Vehicle-cloud integrated data acquisition and uploading method and device, electronic equipment and medium

Abstract

The embodiment of the invention provides a vehicle-cloud integrated data collection and uploading method and device, electronic equipment and a storage medium, and the method comprises the steps: enabling a vehicle to collect the specific abnormal behavior data of road traffic participants according to a preset rule; the vehicle uploads the collected abnormal behavior data to a cloud end, and the cloud end carries out analysis and structured analysis processing on the abnormal behavior data; and obtaining the data processed by the cloud, and uploading the processed data to a management platform according to a standard format. According to the scheme, the repeated uploading of the data can be reduced, the risk of missing data transmission is reduced, the accuracy of the data and the uploading efficiency of the data are improved, and the access load of the management platform cloud can be greatly reduced.

Description

Technical Field

[0001] This invention relates to the field of road traffic data collection, and in particular to a vehicle-cloud integrated data collection and uploading method, device, electronic device, and storage medium. Background Technology

[0002] Existing intelligent connected vehicles can identify various data about road users (other vehicles, roadside facilities, pedestrians, etc.) through their onboard sensors (connected sensors, vision sensors, etc.) during operation. Uploading this data to the intelligent connected vehicle management platform is a necessary function for high-level intelligent connected vehicles.

[0003] Currently, intelligent connected vehicles report data directly to the management platform from the vehicle itself, without any data identification, aggregation, or analysis process. This leads to issues such as duplicate data reporting, as well as errors and omissions. Furthermore, in the foreseeable future, the direct reporting of large amounts of data to the management platform will inevitably overload the platform. Summary of the Invention

[0004] In view of this, the vehicle-cloud integrated data collection and uploading method, device, electronic equipment and storage medium provided in this application can reduce the repeated uploading of data, reduce the risk of data loss, thereby improving the accuracy of data and the efficiency of data uploading, and can also significantly reduce the access load of the management platform cloud.

[0005] According to a first aspect of the embodiments of this application, a vehicle-cloud integrated data collection and uploading method is provided. The method includes: a vehicle collecting specific abnormal behavior data of road traffic participants according to preset rules; the vehicle uploading the collected abnormal behavior data to the cloud, allowing the cloud to analyze and perform structured parsing processing on the abnormal behavior data; obtaining the data processed by the cloud, and uploading the processed data to a management platform in a standard format through the cloud.

[0006] In one implementation, the method includes: the vehicle determining whether it has received a collection task from the cloud; if it has not received it, the preset rule is basic abnormal behavior data, that is, the vehicle collects basic abnormal behavior data of road traffic participants; if it has received it, the preset rule is a collection task, that is, the vehicle collects abnormal behavior data according to the collection task, and in addition to collecting basic abnormal behavior data of road traffic participants, it also collects other custom abnormal behavior data according to the collection task.

[0007] In another implementation, the vehicle uploads the collected abnormal behavior data to the cloud, including: the vehicle directly uploads the abnormal behavior data to the cloud according to the standard format specified by the management platform; or, the vehicle distinguishes the abnormal behavior data, and if it is the basic abnormal behavior data, it uploads it to the cloud according to the standard format specified by the management platform, and if it is the custom abnormal behavior data, it expands it according to the above standard format, fills in the custom abnormal behavior data and related parameter information, and then uploads it to the cloud.

[0008] In another implementation, the cloud-based analysis and structured parsing of the abnormal behavior data includes: classifying the abnormal behavior data into static, semi-static, and dynamic data, setting a storage duration for different categories of abnormal behavior data, and merging similar abnormal behavior data within the storage duration according to parameters such as the location and type of occurrence.

[0009] In another implementation, uploading the processed data to the management platform via the cloud in a standard format includes: instructing the cloud to upload only one piece of data for the same type of abnormal behavior of the same subject to the management platform within the default data sending frequency, in accordance with the standard format specified by the management platform; or, classifying and summarizing the production time interval, observer location area, etc. of the same type of abnormal behavior and uploading it to the management platform.

[0010] In another implementation, the method further includes: enabling the cloud to quickly identify vehicles with abnormal behavior based on the abnormal behavior data analysis results, and correcting the abnormal behavior of the vehicles.

