Carrying tool data processing method, device and system

Abstract

The invention discloses a carrying tool data processing method, device and system. The method relates to the field of data processing and automatic driving, and comprises the following steps: in response to at least one trigger instruction received by data acquisition equipment mounted on a carrying tool, obtaining first data acquired by the data acquisition equipment; data cleaning is conducted on the first data and second data based on the at least one trigger instruction, target instruction data corresponding to the at least one trigger instruction is obtained, and the second data is used for representing data collected by the data collection device before the at least one trigger instruction is received; and sending the target instruction data to a cloud server. According to the method and the device, the technical problems that the efficiency of obtaining the carrying tool data required by the user is low and the data missing condition exists in the prior art are solved.

Description

Technical Field

[0001] The present invention relates to the fields of data processing and autonomous driving, and in particular to a method, device and system for processing vehicle data. Background Art

[0002] Obtaining various information and indicators generated by self-driving vehicles and other means of transport, including real-time location, speed, driving route, fuel consumption, load, vehicle health status and other data of the means of transport in various important scenarios, can help companies monitor the operation of the means of transport in real time, improve transportation efficiency and safety, optimize vehicle scheduling, and can also be used to predict maintenance cycles and promptly detect and resolve vehicle failures.

[0003] At present, the relevant technology usually obtains the vehicle data required by users by means of data latching, that is, data latching is performed in response to receiving a related trigger instruction. The data actually required by the user may not be available near the time of the trigger instruction, resulting in that the data obtained through data latching may not contain the data actually required by the user; or the data latching capability of the data processing equipment on the vehicle may not meet the actual concurrent data latching requirements, resulting in data latching failure for some data, resulting in low efficiency in obtaining the vehicle data required by users in the relevant technology and data missing.

[0004] To address the above-mentioned problems, no effective solution has been proposed yet. Summary of the invention

[0005] The embodiments of the present invention provide a method, device and system for processing vehicle data, so as to at least solve the technical problems in the related art of low efficiency in obtaining vehicle data required by users and the existence of data missing.

[0006] According to one aspect of an embodiment of the present invention, a method for processing vehicle data is provided, comprising: in response to a data acquisition device installed on the vehicle receiving at least one trigger instruction, acquiring first data collected by the data acquisition device; performing data cleaning on the first data and the second data based on the at least one trigger instruction to obtain target instruction data corresponding to the at least one trigger instruction, wherein the second data is used to represent the data collected by the data acquisition device before receiving the at least one trigger instruction; and sending the target instruction data to a cloud server.

[0007] According to another aspect of an embodiment of the present invention, a device for processing vehicle data is provided, including: an acquisition module, used to acquire first data collected by the data acquisition device in response to the data acquisition device installed on the vehicle receiving at least one trigger instruction; a cleaning module, used to clean the first data and the second data based on at least one trigger instruction to obtain target instruction data corresponding to at least one trigger instruction, wherein the second data is used to represent the data collected by the data acquisition device before receiving at least one trigger instruction; and a sending module, used to send the target instruction data to a cloud server.

[0008] According to another aspect of an embodiment of the present invention, a system for processing vehicle data is also provided, including: a data acquisition device installed on the vehicle, for collecting data of the vehicle and forwarding at least one trigger instruction; a processing device, connected to the data acquisition device and a cloud server, for making a data request for first data and second data sent by the data acquisition device based on at least one received trigger instruction, obtaining target instruction data corresponding to at least one trigger instruction, and sending the target instruction data to the cloud server, wherein the second data is used to represent data sent by the data acquisition device before receiving at least one trigger instruction.

[0009] According to another aspect of an embodiment of the present invention, there is further provided an electronic device, comprising: a memory storing an executable program; and a processor for running the program, wherein the method in each embodiment of the present invention is executed when the program is running.

[0010] According to another aspect of an embodiment of the present invention, a computer-readable storage medium is provided. The computer-readable storage medium includes a stored executable program, wherein when the executable program is running, the device where the computer-readable storage medium is located is controlled to execute the methods in various embodiments of the present invention.

[0011] According to another aspect of an embodiment of the present invention, a computer program product is provided, including a computer program. When the computer program is executed by a processor, the method in each embodiment of the present invention is implemented.

[0012] According to another aspect of an embodiment of the present invention, a computer program product is provided, including a non-volatile computer-readable storage medium, wherein the non-volatile computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method in each embodiment of the present invention is implemented.

[0013] According to another aspect of the embodiments of the present invention, a computer program is further provided. When the computer program is executed by a processor, the methods in the embodiments of the present invention are implemented.

[0014] In an embodiment of the present invention, a method for processing vehicle data is provided, comprising: when a data acquisition device installed on a vehicle receives at least one trigger instruction, firstly, the first data collected by the data acquisition device in real time is obtained. Then, the first data and the second data are cleaned based on at least one trigger instruction to obtain the target instruction data corresponding to the at least one trigger instruction, and the second data is used to characterize the data collected by the data acquisition device before receiving the at least one trigger instruction. Finally, the target instruction data is sent to a cloud server. It is easy to notice that the technical solution proposed in the present application can first store the collected data, and then clean the data according to the trigger instruction, which can avoid data loss and ensure that all collected data can be processed and analyzed. Specifically, after receiving the trigger instruction, the first data and the second data are cleaned to improve the accuracy and integrity of the data. Through the cleaning process, invalid data, abnormal data and duplicate data can be removed, so as to obtain more reliable and effective target instruction data, ensure that the data sent to the cloud server is accurately processed and screened, ensure the integrity and accuracy of the data, improve the response speed to user needs and the accuracy of data analysis, and thus solve the technical problems of low efficiency and data missing in obtaining vehicle data required by users in the related technology. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0016] Figure 1 is a flow chart of a method for processing vehicle data according to an embodiment of the present invention;

[0017] Figure 2 is a schematic diagram of an optional process of processing vehicle data according to an embodiment of the present invention;

[0018] Figure 3 It is a schematic diagram of a device for processing vehicle data according to an embodiment of the present invention. DETAILED DESCRIPTION

[0019] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0020] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0021] According to one aspect of an embodiment of the present invention, a method for processing vehicle data is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0022] Figure 1 is a flow chart of a method for processing vehicle data according to an embodiment of the present invention. Figure 1 As shown, the method comprises the following steps:

[0023] Step S102: In response to a data acquisition device installed on a vehicle receiving at least one trigger instruction, first data collected by the data acquisition device is acquired.

[0024] The above-mentioned means of transport may refer to tools or equipment for transporting goods or personnel. The means of transport may include but are not limited to vehicles, ships, aircraft and drones, etc. In the present application, the means of transport is preferably an autonomous driving vehicle. The means of transport can be determined according to actual needs and is not limited here.

