Vehicle data collection system, method, apparatus, storage medium and electronic device

Abstract

The application discloses a vehicle data collection system, method, device, storage medium and electronic equipment, and the system comprises a cloud and a vehicle, the cloud comprises an operator management module, and the vehicle comprises a vehicle cloud link module and a data collection module; the operator management module is used for managing at least one data collection operator through human-computer interaction and storing basic attribute information of each data collection operator into a configuration file; the vehicle cloud link module is used for requesting the configuration file from the operator management module, downloading an un-stored data collection operator from the operator management module to a preset storage space according to the basic attribute information in the configuration file; and the data collection module is used for reading a data collection operator from the preset storage space and collecting vehicle data by using the read data collection operator.

Description

Technical Field

[0001] This application relates to the field of vehicle data acquisition technology, and more specifically, to a vehicle data acquisition system, method, apparatus, storage medium, and electronic device. Background Technology

[0002] Intelligent driving systems all contain a data acquisition device to facilitate fault analysis and troubleshooting, as well as model training. Due to hardware storage and bandwidth limitations, this device typically doesn't collect all data; instead, it collects data only under certain conditions and scenarios, and then feeds the collected data back to the cloud. However, mainstream data acquisition devices all suffer from the following problems:

[0003] (1) Data collection rules are generally fixed on the vehicle side. When encountering new scenarios, the original rules cannot take effect, resulting in the inability to effectively and accurately collect data in new scenarios.

[0004] (2) For data collection in new scenarios to take effect, it generally has to wait until the next version upgrade (i.e., OTA (Over-the-Air) upgrade). Each OTA upgrade by car companies takes at least 6 months, which is obviously not conducive to the quick resolution of problems.

[0005] Therefore, due to the low update efficiency of data collection scenarios, the iteration efficiency of intelligent driving algorithms that require a large amount of high-quality data from multiple scenarios for iterative training will also decrease. Summary of the Invention

[0006] This application provides a vehicle data acquisition system, method, device, storage medium, and electronic device, which can solve the problem that the method of collecting vehicle data based on data acquisition rules fixed on the vehicle end leads to low efficiency in deploying data acquisition rules for new scenarios on the vehicle end, thereby resulting in low efficiency in the iteration of intelligent driving algorithms.

[0007] The specific technical solution is as follows:

[0008] In a first aspect, embodiments of this application provide a vehicle data acquisition system, the system comprising: a cloud and a vehicle, the cloud comprising an operator management module, and the vehicle comprising a vehicle-cloud link module and a data acquisition module;

[0009] The operator management module is used to manage at least one data acquisition operator through human-computer interaction, and to store the basic attribute information of each data acquisition operator in a configuration file. The management of at least one data acquisition operator through human-computer interaction includes creating a data acquisition operator, updating a data acquisition operator, and deleting a data acquisition operator through human-computer interaction.

[0010] The vehicle-cloud link module is used to request the configuration file from the operator management module and download the unstored data acquisition operator from the operator management module to the preset storage space according to the basic attribute information in the configuration file;

[0011] The data acquisition module is used to read data acquisition operators from the preset storage space and use the read data acquisition operators to acquire vehicle data.

[0012] As can be seen from the above solution, this application embodiment achieves dynamic updating capability of data collection rules through a collaborative architecture between the cloud and the vehicle. The cloud-based operator management module supports flexible configuration of collection operators and generation of configuration files through human-machine interaction. The vehicle-cloud link module in the vehicle enables real-time downloading and storage updates of operators, allowing the vehicle to promptly acquire and apply new data collection rules without relying on OTA upgrades. This solves the problems of poor scenario adaptability and long OTA upgrade cycles caused by rule fixation in traditional solutions, effectively improving the real-time performance and accuracy of data collection in new scenarios, significantly enhancing the flexibility of the data collection system and the vehicle manufacturer's ability to quickly handle unexpected scenarios. Since this application embodiment supports real-time downloading and updating of multiple operators across multiple dimensions and scenarios, it can greatly improve the iteration efficiency of intelligent driving models.

[0013] In one possible implementation, the cloud also includes a data demand management module;

[0014] The data demand management module is used to set the data volume information of the return data packet for each data acquisition operator, and send the data volume information to the vehicle-cloud link module;

[0015] The vehicle-cloud link module is also used to receive the data volume information of the data return data packet of each data acquisition operator, and associate the data volume information with the data acquisition operator and store it in the preset storage space;

[0016] The data acquisition module is used to read the data acquisition operator and the corresponding return data packet data volume information from the preset storage space, and to acquire vehicle data based on the read data acquisition operator and the corresponding return data packet data volume information.

[0017] As can be seen from the above scheme, users can set the data volume information of the corresponding return data packet for each data acquisition operator based on the human-computer interaction interface of the data demand management module. This allows the data acquisition module to perform personalized data acquisition according to the user's different acquisition volume requirements for different data acquisition operators.

[0018] In one possible implementation, the basic attribute information includes the version number, name, and hash value of the data acquisition operator;

[0019] The vehicle-cloud link module is also used to store the basic attribute information corresponding to the downloaded data acquisition operator into the preset storage space when downloading the unstored data acquisition operator from the operator management module to the preset storage space;

[0020] The data acquisition module is used to read the data acquisition operator and its corresponding basic attribute information from the preset storage space. If the data acquisition operator is determined to be an unloaded data acquisition operator based on the name and version number in the basic attribute information, the module verifies whether the read data acquisition operator has been tampered with by using the hash value in the basic attribute information. If it is determined that the data acquisition operator has not been tampered with, the module loads the data acquisition operator into memory and collects vehicle data based on the loaded data acquisition operator.

[0021] As can be seen from the above scheme, the embodiments of this application use version number, name and hash value to determine whether the data acquisition operator corresponding to the basic attribute information in the configuration file has been updated or tampered with. Thus, when it is determined that there is an updated and untampered data acquisition operator in the configuration file, the data acquisition module loads the corresponding data acquisition operator into memory for data acquisition. This can avoid duplicate acquisition while ensuring the security of data acquisition.

[0022] In one possible implementation, the data acquisition module includes an operator loading module and an operator execution engine;

[0023] The operator loading module is used to load the data acquisition operator that has not been loaded before from the preset storage space into memory;

[0024] The operator execution engine is used to extract corresponding topic data from the collected vehicle data according to the topics subscribed to by the data acquisition operator in memory, extract key signals from the topic data according to the topic field information specified in the data acquisition operator, and process the key signals according to the logic and rules defined in the data acquisition operator.

[0025] As can be seen from the above scheme, the embodiments of this application realize the dynamic on-demand loading of data acquisition operators through the operator loading module, avoiding the waste of memory resources caused by loading all operators at once. At the same time, combined with the automated data filtering capability of the operator execution engine based on the subscription mechanism (topic), the target information in the vehicle data stream is accurately matched. Through field-level signal extraction and rule-based processing logic, the real-time transformation from raw data to key business information is realized, effectively improving the targeting and efficiency of data processing. While reducing the computing load on the vehicle side, it supports the flexible collection and analysis needs of multi-dimensional and fine-grained data in complex scenarios, further strengthening the real-time response and adaptive capability of the data acquisition system.

[0026] In one possible implementation, the vehicle-cloud link module is used to send an operator recommendation request to the operator management module, the operator recommendation request including at least one operator recommendation factor obtained from the vehicle;

[0027] The operator management module is used to receive the operator recommendation request sent by the vehicle-cloud link module, and recommend at least one data collection operator name according to the at least one operator recommendation factor and operator recommendation model in the operator recommendation request, and forward the at least one data collection operator name to the data collection module through the vehicle-cloud link module, so that the data collection module can use the data collection operator corresponding to the at least one data collection operator name to collect vehicle data.

[0028] As can be seen from the above scheme, the embodiments of this application utilize the intelligent collaborative mechanism between the vehicle-cloud link module and the operator management module, combined with the operator recommendation factors fed back in real time from the vehicle end, to automatically generate data collection operator names that are suitable for the current needs based on the recommendation model, thereby realizing intelligent matching and accurate push of collection rules, significantly reducing manual screening and configuration costs, and improving the agility of data collection in new scenarios.

[0029] In one possible implementation, the at least one operator recommendation factor includes at least one of vehicle type, current driving scenario, and historical data collection habits of the vehicle.