[0011] According to a second aspect of the embodiments of this application, a vehicle-cloud integrated data acquisition and uploading device is provided, comprising:

[0012] The perception module is used to identify the behavioral data of road traffic participants through its own onboard sensors;

[0013] The abnormal event identification module is used to collect specific abnormal behavior data of road traffic participants according to preset rules;

[0014] The cloud communication module is used to upload the collected abnormal behavior data to the cloud, so that the cloud can analyze and perform structured parsing on the abnormal behavior data, and upload the processed data to the management platform in a standard format.

[0015] According to a third aspect of the present application, an electronic device is provided, including: a processor, a memory, a communication interface, and a bus, wherein the processor, the communication interface, and the memory communicate with each other via the bus; the memory is used to store at least one executable instruction, which causes the processor to perform an operation corresponding to the method described in the first aspect above.

[0016] According to a fourth aspect of the embodiments of this application, a computer-readable storage medium is provided, wherein computer instructions are stored on the computer-readable storage medium, and when executed by a processor, the computer instructions cause the processor to perform the method described in the second aspect above.

[0017] As shown in the above technical solution, the vehicle uploads the collected abnormal behavior data to the cloud, processes it in the cloud, and then uploads it to the management platform. This not only reduces duplicate data uploads and lowers the risk of data loss, thereby improving data accuracy and upload efficiency, but also significantly reduces the access load on the management platform cloud. Furthermore, this method facilitates the cloud's rapid identification and correction of abnormal behavior in vehicles of its own brand, improving the efficiency of resolving issues with its own brand vehicles. Attached Figure Description

[0018] Figure 1 This is a flowchart of a vehicle-cloud integrated data collection and uploading method according to an embodiment of this application;

[0019] Figure 2 This is a framework diagram of a vehicle-cloud integrated data acquisition and uploading device according to an embodiment of this application;

[0020] Figure 3 This is a schematic diagram illustrating an application scenario of a vehicle-cloud integrated data collection and uploading method according to an embodiment of this application;

[0021] Figure 4 This is a schematic diagram of an electronic device provided in one embodiment of this application. Detailed Implementation

[0022] To provide a clearer understanding of the technical features, objectives, and effects of the embodiments of the present invention, specific implementation methods of the embodiments of the present invention will now be described with reference to the accompanying drawings.

[0023] In this document, “illustrative” means “serving as an example, illustration or description”, and any illustration or implementation described herein as “illustrative” should not be construed as a more preferred or advantageous technical solution.

[0024] To enable those skilled in the art to better understand the technical solutions in the embodiments of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art should fall within the protection scope of the present invention.

[0025] The specific implementation of the embodiments of the present invention will be further described below with reference to the accompanying drawings.

[0026] Figure 1 This is a flowchart illustrating a vehicle-cloud integrated data collection and uploading method according to an embodiment of the present invention.

[0027] like Figure 1 As shown, the data collection and uploading method for vehicle-cloud integration includes the following steps:

[0028] In step S110, the vehicle collects specific abnormal behavior data of road traffic participants according to preset rules.

[0029] Specifically, during the driving process, the vehicle uses its own onboard sensors to identify and collect abnormal behavior data of road traffic participants; among which, the sensors can be network sensors, vision sensors, or various types of sensors installed / carried by the vehicle, and are not limited in this invention; road traffic participants can be other vehicles on the road, relevant roadside facilities, and pedestrians, etc.

[0030] Specifically, before step S110, the following may also be included:

[0031] Step S100: The vehicle determines whether it has received the data collection task sent from the cloud.

[0032] If no data collection task is received from the cloud, the preset rule in step S110 refers to the basic abnormal behavior data in the default state, and collecting specific abnormal behavior data of road traffic participants refers to collecting the basic abnormal behavior data of road traffic participants.

[0033] If a data collection task has been received from the cloud, the preset rule in step S110 refers to the data collection task sent from the cloud. Collecting specific abnormal behavior data of road traffic participants means that in addition to collecting basic abnormal behavior data of road traffic participants, other custom abnormal behavior data are also collected according to the requirements of the data collection task.

[0034] Specifically, the basic abnormal behavior data in the default state is mainly related to BSM (Basic Safety Message). For example, it can be divided into two categories: the first category is data with unreasonable values ​​of certain fields in the BSM, and the second category is data in the BSM that is inconsistent with the content of previous messages of the same type. For example, it includes abnormal sending interval, abnormal static fields, abnormal security layer data, abnormal position, abnormal speed, abnormal acceleration, etc.

