Intelligent vehicle data processing method, apparatus, device, and storage medium

Abstract

The application relates to an intelligent vehicle data processing method, device and equipment and a storage medium. The method comprises the following steps: determining a first parameter corresponding to vehicle information of a vehicle end according to the vehicle information of the vehicle end, and sending the first parameter to the vehicle end; receiving first data obtained by screening the first parameter by the vehicle end, and storing the first data in a data warehouse based on a preset form; determining a second parameter corresponding to business information of a vehicle according to the business information of the vehicle, calling the first data stored based on the preset form in the data warehouse, identifying a field corresponding to the second parameter in the first data stored based on the preset form, analyzing the field to obtain second data, and determining a processing result of the business information of the vehicle based on the second data. The application can save computing resources and storage resources.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of automobile control, in particular to an intelligent vehicle data processing method and device, equipment and a storage medium. BACKGROUND

[0002] With the rapid development of automobile intelligence and networking, the scale of data messages reported by vehicles has expanded dramatically, which poses a severe challenge to automobile manufacturers, especially large automobile manufacturers. The massive data generated by vehicles during operation, including but not limited to the use data of various intelligent driving functions such as intelligent cruise, NOA (Navigate on Autopilot, navigation assisted driving), CNO (City Navigation Guided Pilot, city navigation assisted driving), memory parking, AEB (Autonomous Emergency Braking, automatic emergency braking), automatic parking, etc. However, the sharp increase in these data not only increases the burden of storage and computing resources, but also makes it particularly complex and difficult to extract valuable information and perform efficient analysis from the massive data.

[0003] Although the existing solutions can process the data reported by vehicles to some extent, they generally have low resource utilization and insufficient data analysis depth. Traditional methods often fail to dynamically configure vehicle information according to vehicle differences, resulting in unnecessary data redundancy storage and invalid computation, increasing the system burden and causing waste of storage and computing resources. Therefore, there is an urgent need for a method to solve the above problems. SUMMARY

[0004] Based on this, the present application provides an intelligent vehicle data processing method, device, equipment and storage medium to solve the problems in the prior art.

[0005] In a first aspect, an intelligent vehicle data processing method is provided, comprising:

[0006] determining a first parameter corresponding to vehicle information of a vehicle end according to the vehicle information, and sending the first parameter to the vehicle end;

[0007] receiving first data obtained by filtering the first parameter by the vehicle end, and storing the first data in a data warehouse based on a preset form;

[0008] determining a second parameter corresponding to vehicle business information according to the business information, calling first data stored based on a preset form in the data warehouse, identifying a field corresponding to the second parameter in the first data stored based on a preset form, and obtaining second data by analyzing the field;

[0009] determine a processing result of vehicle service information based on the second data.

[0010] According to an implementable manner in embodiments of the present application, the receiving the first data obtained by the vehicle end according to the first parameter and storing the first data in the data warehouse based on a preset form comprises:

[0011] receiving the first data obtained by the vehicle end according to the first parameter through a message queue transmission protocol, and storing the first data in a message middleware;

[0012] The message middleware sends the first data to the data warehouse, and the data warehouse stores the first data based on a preset form.

[0013] According to an implementable manner in embodiments of the present application, the message middleware sends the first data to the data warehouse comprises:

[0014] The message middleware sends the first data to the data processing platform in batches based on a preset time interval;

[0015] The data processing platform receives the first data and eliminates abnormal data in the first data;

[0016] The data processing platform obtains vehicle information corresponding to the first data, binds the first data with the corresponding vehicle information to obtain first data of bound vehicle information;

[0017] The first data of bound vehicle information is sent to the data warehouse.

[0018] According to an implementable manner in embodiments of the present application, the storing the first data in the data warehouse based on a preset form comprises:

[0019] storing the first data in a first layer of the data warehouse based on a json form.

[0020] According to an implementable manner in embodiments of the present application, the determining a second parameter corresponding to the service information according to vehicle service information, calling first data stored based on a preset form in the data warehouse, identifying a field corresponding to the second parameter in the first data stored based on the preset form, and analyzing the field to obtain second data comprises:

[0021] obtaining vehicle service information and determining a second parameter corresponding to the service information;

[0022] According to a pre-written SQL statement, the first data stored in the form of json in the data warehouse is called, a field corresponding to the second parameter is identified in the first data, second data is obtained by parsing the field, and the second data is stored in a second layer of the data warehouse.

[0023] According to an implementable manner in the embodiment of the application, the processing result of the vehicle service information is determined based on the second data, and the processing result includes:

[0024] Based on the second data stored in the second layer of the data warehouse, an intermediate processing result of the vehicle service information is calculated, and the intermediate processing result is stored in a third layer of the data warehouse.