[0030] Secondly, embodiments of this application provide a vehicle data collection method, the method being applied in the cloud, the method comprising:

[0031] At least one data acquisition operator is managed through human-computer interaction, and the basic attribute information of each data acquisition operator is stored in a configuration file. The management of at least one data acquisition operator through human-computer interaction includes creating a data acquisition operator, updating a data acquisition operator, and deleting a data acquisition operator through human-computer interaction.

[0032] The system receives a configuration file request from a vehicle and sends the configuration file to the vehicle so that the vehicle can download unstored data acquisition operators from the cloud to a preset storage space based on the basic attribute information in the configuration file, read the data acquisition operators from the preset storage space, and use the read data acquisition operators to collect vehicle data.

[0033] In one possible implementation, the method further includes:

[0034] The data volume information of the return data packet for each data acquisition operator is set, and the data volume information is sent to the vehicle so that the vehicle can acquire vehicle data according to the data volume information of the read data acquisition operator and its corresponding return data packet.

[0035] In one possible implementation, the basic attribute information includes the version number, name, and hash value of the data acquisition operator;

[0036] The version number and the name are used to determine whether the data acquisition operator is the first time it has appeared, and / or whether the data acquisition operator has been updated;

[0037] The hash value is used to verify whether the data acquisition operator has been tampered with.

[0038] In one possible implementation, the method further includes:

[0039] Receive an operator recommendation request sent by the vehicle, the operator recommendation request including at least one operator recommendation factor obtained from the vehicle;

[0040] Based on the at least one operator recommendation factor and operator recommendation model in the operator recommendation request, at least one data acquisition operator name is recommended, and the at least one data acquisition operator name is sent to the vehicle so that the vehicle can use the data acquisition operator corresponding to the at least one data acquisition operator name to collect vehicle data.

[0041] In one possible implementation, the at least one operator recommendation factor includes at least one of vehicle type, current driving scenario, and historical data collection habits of the vehicle.

[0042] As can be seen from the above solution, this application embodiment achieves dynamic updating capability of data collection rules through a collaborative architecture between the cloud and the vehicle. The cloud-based operator management module supports flexible configuration of collection operators and generation of configuration files through human-machine interaction. The vehicle-cloud link module in the vehicle enables real-time downloading and storage updates of operators, allowing the vehicle to promptly acquire and apply new data collection rules without relying on OTA upgrades. This solves the problems of poor scenario adaptability and long OTA upgrade cycles caused by rule fixation in traditional solutions, effectively improving the real-time performance and accuracy of data collection in new scenarios, significantly enhancing the flexibility of the data collection system and the vehicle manufacturer's ability to quickly handle unexpected scenarios. Since this application embodiment supports real-time downloading and updating of multiple operators across multiple dimensions and scenarios, it can greatly improve the iteration efficiency of intelligent driving models.

[0043] Thirdly, embodiments of this application provide a vehicle data collection method, the method being applied to a vehicle, the method comprising:

[0044] Send a configuration file request to the cloud;

[0045] Receive the configuration file sent from the cloud, the configuration file includes basic attribute information of at least one data acquisition operator managed by the cloud through human-computer interaction, and managing at least one data acquisition operator through human-computer interaction includes creating a data acquisition operator, updating a data acquisition operator, and deleting a data acquisition operator through human-computer interaction.

[0046] Based on the basic attribute information in the configuration file, the unstored data acquisition operator is downloaded from the cloud to the preset storage space, the data acquisition operator is read from the preset storage space, and vehicle data is collected using the read data acquisition operator.

[0047] In one possible implementation, the method further includes:

[0048] Receive data volume information of each data acquisition operator return data packet sent by the cloud, and associate the data volume information with the data acquisition operator and store it in a preset storage space;

[0049] Reading data acquisition operators from the preset storage space and using the read data acquisition operators to acquire vehicle data includes:

[0050] The system reads the data volume information of the data acquisition operator and the corresponding return data packet from the preset storage space, and collects vehicle data based on the read data volume information of the data acquisition operator and the corresponding return data packet.

[0051] In one possible implementation, the basic attribute information includes the version number, name, and hash value of the data acquisition operator;

[0052] The method further includes:

[0053] When downloading an unstored data acquisition operator from the cloud to a preset storage space, the basic attribute information corresponding to the downloaded data acquisition operator is stored in the preset storage space;

[0054] Before collecting vehicle data using the data acquisition operator, the method further includes:

[0055] The data acquisition operator and its corresponding basic attribute information are read from the preset storage space. If the corresponding data acquisition operator is determined to be an unloaded data acquisition operator based on the name and version number in the basic attribute information, the read data acquisition operator is verified by the hash value in the basic attribute information to see if it has been tampered with. If it is determined that it has not been tampered with, the data acquisition operator is loaded into memory.

[0056] In one possible implementation, vehicle data is collected using a data acquisition operator, including:

[0057] Based on the topics subscribed to by the data acquisition operator in memory, corresponding topic data is extracted from the collected vehicle data. Based on the topic field information specified in the data acquisition operator, key signals are extracted from the topic data, and the key signals are processed according to the logic and rules defined in the data acquisition operator.

[0058] In one possible implementation, the method further includes:

[0059] Send an operator recommendation request to the cloud, the operator recommendation request including at least one operator recommendation factor obtained from the vehicle;

[0060] Receive the name of at least one data collection operator recommended by the cloud, wherein the name of the at least one data collection operator is determined by the cloud based on the at least one operator recommendation factors and the operator recommendation model;

[0061] Reading data acquisition operators from the preset storage space includes:

[0062] Read the data acquisition operator corresponding to the name of the at least one data acquisition operator recommended by the cloud from the preset storage space.

[0063] In one possible implementation, the at least one operator recommendation factor includes at least one of vehicle type, current driving scenario, and historical data collection habits of the vehicle.

[0064] As can be seen from the above solution, this application embodiment achieves dynamic updating capability of data collection rules through a collaborative architecture between the cloud and the vehicle. The cloud-based operator management module supports flexible configuration of collection operators and generation of configuration files through human-machine interaction. The vehicle-cloud link module in the vehicle enables real-time downloading and storage updates of operators, allowing the vehicle to promptly acquire and apply new data collection rules without relying on OTA upgrades. This solves the problems of poor scenario adaptability and long OTA upgrade cycles caused by rule fixation in traditional solutions, effectively improving the real-time performance and accuracy of data collection in new scenarios, significantly enhancing the flexibility of the data collection system and the vehicle manufacturer's ability to quickly handle unexpected scenarios. Since this application embodiment supports real-time downloading and updating of multiple operators across multiple dimensions and scenarios, it can greatly improve the iteration efficiency of intelligent driving models.

[0065] Fourthly, embodiments of this application provide a vehicle data acquisition device, which is applied in the cloud and includes:

[0066] A management unit is used to manage at least one data acquisition operator through human-computer interaction. The management of at least one data acquisition operator through human-computer interaction includes at least one of creating a data acquisition operator, updating a data acquisition operator, and deleting a data acquisition operator through human-computer interaction.

[0067] A storage unit is used to store the basic attribute information of each data acquisition operator into a configuration file;

[0068] The receiving unit is used to receive configuration file requests sent by the vehicle.

[0069] The sending unit is used to send the configuration file to the vehicle, so that the vehicle can download the unstored data acquisition operator from the cloud to the preset storage space according to the basic attribute information in the configuration file, read the data acquisition operator from the preset storage space, and use the read data acquisition operator to collect vehicle data.

[0070] In one possible implementation, the device further includes:

[0071] The setting unit is used to set the data volume information of the return data packet for each of the data acquisition operators;

[0072] The sending unit is further configured to send the data volume information to the vehicle, so that the vehicle can collect vehicle data based on the data volume information of the read data acquisition operator and its corresponding return data packet.

[0073] In one possible implementation, the basic attribute information includes the version number, name, and hash value of the data acquisition operator;

[0074] The version number and the name are used to determine whether the data acquisition operator is the first time it has appeared, and / or whether the data acquisition operator has been updated;

[0075] The hash value is used to verify whether the data acquisition operator has been tampered with.

[0076] In one possible implementation, the receiving unit is further configured to receive an operator recommendation request sent by the vehicle, the operator recommendation request including at least one operator recommendation factor obtained from the vehicle;

[0077] The device further includes:

[0078] The model recommendation unit is used to recommend at least one data collection operator name based on the at least one operator recommendation factor and the operator recommendation model in the operator recommendation request.