[0025] The above-mentioned data acquisition equipment may refer to equipment installed on a vehicle for collecting and recording the operating data of the vehicle, which may include various sensors, recorders, positioning systems, data storage devices and communication equipment, etc., for monitoring and recording various parameters and information of the vehicle during operation; the data acquisition equipment can record data such as the vehicle's driving speed, mileage, fuel consumption and location, which can help monitor the vehicle's operating status in real time, detect problems in a timely manner and make adjustments.

[0026] The trigger instruction mentioned above may refer to an instruction received by the data acquisition device installed on the carrier, and the trigger instruction may be different types of instructions, such as platform trigger instructions, fault trigger instructions, takeover trigger instructions, and event trigger instructions. The trigger instruction may be sent by the monitoring platform, or by the device itself or an external system, and is used to trigger the data acquisition device to collect and transmit data. The trigger instruction may be determined according to actual needs and is not limited here.

[0027] The first data mentioned above may refer to the data collected by the data acquisition device in real time. After receiving the trigger instruction, the data acquisition device will collect data according to the instruction requirements, and process and transmit the collected data as the first data. The first data may include the operating status, location information, sensor data, etc. of the carrier, which are used to monitor and analyze the operating conditions of the carrier in real time. The first data can be determined according to actual needs and is not limited here.

[0028] In an optional embodiment, during the processing of the vehicle data, various sensors and monitoring devices can be used to monitor the status and operation of the vehicle in real time, and these data can be transmitted to the data processing platform for analysis and processing. When the data acquisition device receives the trigger instruction, it can start to acquire real-time data and record it. First, the data acquisition device can communicate with the data processing platform through a pre-set communication protocol to receive the trigger instruction. The trigger instruction can be divided into different types, such as the platform trigger instruction is sent by the data processing platform to request the data acquisition device to upload data; the fault trigger instruction is sent when a fault or abnormal situation occurs, and is used to obtain relevant fault information; the takeover trigger instruction is sent when remote control or intervention is required, and is used to implement remote control operations; the event trigger instruction is sent when a specific event occurs, and is used to obtain event-related data. After receiving the trigger instruction, the data acquisition device can start to acquire the first data in real time, that is, the data recorded in real time by the data recorder. These data may include the location information, speed, fuel consumption, temperature, humidity, pressure and other data collected by various sensors of the vehicle, and the data acquisition device can transmit these data to the data processing platform in real time according to the pre-set acquisition cycle and data transmission mode. In the process of acquiring data, the data acquisition device can also process and analyze the data, which may include data parsing, verification, compression and other operations to ensure the accuracy and reliability of the data. In the above steps, in the process of data processing of the carrier, the data acquisition device installed on the carrier receives the trigger instruction and acquires the first data. Through effective data acquisition and transmission, real-time monitoring and control of the status and operation of the carrier can be achieved, ensuring the normal operation of the data acquisition device and accurate data acquisition.

[0029] Step S104: clean the first data and the second data based on at least one trigger instruction to obtain target instruction data corresponding to the at least one trigger instruction.

[0030] The second data is used to represent data collected by the data collection device before receiving at least one trigger instruction.

[0031] The second data mentioned above may refer to data collected by the data collection device before receiving at least one trigger instruction. The second data may include information of various vehicles, such as the position, speed, acceleration, temperature, etc. of the vehicle.

[0032] The above-mentioned target instruction data may refer to the filtered, sorted and cleaned data obtained after data cleaning processing, which is used to meet preset requirements or purposes.

[0033] In an optional embodiment, during the data processing of the carrier, data cleaning can process the first data and the second data to remove incomplete or unnecessary data for subsequent data analysis and processing. The present application can perform data cleaning on the first data and the second data based on at least one trigger instruction to obtain target instruction data corresponding to at least one trigger instruction. Specifically, the data acquisition device can continuously collect data of the carrier, including data of various sensors, position data, etc. When the data acquisition device receives the trigger instruction, the action of data acquisition can be triggered. At this time, the data acquisition device will record the time point when the trigger instruction is received and stop the previous data acquisition work, so that the second data can be obtained. Then, the first data and the second data can be cleaned. The first data can be processed to remove repeated, erroneous or incomplete data, and data verification and formatting can be performed. And the second data can be processed, according to the data collected before receiving the trigger instruction, the unnecessary data is removed and the valid data is retained. After cleaning, the cleaning results of the first data and the second data can be obtained. According to the target instruction corresponding to at least one trigger instruction, the cleaned first data and the second data can be merged to obtain the target instruction data corresponding to the trigger instruction. It can be used for subsequent data analysis and processing to achieve effective management and monitoring of vehicle data. In practical applications, reasonable data cleaning algorithms and processes can be designed to perform data cleaning work in combination with the actual conditions and needs of the vehicle. Vehicle data can be effectively processed to provide support for related applications and decisions.

[0034] Step S106, sending the target instruction data to the cloud server.

[0035] The cloud server mentioned above may refer to a remote server based on cloud computing technology. Through the Internet connection, users can upload data to the cloud server for storage, processing and management. During the data processing of the carrier, the target instruction data is sent to the cloud server, which can realize centralized management, real-time monitoring and remote control of the data.

[0036] In an optional embodiment, the target instruction data can be sent to the cloud server. Specifically, sensors and data acquisition devices can be installed on the carrier, which can monitor the operating status, location, temperature and other information of the carrier in real time. These data can be collected and stored in a local data processing unit. Then, the collected data can be transmitted to the cloud server through a wireless network or Internet of Things technology. This process can be encrypted and compressed by the data transmission protocol to ensure the security and effectiveness of data transmission. When the data arrives at the cloud server, it will be stored in the database and processed and analyzed in real time. In the process of sending the target instruction data to the cloud server, the stability and real-time performance of data transmission can also be considered. The carrier may pass through different regions and network environments, so some data transmission optimization technologies such as packet retransmission, data compression, data verification, etc. can be adopted to ensure the integrity and accuracy of the data. After the data arrives at the cloud server, it can be monitored and controlled in real time through the cloud application. The user can check the status and location of the carrier at any time, monitor abnormal conditions during transportation, and send instructions to control the operation of the carrier. This can improve transportation efficiency, reduce costs, and ensure the safe transportation of goods. The data transmission process can adopt Internet of Things technology and cloud computing technology to achieve efficient processing and management of data.