[0035] Specifically, if the cloud sends a data collection task to the vehicle, the vehicle, in addition to collecting basic abnormal behavior data, also needs to collect customized abnormal behavior data according to the requirements of the task. Therefore, the data collection task sent from the cloud to the vehicle may include, but is not limited to, the following list of abnormal behavior data:

[0036] (1) The MAP (map), SPAT (traffic light information), RSI (road information), and RSM (road traffic participant information) message fields sent by the roadside equipment are unreasonable;

[0037] (2) The MAP message sent by the roadside equipment is inconsistent with the current road status collected or obtained by the vehicle.

[0038] (3) The SPAT, RSI, and RSM messages sent by the roadside equipment differ significantly from the key target data (such as location, type, countdown, etc.) identified by the sensing equipment (such as cameras, millimeter-wave radar, lidar, etc.);

[0039] (4) The key data (such as location, type, countdown, etc.) of the RSM messages sent by the roadside equipment and the BSM messages sent by the opposing vehicle are quite different;

[0040] (5) The PSM (Pedestrian Safety Message) fields sent by portable devices are unreasonable;

[0041] (6) The PSM (pedestrian safety message) sent by the portable device differs significantly from the key target data (such as location, type, countdown, etc.) identified by the sensing device (such as camera, millimeter-wave radar, lidar, etc.);

[0042] (7) The vehicle captures messages from the same competitor for an extended period of time, and from a temporal perspective, the message fields are unreasonable. Specifically, this may include, but is not limited to:

[0043] a) The historical trajectory information carried in the BSM messages sent by the vehicle is inconsistent with the actual trajectory information;

[0044] b) The rules for changing vehicle IDs and certificates do not meet the standards;

[0045] c) The countdown timers on the roadside traffic lights have unreasonable jumps;

[0046] d) Expired road information is displayed on the roadside for an extended period of time;

[0047] e) The historical trajectory information carried by the RSM messages sent from the roadside differs significantly from the actual trajectory information.

[0048] Specifically, a private data format can be set between the cloud and the vehicle to assign numbers to the aforementioned abnormal behavior data and issue collection tasks based on these numbers.

[0049] In step S120, the vehicle uploads the collected abnormal behavior data to the cloud.

[0050] Specifically, vehicles can upload the collected abnormal behavior data to the cloud in the standard format specified by the management platform; for example, uploading it to the cloud using the V2XSecMbr structure specified in the relevant standards of the management platform, as shown in the following figure:

[0051]

[0052] Specifically, when vehicles upload collected abnormal behavior data to the cloud, they can also distinguish between different types of abnormal behavior data.

[0053] If it is basic abnormal behavior data, it should still be uploaded to the cloud in the standard format specified by the management platform, such as uploading it to the cloud in the format of V2XSecMbr structure.

[0054] If it is custom abnormal behavior data, you can expand it according to the above standard format, fill in the custom abnormal behavior data and related parameter information and then upload it to the cloud;

[0055] Specifically, on the one hand, one can refer to the V2XSecMbr structure and make corresponding extensions. On the basis of having the same external structure as the V2XSecMbr structure, the report field of V2XMbrData can be filled with custom abnormal behavior data. On the other hand, one can directly fill the report field of V2XMbrData with custom abnormal behavior data and upload it to the cloud, carrying information such as generation time and observer location. Furthermore, flexible encoding methods (such as json, xml, protobuf, asn.1, etc.) can be used to achieve vehicle-to-cloud data reporting.

[0056] In this embodiment, while collecting basic abnormal behavior data to meet the data reporting requirements to the management platform, custom abnormal behavior data can also be collected, which facilitates the rapid identification of vehicles with abnormal behavior in the cloud and the correction of corresponding problems, thereby improving the efficiency of vehicle problem correction.

[0057] Step S130: The cloud performs analysis and structured parsing processing on the abnormal behavior data.

[0058] Specifically, enabling the cloud to analyze and perform structured parsing of abnormal behavior data means that the cloud classifies abnormal behavior data into static, semi-static, and dynamic data, sets the storage duration for different categories of abnormal behavior data, and merges data of the same type of abnormal behavior within the storage duration according to parameters such as the location and type of occurrence.

[0059] Furthermore, including:

[0060] (1) For static and semi-static data (MAP, SPAT, RSI), the received abnormal behavior data is stored for a specific duration, such as 24 hours, but the specific duration can be customized. When new abnormal behavior data is received within this specific duration, it is compared with the identified abnormal behavior data. If the location and type are the same, the abnormal behavior data is merged and the existence time of the abnormal behavior is updated.

