Vehicle control, task processing method, device, computing apparatus and system

Abstract

The application discloses a vehicle control method, a task processing method, a device, a computing device and a system. The vehicle control method comprises: obtaining a driving control task to be executed and a target parameter associated with the driving control task; and executing a corresponding algorithm based on the target parameter to enable a driving control system to complete the driving control task. Through the above technical solution, accurate vehicle parameters are obtained according to the driving control task, and the reliability of driving control is improved.

Description

Technical Field

[0001] This application relates to the field of vehicle control, and more particularly to a vehicle control, task processing method, apparatus, computing device, and system. Background Technology

[0002] In autonomous driving scenarios, driving control tasks such as vehicle localization, detection, and tracking all require accurate vehicle parameters. With the development of vehicle control technology and the increasing demand for various intelligent functions, the number of vehicle parameters used is growing. These parameters change with variations in vehicle hardware information, necessitating continuous updates and maintenance. How to effectively manage vehicle parameters and ensure that the vehicle-side can use valid parameters for vehicle control is a pressing issue that needs to be addressed.

[0003] In current parameter management solutions, vehicle parameters are recorded and used by the vehicle itself, relying on manual recording or updates. This is inconvenient for maintenance and cannot guarantee their up-to-dateness. Furthermore, the validity and timeliness of vehicle parameters cannot be guaranteed for different driving control tasks. If correct and usable vehicle parameters cannot be obtained, driving control functions will be affected, and the vehicle may fail to depart successfully. Summary of the Invention

[0004] This application provides a vehicle control, task processing method, apparatus, computing device, and system to obtain accurate vehicle parameters based on driving control tasks, thereby improving the reliability of driving control.

[0005] This application provides a vehicle control method, including: acquiring a driving control task to be executed and target parameters associated with the driving control task; and executing a corresponding algorithm based on the target parameters so that the driving control system can complete the driving control task.

[0006] This application embodiment also provides a task processing method for execution in a second computing device, comprising: receiving a target parameter request sent by a first computing device; and in response to the target parameter request sent by the first computing device, sending a target parameter corresponding to the metadata to the first computing device, so that the first computing device executes a corresponding algorithm based on the target parameter, so that the driving control system can complete the driving control task.

[0007] This application also provides a vehicle control device, including: a parameter acquisition module, configured to acquire a driving control task to be executed and target parameters associated with the driving control task; and an algorithm execution module, configured to execute a corresponding algorithm based on the target parameters so that the driving control system can complete the driving control task.

[0008] This application embodiment also provides a task processing device residing in a second computing device, including: a receiving module configured to receive a target parameter request sent by a first computing device; and a processing module configured to, in response to the target parameter request sent by the first computing device, send target parameters associated with a driving control task to the first computing device, so that the first computing device executes a corresponding algorithm based on the target parameters, so that the driving control system can complete the driving control task.

[0009] This application also provides a first computing device, including: one or more processors; a storage device for storing one or more programs; when one or more programs are executed by one or more processors, the one or more processors implement the above-described vehicle control method.

[0010] This application also provides a second computing device, including: one or more processors; a storage device for storing one or more programs; and when one or more programs are executed by one or more processors, the one or more processors implement the above-described task processing method.

[0011] This application also provides a vehicle control system, including a first computing device and a second computing device, which are connected via a network; the second computing device is used to manage target parameters associated with driving control tasks and metadata corresponding to the target parameters; the first computing device is used to acquire the target parameters and control the vehicle according to the target parameters.

[0012] This application provides a vehicle control and task processing method, apparatus, computing device, and system. The vehicle control method includes: acquiring a driving control task to be executed and target parameters associated with the driving control task; and executing a corresponding algorithm based on the target parameters to enable the driving control system to complete the driving control task. Through the above technical solution, accurate vehicle parameters are obtained based on the driving control task, thereby improving the reliability of driving control. Attached Figure Description

[0013] Figure 1 A flowchart illustrating a vehicle control method provided in one embodiment of this application;

[0014] Figure 2 A flowchart of a vehicle control method provided in another embodiment of this application;

[0015] Figure 3 A schematic diagram illustrating a process for obtaining target parameters according to an embodiment of this application;

[0016] Figure 4 A flowchart of a vehicle control method provided in another embodiment of this application;

[0017] Figure 5 A flowchart illustrating a task processing method provided in one embodiment of this application;

[0018] Figure 6 A flowchart of a task processing method provided in another embodiment of this application;

[0019] Figure 7 This is a schematic diagram of the structure of a vehicle control device provided in one embodiment of this application;

[0020] Figure 8 This is a schematic diagram of the structure of a task processing device provided in an embodiment of this application;

[0021] Figure 9 A schematic diagram of the hardware structure of a first computing device provided in an embodiment of this application;

[0022] Figure 10 A schematic diagram of the hardware structure of a second computing device provided in an embodiment of this application;

[0023] Figure 11 This is a schematic diagram of the structure of a vehicle control system provided in an embodiment of this application. Detailed Implementation

[0024] The present application will now be described in further detail with reference to the accompanying drawings and embodiments. It is understood that the specific embodiments described herein are merely illustrative of the application and not intended to limit it. Furthermore, the embodiments and features described herein can be combined with each other unless otherwise specified. It should also be noted that, for ease of description, only the parts relevant to the present application are shown in the accompanying drawings, not the entire structure.

[0025] Before discussing the exemplary embodiments in more detail, it should be noted that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although the flowcharts describe the steps as sequential processes, many of these steps can be performed in parallel, concurrently, or simultaneously. Furthermore, the order of the steps can be rearranged. The process can be terminated when its operation is complete, but may also have additional steps not included in the figures. The process can correspond to a method, function, procedure, subroutine, subroutine, etc.

[0026] It should be noted that the concepts of "first" and "second" mentioned in the embodiments of this application are only used to distinguish different devices, modules, units or other objects, and are not used to limit the order or interdependence of the functions performed by these devices, modules, units or other objects.

[0027] In this application embodiment, a vehicle control method is provided, which obtains target parameters associated with driving control tasks and automatically executes corresponding algorithms to provide a reliable basis for the driving control system to complete driving control tasks.

[0028] Figure 1 This is a flowchart illustrating a vehicle control method provided in one embodiment of this application. Figure 1 As shown, the method provided in this embodiment includes:

[0029] S110: Obtain the driving control task to be executed, and the target parameters associated with the driving control task.

[0030] In this embodiment, the driving control task refers to the task that the vehicle needs to complete during autonomous driving, which can be controlled and executed by the driving control system. The driving control system is used to perform real-time and continuous control of the vehicle. The driving control task is related to the departure time, driving start point, driving end point, driving scenario, etc. For example, for a cargo transportation task, it is necessary to obtain the vehicle's driving path and determine the trailer and load-bearing capacity of the vehicle; for a reversing task, it is necessary to determine the parking space and reversing start point; for a passenger transport task, it is necessary to obtain the vehicle's driving path and determine the drop-off points of each passenger.

[0031] The target parameters associated with the driving control task refer to the various hardware and software configuration parameters required to execute the driving control task. These include various hardware and software configuration parameters that affect the control method or control algorithm of the driving control system. These target parameters may include the physical parameters of different tractors and trailers, the layout and calibration information of various sensors on the vehicle, and the software for vehicle-side services and the corresponding software allocation resources. The target parameters also include parameters related to the algorithm models obtained by machine learning training. These algorithm models are used to automatically execute corresponding algorithms based on the obtained target parameters for different driving control tasks, such as localization algorithms, perception algorithms, decision-making algorithms, control algorithms, road condition analysis algorithms, path planning algorithms, and obstacle avoidance algorithms.