[0037] In an embodiment of the present invention, a method for processing vehicle data is provided, comprising: when a data acquisition device installed on a vehicle receives at least one trigger instruction, firstly, the first data collected by the data acquisition device in real time is obtained. Then, the first data and the second data are cleaned based on at least one trigger instruction to obtain the target instruction data corresponding to the at least one trigger instruction, and the second data is used to characterize the data collected by the data acquisition device before receiving the at least one trigger instruction. Finally, the target instruction data is sent to a cloud server. It is easy to notice that the technical solution proposed in the present application can first store the collected data, and then clean the data according to the trigger instruction, which can avoid data loss and ensure that all collected data can be processed and analyzed. Specifically, after receiving the trigger instruction, the first data and the second data are cleaned to improve the accuracy and integrity of the data. Through the cleaning process, invalid data, abnormal data and duplicate data can be removed, so as to obtain more reliable and effective target instruction data, ensure that the data sent to the cloud server is accurately processed and screened, ensure the integrity and accuracy of the data, improve the response speed to user needs and the accuracy of data analysis, and thus solve the technical problems of low efficiency and data missing in obtaining vehicle data required by users in the related technology.

[0038] In an embodiment of the present invention, data cleaning is performed on first data and second data based on at least one trigger instruction to obtain target instruction data corresponding to the at least one trigger instruction, including: determining at least one cleaning time period based on the type of at least one trigger instruction, wherein at least one cleaning time period corresponds one-to-one to at least one trigger instruction; based on the at least one cleaning time period, data cleaning is performed on the first data and second data to obtain cleaned data; and target instruction data is generated based on the cleaned data and at least one trigger instruction.

[0039] The above-mentioned cleaning time period may refer to a pre-set time period for cleaning or trimming data, that is, a specific time range for cleaning and screening data when processing vehicle data. The setting of the cleaning time period can be determined according to specific data processing requirements and trigger instructions. By reasonably setting the cleaning time period, it can help to better process and analyze vehicle data and improve the quality and accuracy of the data. Different trigger instructions can correspond to different cleaning time periods. The cleaning time period can be set according to actual needs and is not limited here.

[0040] In the vehicle data processing process of the present application, the setting of the cleaning time period can help to better understand and analyze the data, reduce the impact of noise and erroneous data, and improve the quality and accuracy of the data. Specifically, the setting of the cleaning time period can be associated with a trigger instruction, such as a platform trigger instruction, a fault trigger instruction, a takeover trigger instruction, or an event trigger instruction. When processing vehicle data, the time period that needs to be cleaned and processed can be determined based on these trigger instructions in order to better analyze and understand the data. For example, if you want to process the fault data of a vehicle, you can determine the cleaning time period through the fault trigger instruction. The cleaning time period can be set to start from a period of time before the fault trigger instruction occurs and end at a period of time after the fault trigger instruction occurs. During this time period, the data can be cleaned and screened in order to better analyze and understand the fault data.

[0041] In an optional embodiment, the first data and the second data can be cleaned based on at least one trigger instruction. Specifically, the type of the trigger instruction can be determined, which can be a platform trigger instruction, a fault trigger instruction, a takeover trigger instruction or an event trigger instruction. According to this trigger instruction, the first data and the second data can be screened and filtered to perform subsequent data cleaning operations. According to the type of the trigger instruction, at least one cleaning time period can be determined. The cleaning time period can be a fixed time period or a dynamic time period, which is adjusted according to actual conditions. The cleaning time period corresponds to the trigger instruction one by one, and the adaptive adjustment of the cleaning and screening time length with the trigger instruction can be achieved, which can ensure the timeliness and accuracy of data cleaning. Then, according to the determined cleaning time period, the first data and the second data can be cleaned. The data cleaning can include data deduplication, data formatting, data verification and other operations to ensure the accuracy and integrity of the data. The cleaned data can be further processed and analyzed. Finally, based on the cleaned data and the trigger instruction, the target instruction data can be generated. The target instruction data can be the processed data or the summary statistical results of the data, which are generated according to actual needs. By determining the correspondence between the cleaning time period and the trigger instruction, the adaptive adjustment of the cleaning screening time with the trigger instruction can be achieved, which can ensure the adaptability and effectiveness of data cleaning. When the trigger instruction occurs, the data cleaning operation can be performed in time to ensure the real-time and timeliness of the data. It can effectively improve the efficiency and quality of data processing of carriers, ensure the accuracy, timeliness and consistency of the data, and provide a reliable data basis for subsequent data analysis and application.

[0042] In an embodiment of the present invention, at least one cleaning time period is determined based on the type of at least one trigger instruction, including: in response to any one of the trigger instructions being a cloud trigger, a fault trigger or an event trigger, based on the triggering moment of the trigger instruction, determining the cleaning time period corresponding to the trigger instruction; in response to any one of the trigger instructions being a takeover trigger, determining at least one target data containing a preset tag from the second data, and determining the cleaning time period based on the latest occurrence moment corresponding to the preset tag contained in the at least one target data, wherein the preset tag is used to characterize that the carrier has entered a parking state.

[0043] The cloud trigger mentioned above may refer to an operation or command sent in the cloud to trigger the processing of vehicle data. The cloud trigger may be a command sent by a cloud server or control center to a vehicle, such as remotely controlling the operation, stopping or changing the operation mode of the vehicle.

[0044] The above-mentioned fault triggering may refer to triggering the data processing system to perform corresponding processing when a fault or abnormality occurs in the carrier. The fault triggering may be that the sensor or monitoring device of the carrier detects the fault or abnormality, and then sends a signal to the data processing system for processing or alarm.

[0045] The above-mentioned event triggering may refer to triggering the processing of vehicle data when a specific event occurs. Event triggering may be triggering the data processing system to perform corresponding processing according to a preset event or condition, such as the vehicle arriving at a designated location, completing a specific task, encountering an obstacle, etc.

[0046] The above-mentioned takeover trigger may refer to triggering the data processing system to perform corresponding processing when the driver or user intervenes or manually controls the vehicle. The takeover trigger may be to switch to manual mode or perform corresponding processing through the takeover trigger when manual operation or intervention of the vehicle is required.

[0047] The above-mentioned preset label may refer to a sign or identification indicating that the vehicle has entered a parking state, and may be a sign that the vehicle has entered a parking state after the vehicle speed has become zero.

[0048] In an optional embodiment, during the vehicle data processing process, the cleaning time period can be determined based on the type of trigger instruction, and the vehicle data can be effectively cleaned and organized to ensure the accuracy and reliability of the data. Specifically, the cleaning time period can be determined according to the type of trigger instruction, and the types of trigger instructions can be divided into cloud trigger, fault trigger, event trigger, and takeover trigger, etc. For cloud trigger, fault trigger, and event trigger, the cleaning time period can be determined according to the triggering moment, and the cleaning time period can also be determined based on the preset time before and after the triggering moment. For example, when a cloud-triggered instruction is received, the time period from 15s to 5s before the triggering moment of the instruction can be used as the cleaning time period, so as to ensure that the data related to the triggering instruction is cleaned.