[0061] (2) For dynamic data (BSM, RSM, PSM), the received abnormal behavior data is stored for a specific duration, such as 1 hour. Similarly, this specific duration can also be customized. In general, dynamic data is updated more frequently, so its single storage duration is shorter than that of static or semi-static data. Similarly, when a new abnormal behavior is received within this specific duration, it is compared with the identified abnormal behavior. If the location and type are the same, the abnormal behavior data is merged and the existence time of the abnormal behavior is updated.

[0062] Specifically, when the cloud identifies the same abnormal behavior entities but differ in type, location, and time, they can be grouped and recorded for processing.

[0063] Step S140: Obtain the processed data from the cloud and upload the processed data to the management platform in a standard format via the cloud.

[0064] Specifically, the cloud can set a default data sending frequency with the management platform, such as once per minute, meaning that the cloud uploads abnormal behavior data to the management platform once every minute in a standard format.

[0065] Specifically, the cloud can be configured to not analyze or process abnormal behavior data reported by vehicles within a certain number of data transmission frequencies within the default frequency. Instead, the cloud will directly upload the received abnormal behavior data to the management platform. For example, the specified number of data points could be 10. That is, if the cloud receives fewer than 10 V2XSecMbr standard format data reports from vehicles within one minute, it will not perform data analysis or processing and will directly upload the received V2XSecMbr standard format data to the management platform.

[0066] Furthermore, the processed data is uploaded to the management platform via the cloud in a standard format. Specifically, the cloud uploads only one piece of data for the same type of abnormal behavior from the same subject to the management platform, within the default data sending frequency, according to the standard format specified by the management platform; or, it categorizes and summarizes the production time interval, observer location area, etc., of the same type of abnormal behavior and uploads it to the management platform. Details may include:

[0067] (1) Using V2XSecMbr standard format fields, all abnormal behavior data within the default data sending frequency (e.g., 1 minute) are deduplicated and categorized, and only one data record of the same type of abnormal behavior of the same subject is uploaded to the management platform;

[0068] (2) Expand the V2XMbrData report to include fields such as generationTime and observationLocation. Specifically, the cloud expands the original single fields, categorizes and summarizes the generationInterval and observationRegion for the same type of abnormal behavior, and uploads them to the management platform; Specifically:

[0069] a) generationInterval is an array of 2 elements, containing 2 Time32 fields, representing the start and end times of the production time;

[0070] b) The observationRegion field consists of two fields: center point and radius, representing the center and radius of the circle covering the observer's location area.

[0071] In this embodiment, by classifying and categorizing abnormal behavior data before uploading it to the management platform, we can reduce duplicate data uploads and lower the risk of data mistransmission or omission, thereby improving data accuracy and upload efficiency. More importantly, this also significantly reduces the amount of data uploaded to the management platform, thereby reducing the access load on the management platform and easing its burden.

[0072] The vehicle-cloud integrated data collection and uploading method in this embodiment may further include:

[0073] Step S150: The cloud platform quickly identifies vehicles with abnormal behavior based on the abnormal behavior data analysis results and corrects the abnormal behavior of the vehicles.

[0074] Specifically, when the abnormal behavior data received by the cloud is related to its own brand vehicles, the abnormal vehicle's ID number can be used as an index to record information such as the time, location, and type of the abnormal behavior, ultimately enabling quick identification of the abnormal vehicle and correction of the corresponding issues.

[0075] Specifically, the system can determine whether a vehicle is a proprietary brand vehicle by comparing the uploaded data with information such as the vehicle's size, color, type, and brand ID number.

[0076] In conclusion, this invention provides a vehicle-cloud integrated data collection and uploading method. Vehicles upload collected abnormal behavior data to the cloud, which then processes the data before uploading it to the management platform. This not only reduces duplicate data uploads and lowers the risk of data loss, thereby improving data accuracy and upload efficiency, but also significantly reduces the access load on the management platform cloud. Furthermore, this method facilitates the cloud's rapid identification and correction of abnormal behavior in vehicles of its own brand, improving the efficiency of resolving issues with these vehicles.

[0077] Figure 2 To describe another embodiment of the vehicle-cloud integrated data acquisition and uploading device of this application, such as Figure 2 As shown, vehicle 201 also includes a perception module 2011, an abnormal event recognition module 2012 and a cloud communication module 2013. Cloud 202 may also include a task distribution module 2021, a data collection module 2022, a data analysis and processing module 2023, an abnormal data upload module 2024 and an abnormal data recording module 2025.