[0032] In one embodiment, the target parameter may be read directly from the vehicle-side parameter package by the vehicle, provided that the locally stored vehicle-side parameter package is correct; or, if the vehicle software and / or hardware information changes, it may be obtained from the vehicle parameters stored in the cloud according to the driving control task.

[0033] S120: Executes the corresponding algorithm based on the target parameters so that the driving control system can complete the driving control task.

[0034] In this embodiment, the vehicle provides the target parameters associated with the driving control task and the execution results of the algorithm (such as road condition analysis results, path planning results and / or obstacle avoidance instructions) to the driving control system so that the driving control system can complete the driving control task during the unmanned driving process.

[0035] In one embodiment, the driving control task includes at least one of the following information: driving start point, driving end point, driving scenario, vehicle number, and trailer number.

[0036] The driving start point is typically the vehicle's departure point, i.e., where the vehicle is parked; the driving end point is the destination, such as transporting goods to a designated location, where the designated location is the driving end point. Driving scenarios include reversing, long-distance driving, short-distance driving, continuous driving, intermittent driving, highway driving, mountain road driving, cargo driving, and / or passenger driving, etc., with different driving scenarios associated with different target parameters. For example, in reversing, target parameters related to the reversing function need to be obtained, such as the command to turn off some forward sensors and the command to turn on the rear camera and radar, to facilitate monitoring the status behind the vehicle. In highway driving scenarios, target parameters related to the cruise control function can be obtained to automatically control the vehicle speed and reduce unnecessary speed changes, saving fuel, and the command to turn off the rear sensors can also be obtained, along with as many target parameters as possible from the forward sensors. In scenarios with complex terrain and road conditions, such as mountain road driving, target parameters related to the panoramic imaging function can be obtained to obtain the configuration of all-around sensors, or to automatically determine when and which target parameters should be read, to adapt to complex terrain and road conditions. The vehicle number is used to uniquely identify the vehicle that has been dispatched. It can be a license plate number, vehicle identification number (VIN), or other unique identifier for the vehicle. This vehicle number can be the tractor number. The trailer number is used to uniquely identify the trailer that the vehicle is attached to. Different trailer models, sizes, or shapes can also affect the target parameters required for autonomous driving control.

[0037] In one embodiment, the target parameter is also associated with vehicle parameter change information; the parameter change information includes at least one of the following: vehicle model information, trailer information, pairing relationship between vehicle model information and trailer information, sensor information, and vehicle-side server configuration.

[0038] Specifically, if the vehicle's software and / or hardware information changes, the target parameters need to be reacquired. For example, this could involve changing the vehicle model, replacing the trailer of the vehicle, changing the pairing relationship between the vehicle model and the trailer, changing the layout or calibration parameters of the sensors installed on the vehicle, or changing the configuration of the vehicle-side server used.

[0039] For example, for driverless trucks or tractor units, the trailers they carry may be changed daily, and the trailer configuration parameters need to be updated accordingly. By establishing a pairing relationship between vehicle models and trailers, the corresponding trailer configuration parameters can be flexibly obtained even when the vehicle model changes, improving the reliability of trailer use during driving control.

[0040] For example, different server configurations correspond to different server software and software resource allocations. Different types of servers have different configurations, and even servers of the same type can have different configuration schemes. This server configuration can be hardware configuration, such as different Central Processing Unit (CPU) configurations and / or different Graphics Processing Unit (GPU) configurations (or it can involve servers of different thicknesses). The software resource allocation scheme may also differ. Based on the changes in the vehicle-side server configuration, the resource allocation scheme for the vehicle-side server can be flexibly obtained to improve the actual execution efficiency of the software and avoid mutual interference. Furthermore, for different types of servers, the sockets corresponding to the vehicle-side service software may also be different.

[0041] In one embodiment, the target parameters include at least one of the following: vehicle size, vehicle model, hardware layout and calibration information; trailer identification, trailer size and sensor information installed on the trailer; sensor type, number, setting position and angle; parameters of the algorithm model bound to the driving control task; and configuration parameters of the correspondence between the vehicle-side service software and the software-allocated resources.

[0042] In this embodiment, the target parameters include one or more of the following:

[0043] 1) Parameters associated with the vehicle, such as vehicle size, vehicle model, vehicle hardware layout and / or calibration information, can be pre-assigned a unique number to the vehicle to facilitate the maintenance of the parameters associated with the vehicle.

[0044] The hardware layout includes the sensors installed on the vehicle and the functions of each sensor. For example, the image sensor camera1 is a forward-facing left-side camera, camera2 is a side-facing right-side camera, and lidar1 is a lidar under the right-side rearview mirror.

[0045] The calibration information includes the positional relationships between the sensors and their positional relationships relative to the vehicle. For example, the positional offset and rotation of camera1 relative to the vehicle's center point (which can be set according to actual needs, usually the center point of the vehicle's front axle or other physically stable positions) can be represented using three-dimensional coordinates (yaw / roll / pitch) or quaternions. The calibration information describes the positional and rotational relationships between the sensors, allowing for the fusion of information from multiple sensors at different locations in three-dimensional space during driving control.

[0046] 2) Parameters associated with the trailer, such as trailer identification, trailer dimensions, and sensor information installed on the trailer. A unique number can be pre-assigned to each trailer for easy maintenance of these parameters. Trailer dimensions include the trailer's size, length, and / or wheelbase. There are several ways to obtain the trailer number, such as determining the required trailer and its number before departure via vehicle trip management services as a target parameter; manually specifying the trailer number as a target parameter; or reading the trailer number from an external storage device installed on the trailer as a target parameter.

[0047] 3) Parameters associated with the sensor, such as the sensor type, number, location, and angle. For pluggable sensors, these parameters can be obtained by reading the sensor's identifier or by detecting the pluggable sensor's plug-in / plug-out signals, connection or disconnection status with the vehicle, etc.

[0048] 4) Parameters of the algorithm model bound to the driving control task, such as the type of algorithm model obtained by machine learning training (e.g., clustering algorithm, neural network model and support vector machine model), model parameters (e.g., cluster centers, network structure, labels, weights and number of iterations), and the format of input and output data.

[0049] It should be noted that all parameters involved in the algorithm model can be considered target parameters. However, the algorithm model is typically a configuration containing a large number of parameters and consuming significant storage, which can affect the overall file size and processing efficiency of the configuration file. In this embodiment, the algorithm model itself may not be considered a target parameter, but determining which algorithm model to select for different driving control tasks is part of the target parameters; that is, the type of algorithm model is considered a target parameter.

[0050] 5) Configuration parameters for the correspondence between vehicle-side service software and software-allocated resources.

[0051] The mapping between server software and allocated resources differs depending on the server type. Target parameters include configuration parameters detailing this mapping. For example, if the vehicle is using a 3U (3Unit, where U or Unit represents the external dimensions of the server) server that day, the required target parameters would include the software configuration and corresponding allocated resources on the 3U server. If a 7U (7Unit) server is used that day, the required target parameters would include the software configuration and corresponding allocated resources on the 7U server. Additionally, target parameters may also include configuration parameters detailing the mapping between vehicle-side service software and sockets.

[0052] In one embodiment, the algorithm model bound to the driving control task specifically includes algorithm models corresponding to different vehicle models and trailer types. For example, the length, wheelbase, weight, and other parameters of different vehicle models and trailers will result in differences in the field of view of the cameras installed on the vehicle, the obstructed areas, the vehicle's counterweight, and the vehicle's physical parameters. Multiple different algorithm models can be trained for different vehicle models and trailer types, or a general model can be trained.