[0049] In another optional embodiment, for takeover trigger, considering that in the application scenario of autonomous driving, the driver generally takes over the vehicle 1 to 2 minutes after the vehicle stops to generate a takeover trigger. At this time, cleaning the data based on the trigger instruction may cause data loss for a long period of time before and after the vehicle stops. The present application proposes that when the trigger instruction is a takeover trigger, the vehicle entering the parking state can be set as a preset label, so that the data can be cleaned based on the time before and after the vehicle stops, thereby improving the integrity and accuracy of data cleaning. The present application can determine the target data containing the preset label from the second data, and determine the cleaning time period according to the latest occurrence time corresponding to the preset label contained in the target data. By identifying these labels and determining the latest occurrence time, the cleaning time period can be effectively determined so that the data in the parking state can be cleaned and processed in a timely manner.

[0050] In the above steps, by determining the cleaning time period according to the type of trigger instruction, adaptability of data cleaning can be achieved, which can effectively improve the efficiency and accuracy of vehicle data processing, ensure the quality and reliability of the data, and thus provide a reliable basis for data analysis and application.

[0051] In an embodiment of the present invention, data cleaning is performed on the first data and the second data based on at least one cleaning time period to obtain the cleaned data, including: determining data whose storage time is within at least one cleaning time period from the first data and the second data to obtain the cleaned data.

[0052] In an optional embodiment, at least one cleaning time period can be determined, and then the data whose storage time is within the cleaning time period can be screened out from the first data and the second data. This can be achieved by comparing the timestamp, storage time and cleaning time period of the data. The data within the time range can be retained, and other data will be filtered out. After determining the data that meets the conditions, further cleaning operations can be performed on these data, such as removing duplicate data, correcting erroneous data, filling missing data, etc. The cleaning operation can be implemented through programming languages ​​or data processing tools, setting a cleaning time period and cleaning the data. By cleaning the data, invalid or erroneous data can be excluded, thereby ensuring the accuracy and reliability of the data, which can help improve the quality and reliability of the data, reduce the complexity of data processing, and ensure the consistency of the data, thereby providing a reliable basis for subsequent data analysis and decision-making.

[0053] In an embodiment of the present invention, target instruction data is generated based on the cleaned data and at least one trigger instruction, including: obtaining at least one tag and the occurrence time of at least one tag contained in the cleaned data, any one tag is used to characterize one of the following: a preset fault occurs in the carrier, the carrier enters a parking state, and a preset event occurs in the carrier; based on the number of at least one tag and the number of at least one trigger instruction, the data duration of the target instruction data is determined; based on the type of at least one trigger instruction, the tag and the occurrence time of the tag, and the data duration, the target instruction data is generated.

[0054] In an optional embodiment, when processing the vehicle data, the data can be cleaned and processed according to the preset time limit to ensure the accuracy and reliability of the data. When processing data, sometimes a piece of data contains only one label or contains multiple operation types or multiple labels. For example, when a piece of data contains only one label, the time length of the data can be set to 25s; if a piece of data contains multiple operation types or multiple labels, the time length of the data can be set to no more than 45s. The time setting here can also be determined according to actual needs and is not limited here. Specifically, when cleaning the data, the range of the cleaning time period can be determined first. The cleaning time period can be set according to specific needs, and can be determined according to the timestamp of the data. Then, the first data and the second data can be cleaned, which can include processing the data format, data content, data accuracy, etc. When cleaning the data, the data length can be adjusted according to the preset time limit, and the data can be analyzed and processed to ensure that the data meets the specified time requirements. The cleaned data can be further analyzed and processed, such as the number of statistical data, time distribution, etc., which can help better understand the characteristics and laws of the data and provide support for subsequent data analysis and application.

[0055] In the above steps, the cleaned data meets the pre-set time limit, ensuring the integrity and consistency of the data, facilitating subsequent data analysis and application, avoiding errors caused by incomplete or inconsistent data, and effectively improving the quality and availability of data, providing a reliable data foundation for subsequent data analysis and application. The pre-set time limit can ensure the accuracy, integrity and reliability of the data, providing effective support and guarantee for data processing.

[0056] In an embodiment of the present invention, based on the number of at least one tag and the number of at least one trigger instruction, the data duration of the target instruction data is determined, including: in response to the number of at least one tag being less than or equal to a first preset number, and the number of at least one trigger instruction being less than or equal to a second preset number, determining the data duration as the first preset duration; in response to the number of at least one tag being greater than the first preset number, or the number of at least one trigger instruction being greater than the second preset number, determining the data duration based on at least one trigger instruction, wherein the data duration is less than or equal to the second preset duration, and the second preset duration is greater than the first preset duration.

[0057] The first preset number mentioned above may refer to a preset parameter for measuring the number of tags in a trigger instruction, which may be 1, etc. The first preset number may be determined according to actual needs and is not limited here.

[0058] The above-mentioned second preset number may refer to a pre-set parameter for measuring the number of trigger instructions. The second preset number may be the same as the first preset number or different from the first preset number. It may be 1, etc. The second preset number may be determined according to actual needs and is not limited here.

[0059] When processing the vehicle data, the duration of the data can be determined according to the number of tags and the number of trigger instructions in the data. Specifically, the first preset number and the second preset number can be defined first, which are used to measure the number of tags and the number of trigger instructions respectively. It can be assumed that the first preset number is n1 and the second preset number is n2, and the first preset duration is set to t1, which can be 25s, etc.; the second preset duration is t2, which can be 45s, etc. For each piece of data, the number of tags and the number of trigger instructions contained therein can be counted first. If the number of at least one tag is less than or equal to the first preset number, and the number of at least one trigger instruction is less than or equal to the second preset number, then the duration of the data can be set to the first preset duration t1. If the number of at least one tag is greater than the first preset number, or the number of at least one trigger instruction is greater than the second preset number, the duration of the data can be determined according to at least one trigger instruction. In this case, it can be compared whether the duration of the data is less than or equal to the second preset duration t2. If so, the duration of the data can be determined according to the trigger instruction; if not, the duration of the data is t2. In the above steps, by setting two preset numbers and corresponding durations, and determining the data duration according to the number of tags and the number of trigger instructions, the data duration can be dynamically adjusted according to the actual situation, and the data processing requirements in different situations can be better adapted, thereby improving the flexibility and applicability of the system, and effectively controlling the precision and efficiency of data processing. For simple data, it can be directly processed according to the first preset duration, reducing unnecessary calculation and processing time; for complex data, it can be processed more carefully according to the specific situation to ensure the accuracy and completeness of the data. It can effectively balance the accuracy and efficiency of data processing, improve the flexibility and adaptability of the system, and thus provide a more reliable and efficient solution for the processing of vehicle data.