[0078] There can be multiple vehicles, specifically...

[0079] The perception module 2011 is used to identify the behavioral data of road traffic participants through its own onboard sensors;

[0080] The sensors can be network sensors, vision sensors, or various sensors installed / carried in vehicles, and are not limited in this invention.

[0081] The abnormal event identification module 2012 is used to collect specific abnormal behavior data of road traffic participants according to preset rules;

[0082] Among them, road traffic participants can be other vehicles on the road, related facilities on the roadside, and pedestrians.

[0083] After the perception module 2011 identifies the behavioral data of road traffic participants, the abnormal event identification module 2012 identifies and collects specific abnormal behavioral data of road traffic participants according to preset rules.

[0084] The cloud communication module 2013 is used to upload the collected abnormal behavior data to the cloud, so that the cloud can analyze and perform structured parsing on the abnormal behavior data, and upload the processed data to the management platform in a standard format.

[0085] Specifically, the cloud communication module 2013 can also be used to receive data collection tasks sent from the cloud;

[0086] If the cloud communication module 2013 does not receive the collection task sent from the cloud, the abnormal event identification module 2012 is mainly used to collect basic abnormal behavior data under the default state according to preset rules, mainly data related to BSM (Basic Safety Message). For example, it can be divided into two categories: the first category is data with unreasonable values ​​of certain fields in BSM, and the second category is data in BSM that is inconsistent with the content of previous messages of the same type, such as abnormal sending interval, abnormal static fields, abnormal security layer data, abnormal position, abnormal speed, abnormal acceleration, etc.

[0087] When the cloud communication module 2013 receives a collection task from the cloud, the abnormal event identification module 2012 is used to collect specific abnormal behavior data according to the collection task based on preset rules. That is, in addition to collecting basic abnormal behavior data, it is also necessary to collect other custom abnormal behavior data according to the requirements of the collection task. The detailed list of custom abnormal behavior data has been described in the previous embodiment and will not be repeated here.

[0088] Specifically, the cloud communication module 2013 is used to upload the collected abnormal behavior data to the cloud, including:

[0089] The cloud communication module 2013 uploads the collected abnormal behavior data to the cloud according to the standard format specified by the management platform; for example, it uploads the data to the cloud according to the V2XSecMbr structure format specified in the relevant standards of the management platform; or...

[0090] It can also distinguish abnormal behavior data; if it is basic abnormal behavior data, it should still be uploaded to the cloud in the standard format specified by the management platform, such as uploading to the cloud in the format V2XSecMbr structure; if it is custom abnormal behavior data, it can be expanded in the above standard format, and then uploaded to the cloud after filling in the custom abnormal behavior data and related parameter information.

[0091] Specifically, on the one hand, one can refer to the V2XSecMbr structure and make corresponding extensions. On the basis of having the same external structure as the V2XSecMbr structure, the report field of V2XMbrData can be filled with custom abnormal behavior data. On the other hand, one can directly fill the report field of V2XMbrData with custom abnormal behavior data and upload it to the cloud, carrying information such as generation time and observer location. Furthermore, flexible encoding methods (such as json, xml, protobuf, asn.1, etc.) can be used to achieve vehicle-to-cloud data reporting.

[0092] Specifically, in cloud 202,

[0093] The task distribution module 2021 is used to distribute data collection tasks to vehicles. Specifically, the data collection tasks may include custom abnormal behavior data. The detailed data list has been described in the previous embodiment and will not be repeated here.

[0094] The data collection module 2022 is used to collect abnormal behavior data uploaded by vehicles;

[0095] The Data Analysis and Processing Module 2023 is used to analyze and perform structured parsing processing on the abnormal behavior data collected by the Data Collection Module.

[0096] Specifically, cloud-based analysis and structured parsing of abnormal behavior data refers to the following: the cloud classifies abnormal behavior data into static, semi-static, and dynamic data; sets storage durations for different categories of abnormal behavior data; and within the storage duration, merges data of the same type of abnormal behavior based on parameters such as location and type. Details may include:

[0097] (1) For static and semi-static data (MAP, SPAT, RSI), the received abnormal behavior data is stored for a specific duration, such as 24 hours, but the specific duration can be customized. When new abnormal behavior data is received within this specific duration, it is compared with the identified abnormal behavior data. If the location and type are the same, the abnormal behavior data is merged and the existence time of the abnormal behavior is updated.