[0025] Based on the intermediate processing result stored in the third layer of the data warehouse, a final processing result of the vehicle service information is calculated, and the final processing result is stored in a fourth layer of the data warehouse.

[0026] The final processing result is sent to the vehicle end based on the fourth layer of the data warehouse.

[0027] According to an implementable manner in the embodiment of the application, the first parameter corresponding to the vehicle information is determined according to the vehicle information of the vehicle end, and the first parameter is sent to the vehicle end, and the first parameter includes:

[0028] The first parameter corresponding to the vehicle end is determined according to the vehicle model of the vehicle end, the first message is configured based on the first parameter, and the first message is sent to the vehicle end.

[0029] In a second aspect, an intelligent vehicle data processing method is provided, applied to a vehicle end, and the method includes:

[0030] A first parameter issued by a cloud end is received, wherein the first parameter is determined by the cloud end according to vehicle information of the vehicle end.

[0031] The first data corresponding to the first parameter is filtered based on the first parameter, and the first data is sent to the cloud end, wherein the cloud end is configured to store the first data in a data warehouse based on a preset form, determine a second parameter corresponding to vehicle service information according to the service information, call the first data stored in the form of the preset in the data warehouse, identify a field corresponding to the second parameter in the first data stored in the form of the preset, obtain second data by parsing the field, and determine a processing result of the vehicle service information based on the second data.

[0032] In a third aspect, a computer device is provided, including:

[0033] At least one processor; and

[0034] a memory connected with the at least one processor in communication; wherein,

[0035] The memory stores computer instructions executable by the at least one processor, and the computer instructions are executed by the at least one processor to enable the at least one processor to perform the method involved in the first aspect or the second aspect.

[0036] In a fourth aspect, a computer readable storage medium is provided, and the computer readable storage medium stores computer instructions, and the computer instructions are used to enable a computer to perform the method involved in the first aspect or the second aspect.

[0037] According to the technical content provided by the embodiments of the present application, the first data is filtered by the first parameter corresponding to the vehicle end information and stored in the data warehouse based on a preset form, which reduces the redundancy of data transmission and improves the efficiency of data processing. The data warehouse adopts an efficient data storage and retrieval mechanism, which can quickly respond to query requests and provide strong support for the processing of vehicle business information. The second parameter is determined according to the vehicle business information, and the field corresponding to the second parameter is called in the data warehouse, which can accurately obtain the required data and provide accurate data support for the processing of vehicle business information. This data utilization method improves the data processing speed, reduces the reporting of redundant messages, and saves computing resources and storage resources. BRIEF DESCRIPTION OF DRAWINGS

[0038] Figure 1 FIG. 1 is a flowchart of an intelligent vehicle data processing method cloud end in an embodiment;

[0039] Figure 2 FIG. 2 is a flowchart of an intelligent vehicle data processing method cloud end in an embodiment;

[0040] Figure 3 FIG. 3 is a flowchart of an intelligent vehicle data processing method vehicle end in an embodiment;

[0041] Figure 4 FIG. 4 is a flowchart of an intelligent vehicle data processing method vehicle end in an embodiment;

[0042] Figure 5 FIG. 5 is a schematic structural diagram of a computer device in an embodiment. DETAILED DESCRIPTION

[0043] The present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and not to limit the present application.

[0044] Figure 1A flowchart of an intelligent vehicle data processing method provided by an embodiment of the present application is shown in FIG. 1. The method is applied to a cloud end, and as shown in FIG. 1, the method can include the following steps: Figure 1

[0045] Step 101: determining a first parameter corresponding to vehicle information according to the vehicle information of a vehicle end, and sending the first parameter to the vehicle end.

[0046] Specifically, the first parameter corresponding to the vehicle end can be dynamically configured by a TSP (Telematics Service Provider, vehicle networking service provider) cloud end configuration center according to the vehicle information of the vehicle end, where the vehicle information can be vehicle model information or single vehicle information. The first parameter corresponding to the vehicle model or single vehicle information of the vehicle is configured in the cloud end according to the vehicle model information or single vehicle information of the vehicle, such as vehicle speed, average fuel quantity, mileage, power consumption, ICC (Intelligent Cruise Control), ACC (Adaptive Cruise Control), NOA (Navigate on Autopilot), CNOA (Conditional Navigate on Autopilot), HPA (Home-zone Parking Assist), RPA (Remote Parking Assist), APA (Automatic Parking Assist), AEB (Autonomous Emergency Braking), and the like, and the first parameter corresponding to the vehicle information of the vehicle end is sent to the vehicle end. Thus, the vehicle end can reduce the reporting of unnecessary field information and save computing resources and storage resources according to the first parameter for reporting data.

