JP-7856050-B2 - Method and management system for managing autonomous driving functions in vehicles

Inventors

• 大杉 雅道

Assignees

• トヨタ自動車株式会社

Dates

Publication Date

20260511

Application Date

20230523

Claims (4)

1. A method for managing the autonomous driving function in a vehicle, The management server sends update data indicating data for updating the trained model to at least two vehicles in which automated driving control using a trained model representing a model generated by machine learning is performed, The management server collects verification data from each of the at least two vehicles to which the update data has been transmitted, showing data obtained or generated in connection with the execution of the automated driving control using the updated trained model. The management server performs the following steps: verifying the functionality of the automated driving control using the updated trained model with the verification data collected from the at least two vehicles; The processor that performs the automated driving control of one of the at least two vehicles is, during the automated driving control using the updated trained model and when predetermined collection conditions are met, the processor collects data acquired or generated by the managed object in connection with the execution of the automated driving control within a predetermined collection time based on the timing when the collection conditions are met, as verification data for the managed object. The steps include: the managed entity transmits the verification data for the managed entity to the management server; The collection conditions include the fact that the operator under management intervened in the automated driving control, A method for managing an automated driving function, characterized in that the length of the collection time, based on the timing when the collection conditions are met, is set variably based on the driving skill level of the operator being managed .
2. The method according to claim 1 , A method for managing an automated driving function, characterized in that the collection conditions include the driving environment conditions of the managed object matching pre-set conditions.
3. A system for managing the autonomous driving function in a vehicle, Includes a management server that manages the aforementioned autonomous driving function, The aforementioned management server A process to transmit update data indicating data for updating the trained model to at least two vehicles that are performing automated driving control using a trained model representing a model generated by machine learning, A process of collecting verification data from each of the at least two vehicles to which the update data has been transmitted, showing data obtained or generated in connection with the execution of the automated driving control using the updated trained model, A process to verify the functionality of the automated driving control using the updated trained model, using the verification data collected from the at least two vehicles, Perform The system further includes a processor that performs the automated driving control of one of the vehicles included in the at least two vehicles, The aforementioned processor, During the automated driving control using the updated trained model, and when predetermined collection conditions are met, the process includes collecting data acquired or generated by the managed object in connection with the execution of the automated driving control within a predetermined collection time based on the timing when the collection conditions are met, as verification data for the managed object. The process of sending the verification data for the managed object to the management server, Perform The collection conditions include the fact that the operator under management intervened in the automated driving control, A management system for an automated driving function, characterized in that the length of the collection time, based on the timing when the collection conditions are met, is set variably based on the driving skill level of the operator under management .
4. The system according to claim 3 , The management system for an automated driving function is characterized in that the collection conditions include the driving environment conditions of the subject being managed matching pre-set conditions.

Description

This disclosure relates to a method and system for managing autonomous driving functions in a vehicle. Japanese Patent Publication No. 2015-135552 discloses a system for updating the parameters of image recognition processing performed in multiple vehicles. This conventional system includes a server that communicates with multiple vehicles. This server collects image data captured by each of the multiple vehicles as training data and performs machine learning processing using this training data. This machine learning processing generates data for updating the parameters of the image recognition processing. The server also provides the data generated by the machine learning processing to each of the multiple vehicles from which the training data was collected. The multiple vehicles update the parameters of the image recognition processing using the data provided by the server. Examples of documents illustrating the state of the art in the field related to this disclosure include, in addition to Japanese Patent Publication No. 2015-135552, Japanese Patent Publication Nos. 2022-002118, 2021-532487, 2018-195184, and 2019-156171. Japanese Patent Publication No. 2015-135552Japanese Patent Publication No. 2022-002118Japanese Patent Publication No. 2021-532487Japanese Patent Publication No. 2018-195184Japanese Patent Publication No. 2019-156171 This is a diagram illustrating the outline of an embodiment.This is a block diagram showing an example configuration of an autonomous driving system installed in a vehicle.This is a block diagram showing an example of the functional configuration of the management server.This figure shows an example of instruction data regarding the management of log data.This diagram illustrates the collection time during which log data is extracted and stored.This flowchart shows the processing flow by the autonomous driving system, which is particularly relevant to the embodiment.This flowchart shows the processing flow by the management server, which is particularly relevant to the embodiment. The embodiments of this disclosure will be described below with reference to the drawings. In each drawing, the same or corresponding parts are denoted by the same reference numerals, and their descriptions are simplified or omitted. 1. Overview of the Embodiment Figure 1 is a diagram illustrating the overview of this embodiment. Figure 1 depicts three vehicles 1 and a management server 200. The three vehicles 1 are an example of "at least two vehicles" in this disclosure. Each of the vehicles 1 (hereinafter also referred to as "managed vehicle 1") is equipped with an automated driving system 100 for performing automated driving control of managed vehicle 1. Automated driving means that at least one of the following actions of the vehicle—steering, acceleration, and deceleration—is performed automatically without driver operation by an operator. Automated driving control is a concept that includes not only fully automated driving control but also risk avoidance control, lane keeping assist control, etc. The operator may be a driver riding in managed vehicle 1, or a remote operator remotely controlling managed vehicle 1. The autonomous driving system 100 includes one or more processors 110 (hereinafter simply referred to as "processor" 110) and one or more storage devices 120 (hereinafter simply referred to as "storage device 120"). The processor 110 performs various processes. Examples of processors 110 include CPUs (Central Processing Units), GPUs (Graphics Processing Units), ASICs (Application Specific Integrated Circuits), FPGAs (Field-Programmable Gate Arrays), etc. The storage devices 120 store various information. Examples of storage devices 120 include HDDs (Hard Disk Drives), SSDs (Solid State Drives), volatile memory, non-volatile memory, etc. The management server 200, together with the autonomous driving system 100, constitutes the management system of this embodiment. The management server 200 manages the functions of the autonomous driving system 100, that is, the autonomous driving functions. The management server 200 includes one or more processors 210 (hereinafter simply referred to as "processor 210") and one or more storage devices 220 (hereinafter simply referred to as "storage devices 220"). The processors 210 execute various processes. An example of the processor 210 is the same as that of the processor 110 described above. The storage devices 220 store various information. An example of the storage devices 220 is the same as that of the storage device 120 described above. The management server 200 communicates with each of the autonomous driving systems 100. In communication with the autonomous driving systems 100, the management server 200 sends update data (UPD) and instruction data (INS_LOG) to each of the autonomous driving systems 100. The update data (UPD) is data for updating the trained model. The update data (UPD) includes the trained model itself and model building e