[0098] (2) For dynamic data (BSM, RSM, PSM), the received abnormal behavior data is stored for a specific duration, such as 1 hour. Similarly, this specific duration can also be customized. In general, dynamic data is updated more frequently, so its single storage duration is shorter than that of static or semi-static data. Similarly, when a new abnormal behavior is received within this specific duration, it is compared with the identified abnormal behavior. If the location and type are the same, the abnormal behavior data is merged and the existence time of the abnormal behavior is updated.

[0099] Specifically, when the cloud identifies the same abnormal behavior entities but differ in type, location, and time, they can be grouped and recorded for processing.

[0100] The abnormal data upload module 2024 is used to upload the data processed by the data analysis and processing module to the management platform in a standard format;

[0101] Specifically, the abnormal data upload module 2024 uploads abnormal behavior data to the management platform according to a standard format. Specifically, the cloud platform uploads only one piece of data for the same type of abnormal behavior from the same subject to the management platform, within the default data sending frequency, according to the standard format specified by the management platform; or, it categorizes and summarizes the production time interval, observer location area, etc., of the same type of abnormal behavior and uploads it to the management platform. Details may include:

[0102] (1) Using V2XSecMbr standard format fields, all abnormal behavior data within the default data sending frequency (e.g., 1 minute) are deduplicated and categorized, and only one data record of the same type of abnormal behavior of the same subject is uploaded to the management platform;

[0103] (2) Expand the V2XMbrData report to include fields such as generationTime and observationLocation. Specifically, the cloud expands the original single fields, categorizes and summarizes the generationInterval and observationRegion for the same type of abnormal behavior, and uploads them to the management platform; Specifically:

[0104] a) generationInterval is an array of 2 elements, containing 2 Time32 fields, representing the start and end times of the production time;

[0105] b) The observationRegion field consists of two fields: center point and radius, representing the center and radius of the circle covering the observer's location area.

[0106] Specifically, the cloud can set a default data sending frequency with the management platform, such as once per minute, meaning that the cloud uploads abnormal behavior data to the management platform once every minute in a standard format.

[0107] Specifically, the cloud can be configured to not analyze or process abnormal behavior data reported by vehicles within a certain number of data transmission frequencies within the default frequency. Instead, the cloud will directly upload the received abnormal behavior data to the management platform. For example, the specified number of data points could be 10. That is, if the cloud receives fewer than 10 V2XSecMbr standard format data reports from vehicles within one minute, it will not perform data analysis or processing and will directly upload the received V2XSecMbr standard format data to the management platform.

[0108] The Abnormal Data Recording Module 2025 is used to quickly identify vehicles with abnormal behavior based on the abnormal behavior data analysis results of the Data Analysis and Processing Module, and to record and correct them.

[0109] Specifically, when the abnormal behavior data received by the cloud is related to its own brand vehicles, the abnormal vehicle's ID number can be used as an index to record information such as the time, location, and type of the abnormal behavior, ultimately enabling quick identification of the abnormal vehicle and correction of the corresponding issues.

[0110] In conclusion, the present invention provides a vehicle-cloud integrated data collection and uploading device. Vehicles upload collected abnormal behavior data to the cloud, which then processes the data before uploading it to the management platform. This not only reduces duplicate data uploads and lowers the risk of data loss, thereby improving data accuracy and upload efficiency, but also significantly reduces the access load on the management platform cloud. Furthermore, this method facilitates the cloud's rapid identification and correction of abnormal behavior in vehicles of its own brand, improving the efficiency of resolving issues with these vehicles.

[0111] According to another embodiment of the present invention, an application scenario for a vehicle-cloud integrated data collection and uploading method is provided, see [link to relevant documentation]. Figure 3 The system includes vehicles 301 and cloud 302. There can be multiple vehicles 301. Vehicles 301 collect specific abnormal behavior data of road traffic participants according to preset rules. Vehicles 301 upload the collected abnormal behavior data to cloud 302. Cloud 302 analyzes and performs structured parsing on the abnormal behavior data. The system obtains the processed data from cloud 302 and uploads the processed data to the management platform in a standard format through cloud 302.

[0112] Specifically, if the vehicle does not receive the data collection task sent from the cloud, the specific abnormal behavior data collected refers to basic abnormal behavior data, mainly data related to BSM (Basic Safety Message). For example, it can be divided into two categories: the first category is data with unreasonable values ​​of certain fields in the BSM, and the second category is data in the BSM that is inconsistent with the content of previous messages of the same type, such as abnormal sending interval, abnormal static fields, abnormal safety layer data, abnormal position, abnormal speed, abnormal acceleration, etc.