[0079] The sending unit is further configured to send the name of the at least one data acquisition operator to the vehicle, so that the vehicle can collect vehicle data using the data acquisition operator corresponding to the name of the at least one data acquisition operator.

[0080] In one possible implementation, the at least one operator recommendation factor includes at least one of vehicle type, current driving scenario, and historical data collection habits of the vehicle.

[0081] As can be seen from the above solution, this application embodiment achieves dynamic updating capability of data collection rules through a collaborative architecture between the cloud and the vehicle. The cloud-based operator management module supports flexible configuration of collection operators and generation of configuration files through human-machine interaction. The vehicle-cloud link module in the vehicle enables real-time downloading and storage updates of operators, allowing the vehicle to promptly acquire and apply new data collection rules without relying on OTA upgrades. This solves the problems of poor scenario adaptability and long OTA upgrade cycles caused by rule fixation in traditional solutions, effectively improving the real-time performance and accuracy of data collection in new scenarios, significantly enhancing the flexibility of the data collection system and the vehicle manufacturer's ability to quickly handle unexpected scenarios. Since this application embodiment supports real-time downloading and updating of multiple operators across multiple dimensions and scenarios, it can greatly improve the iteration efficiency of intelligent driving models.

[0082] Fifthly, embodiments of this application provide a vehicle data acquisition device, which is applied to a vehicle and includes:

[0083] The sending unit is used to send configuration file requests to the cloud;

[0084] The receiving unit is used to receive the configuration file sent by the cloud. The configuration file includes basic attribute information of at least one data acquisition operator managed by the cloud through human-computer interaction. Managing at least one data acquisition operator through human-computer interaction includes at least one of creating a data acquisition operator, updating a data acquisition operator, and deleting a data acquisition operator through human-computer interaction.

[0085] The download unit is used to download the unstored data acquisition operator from the cloud to a preset storage space based on the basic attribute information in the configuration file;

[0086] The reading unit is used to read the data acquisition operator from the preset storage space;

[0087] The acquisition unit is used to collect vehicle data using the read data acquisition operator.

[0088] In one possible implementation, the receiving unit is further configured to receive data volume information of each data acquisition operator return data packet sent by the cloud;

[0089] The device further includes:

[0090] The first storage unit is used to associate the data volume information with the data acquisition operator and store it in a preset storage space;

[0091] The reading unit is used to read the data volume information of the data acquisition operator and the corresponding return data packet from the preset storage space;

[0092] The acquisition unit is used to acquire vehicle data based on the data acquisition operator and the data volume information of the corresponding return data packet.

[0093] In one possible implementation, the basic attribute information includes the version number, name, and hash value of the data acquisition operator;

[0094] The device further includes:

[0095] The second storage unit is also used to store the basic attribute information corresponding to the downloaded data acquisition operator into the preset storage space when downloading the unstored data acquisition operator from the cloud to the preset storage space;

[0096] The reading unit is used to read the data acquisition operator and its corresponding basic attribute information from the preset storage space before collecting vehicle data using the data acquisition operator.

[0097] The device further includes:

[0098] The verification unit is used to verify whether the data acquisition operator read has been tampered with by using the hash value in the basic attribute information when the corresponding data acquisition operator is determined to be an unloaded data acquisition operator based on the name and version number in the basic attribute information.

[0099] The loading unit is used to load the data acquisition operator into memory if it is determined that the data has not been tampered with.

[0100] In one possible implementation, the acquisition unit is configured to extract corresponding topic data from the acquired vehicle data according to the topics subscribed to by the data acquisition operator in memory, extract key signals from the topic data according to the topic field information specified in the data acquisition operator, and process the key signals according to the logic and rules defined in the data acquisition operator.

[0101] In one possible implementation, the sending unit is further configured to send an operator recommendation request to the cloud, the operator recommendation request including at least one operator recommendation factor obtained from the vehicle;

[0102] The receiving unit is further configured to receive the name of at least one data collection operator recommended by the cloud, wherein the name of the at least one data collection operator is determined by the cloud based on the at least one operator recommendation factors and the operator recommendation model;

[0103] The reading unit is also used to read the data acquisition operator corresponding to the name of the at least one data acquisition operator recommended by the cloud from the preset storage space.

[0104] In one possible implementation, the at least one operator recommendation factor includes at least one of vehicle type, current driving scenario, and historical data collection habits of the vehicle.

[0105] As can be seen from the above solution, this application embodiment achieves dynamic updating capability of data collection rules through a collaborative architecture between the cloud and the vehicle. The cloud-based operator management module supports flexible configuration of collection operators and generation of configuration files through human-machine interaction. The vehicle-cloud link module in the vehicle enables real-time downloading and storage updates of operators, allowing the vehicle to promptly acquire and apply new data collection rules without relying on OTA upgrades. This solves the problems of poor scenario adaptability and long OTA upgrade cycles caused by rule fixation in traditional solutions, effectively improving the real-time performance and accuracy of data collection in new scenarios, significantly enhancing the flexibility of the data collection system and the vehicle manufacturer's ability to quickly handle unexpected scenarios. Since this application embodiment supports real-time downloading and updating of multiple operators across multiple dimensions and scenarios, it can greatly improve the iteration efficiency of intelligent driving models.

[0106] In a sixth aspect, embodiments of this application provide a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method as described in any possible implementation of the second aspect, or implements the method as described in any possible implementation of the third aspect.

[0107] Seventhly, embodiments of this application provide an electronic device, the electronic device comprising:

[0108] One or more processors;

[0109] The processor is coupled to a storage device for storing one or more programs;

[0110] When the one or more programs are executed by the one or more processors, the electronic device performs the method as described in any possible implementation of the second aspect, or performs the method as described in any possible implementation of the third aspect.

[0111] Eighthly, embodiments of this application provide a computer program product containing instructions that, when executed on a computer or processor, cause the computer or processor to perform the method described in any possible implementation of the second aspect, or to perform the method described in any possible implementation of the third aspect. Attached Figure Description

[0112] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are merely some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without any creative effort.

[0113] Figure 1 This is a schematic diagram of the structure of a vehicle data acquisition system provided in an embodiment of this application;

[0114] Figure 2 This is a schematic diagram of another vehicle data acquisition system provided in an embodiment of this application;

[0115] Figure 3 A flowchart illustrating a vehicle data acquisition method provided in an embodiment of this application;

[0116] Figure 4 A flowchart illustrating another vehicle data acquisition method provided in this application embodiment;

[0117] Figure 5 A block diagram illustrating the composition of a vehicle data acquisition device provided in this application embodiment;

[0118] Figure 6 This is a block diagram of another vehicle data acquisition device provided in an embodiment of this application. Detailed Implementation

[0119] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0120] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. The terms "comprising" and "having," and any variations thereof, in the embodiments and drawings of this application are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or devices.

[0121] This application provides a vehicle data acquisition system, such as... Figure 1 As shown, the system includes: cloud 110 and vehicle 120. Cloud 110 includes operator management module 111, and vehicle 120 includes vehicle-cloud link module 121 and data acquisition module 122.

[0122] The operator management module 111 is used to manage at least one data acquisition operator through human-computer interaction, and to store the basic attribute information of each data acquisition operator in a configuration file. Managing at least one data acquisition operator through human-computer interaction includes creating a data acquisition operator, updating a data acquisition operator, and deleting a data acquisition operator through human-computer interaction.

[0123] The vehicle-cloud link module 121 is used to request a configuration file from the operator management module 111 and download the unstored data acquisition operator from the operator management module 111 to the preset storage space based on the basic attribute information in the configuration file.

[0124] The data acquisition module 122 is used to read data acquisition operators from a preset storage space and use the read data acquisition operators to acquire vehicle 120 data.

[0125] In this embodiment of the application, users (usually technical personnel) can create new data acquisition operators, update existing data acquisition operators, delete existing data acquisition operators, etc. through the human-computer interaction interface corresponding to the operator management module 111. The data acquisition operators can be scripts that include data acquisition logic and rules, written based on scripting languages ​​such as Python and LUA.

[0126] When a new data acquisition operator is created, the operator management module 111 adds the basic attribute information of the data acquisition operator to the configuration file. When an existing data acquisition operator is updated, the operator management module 111 replaces the basic attribute information of the previous data acquisition operator in the configuration file with the updated basic attribute information. When an existing data acquisition operator is deleted, the operator management module 111 deletes the corresponding basic attribute information of the data acquisition operator from the configuration file. The basic attribute information includes at least one of the following: the data acquisition operator's version number, name, hash value, creation time, update time, and operator size.

