CN115017374B - Data analysis method, target vehicle, data analysis system and storage device - Google Patents
Data analysis method, target vehicle, data analysis system and storage device Download PDFInfo
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Abstract
本发明涉及智能网联汽车领域，具体涉及一种数据分析方法、目标车辆、数据分析系统及存储设备。该方法包括：获取目标车辆的驾驶数据以及环境数据；将驾驶数据以及环境数据的标识信息与字段配置表进行匹配，确定需要实时上报至云端服务器的目标数据以及不需要实时上报至云端服务器的其他数据；将目标数据实时上报至云端服务器，以使云端服务器对目标数据进行解析；对其他数据进行计算，以对目标车辆的驾驶行为进行监测。上述方法，将目标数据实时上报至云端服务器，并对其他数据进行计算，以对目标车辆的驾驶行为进行监测。从而不仅减少了云端服务器的计算量，且实现了对目标车辆驾驶行为的双重监控，保证了目标车辆驾驶行为的安全性。
The present invention relates to the field of intelligent networked vehicles, and specifically to a data analysis method, a target vehicle, a data analysis system and a storage device. The method comprises: obtaining driving data and environmental data of a target vehicle; matching the identification information of the driving data and the environmental data with a field configuration table, determining the target data that needs to be reported to a cloud server in real time and other data that does not need to be reported to the cloud server in real time; reporting the target data to the cloud server in real time so that the cloud server can parse the target data; calculating other data to monitor the driving behavior of the target vehicle. The above method reports the target data to the cloud server in real time, and calculates other data to monitor the driving behavior of the target vehicle. Thereby, not only the amount of calculation of the cloud server is reduced, but also the dual monitoring of the driving behavior of the target vehicle is realized, and the safety of the driving behavior of the target vehicle is ensured.
Description
Technical Field
The invention relates to the field of intelligent network automobiles, in particular to a data analysis method, a target vehicle, a data analysis system and storage equipment.
Background
The intelligent network-connected automobile platform can provide vehicle related data display for a browser end or a mobile phone end user, and can monitor and analyze vehicles and drivers. The Internet users can know the vehicle and the driver better, so that the vehicle is maintained better and the driving safety is improved.
In an actual scene, the vehicle terminal uploads all data acquired by the vehicle terminal to a cloud server, and the cloud server provides vehicle basic information for an interconnection terminal, monitors vehicle target data, analyzes driving conditions and the like through a big data platform and cloud computing service.
According to the method, all data acquired by the vehicle terminal are uploaded to the cloud server, and as vehicles increase, the calculation pressure of the cloud server is increased, so that the monitoring of the vehicle end is possibly delayed, the decision planning by the cloud server is not timely due to the delay of the monitoring of the vehicle end, and even life and property risks are caused in serious cases.
Disclosure of Invention
In view of the above, the embodiment of the invention provides a data analysis method, which aims to solve the problem that the cloud server calculates pressure increase, which may cause delay in monitoring vehicles and result in untimely decision planning.
According to a first aspect, an embodiment of the present invention provides a data analysis method, applied to a target vehicle, including:
Acquiring driving data and environment data of a target vehicle;
Matching the identification information of the driving data and the environment data with the field configuration table, and determining target data which need to be reported to the cloud server in real time and other data which do not need to be reported to the cloud server in real time; the field configuration table includes identification information of the target data;
the target data are reported to the cloud server in real time, so that the cloud server analyzes the target data;
Other data is calculated to monitor the driving behavior of the target vehicle.
According to the data analysis method provided by the embodiment of the invention, the driving data and the environment data of the target vehicle are obtained, the identification information of the driving data and the environment data is matched with the field configuration table, and the target data which needs to be reported to the cloud server in real time and other data which does not need to be reported to the cloud server in real time are determined, so that the accuracy of the determined target data and other data can be ensured. And then, reporting the target data to the cloud server in real time so that the cloud server can solve the target data. Instead of uploading all driving data and environmental data to the cloud server, the data amount uploaded to the cloud server can be reduced, and then the calculation pressure of the cloud server is reduced, so that the cloud server is ensured not to delay monitoring of the target vehicle, and errors of monitoring results of the target vehicle are avoided. In addition, the target vehicle can calculate other data, so that the driving behavior of the target vehicle is monitored. According to the method, the target data are reported to the cloud server in real time, so that the cloud server analyzes the target data, calculates other data, and monitors driving behaviors of the target vehicle. Therefore, the calculated amount of the cloud server is reduced, double monitoring of the cloud server and the target vehicle on the driving behavior of the target vehicle is realized, and the safety of the driving behavior of the target vehicle is ensured. In addition, timeliness and accuracy of monitoring the vehicle end are guaranteed, and timeliness of decision making planning of the cloud server is guaranteed.