[0047] Step 102: receiving first data filtered by the vehicle end according to the first parameter, and storing the first data in a data warehouse based on a preset form.

[0048] Specifically, the vehicle end filters the first data to be reported according to the first parameter and reports the first data. The cloud end receives the first data filtered by the vehicle end according to the first parameter and stores the first data in a data warehouse based on a preset form. The preset form is a lightweight data exchange format, which occupies less storage space, making data transmission and storage more efficient. For example, the preset form can be json form, xml format, etc.

[0049] ​Step 103: determining a second parameter corresponding to the service information according to the vehicle service information, calling first data stored in a preset form in the data warehouse, identifying a field corresponding to the second parameter in the first data stored in the preset form, and parsing the field to obtain second data.

[0050] Specifically, the vehicle service information is service information of an intelligent vehicle, for example, automatic driving service. A second parameter corresponding to the service information is determined according to the vehicle service information, wherein the second parameter represents a parameter required for processing the service information. For example, the service information is automatic driving service, and the second parameter required for the automatic driving service includes parameters such as ACC, NOA, AEB, etc. Further, a field corresponding to the second parameter is identified in the first data stored in the preset form, wherein the original data generated according to the TSP configuration in the data warehouse based on the preset form is identified to obtain the second data, thereby saving storage and computing resources.

[0051] Step 104: determining a processing result of the vehicle service information based on the second data.

[0052] Specifically, based on the above steps, the processing result of the service information is calculated based on the second data in this step, for example, the intelligent driving usage of ACC, NOA, AEB, etc. is calculated based on the parameters such as ACC, NOA, AEB, etc., thereby obtaining the processing result of the vehicle end automatic driving service. Further, the mileage, time length, and number of times of APA, ACC, and NOA of each vehicle can be calculated as needed, which can reflect the safe driving of the vehicle, and the user can better release the hands, and the vehicle can take over the vehicle in danger, thereby ensuring the safety of driving and making the driving more relaxed and safe.

[0053] It can be seen that the embodiments of the application determine the first parameter corresponding to the vehicle information through the vehicle information of the vehicle end, and send the first parameter to the vehicle end; receive the first data obtained by the vehicle end according to the first parameter, and store the first data in the data warehouse based on the preset form; determine the second parameter corresponding to the business information according to the vehicle business information, call the first data stored based on the preset form in the data warehouse, identify the field corresponding to the second parameter in the first data stored based on the preset form, and parse the field to obtain the second data; determine the processing result of the vehicle business information based on the second data. The first data is filtered through the first parameter corresponding to the vehicle end information and stored in the data warehouse based on the preset form, which reduces the redundancy of data transmission and improves the efficiency of data processing. The data warehouse uses an efficient data storage and retrieval mechanism, which can quickly respond to query requests and provide strong support for the processing of vehicle business information. According to the vehicle business information, the second parameter is determined, and the field corresponding to the second parameter is called in the data warehouse, which can accurately obtain the required data and provide accurate data support for the processing of vehicle business information. This data utilization method improves the data processing speed, reduces the reporting of redundant messages, and saves computing resources and storage resources.

[0054] In an embodiment of the application, determining the first parameter corresponding to the vehicle information according to the vehicle information of the vehicle end and sending the first parameter to the vehicle end comprises: determining the first parameter corresponding to the vehicle end according to the vehicle type of the vehicle end, configuring a first message based on the first parameter, and sending the first message to the vehicle end.

[0055] Specifically, as shown in Figure 1 , and in combination with Figure 2 , the TSP cloud end can determine the first parameter corresponding to the vehicle end according to the vehicle type, configure the required first message based on the first parameter, and send the instruction for configuring the first message to the desktop head unit (DHU, intelligent vehicle-mounted system) through the interface. The desktop end receives the sent instruction, uploads the corresponding field according to the specified, obtains the data of the CAN bus in the DHU end, sends the frame number, APA, ACC, NOA, and reporting time to the FlexRay bus, and sends the data to the cloud end through the BGM gateway.

[0056] It can be seen that the TSP cloud end can determine the first parameter corresponding to the vehicle end according to the vehicle type, and the data transmission is no longer the same, but can be customized according to the needs of different vehicle types. This adaptability enhances the pertinence and effectiveness of data transmission, and can realize customized transmission.

[0057] In an embodiment of the present application, the receiving vehicle end receives the first data filtered according to the first parameter, and stores the first data in the data warehouse based on a preset form, including: receiving the first data filtered according to the first parameter by the vehicle end through the message queue transmission protocol, and storing the first data in the message middleware; the message middleware sends the first data to the data warehouse, and the data warehouse stores the first data based on a preset form.