[0060] In an embodiment of the present invention, sending target instruction data to a cloud server includes: generating a cleaning record based on the target instruction data; sending the cleaning record to the cloud server and receiving a data extraction instruction returned by the cloud server; and sending the target instruction data to the cloud server.

[0061] In an optional embodiment, during the data processing of the carrier, the target instruction data can also be sent to the cloud server. Specifically, the collected data can be transmitted to the cloud server via a wireless network or other communication methods, and the Internet of Things technology can be used to realize data transmission to ensure that the data can be stably and efficiently transmitted to the cloud server. On the cloud server, the target instruction data can be received and processed, which can include data parsing, cleaning, storage and analysis. The generation of cleaning records can ensure the accuracy and integrity of the data and remove unnecessary information or erroneous data. The cleaning records can be stored on the cloud server for subsequent data analysis and use, and the cloud database can be used to store data to ensure data security and reliability. Then, the cloud server can generate data extraction instructions based on the cleaning records, which can include query, analysis or operation of the data, and these instructions can be sent to the carrier to realize remote control and management of the carrier. After the carrier receives the data extraction instructions sent by the cloud server, it can perform the corresponding operations and feedback the results to the cloud server, and the two-way transmission of data can be realized through the real-time communication protocol to ensure the timely execution and feedback of the instructions. Through the above steps, real-time monitoring and management of vehicle data are achieved, the efficiency and accuracy of data processing are improved, and remote control and operation of the vehicle are also achieved.

[0062] In an embodiment of the present invention, when the target instruction data contains multiple instruction data, receiving the data extraction instruction returned by the cloud server includes: receiving multiple extraction instructions returned in sequence by the cloud server, wherein the data extraction instruction contains multiple extraction instructions, wherein the sending order of the multiple extraction instructions is determined based on the type and trigger time of the trigger instructions contained in the multiple instruction data; sending the target instruction data to the cloud server includes: sending multiple instruction data to the cloud server in sequence.

[0063] In an optional embodiment, when the target instruction data contains multiple instruction data, a data extraction instruction returned by the cloud server can be received. Specifically, after the cloud server receives the cleaning record uploaded by the vehicle, it can first parse and process the data, complete the priority sorting according to the operation type and trigger time, and generate multiple extraction instructions. Then, the cloud server can send these extraction instructions to the vehicle in sequence. Each extraction instruction contains multiple specific data instructions. The sending order of these data instructions is determined based on the type and trigger time of the trigger instructions contained in the multiple instruction data. After the vehicle receives the extraction instruction, it extracts the corresponding data in sequence according to the specific data instructions contained therein, and uploads the data to the cloud server. The uploaded data is processed and stored by the cloud server to complete the entire data extraction and transmission process.

[0064] In another optional embodiment, the target instruction data can be sent to the cloud server. Specifically, after the vehicle-side processes the cleaning record, the generated multiple instruction data can be sent to the cloud server in sequence. Then, after receiving these instruction data, the cloud server parses and processes them, and stores and subsequently processes them according to the content and priority of the data. The cloud server can perform further operations based on the received instruction data, such as generating extraction instructions, triggering other actions, or responding to user requests. Through the implementation of the above steps, data interaction and instruction transmission between the vehicle-side and the cloud can be realized, ensuring accurate, timely and orderly transmission of data.

[0065] In the above steps, by prioritizing and issuing extraction instructions in order, and determining the sending order according to the type and time of the triggering instructions, the timely extraction and transmission of data can be guaranteed, the overall data processing efficiency can be improved, the accuracy and completeness of the data can be guaranteed, data loss or confusion can be avoided, the efficiency of data processing and transmission can be effectively improved, and the stability and reliability of the system can be ensured.

[0066] In an embodiment of the present invention, the target instruction data is identified by a cloud server to obtain an identification result, and the target instruction data is marked based on the identification result, wherein the identification result includes at least one of the following information: the reason for the vehicle to be parked, the reason for a preset fault of the vehicle, and the event information of a preset event of the vehicle.

[0067] In an optional embodiment, during the processing of the vehicle data, the target instruction data can be identified by the cloud server to obtain the identification result, and the target instruction data can be marked based on the identification result. The identification result may include the parking reason of the vehicle in the parking state, the fault reason of the preset fault of the vehicle, and the event information of the preset event of the vehicle. Specifically, first, the target instruction data can be transmitted to the cloud server for processing, and various technologies and algorithms can be used to identify the target instruction data on the cloud server, which may include machine learning, deep learning, natural language processing and other technologies. Through these technologies, the server can extract relevant information from the target instruction data, including the status of the vehicle, fault information or event information. When the relevant information in the target instruction data is identified, the server can mark the target instruction data according to this information, and the marking process can be understood as adding tags to the target instruction data for subsequent processing and analysis. For example, if it is identified that the parking reason of the vehicle in the parking state is due to traffic jam, then the target instruction data can be marked with a label such as "traffic jam". Through the above processing process, the target instruction data can be automatically identified and marked, thereby improving the efficiency and accuracy of data processing. It can also help to better understand and analyze the status and situation of the carrier, and provide strong support for subsequent decision-making and optimization.

[0068] In the above steps, through the automatic recognition and labeling functions of the cloud server, the target instruction data can be automatically processed, the need for human intervention can be reduced, the accuracy and consistency of the data can be ensured, and data quality problems caused by human errors can be reduced. It can realize automatic data processing and improve data processing efficiency, providing better support for subsequent data analysis and decision-making.

[0069] In the embodiment of the present invention, when the type of any trigger instruction is cloud trigger, any trigger instruction is sent by the cloud server and forwarded to the data acquisition device through a carrier.

[0070] In an optional embodiment, during the processing of the carrier data, when the type of any trigger instruction is cloud-triggered, the instruction can be sent through the cloud server and forwarded to the data acquisition device through the carrier. Specifically, first, the cloud server receives the user's instruction request, and can generate corresponding instructions according to the user's needs and send them to the carrier. Then, after the carrier receives the instruction sent by the cloud server, it can parse and verify it to ensure the integrity and legality of the instruction. The carrier can have the ability to connect to the network and parse instructions to ensure that the instructions can be correctly transmitted and executed. Finally, after receiving the instruction, the data acquisition device can perform corresponding operations according to the instruction requirements, such as collecting data, uploading data, etc. Through the above steps, the process of forwarding instructions to the data acquisition device through the carrier is realized when the type of any trigger instruction is cloud-triggered.

[0071] In the above process, commands are sent through the cloud server and forwarded to the data acquisition equipment through the carrier, realizing remote control of the data acquisition equipment. Users can send commands through the cloud server in real time without on-site operation, reducing the time and cost of data transmission and improving the efficiency and accuracy of data acquisition. It has achieved technical effects such as remote control, improved efficiency and enhanced safety, and provided important technical support for the development of carrier data processing.