With reference to the first aspect, in a first implementation manner of the first aspect, reporting, in real time, the target data to the cloud server includes:
converting the target data into target format data;
and uploading the target format data to the cloud server in real time.
According to the data analysis method provided by the embodiment of the invention, the target data are converted into the target format data, and the target format data are uploaded to the cloud server in real time, so that the cloud server can receive the target format data, unification of data formats received by the cloud server is ensured, further, the calculation efficiency of the cloud server can be improved, the increase of calculation pressure of the cloud server is avoided, delay in monitoring of vehicles is possibly caused, and errors in monitoring results of the vehicles are possibly caused.
With reference to the first implementation manner of the first aspect, in a second implementation manner of the first aspect, converting the target data into the target format data includes:
Acquiring a data structure of target data;
Extracting all data in each layer of structure according to the data structure of the target data, and adding the extracted all data into the structure identification;
and splicing all the data added with the structure identifier to generate target format data.
The data analysis method provided by the embodiment of the invention acquires the data structure of the target data. And then, extracting all data in each layer of structure according to the data structure of the target data, and adding the extracted all data into the structure identifier, thereby ensuring the accuracy of the extracted all data in each layer of structure and ensuring the accuracy of the structure identifier added by all data. And then, all the data added with the structure identifier are spliced to generate target format data, so that the accuracy of the generated target format data is ensured.
With reference to the first aspect, in a third implementation manner of the first aspect, calculating other data to monitor driving behavior of the target vehicle includes:
acquiring a calculation rule sent by a cloud server;
calculating other data based on the calculation rule to obtain calculation data;
Based on the calculation data, analyzing the driving behaviors corresponding to the target vehicle, and visually outputting the driving behaviors corresponding to the target vehicle;
And when the dangerous driving behavior of the target vehicle is determined based on the driving behavior, sending out prompt information.
According to the data analysis method provided by the embodiment of the invention, the calculation rule sent by the cloud server is obtained, other data are calculated based on the calculation rule, the calculated data are obtained, and the accuracy of the obtained calculated data is ensured. Then, based on the calculation data, the driving behaviors corresponding to the target vehicles are analyzed, the accuracy of the driving behaviors corresponding to the analyzed target vehicles is guaranteed, and the driving behaviors corresponding to the target vehicles are visually output, so that a user can see the driving behaviors, and the dangerous driving behaviors can be corrected conveniently by the user. When the dangerous driving behavior of the target vehicle is determined based on the driving behavior, prompt information is sent out, so that a user can be reminded of correcting the dangerous driving behavior.
With reference to the third implementation manner of the first aspect, in a fourth implementation manner of the first aspect, after calculating other data based on the calculation rule, the method further includes:
And periodically uploading the calculated data to the cloud server.
According to the data analysis method provided by the embodiment of the invention, the calculated data is periodically uploaded to the cloud server, so that the cloud server can receive the calculated data, does not need to receive other data or calculate other data, the data volume uploaded to the cloud server can be reduced, the calculation pressure of the cloud server is further reduced, the monitoring of the target vehicle by the cloud server is ensured not to be delayed, and the error of the monitoring result of the target vehicle is avoided. In addition, after the cloud server receives the calculation data, the target vehicle can be monitored more fully on the surface, and the safety of the driving behavior of the target vehicle is ensured.