[0058] Specifically, as shown in Figure 1 and in combination with Figure 2 , the vehicle end sends the first data filtered based on the first parameter to the message queue transmission protocol MQTT (Message Queuing Telemetry Transport) through the BGM gateway. The cloud end receives the first data through the message queue transmission protocol, and seamlessly connects the data in the MQTT to the message middleware TSP KAFKA through Kafka-connect-mqtt. The message middleware TSP KAFKA sends the first data to the data warehouse, and the data warehouse stores the first data based on a preset form.

[0059] In an embodiment of the present application, the message middleware sends the first data to the data warehouse, including: the message middleware sends the first data to the data processing platform in batches based on a preset time interval; the data processing platform receives the first data and eliminates abnormal data in the first data; the data processing platform obtains vehicle information corresponding to the first data, binds the first data with the corresponding vehicle information to obtain first data with bound vehicle information; and the first data with bound vehicle information is sent to the data warehouse.

[0060] Specifically, as shown in Figure 1 and in combination with Figure 2 , the message middleware TSP KAFKA collects logs as a high-performance message system, and provides the consumption end for consumption through the subscription mode. The data processing platform spark consumes TSP KAFKA in batches, for example, consuming TSP KAFKA once every 15 minutes. The data processing platform spark parses the reported signal messages in batches through offline jobs, and binds the vehicle series pushed by the MES at the same time, so that each message is bound with a vehicle series. The message bound with the vehicle series is stored in the data warehouse. The data processing platform spark also cleanses abnormal data, and eliminates abnormal data in the first data, such as eliminating abnormal latitude and longitude information, and filtering and removing data exceeding the normal latitude and longitude range according to the latitude and longitude range in China.

[0061] It can be seen that the embodiments of the present application are responsible for consuming the data reported by the vehicle from the Kafka message system through the data processing platform, performing abnormal data cleaning, binding vehicle information, storing the processed data into the data warehouse. The consumption of the data processing platform is executed once every preset time interval, ensuring the timeliness and accuracy of the data. In this way, the data processing platform plays a key role in data processing and analysis, supporting subsequent data warehouse hierarchical management, intelligent driving usage analysis and data visualization display processes.

[0062] In an embodiment of the present application, the first data is stored in the data warehouse based on a preset form, including: storing the first data in the data warehouse based on a json form.

[0063] Specifically, in order to save storage resources, the data warehouse stores the first data based on the json storage format. Json is a lightweight data exchange format, which occupies less storage space compared to other formats, making data transmission and storage more efficient. The first data is stored in the first layer of the data warehouse based on the json form. The first layer is the ods layer, and the ods layer in the data warehouse only stores the original data generated according to the TSP configuration in the json form.

[0064] In an embodiment of the present application, the second parameter corresponding to the business information is determined according to the vehicle business information, the first data stored in the data warehouse based on the preset form is called, the field corresponding to the second parameter is identified in the first data stored based on the preset form, the second data is obtained by parsing the field, including: obtaining the vehicle business information and determining the second parameter corresponding to the business information; calling the first data stored in the data warehouse based on the json form according to the pre-written SQL statement, identifying the field corresponding to the second parameter in the first data, obtaining the second data by parsing the field, and storing the second data in the second layer of the data warehouse.

[0065] Specifically, the first layer, i.e., the ods layer, in the data warehouse only stores original data generated according to the TSP configuration in the form of json. A second parameter corresponding to the business information is determined according to the business information, only the fields corresponding to the second parameter are parsed, and are put into the second layer, i.e., the dwd, of the data warehouse. In this embodiment, the data warehouse includes the first layer, i.e., the ods layer, and the second layer, i.e., the dwd layer. According to the second parameter, only the required fields are parsed from the original data in the form of json in the ods layer and are stored in the dwd layer, so as to reduce the data of the parsed fields and further reduce the storage space. The DolphinScheduler offline scheduling task can call the original json data of the data warehouse according to the written SQL (Structured Query Language), parse only the required fields, and avoid parsing all the fields, thereby avoiding waste of resources and improving the parsing efficiency.

[0066] In an embodiment of the present application, the processing result of the vehicle business information is determined based on the second data, including: based on the second data stored in the second layer of the data warehouse, calculating an intermediate processing result of the vehicle business information, storing the intermediate processing result in the third layer of the data warehouse; based on the intermediate processing result stored in the third layer of the data warehouse, calculating a final processing result of the vehicle business information, storing the final processing result in the fourth layer of the data warehouse; based on the fourth layer of the data warehouse, sending the final processing result to the vehicle end.