[0072] The technical solution proposed in this application is explained below in combination with an optional application scenario. This application proposes a method for automatically cleaning and labeling high-value data. During the operation of autonomous driving vehicles, a large amount of data will be generated. Mining high-value scenarios from the operating data plays a relatively important role in improving the capabilities of the autonomous driving system. At present, high-quality scenarios are generally defined as scenarios where problems occur.

[0073] The ways to obtain problem data in related technologies may at least include: platform triggering, fault triggering, takeover triggering and event triggering. Among them, platform triggering is to complete the data latching process on the vehicle side by sending a data latching instruction to the specified vehicle on the cloud platform; fault triggering can be triggered when a specified fault occurs on the vehicle side, takeover triggering can be triggered when the vehicle has remote control driving takeover or manual driving takeover, and event triggering can complete data latching on the vehicle side when a specific event occurs.

[0074] The technical solution proposed in this application can use the data recorder to store all the original data in real time, and clean the required data from the original data in real time according to the trigger conditions. The data recorder has a large storage space, which can save enough cleaned data, and make the most of the network bandwidth to upload the required cleaned data to the cloud; this method can ensure that when one data is being generated, other data triggering requirements can be completed at the same time; this application adopts data cleaning instead of data latching. This application stores data through the data recorder and cleans the data according to the trigger conditions. It can ensure that the cleaned data contains the problem time.

[0075] During the data cleaning process, the main information contained in a piece of data may include the operation type, label and label occurrence time, data duration, etc. Among them, the operation types are platform trigger, fault trigger, takeover trigger and event trigger. A piece of data may contain multiple operation types. For example, when the platform sends a latch instruction, a certain fault happens to occur on the vehicle side at this time, then the operation type of this piece of data includes platform trigger and fault trigger. One type of operation can occur at one moment, and the operation types occurring at different moments are different, so they need to be recorded.

[0076] In this application, a piece of data may have one or more labels, and the label can be a certain fault, a certain parking reason, or a defined event. If a piece of data contains only one label, the duration of the data can be set to 25 seconds. When the operation type is cloud-triggered, fault-triggered, or event-triggered, data cleaning can be the time period between 15 seconds before and 5 seconds after the trigger moment; when the operation type is takeover triggered, data cleaning can be the time period between 20 seconds before and 5 seconds after the most recent parking before takeover. Considering that takeover often occurs 1 to 2 minutes after the vehicle is parked, the 10 seconds before and 5 seconds after the takeover moment often do not include the problem moment. Therefore, when takeover occurs, the most recent parking event can be found forward and the detailed parking reason can be used as a label. If a piece of data contains multiple operation types or multiple labels, the duration of a piece of data can be set to no more than 45 seconds.

[0077] In this application, the occurrence time corresponding to the label can be the time when a certain fault, event or a certain takeover occurs, and the number of labels and the number of occurrence times corresponding to the labels can be the same. When the trigger condition is met, the duration of the stored data can be determined based on the label of the data to facilitate subsequent cleaning.

[0078] The present application can realize cloud triggering. When a person manually clicks to latch on the cloud platform, the latching instruction is sent to the vehicle side via the vehicle-to-vehicle / infrastructure communication technology (Vehicle-to-Everything, referred to as V2X), and the data recording module on the vehicle side passes the instruction to the network access server (Network Attached Storage, referred to as NAS), completes the cleaning in the NAS, and obtains the cleaned data; when the triggering instruction belongs to a fault trigger, a takeover trigger or an event trigger, when the vehicle is in operation and is triggered by meeting the set conditions, the data recording module on the vehicle side can pass the triggering information to the NAS, complete the cleaning in the NAS, and obtain the cleaned data. During the data cleaning process on the vehicle side, the status displayed on the cloud platform is latching.

[0079] After the data cleaning of this application is completed, the data cleaning record can be sent to the cloud. At this time, the status displayed on the cloud platform is waiting for upload. After the cleaning record of the vehicle is uploaded to the cloud, the cloud can complete the priority sorting according to the operation type and trigger time, and issue extraction instructions one by one. After the vehicle receives the extraction instruction, it uploads the corresponding data to the cloud. During this process, the status displayed on the cloud platform is extracting. If there are too many files after cleaning, resulting in them being overwritten before being uploaded to the cloud, the status displayed on the cloud platform during this process may be that the extracted file does not exist. After the file is successfully extracted to the cloud, the status displayed on the cloud platform is successful extraction. If there are abnormal conditions during the extraction process that cause the data to not be extracted to the cloud, the status displayed on the cloud platform may be extraction failure.

[0080] The technical solution proposed in this application can realize automatic data labeling. Specifically, the data uploaded to the cloud can be automatically labeled according to the matched events and faults. The reported data contains the reasons and can be labeled according to the reasons and events. The labeled data can be automatically transferred to the corresponding R&D personnel to complete the corresponding root cause analysis, and finally complete the archiving of the data according to the root cause after manual confirmation for subsequent version release testing. Fault labels may include but are not limited to: no data from the lidar, regression planning trajectory failure, interruption of decision data receiving communication, abnormal access to the distance between the initial point of the trajectory and the origin, etc. Event labels may include but are not limited to: abnormal parking due to deviation from the trajectory, system speed limit parking, minimum safety system no trajectory overstepping, and microcontroller task (Microcontroller Task, referred to as MCU-TASK) exceeding the specified threshold.

[0081] The technical solution proposed in this application adopts real-time cleaning instead of latching through latching instructions, which can ensure successful data acquisition and no latching failure; data is acquired by finding the parking time point and then intercepting a specific time period to ensure that the obtained data includes the problem time.

[0082] Figure 2is a schematic diagram of an optional process of processing vehicle data according to an embodiment of the present invention, such as Figure 2 As shown, the processing process of the carrier data can be realized by data transmission between the cloud server, the wireless communication device, the data acquisition device and the network access server. Specifically, the cloud server can send a cloud trigger instruction to the wireless communication device, the data acquisition device can transmit the trigger time and trigger content to the network access server, the data acquisition device can reply that it is storing, the cloud server can display that it is storing, the network access server can complete the cleaning, the data acquisition device can reply that it is waiting for upload, the cloud server can display that it is waiting for upload on the platform, the cloud automatically issues an extraction instruction, the wireless communication device can transmit the extraction instruction to the data acquisition device, the data acquisition device can determine whether the extraction file exists, when the extraction file does not exist, reply that the extraction file does not exist, and display that the extraction file does not exist on the platform of the cloud server; when the extraction file exists, the data acquisition device replies that it is extracting, and displays that it is extracting on the platform of the cloud server; the data acquisition device uploads data and receives files based on the cloud server; the data acquisition device can determine whether the upload is successful, when the upload is successful, the data acquisition device replies that the extraction is successful, and prompts the cloud server that the extraction is successful and can be downloaded; when the upload fails, the data acquisition device replies that the extraction fails, and prompts the cloud server that the extraction fails.