[0127] The vehicle-to-cloud link module 121 in the vehicle is mainly used for communication with the cloud. The vehicle-to-cloud link module 121 can periodically or irregularly request configuration files from the operator management module 111. When the vehicle-to-cloud link module 121 requests a configuration file for the first time, it downloads all data acquisition operators involved in the configuration file from the operator management module 111 to a preset storage space. When the vehicle-to-cloud link module 121 is not requesting a configuration file for the first time, it can first determine whether the configuration file has been updated. If it has been updated, it only downloads the updated data acquisition operators from the operator management module 111 to the preset storage space. After updating the configuration file, the operator management module 111 can modify information such as the configuration file's version number and update time, allowing the vehicle-to-cloud link module 121 to quickly determine whether the configuration file has been updated. The preset storage space includes a disk, etc.

[0128] The data acquisition module 122 will periodically or irregularly read data acquisition operators from the preset storage space and use the read data acquisition operators to collect vehicle 120 data.

[0129] The vehicle data acquisition system provided in this application embodiment enables dynamic updating of data acquisition rules through a collaborative architecture between the cloud and the vehicle. The cloud-based operator management module supports flexible configuration of acquisition operators and generation of configuration files via human-machine interaction. The vehicle-cloud link module in the vehicle enables real-time downloading and storage updates of operators, allowing the vehicle to promptly acquire and apply new data acquisition rules without relying on OTA upgrades. This solves the problems of poor scenario adaptability and long OTA upgrade cycles caused by fixed rules in traditional solutions, effectively improving the real-time performance and accuracy of data acquisition in new scenarios, and significantly enhancing the flexibility of the data acquisition system and the vehicle manufacturer's ability to quickly handle unexpected scenarios. Because this application embodiment supports real-time downloading and updating of multiple operators across multiple dimensions and scenarios, it can greatly improve the iteration efficiency of intelligent driving models.

[0130] In one possible implementation, such as Figure 2 As shown, the cloud 110 also includes a data demand management module 112;

[0131] The data demand management module 112 is used to set the data volume information of the return data packet of each data acquisition operator and send the data volume information to the vehicle-cloud link module 121;

[0132] The vehicle-cloud link module 121 is also used to receive the data volume information of the data packets returned by each data acquisition operator, and to associate the data volume information with the data acquisition operator and store it in a preset storage space;

[0133] The data acquisition module 122 is used to read the data volume information of the data acquisition operator and the corresponding return data packet from the preset storage space, and to collect vehicle 120 data according to the read data acquisition operator and the corresponding return data packet data volume information.

[0134] In this embodiment, the data volume information of the return data packet for each data acquisition operator includes the number of return data packets and / or the traffic of each data acquisition operator. The data volume information of the return data packets for different data acquisition operators may be the same or different.

[0135] Users can set the data volume information of the corresponding return data packet for each data acquisition operator based on the human-computer interaction interface corresponding to the data demand management module 112, so that the data acquisition module 122 can perform personalized acquisition according to the user's different acquisition volume requirements for different data acquisition operators.

[0136] In one possible implementation, the basic attribute information includes the version number, name, and hash value of the data acquisition operator;

[0137] The vehicle-cloud link module 121 is also used to store the basic attribute information corresponding to the downloaded data acquisition operator into the preset storage space when downloading the unstored data acquisition operator from the operator management module 111 to the preset storage space.

[0138] The data acquisition module 122 is used to read data acquisition operators and their corresponding basic attribute information from a preset storage space. If the corresponding data acquisition operator is determined to be an unloaded data acquisition operator based on the name and version number in the basic attribute information, the module verifies whether the read data acquisition operator has been tampered with by using the hash value in the basic attribute information. If it is determined that the data acquisition operator has not been tampered with, the module loads the data acquisition operator into memory and collects vehicle 120 data based on the loaded data acquisition operator.

[0139] In this embodiment of the application, the vehicle-cloud link module 121 can associate and store the downloaded operator management module 111 with its corresponding basic attribute information in a preset storage space.

[0140] After the data acquisition module 122 reads the data acquisition operator and its corresponding basic attribute information from the preset storage space, it can compare the name and version number in the basic attribute information with the name and version number of the data acquisition operator already loaded in memory to determine whether the version number corresponding to the same name has changed. If it has changed, it means that the data acquisition operator has been updated, and the original data acquisition operator in memory needs to be deleted, and the updated data acquisition operator needs to be loaded into memory. If it has not changed, there is no need to reload. If it is determined that the data acquisition operator is an unloaded data acquisition operator, the data acquisition module 122 can also calculate the hash value of the read data acquisition operator and compare the temporarily calculated hash value with the hash value corresponding to the data acquisition operator read from the preset storage space. If the two are the same, it means that the data acquisition operator has not been tampered with, and the data acquisition operator can be loaded into memory for data acquisition. If the two are different, it means that the data acquisition operator has been tampered with, posing an attack risk, and there is no need to load it; the data acquisition operator in the preset storage space is deleted.

[0141] Furthermore, assuming the data acquisition operator has not been tampered with, the hash value of the data acquisition operator read from the preset storage space can be compared with the hash value of the data acquisition operator stored in memory. If they are different, it can be further confirmed that the hash value of the data acquisition operator has been updated. The hash value can be an MD5 (Message-Digest Algorithm 5) value, a SHA-1 (Secure Hash Algorithm 1) value, or a SHA-256 (Secure Hash Algorithm 256) value, etc.

[0142] This application embodiment uses version number, name, and hash value to determine whether the data acquisition operator corresponding to the basic attribute information in the configuration file has been updated or tampered with. Therefore, when it is determined that there is an updated and untampered data acquisition operator in the configuration file, the data acquisition module loads the corresponding data acquisition operator into memory for data acquisition. This can avoid duplicate acquisition while ensuring the security of data acquisition.

[0143] In one possible implementation, such as Figure 2 As shown, the data acquisition module 122 includes an operator loading module 1221 and an operator execution engine 1222;

[0144] Operator loading module 1221 is used to load unloaded data acquisition operators from preset storage space into memory;

[0145] The operator execution engine 1222 is used to extract corresponding topic data from the collected vehicle 120 data according to the topic subscribed by the data acquisition operator in memory, extract key signals from the topic data according to the topic field information specified in the data acquisition operator, and process the key signals according to the logic and rules defined in the data acquisition operator.

[0146] In this embodiment, the topics subscribed to by different data acquisition operators may be the same or different. Topics include: topics related to the powertrain system, topics related to driving status, topics related to the safety system, and topics related to the electrical system. Topics related to the powertrain system include engine speed, engine temperature, and fuel level. Topics related to driving status include speed, acceleration, mileage, and distance to obstacles. Topics related to the safety system include braking system status, tire pressure, and airbag status. Topics related to the electrical system include battery voltage and the status of electrical equipment (such as the operating status of headlights, radio, and air conditioning).

[0147] The data in a topic may contain a large number of fields, but the data collection operator may only need a few of them. Therefore, it is also necessary to extract key signals from the topic data based on the topic field information specified in the data collection operator.

[0148] For example, if the subscribed topic field includes / sensors / vehicle / speed, the returned raw data will include:

[0149] {

[0150] "timestamp":1620000000,

[0151] "value":80,

[0152] "unit":"km / h",

[0153] "sensor_id":"speed_sensor_001",

[0154] "status":"normal" / / Sensor status (e.g., whether it is faulty)

[0155] }

[0156] Among them, the key signals are only the value (vehicle speed) and the unit (unit).

[0157] Redundant fields: timestamp may be managed uniformly by the system, and sensor_id and status are irrelevant in this scenario.

[0158] The following example illustrates the data collection process:

[0159] Suppose we are collecting operational data from vehicle 120, and a data collection operator in memory is subscribed to the topic "vehicle speed". When the operator executes engine 1222, it will find all data related to "vehicle speed" from a large amount of vehicle 120 data. For example, the collected vehicle data may include information on speed, temperature, battery level, etc., but only the "vehicle speed" topic data will be extracted.

[0160] Next, within the "vehicle speed" topic data, the data acquisition operator specifies that it should focus on the "instantaneous speed" field. The operator execution engine 1222 then extracts the "instantaneous speed" as a key signal from the "vehicle speed" data. The logic and rules defined by the data acquisition operator are to calculate the average speed per minute. The operator execution engine 1222 processes the extracted "instantaneous speed" key signal according to this rule, statistically calculating the instantaneous speeds within each minute to ultimately obtain the average speed per minute.