[0067] Specifically, based on the parsed second data stored in the second layer, i.e., the dwd, of the data warehouse, an intermediate processing result of the vehicle business information is calculated, and the intermediate processing result is stored in the third layer, i.e., the dws layer, of the data warehouse. Based on the intermediate processing result stored in the third layer, i.e., the dws layer, of the data warehouse, a final processing result of the vehicle business information is calculated, and the final processing result is stored in the fourth layer, i.e., the ads layer, of the data warehouse. In this embodiment, the data warehouse includes the first layer, i.e., the ods layer, and the second layer, i.e., the dwd layer, in addition to the third layer, i.e., the dws layer, and the fourth layer, i.e., the ads layer. The dws layer mainly performs pre-aggregation according to the business, serves as an intermediate layer of the business, and generates an intermediate result, i.e., a preliminary operation result. The ads layer mainly stores some final business indicators, which can be directly called by the business layer through an interface, and the final result is obtained through the collection of the intermediate result.

[0068] For example, for the vehicle ACC service, the dws layer divides the vehicle ACC journey, and calculates the duration of each journey according to the start time and end time of each journey. The ads layer calculates the duration of the journey in a day according to the duration of each journey calculated by the dws layer, and obtains the ACC driving time statistics of the intelligent vehicle in a day. For ICC, ACC, NOA, CNOA, HPA, RPA, APA and other intelligent driving services, the intelligent driving situation in a preset time period can also be obtained based on the same or similar method.

[0069] Further, the cloud interface obtains the calculated ads result set, and displays the result set to the vehicle machine or the mobile phone end through authentication authorization. The vehicle machine end displays data through a PKI (Public Key Infrastructure) two-way authorized interface, and the mobile phone end displays data through a PKI two-way authorized interface. Therefore, the client can display the behavior statistics of the intelligent driving in daily life, and the customer can intuitively obtain intelligent driving auxiliary information and drive more safely through the display of the historical intelligent driving data.

[0070] It can be seen that the embodiments of the application can calculate the relevant data of the intelligent driving service of each vehicle series or each vehicle, such as the mileage, duration and number of APA, ACC and NOA. Through the data, the intelligent driving situation and the safe driving situation of the vehicle can be reflected. The user can better release the hands, and the vehicle can take over the vehicle in danger, so as to ensure the safety of driving and make the driving more relaxed and safe.

[0071] On the basis of the above-mentioned embodiments, in combination with Figure 2 In one specific embodiment of the application, a smart vehicle data processing method includes the following steps:

[0072] [M001] The TSP cloud can configure the required message according to the vehicle type;

[0073] [M002] The configured instructions are issued to the vehicle machine end through the interface;

[0074] [M003] The DHU vehicle machine end receives the issued instructions, uploads the corresponding fields according to the specified upload, and in the DHU end, the CAN bus sends data (frame number, APA (automatic parking assistance), ACC (adaptive cruise control system), NOA (high-order intelligent driving), reporting time, etc.) to the FlexRay bus, and the data is sent to MQTT through the BGM gateway, and the data in MQTT is seamlessly connected to the TSP kafka through Kafka-connect-mqtt;

[0075] [M004] The vehicle machine transmits the message reported by the vehicle to the TSP end through the MQTT channel;

[0076] [M005]TSP KAFKA collects logs as a high-performance message system, and provides consumption for the consumption end through subscription;

[0077] [M006]spark parses the reported signal message in batches through offline jobs, and binds the vehicle series pushed by MES at the same time, so that each message is bound with the vehicle series. The message bound with the vehicle series is stored in the data warehouse;

[0078] [M007]DolphinScheduler offline scheduling task can call the original json data of the data warehouse according to the written SQL, and parse the required fields. Only the required fields are parsed, not all fields. Data layering is performed in the data warehouse, including ods layer, dwd layer, dws layer and ads layer;

[0079] [M008]The ods layer in the data warehouse only stores the original data generated according to the TSP configuration in the form of json. According to the business needs, only the required fields are parsed and put into the dwd data warehouse. The data warehouse stores the data of ods layer, dwd layer, dws layer and ads layer. The ads layer is the aggregated result data which can be directly provided to the interface call;

[0080] [M009]Divide the vehicle ICC / ACC / NOA / CNOA / HPA / RPA / APA trip according to the start time, end time, duration or mileage of each trip, and calculate the driving time or mileage of each segment;

[0081] [M010]Calculate the intelligent driving usage of ICC / ACC / NOA / CNOA / HPA / RPA / APA;

[0082] [M011]The cloud interface obtains the calculated ads result set, and displays it to the vehicle or mobile phone end through authentication and authorization;

[0083] [M012]The vehicle end displays data through the interface of PKI two-way authorization;

[0084] [M013]The mobile phone end displays data through the interface of PKI two-way authorization.