According to a second aspect, an embodiment of the present invention provides a data analysis method, applied to a cloud server, where the cloud server is connected with a target vehicle, the method includes:
Transmitting a field configuration table to the target vehicle;
Receiving target data uploaded by a target vehicle in real time based on a field configuration table; the target data is generated according to the first aspect or a data analysis method in any implementation of the first aspect;
Analyzing the target data to determine whether dangerous driving behaviors exist in the target vehicle;
and when the target vehicle has dangerous driving behaviors, sending alarm information to the target vehicle.
According to the data analysis method provided by the embodiment of the invention, the field configuration table is sent to the target vehicle, so that the target vehicle can determine the target data which needs to be uploaded in real time based on the field configuration table. Then, receiving target data uploaded by the target vehicle in real time based on the field configuration table, analyzing the target data, determining whether dangerous driving behaviors exist in the target vehicle, and ensuring the accuracy of a determination result. When the dangerous driving behavior exists in the target vehicle, alarm information is sent to the target vehicle, so that the target vehicle can receive the dangerous driving behavior information as soon as possible, and the driving safety of the target vehicle is ensured.
With reference to the second aspect, in a first implementation manner of the second aspect, the method further includes:
Sending calculation rules to the target vehicle;
Periodically receiving calculation data obtained by calculating other data of the target vehicle based on calculation rules; the other data are data which are determined by matching the driving data and the identification information of the environmental data with the field configuration table by the target vehicle and do not need to be reported to the cloud server in real time;
based on the calculated data and the target data, analyzing the driving behavior of the target vehicle, and visually outputting the driving behavior corresponding to the target vehicle;
and sending out alarm information when the dangerous driving behavior of the target vehicle is determined based on the driving behavior.
According to the data analysis method provided by the embodiment of the invention, the calculation rule is sent to the target vehicle, so that the target vehicle can calculate other data based on the calculation rule, and the calculated data is obtained. Then, calculation data obtained by calculating other data based on the calculation rule by the target vehicle is periodically received. And analyzing the driving behavior of the target vehicle based on the calculated data and the target data, and visually outputting the driving behavior corresponding to the target vehicle. The accuracy of the driving behaviors corresponding to the analyzed target vehicles is guaranteed, and the driving behaviors corresponding to the target vehicles are visually output, so that a user can see the driving behaviors, and the dangerous driving behaviors can be corrected conveniently. When the dangerous driving behavior of the target vehicle is determined based on the driving behavior, prompt information is sent out, so that a user can be reminded of correcting the dangerous driving behavior.
According to a third aspect, the embodiment of the present invention further provides a target vehicle, a vehicle-mounted computing platform, where the vehicle-mounted computing platform includes a memory and a processor, the memory stores computer instructions, and the processor executes the computer instructions, so as to execute the data analysis method in the first aspect or any implementation manner of the first aspect.
According to a fourth aspect, an embodiment of the present invention further provides a data analysis system, including:
a target vehicle of a third aspect for performing the first aspect or the data analysis method in any of the implementation manners of the first aspect;
the cloud server is connected with the target vehicle and is used for executing the data analysis method in the second aspect or any implementation mode of the second aspect.
According to a fifth aspect, an embodiment of the present invention provides a computer-readable storage medium storing computer instructions for causing a computer to perform the method of data analysis of the first aspect or any implementation of the first aspect and of the second aspect or any implementation of the second aspect.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are needed in the description of the embodiments or the prior art will be briefly described, and it is obvious that the drawings in the description below are some embodiments of the present invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a data analysis method provided by an embodiment of the present invention;
FIG. 2 is a flow chart of a data analysis method according to another embodiment of the present invention;
FIG. 3 is a flow chart of a data analysis method according to another embodiment of the present invention;
FIG. 4 is a frame diagram of a target vehicle in a data analysis method according to another embodiment of the present invention;
FIG. 5 is a flow chart of a data analysis method according to another embodiment of the present invention;
FIG. 6 is a flow chart of a data analysis method provided by another embodiment of the present invention;
FIG. 7 is a cloud flowchart of a data analysis method according to another embodiment of the present invention;
FIG. 8 is a flow chart illustrating a method for analyzing data according to another embodiment of the present invention;
FIG. 9 is a functional block diagram of a data analysis device according to an embodiment of the present invention;
FIG. 10 is a functional block diagram of a data analysis device according to an embodiment of the present invention;
Fig. 11 is a schematic hardware structure of a vehicle-mounted computing platform in a target vehicle according to an embodiment of the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
It should be noted that, in the method for analyzing data provided in the embodiment of the present application, the execution body may be a device of a target vehicle, where the device of the target vehicle may be implemented in a software, hardware or a combination of software and hardware as part or all of a control device in the target vehicle, where the control device is preferably an autopilot domain controller or an intelligent cabin domain controller of the vehicle, and may also be other vehicle-mounted computing platform control components. In the following method embodiments, the execution subject is a target vehicle.