[0053] In one embodiment, the target parameters bound to the driving control task specifically include physical parameters corresponding to different vehicle models. For example, vehicle model A does not support processing steering wheel angle messages, while vehicle model B does support processing steering wheel angle messages. Therefore, the target parameters obtained by vehicle model A when performing the driving control task do not include steering wheel angle messages, but vehicle model B obtains steering wheel angle messages.

[0054] In one embodiment, the target parameters bound to the driving control task specifically include algorithm models corresponding to different driving control tasks. For example, for the reversing task, there exists a set of planning and control algorithms and corresponding algorithm models specifically for reversing; while for the normal driving task, it is not necessary to obtain this set of algorithm models.

[0055] In one embodiment, the method further includes: selecting configuration parameters bound to vehicle model information as target parameters based on the configuration file of the vehicle-side service.

[0056] Specifically, the configuration parameters bound to vehicle model information are automatically selected based on the configuration file in the vehicle-side server. For example, the configuration file in the vehicle-side server records the vehicle model. When the vehicle model is determined, the vehicle's length, wheelbase, weight, and other configurations can also be determined. Therefore, the applicable algorithm model can be used as the target parameters based on the vehicle model's physical parameters, the field of view of the cameras installed on the vehicle, and the vehicle's weight distribution.

[0057] In one embodiment, the method further includes: selecting configuration parameters bound to trailer information as target parameters based on test and maintenance data of driving control tasks within a set time period.

[0058] Specifically, the configuration parameters bound to the trailer information are selected by the test and maintenance system based on vehicle deployment data within a set time period. For example, based on the number of vehicle deployments within a set time period, whether a trailer was attached to each deployment, and which trailer was attached, the system selects the appropriate trailer for the current driving control task and obtains the configuration parameters bound to the trailer information. This avoids frequent trailer changes and ensures trailer applicability. During large-scale operation, the vehicle control system can be integrated into the test and maintenance system to obtain information on each vehicle deployment and automatically select the configuration parameters bound to the trailer information as target parameters for the driving control task.

[0059] In one embodiment, the vehicle control method is adapted to be executed in a first computing device to obtain target parameters associated with a driving control task, including: accessing a second computing device according to the driving control task to obtain metadata associated with the driving control task; and obtaining the corresponding target parameters according to the metadata.

[0060] In this embodiment, the vehicle control method is suitable for execution in a first computing device, such as a vehicle controller, in-vehicle infotainment system (ECU), or vehicle-mounted server. The target parameters corresponding to the driving control task are stored and maintained by a second computing device, such as a cloud server, centralized control node, or network management device. The second computing device can receive parameters input by relevant personnel, as well as parameter update requests from the first computing device or monitor changes in the vehicle's hardware and software information, thereby updating and storing the latest vehicle parameters in a timely manner, allowing the first computing device to retrieve the corresponding target parameters according to the driving control task.

[0061] Furthermore, before acquiring the target parameters, the first computing device first obtains metadata from the second computing device based on the driving control task. Metadata is information used to describe the attributes of the target parameters, and can be used to indicate the target parameter's index name, storage location, update status, and version information records, etc. The first computing device first acquires the metadata based on the driving control task, and then acquires the corresponding target parameters based on the description of the metadata. For example, when a vehicle is equipped with trailer A, it needs to acquire the target parameters corresponding to trailer A. The metadata acquired at this time must at least include a unique index name describing the target parameters corresponding to trailer A. For example, when vehicle X is equipped with trailer A, the index name of the target parameter it might acquire is XA, but when it is equipped with trailer B, the index name of the target parameter it might acquire becomes XB.

[0062] For example, if the vehicle-side server used by the first computing device is a 3U server, the target parameters to be obtained include the software version on the 3U server and the index name of the corresponding socket; if a 7U server is used on the same day, the target parameters to be obtained include the software version on the 7U server and the index name of the corresponding socket.

[0063] In one embodiment, after obtaining the target parameters associated with the driving control task, the method further includes: storing the metadata and the corresponding target parameters as a vehicle-side parameter package; and calling the parameter acquisition interface to read the target parameters in the vehicle-side parameter package.

[0064] In this embodiment, by storing metadata and corresponding target parameters locally in the form of a vehicle-side parameter package, a unified parameter acquisition interface can be used to read the corresponding target parameters from the vehicle-side parameter package for different driving control tasks. This is used for the execution of the corresponding algorithm and for the driving control system, simplifying the storage and retrieval process of target parameters and improving the efficiency of vehicle control.

[0065] Figure 2 A flowchart illustrating a vehicle control method according to another embodiment of this application. Figure 2 As shown, the method includes:

[0066] S210: Obtain the driving control task to be executed.

[0067] S220: Access the second computing device according to the driving control task to obtain metadata associated with the driving control task.

[0068] In one embodiment, the metadata includes at least one of the following:

[0069] The index of the parameter set to which the target parameter belongs. For example, in the second computing device, the target parameters corresponding to different driving control tasks correspond to different parameter sets. The index of the parameter set is used to distinguish between different parameter sets. The first computing device first obtains the index of the parameter set to which the target parameter belongs, and then can obtain the corresponding target parameter from the second computing device according to the index of the parameter set to which the target parameter belongs.

[0070] The creation time and update time of the target parameter are used to quickly determine whether the target parameter is up-to-date;

[0071] Historical version information of the target parameter and the index of each historical version make it easy to quickly roll back to the problematic parameter version;

[0072] The creator and updater of the target parameters are used to quickly find possible contacts when parameters are incorrect;

[0073] The updated description information of the target parameters is used to quickly troubleshoot possible causes when parameters are incorrect. For example, is the update of the target parameters due to changes in the vehicle's software and hardware, or is it an update entered by relevant personnel?

[0074] This embodiment uses metadata to describe the update time, historical version, and updater of target parameters, which facilitates the maintenance, updating, and expansion of metadata. In case of update failure, historical versions can be restored, and in case of errors, the source can be traced to quickly determine the cause of the fault and the solution, thereby improving the reliability of vehicle control.

[0075] S230: Obtain the corresponding target parameters based on the metadata.

[0076] S240: Store the metadata and corresponding target parameters as a vehicle-side parameter package.

[0077] S250: Call the parameter retrieval interface to read the target parameters in the vehicle-side parameter package.

[0078] In this embodiment, the first receiving device obtains specific target parameters from the second computing device based on the acquired metadata and stores them as a local vehicle-side parameter package. When executing the algorithm, the corresponding algorithm can be directly read from the vehicle-side parameter package and executed through a unified parameter acquisition interface. The algorithm code itself can also be read from the vehicle-side parameter package through this parameter acquisition interface. These parameters may not be maintained by the algorithm itself (such as vehicle length and width parameters, which have nothing to do with the algorithm), or they may be maintained by the algorithm developers in the parameter management system (such as unique identifiers used to find the algorithm model).

[0079] S260: Executes the corresponding algorithm based on the target parameters to enable the driving control system to complete the driving task.

[0080] In one embodiment, obtaining the corresponding target parameter based on metadata includes: determining whether the vehicle-side device stores local metadata associated with the driving control task; if so, when the metadata is updated relative to the local metadata stored on the vehicle-side device, obtaining the target parameter corresponding to the metadata from the second computing device.

[0081] In this embodiment, if the vehicle-side stores local metadata associated with the driving control task, it means that the target parameters associated with the driving control task have been obtained and stored as a vehicle-side parameter package based on the local metadata. In this case, if the metadata corresponding to the current driving control task is updated relative to the stored local metadata, the target parameters are obtained again from the second computing device.

[0082] In one embodiment, obtaining the corresponding target parameter based on metadata further includes: when the metadata is not updated relative to the local metadata stored on the vehicle, using the target parameter in the vehicle parameter package corresponding to the local metadata stored locally.