[0083] According to another aspect of an embodiment of the present invention, a device for processing vehicle data is also provided, which can execute the method for processing vehicle data of the above embodiment. The specific implementation method and preferred application scenario are the same as those of the above embodiment and will not be repeated here.

[0084] Figure 3 is a schematic diagram of a device for processing vehicle data according to an embodiment of the present application, such as Figure 3 As shown, the device includes the following: an acquisition module 302 , a cleaning module 304 and a sending module 306 .

[0085] Among them, the acquisition module is used to obtain the first data collected by the data acquisition device in response to the data acquisition device installed on the carrying vehicle receiving at least one trigger instruction; the cleaning module is used to clean the first data and the second data based on at least one trigger instruction to obtain the target instruction data corresponding to at least one trigger instruction, wherein the second data is used to represent the data collected by the data acquisition device before receiving at least one trigger instruction; the sending module is used to send the target instruction data to the cloud server.

[0086] Among them, the cleaning module is also used to determine at least one cleaning time period based on the type of at least one trigger instruction, wherein at least one cleaning time period corresponds one-to-one to at least one trigger instruction; based on at least one cleaning time period, the first data and the second data are cleaned to obtain cleaned data; based on the cleaned data and at least one trigger instruction, target instruction data is generated.

[0087] Among them, the cleaning module is also used to respond to any trigger instruction type of cloud trigger, fault trigger or event trigger, and determine the cleaning time period corresponding to the trigger instruction based on the trigger time of the trigger instruction; in response to any trigger instruction type of takeover trigger, determine at least one target data containing a preset tag from the second data, and determine the cleaning time period based on the latest occurrence time corresponding to the preset tag contained in at least one target data, wherein the preset tag is used to characterize that the carrying vehicle enters a parking state.

[0088] The cleaning module is further used to determine data whose storage time is within at least one cleaning time period from the first data and the second data, and obtain cleaned data.

[0089] Among them, the cleaning module is also used to obtain at least one tag and the occurrence time of at least one tag contained in the cleaned data, and any tag is used to characterize one of the following: a preset fault occurs in the carrier, the carrier enters a parking state, and a preset event occurs in the carrier; based on the number of at least one tag and the number of at least one trigger instruction, the data duration of the target instruction data is determined; based on the type of at least one trigger instruction, the tag and the occurrence time of the tag, and the data duration, the target instruction data is generated.

[0090] Among them, the cleaning module is also used to determine the data duration as the first preset duration in response to the number of at least one tag being less than or equal to the first preset number, and the number of at least one trigger instruction being less than or equal to the second preset number; in response to the number of at least one tag being greater than the first preset number, or the number of at least one trigger instruction being greater than the second preset number, determine the data duration based on at least one trigger instruction, wherein the data duration is less than or equal to the second preset duration, and the second preset duration is greater than the first preset duration.

[0091] Among them, the sending module is also used to generate a cleaning record based on the target instruction data; send the cleaning record to the cloud server and receive the data extraction instruction returned by the cloud server; send the target instruction data to the cloud server.

[0092] Among them, the sending module is also used to receive multiple extraction instructions returned in sequence by the cloud server, wherein the data extraction instruction includes multiple extraction instructions, wherein the sending order of the multiple extraction instructions is determined based on the type and trigger time of the trigger instructions contained in the multiple instruction data; sending the target instruction data to the cloud server includes: sending multiple instruction data to the cloud server in sequence.

[0093] Among them, the target instruction data is identified by the cloud server to obtain an identification result, and the target instruction data is marked based on the identification result, wherein the identification result includes at least one of the following information: the reason why the carrier is in a parking state, the reason why a preset fault occurs in the carrier, and the event information of a preset event occurring in the carrier.

[0094] Among them, when the type of any trigger instruction is cloud trigger, any trigger instruction is sent by the cloud server and forwarded to the data acquisition device through the carrier.

[0095] According to another aspect of an embodiment of the present invention, a system for processing vehicle data is also provided, which can execute the method for processing vehicle data of the above embodiment. The specific implementation method and preferred application scenario are the same as those of the above embodiment and will not be described in detail here. The system for processing vehicle data in the present application includes a data acquisition device and a processing device.

[0096] Among them, the data acquisition device is installed on the carrier, and is used to collect data of the carrier and forward at least one trigger instruction; the processing device is connected to the data acquisition device and the cloud server, and is used to make a data request for the first data and the second data sent by the data acquisition device based on at least one trigger instruction received, obtain the target instruction data corresponding to at least one trigger instruction, and send the target instruction data to the cloud server, wherein the second data is used to represent the data sent by the data acquisition device before receiving at least one trigger instruction.

[0097] In an embodiment of the present invention, the cloud server is also used to identify the target instruction data to obtain an identification result, and mark the target instruction data based on the identification result, wherein the identification result includes at least one of the following information: the reason why the carrier is in a parking state, the reason why a preset fault occurs in the carrier, and event information of a preset event occurring in the carrier.

[0098] An embodiment of the present application further provides an electronic device, comprising: a memory storing an executable program; and a processor for running the program, wherein the program executes the methods in various embodiments of the present invention when running.

[0099] The above-mentioned memory may refer to a device inside a computer for storing data and programs, and may include memory, hard disk, etc., wherein the memory may be used to temporarily store running programs and data, the hard disk may be used to store programs and data for a long time, and the memory may be used to enable the computer to read and write data, and execute programs; the above-mentioned processor may be responsible for executing instructions in computer programs and performing data processing, and may be responsible for controlling and executing various operations, including arithmetic operations, logical operations, data transmission, etc.

[0100] An embodiment of the present application further provides a computer-readable storage medium, which includes a stored executable program, wherein when the executable program is running, the device where the computer-readable storage medium is located is controlled to execute the methods in various embodiments of the present invention.

[0101] The above-mentioned computer storage medium may refer to a medium in a computer memory used to store certain discontinuous physical quantities. Computer storage media mainly include semiconductors, magnetic cores, magnetic drums, magnetic tapes, laser disks, etc.; the stored program included in the computer-readable storage medium may be a set of instructions that can be recognized and executed by a computer, running on an electronic computer, and is an information tool that meets certain needs of people.

[0102] An embodiment of the present application further provides a computer program product, including a computer program, which implements the methods in various embodiments of the present invention when executed by a processor.

[0103] The above-mentioned computer program product may refer to a software program that has been written, tested and released and can be run on a computer or other device. The computer program product may include an application, an operating system, tool software, etc., which is used to implement specific functions or solve specific problems.