[0085] It can be seen that the embodiments of the application can dynamically configure the report message according to the vehicle type through the TSP cloud configuration center, and can also configure according to a single vehicle, thereby reducing the reporting of unnecessary field information, saving computing resources and storage resources. In the big data data warehouse, since the report message is configured according to the need, the storage resource is saved, the storage format is json, only the required field data can be parsed according to the need, and the storage and computing resources are saved. The intelligent driving situation of each vehicle series or each vehicle can be calculated, which can reflect the safe driving situation of the vehicle from the side, and make the driving more relaxed and safe.

[0086] It should be understood that, although Figure 1 The steps in the flowchart of the application are displayed in sequence according to the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in the application, the execution of these steps has no strict order limitation, and these steps can be executed in other orders. Moreover, Figure 1 At least part of the steps in the flowchart of the application can include multiple sub-steps or multiple stages, which are not necessarily executed at the same time, but can be executed at different times, and the execution order of these sub-steps or stages is not necessarily sequential, but can be executed with at least part of other steps or sub-steps or stages of other steps.

[0087] Figure 3 A flowchart of an intelligent vehicle data processing method provided by the embodiments of the application, the method is applied to a vehicle end, such as Figure 3 As shown in the figure, the method can include the following steps:

[0088] Step 301: receiving a first parameter issued by the cloud, wherein the first parameter is determined by the cloud according to the vehicle information of the vehicle end.

[0089] Step 302: filtering first data corresponding to the first parameter based on the first parameter, and sending the first data to the cloud, the cloud is used to store the first data in the data warehouse based on a preset form, determine a second parameter corresponding to the business information according to the vehicle business information, call the first data stored based on the preset form in the data warehouse, identify the field corresponding to the second parameter in the first data stored based on the preset form, parse the field to obtain the second data, and determine the processing result of the vehicle business information based on the second data.

[0090] Specifically, as Figure 3 shown, and in combination with Figure 4After the vehicle terminal starts, the first parameter issued by the cloud is received, the first data is obtained by screening the intelligent driving data based on the first parameter, and the first data is uploaded through the cloud interface, the cloud stores the first data in the data warehouse based on the preset form, the second parameter corresponding to the business information is determined according to the vehicle business information, the first data stored in the data warehouse based on the preset form is called, the field corresponding to the second parameter is identified in the first data stored based on the preset form, the second data is obtained by analyzing the field, the processing result of the vehicle business information is determined based on the second data, and the processing result data is obtained and displayed to the vehicle terminal through authentication authorization.

[0091] In an embodiment of the present application, the first data obtained by the vehicle terminal based on the first parameter is received, and the first data is stored in the data warehouse based on the preset form, including: receiving the first data obtained by the vehicle terminal based on the first parameter through the message queue transmission protocol, and storing the first data in the message middleware; the message middleware sends the first data to the data warehouse, and the data warehouse stores the first data based on the preset form.

[0092] In an embodiment of the present application, the message middleware sends the first data to the data warehouse, including: the message middleware sends the first data to the data processing platform in batches based on the preset time interval; the data processing platform receives the first data and removes the abnormal data in the first data; the data processing platform obtains the vehicle information corresponding to the first data, binds the first data with the corresponding vehicle information to obtain the first data with the bound vehicle information; and the first data with the bound vehicle information is sent to the data warehouse.

[0093] In an embodiment of the present application, the first data is stored in the data warehouse based on the preset form, including: the first data is stored in the first layer of the data warehouse based on the json form.

[0094] In an embodiment of the present application, the second parameter corresponding to the business information is determined according to the vehicle business information, the first data stored in the data warehouse based on the preset form is called, the field corresponding to the second parameter is identified in the first data stored based on the preset form, and the second data is obtained by analyzing the field, including: obtaining the vehicle business information and determining the second parameter corresponding to the business information; calling the first data stored in the data warehouse based on the json form according to the pre-written SQL statement, identifying the field corresponding to the second parameter in the first data, obtaining the second data by analyzing the field, and storing the second data in the second layer of the data warehouse.

[0095] In an embodiment of the present application, the processing result of determining the vehicle service information based on the second data comprises: calculating an intermediate processing result of the vehicle service information based on the second data stored in the second layer of the data warehouse, storing the intermediate processing result in the third layer of the data warehouse; calculating a final processing result of the vehicle service information based on the intermediate processing result stored in the third layer of the data warehouse, storing the final processing result in the fourth layer of the data warehouse; and sending the final processing result to the vehicle end based on the fourth layer of the data warehouse.