[0083] In this embodiment, if the metadata corresponding to the current driving control task is consistent with the already stored local metadata, it is not necessary to obtain the target parameters from the second computing device. Instead, the metadata related to the driving control task in the vehicle-side parameter package can be read directly.

[0084] Figure 3 This is a schematic diagram illustrating a process for obtaining target parameters according to an embodiment of this application. Figure 3 As shown, the second computing device includes a parameter management service, a parameter checking service, and a parameter storage service. Relevant personnel or the first computing device can initiate a parameter update request. The second computing device responds to the request through the parameter management service, collecting and storing the latest vehicle parameters. The parameter management service also triggers a correctness check on the vehicle parameters, and the parameter checking service runs tests to verify their correctness. Once the vehicle parameters pass the check, they are submitted to the parameter storage service, and the parameter management service maintains the parameter metadata.

[0085] The first computing device includes a parameter retrieval service, a parameter acquisition interface, and an algorithm execution module. The parameter retrieval service retrieves corresponding metadata from the parameter management service based on the driving control task, and then obtains specific target parameters from the parameter storage service based on the acquired metadata, storing them as a vehicle-side parameter package. When the user's algorithm module code needs to use the parameters, it reads the parameters from the vehicle-side parameter package through a unified parameter acquisition interface. The parameter management mechanism in this embodiment can dynamically load the configuration of pluggable external components such as mounting boxes and verify the correctness of autonomous vehicle parameters, thereby ensuring the availability and correctness of parameters. It can also efficiently switch configurations, improve the reliability of vehicle control, and guarantee the safety of autonomous driving.

[0086] Figure 4 A flowchart of a vehicle control method provided in another embodiment of this application;

[0087] S310: Obtain the driving control task to be executed.

[0088] S320: Access the second computing device according to the driving control task to obtain metadata associated with the driving control task.

[0089] S330: Based on the package manager, it obtains target parameters from the second computing device according to metadata, wherein the target parameters are processed by the online configuration file editor and stored in the second computing device.

[0090] S340: Store the metadata and corresponding target parameters as a vehicle-side parameter package.

[0091] S350: Based on the software development kit, it calls the preset parameter acquisition interface to read the target parameters in the vehicle-side parameter package according to the driving control task.

[0092] S360: Detects the consistency between the trailer currently mounted on the vehicle and the trailer specified in the driving control task.

[0093] S370: Execute the corresponding algorithm based on the target parameters.

[0094] S380: Sends the target parameters and algorithm execution results to the driving control system so that the driving control system can complete the driving control task.

[0095] In this embodiment, obtaining the corresponding target parameters from the second computing device based on metadata includes: obtaining the target parameters from the second computing device based on metadata using a package manager, wherein the target parameters are processed by an online configuration file editor and then stored in the second computing device.

[0096] Specifically, a package manager is used to store and download target parameters. The package manager is a package management system that can distribute any configuration, data, and software packages in the form of binary files. In some embodiments, the package manager can also be replaced by any package management system, configuration management system, or file storage system. Furthermore, existing vehicle parameters can be edited, packaged, and distributed via an online configuration file editor, and stored in a second computing device as configuration packages. The first computing device retrieves the target parameters associated with the driving control task and corresponding to the metadata from the second computing device based on the package manager.

[0097] In this embodiment, calling the parameter acquisition interface to read the target parameters in the vehicle-side parameter package includes: based on the Software Development Kit (SDK), calling the preset parameter acquisition interface to read the target parameters in the vehicle-side parameter package according to the driving control task.

[0098] Specifically, the first computing device reads the target parameters for the driving control task stored in the vehicle-side parameter package by calling the preset parameter acquisition interface through the SDK. During the execution of the algorithm, the first computing device uses these target parameters as needed and provides these target parameters and the algorithm execution results to the driving control system as needed.

[0099] In this embodiment, before executing the corresponding algorithm based on the target parameters, the method further includes: detecting the consistency between the trailer currently mounted on the vehicle and the trailer specified by the driving control task.

[0100] Specifically, for vehicles with trailers, such as tractors and trucks, the consistency between the currently mounted trailer and the trailer specified in the driving control task is checked before departure. For example, if vehicle #1 is mounted with trailer #3, but in the subsequent driving control task, vehicle #1 needs to use trailer #2, if the currently mounted trailer number does not match the trailer number specified in the driving control task, the tester can be prompted that the trailer mounting may be incorrect, and at least two options can be provided, including trailer #2 and trailer #3. Alternatively, the default option can be the trailer specified in the driving control task, namely trailer #2. The tester needs to confirm that the current selection (trailer #2) is correct, obtain the target parameters bound to this trailer, and then initiate autonomous driving.

[0101] Specifically, a trailer hitch can be viewed as a connectable physical device. By assigning a unique physical number to each trailer hitch, a chip and connecting cables detect whether a hitch is attached or connected, and send the detected trailer hitch number to a first computing device. The first computing device then checks the consistency between this trailer hitch number and the trailer hitch number specified in the driving control task. In some scenarios, a trailer hitch may be uniquely bound to other devices; detecting these other devices can also reveal the currently attached trailer hitch number. For example, when connecting a trailer hitch, a rear-facing camera mounted on the trailer may also be required. In this case, detecting the rear-facing camera's identifier can also determine the consistency between the currently attached trailer hitch and the one specified in the driving control task.

[0102] In this embodiment, before accessing the second computing device according to the driving control task, the method further includes: receiving a parameter configuration instruction generated by the driving control system according to the driving control task to trigger the operation of accessing the second computing device; after executing the corresponding algorithm based on the target parameters, the method further includes: sending the target parameters and the algorithm execution result to the driving control system so that the driving control system can complete the driving control task.

[0103] Specifically, the driving control system uses target parameters to control the vehicle. Before that, the driving control system sends a parameter configuration command to trigger the first computing device to access the second computing device and obtain metadata and target parameters from the second computing device.

[0104] The following details vehicle control methods through specific examples.

[0105] The following events occur in the given order:

[0106] On the morning of X month 1, a camera on vehicle #1 was reinstalled, and the calibration information of the camera relative to the vehicle's position changed.

[0107] On the afternoon of X month 1, vehicle #1 was assigned the driving control task for X month 2, which required it to be loaded with trailer #2, but at this time the vehicle was still loaded with trailer #3.

[0108] On the afternoon of X month 1, technician A updated the camera calibration information for vehicle #1;

[0109] On the morning of X month 2, tester B retrieved the configuration of vehicle #1 and trailer #2 before setting off.

[0110] On the morning of X month 2, driver C replaced trailer #3 with trailer #2 before setting off.

[0111] On the morning of X month 2, driver C drove as usual;

[0112] On the morning of X month 2, the first computing device reads the target parameters in the vehicle-side parameter package through the parameter acquisition interface, and controls the vehicle to complete the driving control task accordingly.

[0113] The above process mainly includes the following steps:

[0114] 1) Vehicle #1 was assigned a driving control task for Month 2nd. During this process, the task management system will generate driving control task data for Vehicle #1 on Month 2nd, describing the various configuration information required for the driving control task, including the information about attaching trailer #2. Different vehicles and different tasks will correspond to different configuration information. Metadata can be mapped to specific configuration information. Storing metadata is to avoid retrieving complete configuration information when transmitting messages and performing availability checks (such as whether the version is up-to-date). Additionally, the task management system can provide some default configuration information (metadata) for driving control tasks on the task assignment interface. The person assigning the task can modify a portion of this information according to the actual situation of the task that day to form the final configuration information required for the task.