[0104] An embodiment of the present application further provides a computer program product, including a non-volatile computer-readable storage medium, wherein the non-volatile computer-readable storage medium is used to store a computer program, and when the computer program is executed by a processor, the method in each embodiment of the present invention is implemented.

[0105] The above-mentioned non-volatile computer-readable storage medium may refer to a medium for storing data. The non-volatile computer-readable storage medium can keep the data from being lost when the power is off, and can be used to store long-term data, such as operating systems, applications, and user files. The non-volatile storage medium may include hard disk drives, solid-state drives, optical disks, and flash memory storage devices, etc.

[0106] The embodiments of the present application further provide a computer program, which implements the methods in the above-mentioned embodiments of the present invention when executed by a processor.

[0107] The above-mentioned computer program may refer to a collection of instructions used to tell a computer to perform a specific task or operation. A computer program may be written by a programmer using a specific programming language and may include algorithms, data structures, logic, and control flows. A computer program may be used for a variety of purposes, including application software, operating systems, and the like.

[0108] In the above embodiments of the present invention, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0109] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only schematic. For example, the division of the units can be a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0110] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0111] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0112] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, disk or optical disk, etc. Various media that can store program codes.

[0113] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for processing vehicle data, characterized in that: include: In response to a data acquisition device installed on a vehicle receiving at least one trigger instruction, acquiring first data collected by the data acquisition device; Performing data cleaning on the first data and the second data based on the at least one trigger instruction to obtain target instruction data corresponding to the at least one trigger instruction, wherein the second data is used to represent the data collected by the data collection device before receiving the at least one trigger instruction; Send the target instruction data to the cloud server.

2. The method according to claim 1, characterized in that: The performing data cleaning on the first data and the second data based on the at least one trigger instruction to obtain target instruction data corresponding to the at least one trigger instruction includes: Determining at least one cleaning time period based on the type of the at least one trigger instruction, wherein the at least one cleaning time period corresponds to the at least one trigger instruction one-to-one; Based on the at least one cleaning time period, performing data cleaning on the first data and the second data to obtain cleaned data; The target instruction data is generated based on the cleaned data and the at least one trigger instruction.

3. The method according to claim 2, characterized in that The step of determining at least one cleaning time period based on the type of the at least one trigger instruction comprises: In response to any trigger instruction being a cloud trigger, a fault trigger, or an event trigger, based on the triggering time of the trigger instruction, determining a cleaning time period corresponding to the trigger instruction; In response to any trigger instruction type being a takeover trigger, at least one target data containing a preset tag is determined from the second data, and the cleaning time period is determined based on the latest occurrence time corresponding to the preset tag contained in the at least one target data, wherein the preset tag is used to characterize that the carrier has entered a parking state.

4. The method according to claim 2 or 3, characterized in that: The step of performing data cleaning on the first data and the second data based on the at least one cleaning time period to obtain cleaned data includes: From the first data and the second data, data whose storage time is within the at least one cleaning time period is determined to obtain the cleaned data.

5. The method according to any one of claims 2 to 4, characterized in that The generating the target instruction data based on the cleaned data and the at least one trigger instruction comprises: Obtaining at least one tag and the occurrence time of the at least one tag contained in the cleaned data, wherein any one of the tags is used to characterize one of the following: a preset fault occurs to the carrier, the carrier enters a parking state, or a preset event occurs to the carrier; Determining the data duration of the target instruction data based on the number of the at least one tag and the number of the at least one trigger instruction; The target instruction data is generated based on the type of the at least one trigger instruction, the tag and the occurrence time of the tag, and the data duration.

6. The method according to claim 5, characterized in that The determining, based on the number of the at least one tag and the number of the at least one trigger instruction, the data duration of the target instruction data includes: In response to the number of the at least one tag being less than or equal to a first preset number, and the number of the at least one trigger instruction being less than or equal to a second preset number, determining the data duration to be the first preset duration; In response to the number of at least one tag being greater than the first preset number, or the number of at least one trigger instruction being greater than the second preset number, the data duration is determined based on the at least one trigger instruction, wherein the data duration is less than or equal to the second preset duration, and the second preset duration is greater than the first preset duration.

7. The method according to any one of claims 1 to 6, characterized in that: The sending of the target instruction data to the cloud server includes: generating a cleaning record based on the target instruction data; Sending the cleaning record to the cloud server, and receiving a data extraction instruction returned by the cloud server; Send the target instruction data to the cloud server.

8. The method according to any one of claims 1 to 7, characterized in that In the case where the target instruction data includes a plurality of instruction data, the receiving the data extraction instruction returned by the cloud server includes: Receiving multiple extraction instructions sequentially returned by the cloud server, wherein the data extraction instruction includes the multiple extraction instructions, and wherein the sending order of the multiple extraction instructions is determined based on the type and trigger time of the trigger instruction included in the multiple instruction data; The sending the target instruction data to the cloud server includes: sending the plurality of instruction data to the cloud server in sequence.

9. The method according to any one of claims 1 to 8, characterized in that The target instruction data is identified by the cloud server to obtain an identification result, and the target instruction data is marked based on the identification result, wherein the identification result includes at least one of the following information: the reason why the carrier is in a parking state, the reason why a preset fault occurs in the carrier, and the event information of a preset event occurring in the carrier.

10. The method according to any one of claims 1 to 9, characterized in that In the case where the type of any trigger instruction is cloud trigger, the any trigger instruction is sent by the cloud server and forwarded to the data acquisition device through the carrier.

11. A device for processing vehicle data, characterized in that: include: An acquisition module, configured to acquire first data collected by a data acquisition device installed on a vehicle in response to the data acquisition device receiving at least one trigger instruction; a cleaning module, configured to clean the first data and the second data based on the at least one trigger instruction to obtain target instruction data corresponding to the at least one trigger instruction, wherein the second data is used to represent the data collected by the data collection device before receiving the at least one trigger instruction; The sending module is used to send the target instruction data to the cloud server.

12. A system for processing vehicle data, characterized in that: include: A data collection device, installed on the vehicle, for collecting data of the vehicle and forwarding at least one trigger instruction; A processing device is connected to the data acquisition device and the cloud server, and is used to make a data request for the first data and the second data sent by the data acquisition device based on the at least one trigger instruction received, obtain the target instruction data corresponding to the at least one trigger instruction, and send the target instruction data to the cloud server, wherein the second data is used to represent the data sent by the data acquisition device before receiving the at least one trigger instruction.

13. The system according to claim 12, characterized in that The cloud server is also used to identify the target instruction data to obtain an identification result, and mark the target instruction data based on the identification result, wherein the identification result includes at least one of the following information: the reason why the carrier is in a parking state, the reason why a preset fault occurs in the carrier, and event information of a preset event occurring in the carrier.

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