[0113] If the vehicle has received the data collection task from the cloud, the specific abnormal behavior data refers to the collection of other custom abnormal behavior data as required by the task, in addition to the basic abnormal behavior data of road traffic participants. Detailed explanations of the custom abnormal behavior data have been provided in the vehicle-cloud integrated data collection and uploading process and will not be repeated here.

[0114] Specifically, this also includes enabling the rapid identification of vehicles exhibiting abnormal behavior based on the analysis results of abnormal behavior data, and correcting the abnormal behavior of these vehicles.

[0115] Specifically, when the abnormal behavior data received by the cloud is related to its own brand vehicles, the abnormal vehicle's ID number can be used as an index to record information such as the time, location, and type of the abnormal behavior, ultimately enabling quick identification of the abnormal vehicle and correction of the corresponding issues.

[0116] In conclusion, this invention provides an application scenario for a vehicle-cloud integrated data collection and uploading method. Vehicles upload collected abnormal behavior data to the cloud, which then processes the data and uploads it to the management platform. This not only reduces duplicate data uploads and lowers the risk of data loss, thereby improving data accuracy and upload efficiency, but also significantly reduces the access load on the management platform cloud. Furthermore, this method facilitates the cloud's rapid identification and correction of abnormal behavior in vehicles of its own brand, improving the efficiency of resolving issues with these vehicles.

[0117] The method in this embodiment is used to implement the corresponding content in the foregoing multiple embodiments and has the beneficial effects of the corresponding method embodiments, which will not be repeated here.

[0118] According to another embodiment of the present invention, an electronic device 400 is provided, see [link to previous document]. Figure 4The present invention will now be described in the form of a structural block diagram of an electronic device 400 that can serve as a server or client of the present invention, which is an example of a hardware device that can be applied to various aspects of the present invention. The electronic device is intended to represent various forms of digital electronic computer devices, such as laptop computers, desktop computers, workstations, user digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile systems, such as user digital processing, cellular phones, smartphones, wearable devices, and other similar computing systems. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0119] The electronic device 400 includes: a processor 402, a communications interface 404, a memory 406, and a bus 408. Among them:

[0120] The processor 402, communication interface 404, and memory 406 communicate with each other via bus 408.

[0121] Communication interface 404 is used to communicate with other electronic devices or servers.

[0122] The processor 402 is used to execute program 410, specifically to execute the relevant steps in the above-described embodiment of the control method for the radio frequency read / write device.

[0123] Specifically, program 410 may include program code that includes computer operation instructions.

[0124] Processor 402 may be a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of this application. The smart device includes one or more processors, which may be processors of the same type, such as one or more CPUs; or processors of different types, such as one or more CPUs and one or more ASICs.

[0125] Memory 406 is used to store program 410. Memory 406 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk storage device.

[0126] Specifically, program 410 can be used to enable processor 402 to perform the following operations: the vehicle collects specific abnormal behavior data of road traffic participants according to preset rules; the vehicle uploads the collected abnormal behavior data to the cloud, the cloud analyzes and performs structured parsing processing on the abnormal behavior data; and the cloud uploads the processed data to the management platform in a standard format.

[0127] The specific implementation of each step in program 410 can be found in the corresponding descriptions of the steps and units in the above embodiments, and will not be repeated here. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process of the devices and modules described above can be referred to the corresponding process descriptions in the foregoing method embodiments, and will not be repeated here.

[0128] Through the electronic device in this embodiment, the vehicle uploads the collected abnormal behavior data to the cloud. After processing in the cloud, the data is then uploaded to the management platform. This not only reduces duplicate data uploads and lowers the risk of data loss, thereby improving data accuracy and upload efficiency, but also significantly reduces the access load on the management platform cloud. Furthermore, this method facilitates the cloud's rapid identification and correction of abnormal behavior in vehicles of its own brand, improving the efficiency of resolving issues with its own brand vehicles.

[0129] This application also provides a computer-readable storage medium storing instructions for causing a machine to perform a control method for a radio frequency read / write device as described herein. Specifically, a system or apparatus equipped with a storage medium storing software program code that implements the functions of any of the embodiments described above, and enabling the computer (or CPU or MPU) of the system or apparatus to read and execute the program code stored in the storage medium.