[0115] 2) Technicians update the camera calibration configuration of vehicle #1. In this step, technicians can edit the configuration using the online tools provided by the parameter management service, or they can edit the configuration file offline and then upload it. After the technicians update the configuration, the parameter management service calls the inspection pipeline provided by the parameter inspection service to confirm whether there are any problems with the updated parameters. This part will check for all problems that can be detected offline, such as mismatches in the calibration configurations of multiple hardware components, but it cannot detect problems that cannot be detected offline, such as minor errors in the calibration parameters of a single hardware component. After passing the parameter configuration check, the parameter management service will store this parameter in the parameter storage service and record information about the latest version of the parameter.

[0116] 3) Before the test personnel depart, they retrieve the configuration of vehicle #1. The parameter retrieval service determines which target parameters should be retrieved based on the driving control task. Then, the parameter retrieval service obtains the latest version of metadata from the parameter management service based on the current vehicle (vehicle #1), and retrieves the corresponding version of the target parameters through the vehicle storage service, storing the target parameters in the local vehicle-side parameter package.

[0117] 4) Before setting off, Tester B obtains the configuration of trailer #2 for vehicle #1 corresponding to the driving control task. However, since trailer #3 is currently mounted on vehicle #1, which is inconsistent with trailer #2 specified in the driving control task, the parameter retrieval service can provide Tester B with at least two options, prompting Tester B to decide whether to ultimately use the target parameters for trailer #2 or trailer #3. Alternatively, the target parameters for trailer #2 specified in the driving control task can be used by default. For target parameters other than those bound to trailers, if the target parameters specified in the driving control task do not match the current actual situation, a similar approach can be used, i.e., prompting relevant personnel to select target parameters, or defaulting to the target parameters specified in the driving control task.

[0118] 5) Driver C changes the trailer and drives the vehicle normally, and the driving control system is activated. It should be noted that if the trailer actually mounted on the vehicle is inconsistent with the trailer in the target parameters when the driving control system is activated, an incorrect trailer mounting message will be given. The driving control system will be activated normally after relevant personnel confirm that there is no error.

[0119] 6) The algorithm execution module reads the target parameters through the parameter acquisition interface and executes the corresponding algorithm. The target parameters and execution results are provided to the driving control system to control the vehicle. The algorithm execution module uses the SDK to call the preset unified parameter acquisition interface to read the specific parameters of different configurations such as vehicle and trailer already stored in the vehicle-side parameter package, and uses these parameters in the specific algorithm according to its own needs.

[0120] The vehicle control method in this embodiment solves the problems of parameter management, storage and maintenance of unmanned vehicles, ensuring the correctness of unmanned driving parameter configuration, and guaranteeing the effectiveness and timeliness of vehicle parameters for different driving control tasks, thus providing a reliable guarantee for driving control safety.

[0121] This application also provides a task processing method. Figure 5 This is a flowchart illustrating a task processing method according to an embodiment of this application. It should be noted that technical details not described in detail in this embodiment can be found in any of the above embodiments.

[0122] like Figure 5 As shown, the method provided in this embodiment includes:

[0123] S410: Receives the target parameter request sent by the first computing device.

[0124] S420: In response to the target parameter request sent by the first computing device, send the target parameters associated with the driving control task to the first computing device so that the first computing device can execute the corresponding algorithm based on the target parameters so that the driving control system can complete the driving control task.

[0125] In this embodiment, the target parameter request includes a driving control task. The target parameter request can be sent from the parameter retrieval service of the first computing device to the parameter storage service of the second computing device. The second computing device sends the target parameters associated with the driving control task to the first computing device for automatic execution of the corresponding algorithm, providing a reliable basis for the driving control system to complete the driving control task.

[0126] Figure 6 A flowchart illustrating a task processing method provided in another embodiment of this application. For example... Figure 6 As shown, in this embodiment, it further includes: receiving a parameter update request sent by a first computing device, the parameter update request containing updated vehicle parameters; checking the correctness of the vehicle parameters, and storing the corrected vehicle parameters and their corresponding metadata.

[0127] In this embodiment, the first computing device can periodically send parameter update requests to the second computing device, or send parameter update requests to the second computing device when changes in the vehicle's hardware and software information are detected. The second computing device collects the latest vehicle parameters based on the parameter update requests and checks the correctness of the vehicle parameters. The checked vehicle parameters can be stored in the parameter storage service of the second computing device.

[0128] S510: Receives a parameter update request sent by the first computing device, the parameter update request containing the updated vehicle parameters.

[0129] S520: Checks the correctness of vehicle parameters and stores the corrected vehicle parameters and their corresponding metadata.

[0130] Specifically, vehicle parameters can be checked using preset scripts and check rules.

[0131] In one embodiment, checking the correctness of vehicle parameters includes at least one of the following:

[0132] 1) Check whether the upper and lower limits of vehicle parameters are within the preset range. For example, check whether the highest and lowest sensitivity of the sensors are within the preset range to avoid the sensors being too sensitive or too low, which would affect the flexibility and safety of driving control. Also, check whether the sensor position is in the expected position.

[0133] 2) Check whether the mathematical calculation results of vehicle parameters belong to the preset set. For example, check whether the trailer required to complete the driving control task in a specific driving scenario is one of the spare trailers, and whether the number of sensors required is less than or equal to the total number of sensors set in the vehicle.

[0134] 3) Check whether the output after substituting the vehicle parameters into the preset code meets the preset conditions. For example, check whether the server software and sockets can achieve normal operation of the software and data communication when using the vehicle-side server with the appropriate configuration.

[0135] 4) Check the correct vehicle parameters and submit them to the parameter storage service. The parameter management service maintains the metadata of the vehicle parameters. When the second computing device receives the metadata request or target parameter request from the first computing device, it can send the metadata associated with the driving control task to the first computing device through the parameter management service, or send the target parameters associated with the driving control task to the first computing device through the parameter storage service.

[0136] S530: In response to the metadata request sent by the first computing device, send metadata associated with the driving control task to the first computing device, the metadata corresponding to the target parameters.

[0137] S540: In response to the target parameter request sent by the first computing device, send the target parameters associated with the driving control task to the first computing device so that the first computing device can execute the corresponding algorithm based on the target parameters so that the driving control system can complete the driving control task.

[0138] In this embodiment, before obtaining the target parameters, the parameter retrieval service of the first computing device can obtain the metadata associated with the driving control task from the parameter management service of the second computing device. Then, the parameter retrieval service obtains the corresponding target parameters based on the metadata, which facilitates the maintenance, updating, rollback and expansion of the target parameters.

[0139] This application also provides a vehicle control device. Figure 7 This is a schematic diagram of the structure of a vehicle control device provided in one embodiment of this application. Figure 7 As shown, the vehicle control device includes a parameter acquisition module 10 and an algorithm execution module 20.

[0140] The parameter acquisition module 10 is configured to acquire the driving control task to be executed and the target parameters associated with the driving control task;

[0141] The algorithm execution module 20 is configured to execute the corresponding algorithm based on the target parameters so that the driving control system can complete the driving control task.

[0142] The vehicle control device in this embodiment obtains target parameters associated with the driving control task and automatically executes the corresponding algorithm, providing a reliable basis for the driving control system to complete the driving control task.

[0143] In one embodiment, the vehicle control device is adapted to reside in a first computing device, wherein the parameter acquisition module 10 includes:

[0144] The metadata acquisition unit is configured to access the second computing device according to the driving control task in order to obtain metadata associated with the driving control task;

[0145] The target parameter acquisition unit is set to obtain the corresponding target parameters based on metadata.

[0146] In one embodiment, the vehicle control device further includes:

[0147] The storage module is configured to store the metadata and the corresponding target parameters as a vehicle-side parameter package after obtaining the corresponding target parameters based on the metadata.