In one embodiment of the present application, as shown in fig. 1, a data analysis method is provided, which is described by taking application of the method to a target vehicle as an example, and includes the following steps:
s11, driving data and environment data of the target vehicle are acquired.
Specifically, the target vehicle may acquire driving data of the target vehicle and environmental data based on its own sensor.
For example, the target vehicle may acquire its own vehicle speed based on a vehicle speed sensor, acquire its own accelerator opening based on an accelerator opening sensor, acquire its own foot pedal pressure based on a foot pedal sensor, and the like. In addition, the target vehicle may acquire an image of the surrounding environment based on the camera installed by itself, acquire information of surrounding obstacles based on the radar system installed by itself, and the like. The embodiment of the present application is not particularly limited.
And S12, matching the identification information of the driving data and the environmental data with the field configuration table, and determining target data which need to be reported to the cloud server in real time and other data which do not need to be reported to the cloud server in real time.
Wherein the field configuration table includes identification information of the target data.
Specifically, the target vehicle may compare the identification information of the driving data and the environmental data with the identification information of the target data included in the field configuration table, so as to determine, from the driving data and the environmental data, the target data that needs to be reported to the cloud server in real time, and other data that does not need to be reported to the cloud server in real time.
And S13, reporting the target data to the cloud server in real time so that the cloud server can analyze the target data.
In an optional embodiment of the application, the target vehicle may package the target data, so as to report the target data to the cloud server in real time, so that the cloud server may analyze the target data.
And S14, calculating other data to monitor the driving behavior of the target vehicle.
Specifically, the target vehicle may calculate other data to obtain calculation data, and monitor driving behavior of the target vehicle based on the calculation data.
For example, the target vehicle may calculate the current vehicle speed of the target vehicle based on the wheel speeds in the other data. Then, based on the current speed of the target vehicle, it is detected whether the target vehicle is overspeed.
This step will be described in detail below.
According to the data analysis method provided by the embodiment of the invention, the driving data and the environment data of the target vehicle are obtained, the identification information of the driving data and the environment data is matched with the field configuration table, and the target data which needs to be reported to the cloud server in real time and other data which does not need to be reported to the cloud server in real time are determined, so that the accuracy of the determined target data and other data can be ensured. And then, reporting the target data to the cloud server in real time so that the cloud server can solve the target data. Instead of uploading all driving data and environmental data to the cloud server, the data amount uploaded to the cloud server can be reduced, and then the calculation pressure of the cloud server is reduced, so that the cloud server is ensured not to delay monitoring of the target vehicle, and errors of monitoring results of the target vehicle are avoided. In addition, the target vehicle can calculate other data, so that the driving behavior of the target vehicle is monitored. According to the method, the target data are reported to the cloud server in real time, so that the cloud server analyzes the target data, calculates other data, and monitors driving behaviors of the target vehicle. Therefore, the calculated amount of the cloud server is reduced, double monitoring of the cloud server and the target vehicle on the driving behavior of the target vehicle is realized, and the safety of the driving behavior of the target vehicle is ensured. In addition, timeliness and accuracy of monitoring the vehicle end are guaranteed, and timeliness of decision making planning of the cloud server is guaranteed.
In one embodiment of the present application, as shown in fig. 2, a data analysis method is provided, and the method is applied to a vehicle-mounted computing platform for illustration, and includes the following steps:
s21, driving data and environment data of the target vehicle are acquired.
For this step, please refer to the description of S11 in fig. 1.