[0130] In this case, the program code read from the storage medium can itself implement the function of any of the above embodiments, and therefore the program code and the storage medium storing the program code constitute part of this application.

[0131] Examples of storage media used to provide program code include floppy disks, hard disks, magneto-optical disks, optical disks (such as CD-ROM, CD-R, CD-RW, DVD-ROM, DVD-RAM, DVD-RW, DVD+RW), magnetic tapes, non-volatile memory cards, and ROMs. Alternatively, program code can be downloaded from a server computer via a communication network.

[0132] Furthermore, it should be clear that not only can the program code read by the computer be executed, but also the operating system or other components operating on the computer can be instructed based on the program code to perform some or all of the actual operations, thereby realizing the function of any of the embodiments described above.

[0133] Furthermore, it is understood that the program code read from the storage medium is written to the memory set in the expansion board inserted into the computer or to the memory set in the expansion module connected to the computer. Then, based on the instructions of the program code, the CPU or other components installed on the expansion board or expansion module execute some and all of the actual operations, thereby realizing the function of any of the above embodiments.

[0134] The present application has been shown and described in detail above with reference to the accompanying drawings and preferred embodiments. However, the present application is not limited to these disclosed embodiments. Based on the above multiple embodiments, those skilled in the art will know that more embodiments of the present application can be obtained by combining the code review methods in the different embodiments above. These embodiments are also within the protection scope of the present application.

Claims

1. A vehicle-cloud integrated data collection uploading method, characterized in that, The method comprises: The vehicle collects specific abnormal behavior data of road traffic participants according to preset rules; The vehicle uploads the collected abnormal behavior data to the cloud, and the cloud analyzes and structurally analyzes the abnormal behavior data; The processed data obtained by the cloud is uploaded to the management platform in a standard format through the cloud.

2. The method of claim 1, wherein, The method comprises: The vehicle determines whether to receive a collection task issued by the cloud; If not, the preset rule is basic abnormal behavior data, that is, the vehicle collects basic abnormal behavior data of road traffic participants; if yes, the preset rule is a collection task, that is, the vehicle collects abnormal behavior data according to the collection task, in addition to collecting basic abnormal behavior data of road traffic participants, it also collects other self-defined abnormal behavior data according to the collection task.

3. The method of claim 1, wherein, The vehicle uploads the collected abnormal behavior data to the cloud, comprising: The vehicle uploads the abnormal behavior data directly to the cloud according to the standard format specified by the management platform; or the vehicle distinguishes the abnormal behavior data, if it is the basic abnormal behavior data, it is uploaded to the cloud according to the standard format specified by the management platform, if it is the self-defined abnormal behavior data, it is extended according to the above standard format, and the self-defined abnormal behavior data and related parameter information are filled in and uploaded to the cloud.

4. The method of claim 1, wherein, The cloud analyzes and structurally analyzes the abnormal behavior data, comprising: The cloud classifies the abnormal behavior data into static, semi-static and dynamic data, sets the storage time length of different classified abnormal behavior data, and merges the same kind of abnormal behavior data according to the parameters such as the location and type within the storage time length.

5. The method of claim 1, wherein, The cloud uploads the processed data to the management platform in a standard format, comprising: The cloud uploads only one data of the same kind of abnormal behavior of the same subject to the management platform within the default data sending frequency according to the standard format specified by the management platform; or the cloud classifies and summarizes the production time interval and observer location area of the same kind of abnormal behavior, and uploads to the management platform.

6. The method of claim 1, wherein, The method further comprises: The cloud quickly identifies abnormal behavior vehicles according to the abnormal behavior data analysis results, and corrects the abnormal behavior of the vehicles.

7. A vehicle-cloud integrated data collection and uploading device, characterized in that, The method comprises: A perception module for identifying behavior data of road traffic participants through sensors carried by itself; An abnormal event identification module for collecting specific abnormal behavior data of road traffic participants according to preset rules; A cloud communication module for uploading the collected abnormal behavior data to the cloud, so that the cloud analyzes and structurally analyzes the abnormal behavior data, and uploads the processed data to the management platform in a standard format.

8. An electronic device comprising: A processor, a communication interface, a memory and a bus, the processor, the communication interface and the memory complete communication with each other through the bus; The memory is used to store at least one executable instruction, and the executable instruction makes the processor execute the operation corresponding to the method in any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The computer readable storage medium stores computer instructions for causing the processor to implement the method for controlling rollback of a scenario according to any one of claims 1-6 when executed.

Images