[0148] The calling module is configured to retrieve the target parameters from the vehicle-side parameter package via the parameter retrieval interface.

[0149] In one embodiment, the target parameter acquisition unit is configured to: determine whether the vehicle terminal stores local metadata associated with the driving control task; if so, when the metadata is updated relative to the local metadata stored on the vehicle terminal, obtain the target parameter corresponding to the metadata from the second computing device.

[0150] In one embodiment, the target parameter acquisition unit is further configured to: when the metadata is not updated relative to the local metadata stored on the vehicle, use the target parameter in the vehicle parameter package corresponding to the local metadata stored locally.

[0151] In one embodiment, the driving control task includes at least one of the following information: driving start point, driving end point, driving scenario, vehicle number, and trailer number.

[0152] In one embodiment, the target parameter is also associated with vehicle parameter change information; the parameter change information includes at least one of the following: vehicle model information, trailer information, pairing relationship between vehicle model information and trailer information, sensor information, and vehicle-side server configuration.

[0153] In one embodiment, the target parameters include at least one of the following: vehicle size, vehicle model, hardware layout and calibration information; trailer identification, trailer size and sensor information installed on the trailer; sensor type, number, setting position and angle; parameters of the algorithm model bound to the driving control task; and configuration parameters of the correspondence between the vehicle-side service software and the software-allocated resources.

[0154] In one embodiment, the metadata includes at least one of the following: an index of the parameter set to which the target parameter belongs; the creation time and update time of the target parameter; historical version information of the target parameter and an index of each historical version; the creator and updater of the target parameter; and update description information of the target parameter.

[0155] In one embodiment, the vehicle control device further includes a first selection module, configured to select configuration parameters bound to vehicle model information as target parameters based on the configuration file of the vehicle-side service.

[0156] In one embodiment, the vehicle control device further includes a second selection module, configured to select configuration parameters bound to the trailer information as target parameters based on test and maintenance data of driving control tasks within a set time period.

[0157] In one embodiment, the target parameter acquisition unit is configured to: acquire target parameters from the second computing device based on metadata according to the package manager, wherein the target parameters are processed by the online configuration file editor and stored in the second computing device.

[0158] In one embodiment, the calling module is configured to: based on the software development kit, call a preset parameter acquisition interface to read the target parameters in the vehicle-side parameter package according to the driving control task.

[0159] In one embodiment, the vehicle control device further includes a detection module configured to detect the consistency between the trailer currently mounted on the vehicle and the trailer specified by the driving control task before executing the corresponding algorithm based on the target parameters.

[0160] In one embodiment, the vehicle control device further includes:

[0161] The triggering module is configured to receive a parameter configuration instruction generated by the driving control system according to the driving control task before accessing the second computing device according to the driving control task, so as to trigger the execution of the operation of accessing the second computing device;

[0162] The sending module is configured to send the target parameters and the algorithm execution results to the driving control system after executing the corresponding algorithm based on the target parameters, so that the driving control system can complete the driving control task.

[0163] The vehicle control device proposed in this embodiment belongs to the same inventive concept as the vehicle control method proposed in the above embodiments. Technical details not described in detail in this embodiment can be found in any of the above embodiments. Furthermore, this embodiment has the same beneficial effects as the vehicle control method.

[0164] This application also provides a task processing device. Figure 8 This is a schematic diagram of a task processing device provided in one embodiment of this application. Figure 8 As shown, the task processing device includes a receiving module 30 and a processing module 40.

[0165] The receiving module 30 is configured to receive the target parameter request sent by the first computing device;

[0166] The processing module 40 is configured to send target parameters associated with the driving control task to the first computing device in response to a target parameter request sent by the first computing device, so that the first computing device can execute a corresponding algorithm based on the target parameters to enable the driving control system to complete the driving control task.

[0167] In this embodiment, the task processing device sends target parameters associated with the driving control task to the first computing device for automatic execution of the corresponding algorithm, providing a reliable basis for the driving control system to complete the driving control task.

[0168] In one embodiment, the task processing apparatus further includes: a metadata response module, configured to send metadata associated with the driving control task to the first computing device in response to a metadata request sent by the first computing device, wherein the metadata corresponds to the target parameters.

[0169] In one embodiment, the task processing apparatus further includes:

[0170] The update module is configured to receive parameter update requests sent by the first computing device, the parameter update requests containing the updated vehicle parameters;

[0171] The inspection module is configured to check the correctness of vehicle parameters and store the vehicle parameters that have been checked correctly, along with their corresponding metadata.

[0172] In one embodiment, the checking module is configured to at least one of the following: checking whether the upper and lower limits of the vehicle parameters belong to a preset range; checking whether the mathematical operation result of the vehicle parameters belongs to a preset set; and checking whether the output after substituting the vehicle parameters into the preset code and running it meets the preset conditions.

[0173] The task processing device proposed in this embodiment and the task processing method proposed in the above embodiments belong to the same inventive concept. Technical details not described in detail in this embodiment can be found in any of the above embodiments. Furthermore, this embodiment has the same beneficial effects as the task processing method.

[0174] This application also provides a first computing device. Figure 9 A schematic diagram of the hardware structure of a first computing device provided in an embodiment of this application is shown below. Figure 9 As shown, the first computing device provided in this application includes a memory 52, a processor 51, and a computer program stored in the memory and executable on the processor. When the processor 51 executes the program, it implements the vehicle control method described above.

[0175] The first computing device may further include a memory 52; the processor 51 in the first computing device may be one or more. Figure 9 Taking a processor 51 as an example; memory 52 is used to store one or more programs; one or more programs are executed by one or more processors 51, so that one or more processors 51 implement the vehicle control method as described in the embodiments of this application.

[0176] The first computing device also includes: a communication device 53, an input device 54, and an output device 55.

[0177] The processor 51, memory 52, communication device 53, input device 54, and output device 55 in the first computing device can be connected via a bus or other means. Figure 9 Taking the example of a connection between China and Israel via a bus.

[0178] The input device 54 can be used to receive input digital or character information, and to generate key signal inputs related to user settings and function control of the first computing device. The output device 55 may include a display device such as a display screen.

[0179] The communication device 53 may include a receiver and a transmitter. The communication device 53 is configured to perform information transmission and reception communication under the control of the processor 51.

[0180] The memory 52, as a computer-readable storage medium, can be configured to store software programs, computer-executable programs, and modules, such as program instructions / modules corresponding to the vehicle control method in this application embodiment (e.g., parameter acquisition module 10 and algorithm execution module 20 in the vehicle control device). The memory 52 may include a program storage area and a data storage area, wherein the program storage area may store the operating system and at least one application program required for a function; the data storage area may store data created based on the use of the first computing device, etc. Furthermore, the memory 52 may include high-speed random access memory and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other non-volatile solid-state storage device. In some instances, the memory 52 may further include memory remotely located relative to the processor 51, and these remote memories can be connected to the first computing device via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0181] This application also provides a second computing device. Figure 10 A schematic diagram of the hardware structure of a second computing device provided in an embodiment of this application is shown below. Figure 10As shown, the second computing device provided in this application includes a memory 62, a processor 61, and a computer program stored in the memory and executable on the processor. When the processor 61 executes the program, it implements the task processing method described above.

[0182] The second computing device may further include a memory 62; the processor 61 in the second computing device may be one or more. Figure 10 Taking a processor 61 as an example; memory 62 is used to store one or more programs; one or more programs are executed by one or more processors 61, so that one or more processors 61 implement the task processing method as described in the embodiments of this application.

[0183] The second computing device also includes: a communication device 63, an input device 64, and an output device 65.