And S22, matching the identification information of the driving data and the environmental data with the field configuration table, and determining target data which need to be reported to the cloud server in real time and other data which do not need to be reported to the cloud server in real time.
Wherein the field configuration table includes identification information of the target data.
For this step, please refer to the description of S11 in fig. 1.
And S23, reporting the target data to the cloud server in real time so that the cloud server can analyze the target data.
In an optional embodiment of the present application, the step S23 "reporting the target data to the cloud server" may include the following steps:
s231, converting the target data into target format data.
In an alternative embodiment of the present application, the step of converting the target data into the target format data in S231 "may include the following steps:
(1) A data structure of the target data is obtained.
(2) And extracting all data in each layer of structure according to the data structure of the target data, and adding the extracted all data into the structure identification.
(3) And splicing all the data added with the structure identifier to generate target format data.
Specifically, the vehicle-mounted computing platform can acquire the data structure of the target data through reading the target data. Then, all data in each layer of structure are extracted according to the data structure of the target data, and the structure identification is added for all data extracted from each layer of structure according to the structure identification of each layer of data. And then, splicing all the data added with the structure identifier to generate target format data.
By way of example, parsing the jt808 protocol data is taken as an example, as shown below, the target data with a 4-layer structure is extracted according to the data structure of the target data, all the data in each layer structure are extracted, the structure identification is added to all the extracted data, and all the data with the structure identification added are spliced to generate the target format data. The generated target format data is stored in the cloud server and the target vehicle, so that communication is convenient on one hand; on the other hand, the target vehicle is configured to perform data analysis on terminal devices (regarded as child nodes in the distributed system) connected with the target vehicle, so as to reduce the calculation amount of the cloud server. Such a configuration may be stored in a database. (Source field name, source_comment field meaning)
The following is an example of converting target data into target format data: (sim of header is used to represent terminal unique number)
sim:040785013932
0-0-1-0:1;0-0-1-1:1;0-0-1-2:0;0-0-1-3:0;0-0-1-4:0;0-0-1-5:0;0-0-1-6:0;0-0-1-8:0;0-0-1-10:0;0-0-1-11:0;0-0-1-12:0;0-0-1-13:0;0-0-1-14:0;0-0-1-15:0;0-0-1-16:0;0-0-1-17:0;0-0-1-18:0;0-0-1-19:0;0-0-1-20:0;0-0-1-21:0;0-0-2:23.755800;0-0-3:114.715622;0-0-4:55;0-0-5:0;0-0-6:0;0-0-7:1640889566;0-1-1:79725.7;0-1-3:0;0-1-48:31;0-1-49:9;0-1-101-0:3;0-1-101-1:0;0-1-102:28700.5;0-1-103:553;0-1-105:83;0-1-106:27;0-1-107-0:1;0-1-107-5:1;0-1-108:0;0-1-109:0;0-1-110:0;0-1-111:0;0-1-112:0;0-1-113:0;0-1-116:10272344;0-1-117:21622855;0-1-118:85;0-1-119:11350511; The target format data is analyzed into a key and value form Map through a program; the configuration table (configuration write cache) is matched to acquire the desired data, so that the analysis and analysis efficiency is improved.
S232, uploading the target format data to the cloud server in real time.
Specifically, the target vehicle uploads the target format data to the cloud server in real time based on the connection with the cloud server.
And S24, calculating other data to monitor the driving behavior of the target vehicle.
For this step, please refer to fig. 1 for description of S14, and detailed description thereof is omitted herein.
The data analysis method provided by the embodiment of the invention acquires the data structure of the target data. And then, extracting all data in each layer of structure according to the data structure of the target data, and adding the extracted all data into the structure identifier, thereby ensuring the accuracy of the extracted all data in each layer of structure and ensuring the accuracy of the structure identifier added by all data. And then, all the data added with the structure identifier are spliced to generate target format data, so that the accuracy of the generated target format data is ensured. And the cloud server can receive the target format data, so that the unification of the data formats received by the cloud server is ensured, the calculation efficiency of the cloud server can be improved, and the increase of the calculation pressure of the cloud server is avoided, so that the delay of the monitoring of the vehicle and the error of the monitoring result of the vehicle can be caused.