[0161] This application embodiment achieves dynamic on-demand loading of data acquisition operators through an operator loading module, avoiding the waste of memory resources caused by loading all operators at once. At the same time, combined with the operator execution engine's automated data filtering capability based on the subscription mechanism (topic), it accurately matches target information in the vehicle data stream. Through field-level signal extraction and rule-based processing logic, it realizes real-time transformation from raw data to key business information, effectively improving the targeting and efficiency of data processing. While reducing the computing load on the vehicle side, it supports the flexible collection and analysis needs of multi-dimensional and fine-grained data in complex scenarios, further enhancing the real-time response and adaptive capabilities of the data acquisition system.

[0162] In one possible implementation, the vehicle-cloud link module 121 is used to send an operator recommendation request to the operator management module 111, the operator recommendation request including at least one operator recommendation factor obtained from the vehicle 120;

[0163] The operator management module 111 is used to receive the operator recommendation request sent by the vehicle-cloud link module 121, and recommend at least one data collection operator name according to at least one operator recommendation factor and operator recommendation model in the operator recommendation request, and forward at least one data collection operator name to the data collection module 122 through the vehicle-cloud link module 121, so that the data collection module 122 can use the data collection operator corresponding to at least one data collection operator name to collect vehicle 120 data.

[0164] Among them, at least one of the following operators is recommended: vehicle type, current driving scenario, and historical data collection habits of the vehicle.

[0165] Regarding vehicle type: Different types of vehicles differ significantly in structure, purpose, and operating characteristics, which determines their different data collection needs. For example, sedans are mainly used for daily urban commuting, and data such as fuel consumption, speed, and engine speed are typically of greater concern to help owners understand the vehicle's economic performance and driving habits. Trucks, on the other hand, undertake freight transport tasks, with long mileage and heavy loads. In addition to the basic data mentioned above, it is also necessary to focus on collecting data such as tire pressure, cargo weight distribution, and braking system status to ensure transportation safety and cargo integrity. Buses, as public transportation vehicles, must consider passenger comfort and operational efficiency; therefore, collecting data such as in-vehicle temperature, humidity, and passenger flow is also crucial.

[0166] For vehicle driving scenarios: Driving scenarios are highly varied, and each scenario has its unique data requirements. In daily commuting, traffic congestion is a common problem, and vehicles may need to frequently start and stop. Collecting data such as speed changes and braking frequency helps analyze the impact of driving behavior on fuel consumption. In long-distance transportation scenarios, drivers need to drive for extended periods, and fatigue is a potential risk. Therefore, collecting physiological data such as driving time, rest time, and heart rate can help determine the driver's fatigue level. Track testing scenarios focus on the vehicle's extreme performance, such as collecting data on maximum acceleration, top speed, and lateral acceleration during cornering, to optimize and tune the vehicle's performance.

[0167] Regarding historical vehicle data collection habits: Users develop certain habits while using vehicle data collection systems. By analyzing the types of data users frequently collect, the frequency of collection, and the specific operators they use, we can understand their personalized needs. For example, some users frequently focus on the vehicle's battery level and driving range; therefore, the system can prioritize recommending data collection operators related to battery performance based on this historical usage habit.

[0168] The operator management module 111 utilizes big data analytics and machine learning algorithms to achieve intelligent recommendations. First, the system collects a large amount of data on vehicle types, driving scenarios, and historical data collection habits to construct a massive dataset. Then, machine learning algorithms (such as decision trees and neural networks) are used to train the dataset, learning the relationships between different factors and data collection operators. During actual recommendations, the operator management module 111, based on the current vehicle type, current driving scenario, and historical data collection habits, retrieves a list of recommended operator names from the trained model. This list is then forwarded to the data collection module 122 via the vehicle-cloud link module 121, enabling the data collection module 122 to collect vehicle 120 data using at least one data collection operator corresponding to its name.

[0169] This application embodiment utilizes an intelligent collaborative mechanism between the vehicle-cloud link module and the operator management module. Combined with real-time operator recommendation factors from the vehicle, it automatically generates data collection operator names tailored to current needs based on a recommendation model. This enables intelligent matching and precise push of collection rules, significantly reducing manual screening and configuration costs and improving the agility of data collection in new scenarios. Simultaneously, through a closed-loop feedback mechanism of dynamic recommendation and on-demand loading, the vehicle can adapt to complex and ever-changing scenario requirements, quickly activating and applying the optimal collection strategy. This ensures both the timeliness and relevance of data collection while avoiding the ineffective loading of redundant operators, further optimizing vehicle-side resource utilization and improving the efficiency of vehicle manufacturer problem diagnosis.

[0170] Based on the above system embodiments, another embodiment of this application also provides a vehicle data collection method, which is applied in the cloud, such as... Figure 3 As shown, the method includes:

[0171] S210: Manage at least one data acquisition operator through human-computer interaction, and store the basic attribute information of each data acquisition operator in a configuration file.

[0172] The data acquisition operator can be a script written in scripting languages ​​such as Python and LUA, containing data acquisition logic and rules. Managing at least one data acquisition operator through human-computer interaction includes creating, updating, or deleting at least one data acquisition operator through human-computer interaction. That is, users can perform operations such as creating, updating, and deleting data acquisition operators on a cloud-based human-computer interaction interface.

[0173] Basic attribute information includes at least one of the following: version number, name, hash value, creation time, update time, operator size, etc. of the data acquisition operator.

[0174] Version number and name are used to determine whether the data acquisition operator is a newly appearing operator, and / or whether the data acquisition operator has been updated. Hash value is used to verify whether the data acquisition operator has been tampered with.

[0175] The operator size can be used by the vehicle to determine whether the storage space is sufficient for the current situation.

[0176] Creation time and update time can also be used by vehicles to determine whether data collection segments have been updated. For example, a vehicle can compare locally stored configuration files with the latest downloaded configuration files line by line and determine whether data collection segments have been updated based on the timestamp of each file.

[0177] S220: Receives a configuration file request sent by the vehicle and sends the configuration file to the vehicle so that the vehicle can download the unstored data acquisition operator from the cloud to the preset storage space based on the basic attribute information in the configuration file, read the data acquisition operator from the preset storage space, and use the read data acquisition operator to collect vehicle data.

[0178] The vehicle periodically or irregularly sends configuration file requests to the cloud. Upon receiving the request, the cloud can distribute the configuration file to the vehicle. The vehicle then uses the basic attribute information in the configuration file to download unstored data acquisition operators from the cloud to a preset storage space, reads the data acquisition operators from the preset storage space, and uses these operators to collect vehicle data. The preset storage space can be a disk or similar object.

[0179] The vehicle data acquisition method provided in this application embodiment enables dynamic updating of data acquisition rules through a collaborative architecture between the cloud and the vehicle. It utilizes a cloud-based operator management module to support flexible configuration of acquisition operators and generate configuration files via human-machine interaction. The vehicle-cloud link module in the vehicle enables real-time downloading and storage updates of operators, allowing the vehicle to promptly acquire and apply new data acquisition rules without relying on OTA upgrades. This solves the problems of poor scenario adaptability and long OTA upgrade cycles caused by fixed rules in traditional solutions, effectively improving the real-time performance and accuracy of data acquisition in new scenarios, significantly enhancing the flexibility of the data acquisition system and the vehicle manufacturer's ability to quickly handle unexpected scenarios. Because this application embodiment supports real-time downloading and updating of multiple operators across multiple dimensions and scenarios, it can greatly improve the iteration efficiency of intelligent driving models.

[0180] In one possible implementation, in practical applications, users often only need to collect vehicle data for a period of time to iteratively train intelligent driving models, and the amount of data in the return data packets required by different data acquisition operators may vary. To address this technical issue, users can also set the data volume information of the return data packets for each data acquisition operator via the cloud and send this information to the vehicle. The vehicle can then collect vehicle data based on the data volume information of the data acquisition operator and its corresponding return data packets. The data volume information includes the number of return data packets and / or the data throughput.