[0184] The processor 61, memory 62, communication device 63, input device 64, and output device 65 in the second computing device can be connected via a bus or other means. Figure 10 Taking the example of a connection between China and Israel via a bus.

[0185] Input device 64 can be used to receive input digital or character information, and to generate key signal inputs related to user settings and function control of the second computing device. Output device 65 may include a display device such as a display screen.

[0186] The communication device 63 may include a receiver and a transmitter. The communication device 63 is configured to perform information transmission and reception communication under the control of the processor 61.

[0187] The memory 62, as a computer-readable storage medium, can be configured to store software programs, computer-executable programs, and modules, such as program instructions / modules corresponding to the task processing method in the embodiments of this application (e.g., the receiving module 30 and processing module 40 in the task processing device). The memory 62 may include a program storage area and a data storage area, wherein the program storage area may store the operating system and at least one application program required for a function; the data storage area may store data created based on the use of the second computing device, etc. Furthermore, the memory 62 may include high-speed random access memory and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other non-volatile solid-state storage device. In some instances, the memory 62 may further include memory remotely located relative to the processor 61, and these remote memories can be connected to the second computing device via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0188] Figure 11This is a schematic diagram of a vehicle control system according to an embodiment of this application. This application also provides a vehicle control system including a first computing device 71 and a second computing device 72, which are connected via a network. The second computing device 72 is used to manage target parameters associated with driving control tasks and the metadata corresponding to the target parameters. The first computing device 71 is used to acquire the target parameters and control the vehicle according to the target parameters.

[0189] In this embodiment, the first computing device 71 can be used to execute the vehicle control method in any of the above embodiments. The second computing device 72 can be used to execute the task processing method in any of the above embodiments.

[0190] In one embodiment, the first computing device 71 obtains target parameters associated with the driving control task, specifically including: the first computing device 71 accessing the second computing device 72 according to the driving control task to obtain metadata associated with the driving control task; and obtaining the corresponding target parameters according to the metadata.

[0191] In one embodiment, after obtaining the corresponding target parameters based on the metadata, the first computing device 71 also stores the metadata and the corresponding target parameters as a vehicle-side parameter package; and calls the parameter acquisition interface to read the target parameters in the vehicle-side parameter package.

[0192] In one embodiment, the first computing device 71 obtains the corresponding target parameters based on metadata, including: the first computing device 71 determines whether the vehicle terminal stores local metadata associated with the driving control task; if so, when the metadata is updated relative to the local metadata stored on the vehicle terminal, the target parameters corresponding to the metadata are obtained from the second computing device 72.

[0193] In one embodiment, when the metadata is not updated relative to the local metadata stored on the vehicle, the first computing device 71 uses the target parameter in the vehicle parameter package corresponding to the local metadata stored locally.

[0194] In one embodiment, the system further includes: a first computing device 71 selecting configuration parameters bound to vehicle model information as target parameters based on the configuration file of the vehicle service.

[0195] In one embodiment, the system further includes: a first computing device 71 selecting configuration parameters bound to the trailer information as target parameters based on test and maintenance data of driving control tasks within a set time period.

[0196] In one embodiment, the first computing device 71 obtains the corresponding target parameters from the second computing device based on metadata, including: the first computing device 71 obtains the target parameters from the second computing device based on metadata using a package manager, wherein the target parameters are processed by an online configuration file editor and then stored in the second computing device.

[0197] In one embodiment, the first computing device 71 calls a parameter acquisition interface to read the target parameters in the vehicle-side parameter package, including: the first computing device 71, based on a software development kit, calls a preset parameter acquisition interface to read the target parameters in the vehicle-side parameter package according to the driving control task.

[0198] In one embodiment, before executing the corresponding algorithm based on the target parameters, the first computing device 71 also detects the consistency between the trailer currently mounted on the vehicle and the trailer specified by the driving control task.

[0199] In one embodiment, before accessing the second computing device according to the driving control task, the first computing device 71 also receives a parameter configuration instruction generated by the driving control system according to the driving control task to trigger the operation of accessing the second computing device.

[0200] After executing the corresponding algorithm based on the target parameters, the first computing device 71 also sends the target parameters and the algorithm execution results to the driving control system so that the driving control system can complete the driving control task.

[0201] In one embodiment, the second computing device 72 receives a target parameter request sent by the first computing device 71; in response to the target parameter request sent by the first computing device 71, the second computing device 72 sends target parameters associated with the driving control task to the first computing device 71, so that the first computing device 71 executes a corresponding algorithm based on the target parameters, so that the driving control system can complete the driving control task.

[0202] In one embodiment, the second computing device 72 also responds to a metadata request sent by the first computing device 71 by sending metadata associated with the driving control task to the first computing device 71, the metadata corresponding to the target parameters.

[0203] In one embodiment, the second computing device 72 further receives a parameter update request sent by the first computing device, the parameter update request containing updated vehicle parameters; checks the correctness of the vehicle parameters, and stores the correct vehicle parameters and their corresponding metadata.

[0204] This application also provides a storage medium storing a computer program, which, when executed by a processor, implements any of the vehicle control methods or task processing methods described in this application.

[0205] The computer storage medium in this application embodiment can be any combination of one or more computer-readable media. The computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. For example, a computer-readable storage medium can be, but is not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of computer-readable storage media (a non-exhaustive list) include: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), flash memory, optical fiber, portable CD-ROM, optical storage device, magnetic storage device, or any suitable combination thereof. The computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0206] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, which can send, propagate, or transmit programs for use by or in connection with an instruction execution system, apparatus, or device.

[0207] Program code contained on a computer-readable medium may be transmitted using any suitable medium, including but not limited to: wireless, wire, optical fiber, radio frequency (RF), etc., or any suitable combination thereof.

[0208] Computer program code for performing the operations of this application can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages ​​such as "C" or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0209] The above description is merely an exemplary embodiment of this application and is not intended to limit the scope of protection of this application. Those skilled in the art will understand that the term "user terminal" encompasses any suitable type of wireless user equipment, such as mobile phones, portable data processing devices, portable web browsers, or vehicle-mounted mobile stations.

[0210] Generally, the various embodiments of this application can be implemented in hardware or dedicated circuitry, software, logic, or any combination thereof. For example, some aspects can be implemented in hardware, while others can be implemented in firmware or software that can be executed by a controller, microprocessor, or other computing device, although this application is not limited thereto.

[0211] Embodiments of this application can be implemented by executing computer program instructions through the data processor of a mobile device, for example, in a processor entity, or through hardware, or through a combination of software and hardware. The computer program instructions can be assembly instructions, Instruction Set Architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, status setting data, or source code or object code written in any combination of one or more programming languages.

[0212] Any block diagram of logical flow in the accompanying drawings of this application may represent program steps, or may represent interconnected logic circuits, modules, and functions, or may represent a combination of program steps and logic circuits, modules, and functions. The computer program may be stored in memory. The memory may be of any type suitable to the local technical environment and may be implemented using any suitable data storage technology, such as, but not limited to, read-only memory (ROM), random access memory (RAM), optical storage devices and systems (Digital Video Disc (DVD) or Compact Disk (CD), etc.). Computer-readable media may include non-transitory storage media. The data processor may be of any type suitable to the local technical environment, such as, but not limited to, general-purpose computers, special-purpose computers, microprocessors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), and processors based on multi-core processor architectures.

[0213] A detailed description of exemplary embodiments of this application has been provided above through exemplary and non-limiting examples. However, various modifications and adjustments to the above embodiments will be apparent to those skilled in the art when considered in conjunction with the accompanying drawings and claims, without departing from the scope of this application. Therefore, the proper scope of this application will be determined by the claims.