[0096] In an embodiment of the present application, the first parameter issued by the cloud end is received, comprising: receiving a first message issued by the cloud end, wherein the cloud end determines the first parameter corresponding to the vehicle end according to the vehicle model of the vehicle end, and configures the first message based on the first parameter.

[0097] According to the specific embodiments provided in the present application, the technical solutions provided in the present application can have the following advantages: through the TSP cloud end configuration center, the reporting message can be dynamically configured according to the vehicle model, or the reporting message can be configured according to a single vehicle, unnecessary field information is reduced, and computing resources and storage resources are saved. In the big data data warehouse, since the reporting message is configured according to the need, the storage resources are saved, the storage format is json, only the required field data can be parsed according to the need, and the storage and computing resources are saved. The intelligent driving situation of each vehicle series or each vehicle can be calculated, the safe driving situation of the vehicle can be reflected from the side, and the driving is more relaxed and safe.

[0098] The same and similar parts among the above embodiments can be referred to each other, and each embodiment mainly describes the difference from other embodiments. Especially, for the device embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the related parts can be referred to the part of the method embodiments.

[0099] It should be noted that the embodiments of the present application can involve the use of user data. In actual application, user-specific personal data can be used in the schemes described in the present application in the range allowed by applicable laws and regulations, for example, the user explicitly agrees, the user is explicitly notified, and the user explicitly authorizes.

[0100] According to the embodiments of the present application, the present application further provides a computer device and a computer readable storage medium. The present application further provides a computer device comprising at least one processor and a memory connected in communication with the at least one processor; wherein the memory stores computer instructions executable by the at least one processor, and the computer instructions are executed by the at least one processor to enable the at least one processor to execute the intelligent vehicle data processing method of any one of the above embodiments.

[0101] As Figure 5FIG. 1 shows a block diagram of a computer device according to an embodiment of the present application. The computer device is intended to represent various forms of digital computers or mobile devices. The digital computer can include a desktop computer, a laptop computer, a workstation, a personal digital assistant, a server, a mainframe computer, and other suitable computers. The mobile device can include a tablet computer, a smart phone, a wearable device, and the like.

[0102] As shown in FIG. 1, the computer device 500 includes a computing unit 501, a ROM 502, a RAM 503, a bus 504, and an input / output (I / O) interface 505. The computing unit 501, the ROM 502, and the RAM 503 are connected to each other through the bus 504. The input / output (I / O) interface 505 is also connected to the bus 504. Figure 5

[0103] The computing unit 501 can perform various processes in the embodiments of the method of the present application according to computer instructions stored in the read-only memory (ROM) 502 or computer instructions loaded from the storage unit 508 to the random access memory (RAM) 503. The computing unit 501 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. The computing unit 501 can include, but is not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. In some embodiments, the method provided by the embodiments of the present application can be implemented as a computer software program, which is tangibly contained in a computer readable storage medium, such as the storage unit 508.

[0104] The RAM 503 can also store various programs and data required for the operation of the device 500. Part or all of the computer program can be loaded and / or installed on the device 500 via the ROM 502 and / or the communication unit 509.

[0105] The input unit 506, the output unit 507, the storage unit 508, and the communication unit 509 in the computer device 500 can be connected to the I / O interface 505. Among them, the input unit 506 can be, for example, a keyboard, a mouse, a touch screen, a microphone, etc.; the output unit 507 can be, for example, a display, a speaker, an indicator light, etc. The device 500 can exchange information, data, etc. with other devices through the communication unit 509.

[0106] It should be noted that the device can also include other components necessary for normal operation. It can also only include components necessary to implement the scheme of the present application, and does not necessarily include all the components shown in the figure.

[0107] ​Various implementations of the systems and techniques described here can be realized in digital electronic circuitry, integrated circuitry, specially designed application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs) computer hardware, firmware, software, and / or combinations thereof.

[0108] Computer instructions for implementing the method of the present application can be written in any combination of one or more programming languages. These computer instructions can be provided to the computing unit 501 such that the computer instructions, when executed by the computing unit 501 such as a processor, cause the steps involved in the embodiments of the method of the present application to be performed.

[0109] The present application also provides a computer readable storage medium having computer instructions stored thereon, the computer instructions being used for causing a computer to perform the intelligent vehicle data processing method of any of the embodiments described above.

[0110] The computer readable storage medium provided by the present application can be a tangible medium, which can contain or store computer instructions for performing the steps involved in the embodiments of the method of the present application. The computer readable storage medium can include, but is not limited to, storage media of electronic, magnetic, optical, electromagnetic, and the like.

[0111] The specific implementation described above does not constitute a limitation on the scope of protection of the present application. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent replacements, and improvements made within the spirit and principles of the present application should be included in the scope of protection of the present application.