[0181] In one possible implementation, different types of vehicles may need to collect different data in different scenarios. In order to meet the personalized needs of data collection and improve the accuracy of subsequent intelligent driving models, this application embodiment also provides the following method: receiving an operator recommendation request sent by a vehicle in the cloud, the operator recommendation request including at least one operator recommendation factor obtained from the vehicle; recommending at least one data collection operator name based on at least one operator recommendation factor and operator recommendation model in the operator recommendation request, and sending at least one data collection operator name to the vehicle so that the vehicle can collect vehicle data using the data collection operator corresponding to at least one data collection operator name.

[0182] The recommendation factors for at least one operator include at least one of the following: vehicle type, current driving scenario, and historical data collection habits. Vehicle type includes cars, trucks, buses, etc. Current driving scenario includes various scenarios such as traffic congestion, highway driving, urban road driving, track testing, and long-distance transportation. Historical data collection habits include the historical data collection habits of all drivers of the vehicle, including data type, collection frequency, and data collection operators used.

[0183] This application embodiment first collects a large amount of data on vehicle types, driving scenarios, and historical data collection habits to construct a massive training set. This training set includes ground truth values ​​for recommended data collection algorithms set based on experience. Then, machine learning algorithms are used to train this training set, learning the correlation between different factors and data collection operators. After training, the trained operator recommendation model can be deployed to the cloud. When a vehicle sends an operator recommendation request, at least one operator recommendation factor from the request is input into the model, which outputs at least one recommended data collection operator name and sends this name to the vehicle. The vehicle then uses the data collection operator corresponding to the at least one data collection operator name to collect vehicle data.

[0184] This application embodiment utilizes an intelligent collaborative mechanism between the vehicle-cloud link module and the operator management module, combined with real-time operator recommendation factors from the vehicle end, to automatically generate data collection operator names that fit the current needs based on a recommendation model. This enables intelligent matching and precise push of collection rules, significantly reducing manual screening and configuration costs and improving the agility of data collection in new scenarios.

[0185] Based on the above system embodiments, another embodiment of this application also provides a vehicle data acquisition method, which is applied to a vehicle, such as... Figure 4 As shown, the method includes:

[0186] S310: Sends a configuration file request to the cloud.

[0187] Because the data collection operators managed in the cloud will be updated, created, or deleted, the corresponding configuration files will also be updated. Therefore, vehicles can send configuration file requests to the cloud periodically or irregularly.

[0188] S320: Receives configuration files sent from the cloud.

[0189] The configuration file includes basic attribute information of at least one data acquisition operator managed via human-computer interaction in the cloud. Managing at least one data acquisition operator via human-computer interaction includes creating, updating, or deleting at least one data acquisition operator through human-computer interaction.

[0190] This attribute information includes at least one of the following: version number, name, hash value, creation time, update time, operator size, etc. of the data acquisition operator.

[0191] S330: Based on the basic attribute information in the configuration file, download the unstored data acquisition operator from the cloud to the preset storage space, read the data acquisition operator from the preset storage space, and use the read data acquisition operator to collect vehicle data.

[0192] After receiving the configuration file, the vehicle can first download the unstored data acquisition operator from the cloud to the preset storage space based on the basic attribute information in the configuration file, then read the data acquisition operator from the preset storage space, extract the corresponding topic data from the collected vehicle data according to the topic subscribed by the data acquisition operator in memory, extract key signals from the topic data according to the topic field information specified in the data acquisition operator, and process the key signals according to the logic and rules defined in the data acquisition operator.

[0193] In this embodiment, the topics subscribed to by different data acquisition operators may be the same or different. Topics include: topics related to the powertrain system, topics related to driving status, topics related to the safety system, and topics related to the electrical system. Topics related to the powertrain system include engine speed, engine temperature, and fuel level. Topics related to driving status include speed, acceleration, mileage, and distance to obstacles. Topics related to the safety system include braking system status, tire pressure, and airbag status. Topics related to the electrical system include battery voltage and the status of electrical equipment (such as the operating status of headlights, radio, and air conditioning).

[0194] Furthermore, when downloading unstored data acquisition operators from the cloud to a preset storage space, the vehicle can also store the basic attribute information corresponding to the downloaded data acquisition operators in the preset storage space. Thus, before collecting vehicle data using the read data acquisition operators, the vehicle can read the data acquisition operators and their corresponding basic attribute information from the preset storage space. If the corresponding data acquisition operator is determined to be an unloaded data acquisition operator based on the name and version number in the basic attribute information, the vehicle can verify whether the read data acquisition operator has been tampered with by using the hash value in the basic attribute information. If it is determined that the data acquisition operator has not been tampered with, the vehicle can load the data acquisition operator into memory.

[0195] The vehicle data acquisition method provided in this application embodiment enables dynamic updating of data acquisition rules through a collaborative architecture between the cloud and the vehicle. It utilizes a cloud-based operator management module to support flexible configuration of acquisition operators and generate configuration files via human-machine interaction. The vehicle-cloud link module in the vehicle enables real-time downloading and storage updates of operators, allowing the vehicle to promptly acquire and apply new data acquisition rules without relying on OTA upgrades. This solves the problems of poor scenario adaptability and long OTA upgrade cycles caused by fixed rules in traditional solutions, effectively improving the real-time performance and accuracy of data acquisition in new scenarios, significantly enhancing the flexibility of the data acquisition system and the vehicle manufacturer's ability to quickly handle unexpected scenarios. Because this application embodiment supports real-time downloading and updating of multiple operators across multiple dimensions and scenarios, it can greatly improve the iteration efficiency of intelligent driving models.

[0196] In one possible implementation, in practical applications, users often only need to collect vehicle data for a period of time to iteratively train intelligent driving models, and the amount of data in the return data packets required by different data acquisition operators may vary. To address this technical issue, the vehicle can also receive data volume information of each data acquisition operator's return data packet sent from the cloud, and associate this data volume information with the data acquisition operator in a preset storage space. Correspondingly, the step "reading data acquisition operators from the preset storage space and collecting vehicle data using the read data acquisition operators" includes: reading the data volume information of the data acquisition operators and their corresponding return data packets from the preset storage space; collecting vehicle data based on the read data volume information of the data acquisition operators and their corresponding return data packets, thereby ensuring that the vehicle data fed back to the cloud by the vehicle meets the user's required data volume. The data volume information includes the number of return data packets and / or the data flow.

[0197] In one possible implementation, different types of vehicles may require different data collection in different scenarios. To meet the personalized needs of data collection and improve the accuracy of subsequent intelligent driving models, this application embodiment also provides the following method: the vehicle sends an operator recommendation request to the cloud, the operator recommendation request including at least one operator recommendation factor obtained from the vehicle; and receives the name of at least one data collection operator recommended by the cloud, the name of the at least one data collection operator being determined by the cloud based on at least one operator recommendation factor and an operator recommendation model. Thus, when the vehicle needs to read a data collection operator from a preset storage space, it can read the data collection operator corresponding to the name of the at least one data collection operator recommended by the cloud from the preset storage space, so as to collect the corresponding vehicle data based on the data collection operator recommended by the cloud.

[0198] At least one of the following operators is included as a recommendation factor: vehicle type, current driving scenario, and historical data collection habits. The operator recommendation model is trained on a training set using machine learning algorithms to learn the correlation between different factors and data collection operators. The training set includes a large number of vehicle types, driving scenarios, and historical data collection habits.

[0199] This application embodiment utilizes an intelligent collaborative mechanism between the vehicle-cloud link module and the operator management module, combined with real-time operator recommendation factors from the vehicle end, to automatically generate data collection operator names that fit the current needs based on a recommendation model. This enables intelligent matching and precise push of collection rules, significantly reducing manual screening and configuration costs and improving the agility of data collection in new scenarios.

[0200] Based on the above method embodiments, another embodiment of this application provides a vehicle data acquisition device, which is applied in the cloud, such as... Figure 5 As shown, the device includes:

[0201] Management unit 410 is used to manage at least one data acquisition operator through human-computer interaction. The management of at least one data acquisition operator through human-computer interaction includes creating a new data acquisition operator, updating a data acquisition operator, and deleting a data acquisition operator through human-computer interaction.

[0202] Storage unit 420 is used to store the basic attribute information of each data acquisition operator into a configuration file;

[0203] The receiving unit 430 is used to receive configuration file requests sent by the vehicle;

[0204] The sending unit 440 is used to send the configuration file to the vehicle, so that the vehicle can download the unstored data acquisition operator from the cloud to the preset storage space according to the basic attribute information in the configuration file, read the data acquisition operator from the preset storage space, and use the read data acquisition operator to collect vehicle data.