Claims

1. A vehicle control method, characterized in that, Suitable for execution in a first computing device located at the end of the vehicle, the method includes: Obtain the driving control tasks to be executed; Access a second computing device located in the cloud to obtain metadata associated with the driving control task; Obtain the corresponding target parameters based on the metadata; Based on the target parameters, the corresponding algorithm is executed so that the driving control system can complete the driving control task; The acquisition of the corresponding target parameters based on the metadata includes: Determine whether the vehicle-side device stores local metadata associated with the driving control task; If so, when the metadata is updated relative to the local metadata stored on the vehicle, the target parameters corresponding to the metadata are obtained from the second computing device. The target parameters include the parameters of the algorithm model bound to the driving control task.

2. The method according to claim 1, characterized in that, The algorithm models bound to the driving control task include: algorithm models corresponding to different vehicle models and trailer types.

3. The method according to claim 2, characterized in that, After obtaining the corresponding target parameters based on the metadata, the process also includes: The metadata and corresponding target parameters are stored as a vehicle-side parameter package; Call the parameter retrieval interface to read the target parameters from the vehicle-side parameter package.

4. The method according to claim 1, characterized in that, The target parameters also include the layout information of various sensors on the vehicle and the calibration information of various sensors.

5. The method according to claim 1, characterized in that, The step of obtaining the corresponding target parameters based on the metadata also includes: When the metadata is not updated relative to the local metadata stored on the vehicle, the target parameter in the vehicle parameter package corresponding to the local metadata stored locally is used.

6. The method according to claim 1, characterized in that, The driving control task includes at least one of the following information: driving start point, driving end point, driving scenario, vehicle number, and trailer number.

7. The method according to claim 1, characterized in that, The target parameters are also related to vehicle parameter change information; The parameter change information includes at least one of the following: vehicle model information, trailer information, pairing relationship between vehicle model information and trailer information, sensor information, and vehicle-side server configuration.

8. The method according to claim 1, characterized in that, The target parameter includes at least one of the following: Vehicle dimensions, vehicle model, hardware layout, and calibration information; Mounting box markings, mounting box dimensions, and sensor information installed on the mounting box; The type, number, location, and angle of the sensors; Configuration parameters relating the vehicle-side service software to the software-allocated resources.

9. The method according to claim 2, characterized in that, The metadata includes at least one of the following: The index of the parameter set to which the target parameter belongs; The creation time and update time of the target parameters; The historical version information of the target parameter and the index of each historical version; The creator and updater of the target parameters; Updated description information for the target parameters.

10. The method according to claim 8, characterized in that, Also includes: The configuration parameters that are bound to the vehicle model information are selected as the target parameters based on the configuration file of the vehicle service.

11. The method according to claim 8, characterized in that, Also includes: Based on the test and maintenance data of the driving control task within a set time period, the configuration parameters bound to the trailer information are selected as the target parameters.

12. The method according to claim 3, characterized in that, The step of obtaining the corresponding target parameters from the second computing device based on the metadata includes: Based on the package manager, target parameters are obtained from the second computing device according to the metadata, wherein the target parameters are processed by the online configuration file editor and stored in the second computing device.

13. The method according to claim 3, characterized in that, Calling the parameter retrieval interface to read the target parameters from the vehicle-side parameter package includes: Based on the software development kit, the target parameters in the vehicle-side parameter package are read by calling a preset parameter acquisition interface according to the driving control task.

14. The method according to claim 3, characterized in that, Before executing the corresponding algorithm based on the target parameters, the following steps are also included: The system checks the consistency between the trailer currently mounted on the vehicle and the trailer specified in the driving control task.

15. The method according to any one of claims 2-14, characterized in that, Before accessing the second computing device according to the driving control task, it also includes: Receive parameter configuration instructions generated by the driving control system based on the driving control task to trigger the operation of accessing the second computing device; After executing the corresponding algorithm based on the target parameters, the process further includes: The target parameters and algorithm execution results are sent to the driving control system so that the driving control system can complete the driving control task.

16. A task processing method, characterized in that, The method, intended to be executed on a second computing device located in the cloud, includes: Receive the target parameter request sent by the first computing device located at the vehicle end; In response to a target parameter request sent by the first computing device, a target parameter associated with the driving control task is sent to the first computing device so that the first computing device executes a corresponding algorithm based on the target parameter, so that the driving control system can complete the driving control task. Sending target parameters associated with the driving control task to the first computing device includes: Receive a target parameter request sent by the first computing device when it determines that the vehicle-side storage contains metadata associated with the driving control task and that the metadata is updated relative to the local metadata stored on the vehicle-side. In response to the target parameter request, the target parameters corresponding to the metadata are sent to the first computing device. The target parameters include parameters of the algorithm model bound to the driving control task.

17. The method according to claim 16, characterized in that, Also includes: In response to a metadata request sent by the first computing device, metadata associated with the driving control task is sent to the first computing device, the metadata corresponding to the target parameter.

18. The method according to claim 16, characterized in that, Also includes: Receive a parameter update request sent by the first computing device, the parameter update request containing updated vehicle parameters; Check the correctness of vehicle parameters and store the corrected vehicle parameters and their corresponding metadata.

19. The method according to claim 18, characterized in that, Check the accuracy of vehicle parameters, including at least one of the following: Check whether the upper and lower limits of the vehicle parameters are within the preset range; Check whether the mathematical operation result of the vehicle parameters belongs to a preset set; Check whether the output after substituting the vehicle parameters into the preset code meets the preset conditions.

20. A vehicle control device, characterized in that, The vehicle control device, suitable for residing in a first computing device located at the end of the vehicle, includes: The parameter acquisition module is configured to acquire the driving control task to be executed and the target parameters associated with the driving control task; The algorithm execution module is configured to execute the corresponding algorithm based on the target parameters so that the driving control system can complete the driving control task; The parameter acquisition module is further configured to access a second computing device located in the cloud according to the driving control task, to obtain metadata associated with the driving control task, and to obtain the corresponding target parameters according to the metadata; The parameter acquisition module is further configured to determine whether the vehicle-side storage contains local metadata associated with the driving control task. If so, when the metadata is updated relative to the local metadata stored on the vehicle-side, the target parameter corresponding to the metadata is obtained from the second computing device. The target parameter includes the parameters of the algorithm model bound to the driving control task.

21. A task processing device, characterized in that, The task processing unit, residing in a second computing device located in the cloud, includes: The receiving module is configured to receive target parameter requests sent by a first computing device located at the vehicle end. The processing module is configured to send target parameters associated with the driving control task to the first computing device in response to a target parameter request sent by the first computing device, so that the first computing device executes a corresponding algorithm based on the target parameters, so that the driving control system can complete the driving control task. The receiving module is further configured to receive a target parameter request sent by the first computing device when it determines that the vehicle-side storage contains metadata associated with the driving control task and that the metadata is updated relative to the local metadata stored on the vehicle-side. The processing module is further configured to send the target parameters corresponding to the metadata to the first computing device in response to the target parameter request. The target parameters include parameters of the algorithm model bound to the driving control task.

22. A first computing device residing at a vehicle end, characterized in that, include: One or more processors; Storage device for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the vehicle control method as described in any one of claims 1-15.

23. A second computing device residing in the cloud, characterized in that, include: One or more processors; Storage device for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the task processing method as described in any one of claims 16-19.

24. A vehicle control system, comprising a first computing device as claimed in claim 22 and a second computing device as claimed in claim 23, wherein the first computing device and the second computing device are connected via a network; The second computing device is used to manage target parameters associated with driving control tasks and the metadata corresponding to the target parameters; The first computing device is used to acquire the target parameters and control the vehicle according to the target parameters.

Images