parameters. How to update.

7. To a computer, Determine whether the data format of the mobile device data, which is data about the mobile device provided by the mobile device, is in the default data format. If it is determined that the data format of the mobile device data is not the default data format, the data format of the mobile device data will be modified to the default data format. Characteristic information relating to the mobile device is extracted from the mobile device data in the predetermined data format. Using a trained model that takes extracted feature information as input and outputs state information indicating the state of the mobile device corresponding to the feature information, the state of the mobile device is estimated. An algorithm for optimizing the parameters used by each of the multiple control devices provided in the mobile device, and the calculation of the optimized parameters using the mobile device data and the state information, The parameters used by each of the multiple control devices are updated using the calculated optimized parameters. Update.

8. A data format determination means for determining whether the data format of mobile device data, which is data relating to a mobile device provided by a mobile device, is a predetermined data format, If it is determined that the data format of the mobile device data is not the default data format, a data format correction means for correcting the data format of the mobile device data to the default data format is provided. A feature extraction means for extracting feature information relating to the mobile device from the mobile device data in the predetermined data format, A state estimation means estimates the state of the mobile device using a trained model that takes the feature information extracted by the feature extraction means as input information and outputs state information indicating the state of the mobile device corresponding to the feature information. An algorithm for optimizing the parameters used by each of the multiple control devices provided in the mobile device, and a parameter calculation means for calculating the optimized parameters using the mobile device data and the state information. A parameter update instruction means provides each of the plurality of control devices with a parameter update instruction means that causes each of the plurality of control devices to update the parameters it uses using the optimized parameters calculated by the parameter calculation means. Equipped with, information processing device.

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