[0205] In one possible implementation, the device further includes:

[0206] The setting unit is used to set the data volume information of the return data packet for each of the data acquisition operators;

[0207] The sending unit 440 is further configured to send the data volume information to the vehicle, so that the vehicle can collect vehicle data based on the data volume information of the read data acquisition operator and its corresponding return data packet.

[0208] In one possible implementation, the basic attribute information includes the version number, name, and hash value of the data acquisition operator;

[0209] The version number and the name are used to determine whether the data acquisition operator is the first time it has appeared, and / or whether the data acquisition operator has been updated;

[0210] The hash value is used to verify whether the data acquisition operator has been tampered with.

[0211] In one possible implementation, the receiving unit 430 is further configured to receive an operator recommendation request sent by the vehicle, the operator recommendation request including at least one operator recommendation factor obtained from the vehicle;

[0212] The device further includes:

[0213] The model recommendation unit is used to recommend at least one data collection operator name based on the at least one operator recommendation factor and the operator recommendation model in the operator recommendation request;

[0214] The sending unit 440 is further configured to send the name of the at least one data acquisition operator to the vehicle, so that the vehicle can collect vehicle data using the data acquisition operator corresponding to the name of the at least one data acquisition operator.

[0215] In one possible implementation, the at least one operator recommendation factor includes at least one of vehicle type, current driving scenario, and historical data collection habits of the vehicle.

[0216] The vehicle data acquisition device provided in this application embodiment enables dynamic updating of data acquisition rules through a collaborative architecture between the cloud and the vehicle. It utilizes a cloud-based operator management module to support flexible configuration of acquisition operators and generate configuration files via human-machine interaction. The vehicle-cloud link module in the vehicle enables real-time downloading and storage updates of operators, allowing the vehicle to promptly acquire and apply new data acquisition rules without relying on OTA upgrades. This solves the problems of poor scenario adaptability and long OTA upgrade cycles caused by fixed rules in traditional solutions, effectively improving the real-time performance and accuracy of data acquisition in new scenarios, significantly enhancing the flexibility of the data acquisition system and the vehicle manufacturer's ability to quickly handle unexpected scenarios. Because this application embodiment supports real-time downloading and updating of multiple operators across multiple dimensions and scenarios, it greatly improves the iteration efficiency of intelligent driving models.

[0217] Based on the above method embodiments, another embodiment of this application provides a vehicle data acquisition device, which is applied to a vehicle, such as... Figure 6 As shown, the device includes:

[0218] Sending unit 510 is used to send configuration file requests to the cloud;

[0219] The receiving unit 520 is used to receive the configuration file sent by the cloud. The configuration file includes basic attribute information of at least one data acquisition operator managed by the cloud through human-computer interaction. Managing at least one data acquisition operator through human-computer interaction includes creating a new data acquisition operator, updating a data acquisition operator, and deleting a data acquisition operator through human-computer interaction.

[0220] Download unit 530 is used to download unstored data acquisition operators from the cloud to a preset storage space based on the basic attribute information in the configuration file;

[0221] Reading unit 540 is used to read data acquisition operators from the preset storage space;

[0222] The acquisition unit 550 is used to acquire vehicle data using the read data acquisition operator.

[0223] In one possible implementation, the receiving unit 520 is further configured to receive data volume information of each data acquisition operator return data packet sent by the cloud;

[0224] The device further includes:

[0225] The first storage unit is used to associate the data volume information with the data acquisition operator and store it in a preset storage space;

[0226] The reading unit is used to read the data volume information of the data acquisition operator and the corresponding return data packet from the preset storage space;

[0227] The acquisition unit is used to acquire vehicle data based on the data acquisition operator and the data volume information of the corresponding return data packet.

[0228] In one possible implementation, the basic attribute information includes the version number, name, and hash value of the data acquisition operator;

[0229] The device further includes:

[0230] The second storage unit is also used to store the basic attribute information corresponding to the downloaded data acquisition operator into the preset storage space when downloading the unstored data acquisition operator from the cloud to the preset storage space;

[0231] The reading unit is used to read the data acquisition operator and its corresponding basic attribute information from the preset storage space before collecting vehicle data using the data acquisition operator.

[0232] The device further includes:

[0233] The verification unit is used to verify whether the data acquisition operator read has been tampered with by using the hash value in the basic attribute information when the corresponding data acquisition operator is determined to be an unloaded data acquisition operator based on the name and version number in the basic attribute information.

[0234] The loading unit is used to load the data acquisition operator into memory if it is determined that the data has not been tampered with.

[0235] In one possible implementation, the acquisition unit is configured to extract corresponding topic data from the acquired vehicle data according to the topics subscribed to by the data acquisition operator in memory, extract key signals from the topic data according to the topic field information specified in the data acquisition operator, and process the key signals according to the logic and rules defined in the data acquisition operator.

[0236] In one possible implementation, the sending unit is further configured to send an operator recommendation request to the cloud, the operator recommendation request including at least one operator recommendation factor obtained from the vehicle;

[0237] The receiving unit is further configured to receive the name of at least one data collection operator recommended by the cloud, wherein the name of the at least one data collection operator is determined by the cloud based on the at least one operator recommendation factors and the operator recommendation model;

[0238] The reading unit is also used to read the data acquisition operator corresponding to the name of the at least one data acquisition operator recommended by the cloud from the preset storage space.

[0239] In one possible implementation, the at least one operator recommendation factor includes at least one of vehicle type, current driving scenario, and historical data collection habits of the vehicle.

[0240] The vehicle data acquisition device provided in this application embodiment enables dynamic updating of data acquisition rules through a collaborative architecture between the cloud and the vehicle. It utilizes a cloud-based operator management module to support flexible configuration of acquisition operators and generate configuration files via human-machine interaction. The vehicle-cloud link module in the vehicle enables real-time downloading and storage updates of operators, allowing the vehicle to promptly acquire and apply new data acquisition rules without relying on OTA upgrades. This solves the problems of poor scenario adaptability and long OTA upgrade cycles caused by fixed rules in traditional solutions, effectively improving the real-time performance and accuracy of data acquisition in new scenarios, significantly enhancing the flexibility of the data acquisition system and the vehicle manufacturer's ability to quickly handle unexpected scenarios. Because this application embodiment supports real-time downloading and updating of multiple operators across multiple dimensions and scenarios, it greatly improves the iteration efficiency of intelligent driving models.

[0241] Based on the above method embodiments, another embodiment of this application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method as described in any of the above embodiments.

[0242] Based on the above method embodiments, another embodiment of this application provides an electronic device or computer device, the electronic device comprising:

[0243] One or more processors;

[0244] The processor is coupled to a storage device for storing one or more programs;

[0245] When the one or more programs are executed by the one or more processors, the electronic device performs the method as described in any of the possible implementations above.

[0246] Based on the above embodiments, another embodiment of this application provides a computer program product, which includes instructions that, when executed on a computer or processor, cause the computer or processor to perform the method described in any of the above embodiments.

[0247] The above method and device embodiments correspond to the system embodiments and have the same technical effects. For detailed descriptions, please refer to the system embodiments. Specific implementation details of the method and device embodiments can be found in the system implementation section and will not be repeated here. Those skilled in the art will understand that the accompanying drawings are merely schematic diagrams of one embodiment, and the modules or processes shown in the drawings are not necessarily essential for implementing this application.

[0248] Those skilled in the art will understand that the modules in the apparatus of the embodiments can be distributed in the apparatus of the embodiments as described in the embodiments, or they can be located in one or more devices different from this embodiment with corresponding changes. The modules of the above embodiments can be combined into one module, or they can be further divided into multiple sub-modules.

[0249] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A vehicle data acquisition system, characterized in that, The system includes: a cloud and a vehicle; the cloud includes an operator management module; the vehicle includes a vehicle-cloud link module and a data acquisition module. The operator management module is used to manage at least one data acquisition operator through human-computer interaction, and to store the basic attribute information of each data acquisition operator in a configuration file. The management of at least one data acquisition operator through human-computer interaction includes creating a data acquisition operator, updating a data acquisition operator, and deleting a data acquisition operator through human-computer interaction. The vehicle-cloud link module is used to request the configuration file from the operator management module and download the unstored data acquisition operator from the operator management module to the preset storage space according to the basic attribute information in the configuration file; The data acquisition module is used to read data acquisition operators from the preset storage space and use the read data acquisition operators to acquire vehicle data.