Claims

1. A method for processing intelligent vehicle data, applied in the cloud, characterized in that, The method includes: The first parameter corresponding to the vehicle information is determined based on the vehicle information on the vehicle terminal, and the first parameter is sent to the vehicle terminal. The system receives the first data obtained by the vehicle terminal based on the first parameter and stores the first data in a data warehouse in a preset format. Based on the vehicle business information, a second parameter corresponding to the business information is determined. First data stored in a preset format is retrieved from the data warehouse. The field corresponding to the second parameter is identified in the first data stored in the preset format. The field is parsed to obtain the second data. The processing result of vehicle business information is determined based on the second data; The step of storing the first data in a data warehouse based on a preset format includes: storing the first data in the first layer of the data warehouse based on JSON format; The process of determining a second parameter corresponding to the vehicle business information based on the vehicle business information, retrieving first data stored in a preset format from the data warehouse, identifying the field corresponding to the second parameter in the first data stored in the preset format, and parsing the field to obtain the second data includes: Obtain vehicle business information and determine the second parameter corresponding to the business information; call the first data stored in the data warehouse in JSON format according to the pre-written SQL statement, identify the field corresponding to the second parameter in the first data, parse the field to obtain the second data, and store the second data in the second layer of the data warehouse.

2. The intelligent vehicle data processing method according to claim 1, characterized in that, The step of receiving the first data obtained by the vehicle terminal according to the first parameter and storing the first data in a data warehouse according to a preset format includes: The system receives the first data obtained by the vehicle terminal based on the first parameter through the message queue transmission protocol, and stores the first data in the message middleware. The message middleware sends the first data to the data warehouse, and the data warehouse stores the first data based on a preset format.

3. The intelligent vehicle data processing method according to claim 2, characterized in that, The message middleware sends the first data to the data warehouse, including: The message middleware sends the first data to the data processing platform in batches based on a preset time interval; The data processing platform receives the first data and removes abnormal data from the first data. The data processing platform obtains vehicle information corresponding to the first data and binds the first data to the corresponding vehicle information to obtain first data with bound vehicle information. The first data of the bound vehicle information is sent to the data warehouse.

4. The intelligent vehicle data processing method according to claim 1, characterized in that, The processing result of vehicle business information is determined based on the second data, including: Based on the second data stored in the second layer of the data warehouse, the intermediate processing result of the vehicle business information is calculated, and the intermediate processing result is stored in the third layer of the data warehouse; Based on the intermediate processing results stored in the third layer of the data warehouse, the final processing result of the vehicle business information is calculated, and the final processing result is stored in the fourth layer of the data warehouse. The final processing result is sent to the vehicle based on the fourth layer of the data warehouse.

5. The intelligent vehicle data processing method according to claim 1, characterized in that, The step of determining a first parameter corresponding to the vehicle information based on the vehicle information on the vehicle terminal, and sending the first parameter to the vehicle terminal, includes: The first parameter corresponding to the vehicle terminal is determined based on the vehicle model, a first message is configured based on the first parameter, and the first message is sent to the vehicle terminal.

6. A smart vehicle data processing method, applied to the vehicle end, characterized in that, The method includes: Receive the first parameter sent from the cloud, wherein the first parameter is determined by the cloud based on the vehicle information on the vehicle side; Based on the first parameter, filter the first data corresponding to the first parameter, send the first data to the cloud, the cloud is used to store the first data in a data warehouse in a preset format, determine the second parameter corresponding to the business information according to the vehicle business information, call the first data stored in the preset format in the data warehouse, identify the field corresponding to the second parameter in the first data stored in the preset format, parse the field to obtain the second data, and determine the processing result of the vehicle business information based on the second data. The step of storing the first data in a data warehouse based on a preset format includes: storing the first data in the first layer of the data warehouse based on JSON format; The process of determining a second parameter corresponding to the vehicle business information based on the vehicle business information, retrieving first data stored in a preset format from the data warehouse, identifying the field corresponding to the second parameter in the first data stored in the preset format, and parsing the field to obtain the second data includes: Obtain vehicle business information and determine the second parameter corresponding to the business information; call the first data stored in the data warehouse in JSON format according to the pre-written SQL statement, identify the field corresponding to the second parameter in the first data, parse the field to obtain the second data, and store the second data in the second layer of the data warehouse.

7. A computer device, comprising: At least one processor; as well as A memory communicatively connected to the at least one processor; wherein, The memory stores computer instructions executable by the at least one processor, which, when executed by the at least one processor, enables the at least one processor to perform the method of any one of claims 1-5.

8. A computer-readable storage medium storing computer instructions thereon, characterized in that, The computer instructions are used to cause the computer to perform the method according to any one of claims 1 to 5.

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