2. The system according to claim 1, characterized in that, The cloud also includes a data demand management module; The data demand management module is used to set the data volume information of the return data packet for each data acquisition operator, and send the data volume information to the vehicle-cloud link module; The vehicle-cloud link module is also used to receive the data volume information of the data return data packet of each data acquisition operator, and associate the data volume information with the data acquisition operator and store it in the preset storage space; The data acquisition module is used to read the data acquisition operator and the corresponding return data packet data volume information from the preset storage space, and to acquire vehicle data based on the read data acquisition operator and the corresponding return data packet data volume information.

3. The system according to claim 1, characterized in that, The basic attribute information includes the version number, name, and hash value of the data acquisition operator; The vehicle-cloud link module is also used to store the basic attribute information corresponding to the downloaded data acquisition operator into the preset storage space when downloading the unstored data acquisition operator from the operator management module to the preset storage space; The data acquisition module is used to read the data acquisition operator and its corresponding basic attribute information from the preset storage space. If the data acquisition operator is determined to be an unloaded data acquisition operator based on the name and version number in the basic attribute information, the module verifies whether the read data acquisition operator has been tampered with by using the hash value in the basic attribute information. If it is determined that the data acquisition operator has not been tampered with, the module loads the data acquisition operator into memory and collects vehicle data based on the loaded data acquisition operator.

4. The system according to claim 1, characterized in that, The data acquisition module includes an operator loading module and an operator execution engine; The operator loading module is used to load the data acquisition operator that has not been loaded before from the preset storage space into memory; The operator execution engine is used to extract corresponding topic data from the collected vehicle data according to the topics subscribed to by the data acquisition operator in memory, extract key signals from the topic data according to the topic field information specified in the data acquisition operator, and process the key signals according to the logic and rules defined in the data acquisition operator.

5. The system according to any one of claims 1-4, characterized in that, The vehicle-cloud link module is used to send an operator recommendation request to the operator management module, wherein the operator recommendation request includes at least one operator recommendation factor obtained from the vehicle; The operator management module is used to receive the operator recommendation request sent by the vehicle-cloud link module, and recommend at least one data collection operator name according to the at least one operator recommendation factor and operator recommendation model in the operator recommendation request, and forward the at least one data collection operator name to the data collection module through the vehicle-cloud link module, so that the data collection module can use the data collection operator corresponding to the at least one data collection operator name to collect vehicle data.

6. The system according to claim 5, characterized in that, The at least one operator recommendation factor includes at least one of the following: vehicle type, current driving scenario, and historical data collection habits of the vehicle.

7. A method for collecting vehicle data, characterized in that, The method is applied in the cloud and includes: At least one data acquisition operator is managed through human-computer interaction, and the basic attribute information of each data acquisition operator is stored in a configuration file. The management of at least one data acquisition operator through human-computer interaction includes creating a data acquisition operator, updating a data acquisition operator, and deleting a data acquisition operator through human-computer interaction. The system receives a configuration file request from a vehicle and sends the configuration file to the vehicle so that the vehicle can download unstored data acquisition operators from the cloud to a preset storage space based on the basic attribute information in the configuration file, read the data acquisition operators from the preset storage space, and use the read data acquisition operators to collect vehicle data.

8. The method according to claim 7, characterized in that, The method further includes: The data volume information of the return data packet for each data acquisition operator is set, and the data volume information is sent to the vehicle so that the vehicle can acquire vehicle data according to the data volume information of the read data acquisition operator and its corresponding return data packet.

9. The method according to claim 7 or 8, characterized in that, The method further includes: Receive an operator recommendation request sent by the vehicle, the operator recommendation request including at least one operator recommendation factor obtained from the vehicle; Based on the at least one operator recommendation factor and operator recommendation model in the operator recommendation request, at least one data acquisition operator name is recommended, and the at least one data acquisition operator name is sent to the vehicle so that the vehicle can use the data acquisition operator corresponding to the at least one data acquisition operator name to collect vehicle data.

10. A method for collecting vehicle data, characterized in that, The method is applied to a vehicle, and the method includes: Send a configuration file request to the cloud; Receive the configuration file sent from the cloud, the configuration file includes basic attribute information of at least one data acquisition operator managed by the cloud through human-computer interaction, and managing at least one data acquisition operator through human-computer interaction includes creating a data acquisition operator, updating a data acquisition operator, and deleting a data acquisition operator through human-computer interaction. Based on the basic attribute information in the configuration file, the unstored data acquisition operator is downloaded from the cloud to the preset storage space, the data acquisition operator is read from the preset storage space, and vehicle data is collected using the read data acquisition operator.

11. The method according to claim 10, characterized in that, The method further includes: Receive data volume information of each data acquisition operator return data packet sent by the cloud, and associate the data volume information with the data acquisition operator and store it in a preset storage space; Reading data acquisition operators from the preset storage space and using the read data acquisition operators to acquire vehicle data includes: The system reads the data volume information of the data acquisition operator and the corresponding return data packet from the preset storage space, and collects vehicle data based on the read data volume information of the data acquisition operator and the corresponding return data packet.

12. The method according to claim 10, characterized in that, The basic attribute information includes the version number, name, and hash value of the data acquisition operator; The method further includes: When downloading an unstored data acquisition operator from the cloud to a preset storage space, the basic attribute information corresponding to the downloaded data acquisition operator is stored in the preset storage space; Before collecting vehicle data using the data acquisition operator, the method further includes: The data acquisition operator and its corresponding basic attribute information are read from the preset storage space. If the corresponding data acquisition operator is determined to be an unloaded data acquisition operator based on the name and version number in the basic attribute information, the read data acquisition operator is verified by the hash value in the basic attribute information to see if it has been tampered with. If it is determined that it has not been tampered with, the data acquisition operator is loaded into memory.

13. The method according to claim 10, characterized in that, Vehicle data is collected using data acquisition operators, including: Based on the topics subscribed to by the data acquisition operator in memory, corresponding topic data is extracted from the collected vehicle data. Based on the topic field information specified in the data acquisition operator, key signals are extracted from the topic data, and the key signals are processed according to the logic and rules defined in the data acquisition operator.

14. The method according to any one of claims 10-13, characterized in that, The method further includes: Send an operator recommendation request to the cloud, the operator recommendation request including at least one operator recommendation factor obtained from the vehicle; Receive the name of at least one data collection operator recommended by the cloud, wherein the name of the at least one data collection operator is determined by the cloud based on the at least one operator recommendation factors and the operator recommendation model; Reading data acquisition operators from the preset storage space includes: Read the data acquisition operator corresponding to the name of the at least one data acquisition operator recommended by the cloud from the preset storage space.

15. A vehicle data acquisition device, characterized in that, The device is used in the cloud and includes: A management unit is used to manage at least one data acquisition operator through human-computer interaction. The management of at least one data acquisition operator through human-computer interaction includes at least one of creating a data acquisition operator, updating a data acquisition operator, and deleting a data acquisition operator through human-computer interaction. A storage unit is used to store the basic attribute information of each data acquisition operator into a configuration file; The receiving unit is used to receive configuration file requests sent by the vehicle. The sending unit is used to send the configuration file to the vehicle, so that the vehicle can download the unstored data acquisition operator from the cloud to the preset storage space according to the basic attribute information in the configuration file, read the data acquisition operator from the preset storage space, and use the read data acquisition operator to collect vehicle data.

16. A vehicle data acquisition device, characterized in that, The device is applied to a vehicle, and the device includes: The sending unit is used to send configuration file requests to the cloud; The receiving unit is used to receive the configuration file sent by the cloud. The configuration file includes basic attribute information of at least one data acquisition operator managed by the cloud through human-computer interaction. Managing at least one data acquisition operator through human-computer interaction includes at least one of creating a data acquisition operator, updating a data acquisition operator, and deleting a data acquisition operator through human-computer interaction. The download unit is used to download the unstored data acquisition operator from the cloud to a preset storage space based on the basic attribute information in the configuration file; The reading unit is used to read the data acquisition operator from the preset storage space; The acquisition unit is used to collect vehicle data using the read data acquisition operator.

17. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by a processor, it implements the method as described in any one of claims 7-9, or the method as described in any one of claims 10-14.

18. An electronic device, characterized in that, The electronic device includes: One or more processors; The processor is coupled to a storage device for storing one or more programs; When the one or more programs are executed by the one or more processors, the electronic device performs the method as described in any one of claims 7-9, or performs the method as described in any one of claims 10-14.

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