In one embodiment of the present application, as shown in fig. 3, a data analysis method is provided, and the method is applied to a vehicle-mounted computing platform for illustration, and includes the following steps:
S31, driving data and environment data of the target vehicle are acquired.
For this step, please refer to the description of S21 in fig. 2, and details are not described here.
And S32, matching the identification information of the driving data and the environmental data with the field configuration table, and determining target data which need to be reported to the cloud server in real time and other data which do not need to be reported to the cloud server in real time.
Wherein the field configuration table includes identification information of the target data.
For this step, please refer to the description of S22 in fig. 2, and details are not described here.
And S33, reporting the target data to the cloud server in real time so that the cloud server can analyze the target data.
For this step, please refer to the description of S23 in fig. 2, and details are not described here.
And S34, calculating other data to monitor the driving behavior of the target vehicle.
In an alternative embodiment of the present application, the step of calculating the other data to monitor the driving behavior of the target vehicle in S34 "may include the following steps:
s341, acquiring a calculation rule sent by the cloud server.
Specifically, the target vehicle may acquire the calculation rule sent by the cloud server based on the connection with the cloud server.
And S342, calculating other data based on the calculation rule to obtain calculation data.
Specifically, the target vehicle may calculate other data based on the calculation rule, resulting in calculated data.
For example, the target vehicle may calculate the current vehicle speed of the target vehicle based on the wheel speeds in the other data.
S343, analyzing the driving behaviors corresponding to the target vehicle based on the calculated data, and visually outputting the driving behaviors corresponding to the target vehicle.
Specifically, the target vehicle may analyze driving behaviors corresponding to the target vehicle based on the calculation data, and visually output the driving behaviors corresponding to the target vehicle.
In an alternative embodiment, the target vehicle may display the corresponding driving behavior of the target vehicle in a display component of the target vehicle itself.
In another alternative embodiment, the target vehicle may transmit the driving behavior corresponding to the target vehicle to the terminal device based on the connection between the target vehicle and the terminal device, and display the driving behavior corresponding to the target vehicle based on the terminal device.
And S344, when the dangerous driving behavior of the target vehicle is determined based on the driving behavior, a prompt message is sent out.
Specifically, when it is determined that the target vehicle has dangerous driving behavior based on the driving behavior, the target vehicle may issue a prompt message. The method for sending the prompt information by the target vehicle can be outputting a voice prompt or outputting a light prompt, and the embodiment of the application does not limit the method for sending the prompt information by the target vehicle specifically.
And S345, periodically uploading the calculation data to a cloud server.
Specifically, after the calculation data is obtained by the target vehicle, the calculation data of a period of time or a path may be periodically uploaded to the cloud server. The uploading period can be set according to the calculation task amount of the cloud server, can be set according to the calculation efficiency of the target vehicle, can be 5 minutes or 10 minutes, and is not particularly limited in the embodiment of the application.
According to the data analysis method provided by the embodiment of the invention, the calculation rule sent by the cloud server is obtained, other data are calculated based on the calculation rule, the calculated data are obtained, and the accuracy of the obtained calculated data is ensured. Then, based on the calculation data, the driving behaviors corresponding to the target vehicles are analyzed, the accuracy of the driving behaviors corresponding to the analyzed target vehicles is guaranteed, and the driving behaviors corresponding to the target vehicles are visually output, so that a user can see the driving behaviors, and the dangerous driving behaviors can be corrected conveniently by the user. When the dangerous driving behavior of the target vehicle is determined based on the driving behavior, prompt information is sent out, so that a user can be reminded of correcting the dangerous driving behavior. In addition, the vehicle-mounted computing platform periodically uploads the computing data to the cloud server, so that the cloud server can receive the computing data, does not need to receive other data or compute other data, the data volume uploaded to the cloud server can be reduced, the computing pressure of the cloud server is reduced, the cloud server is guaranteed to monitor the target vehicle without delay, and the error of the monitoring result of the target vehicle is avoided. In addition, after the cloud server receives the calculation data, the target vehicle can be monitored more fully on the surface, and the safety of the driving behavior of the target vehicle is ensured.
Fig. 4 is a schematic diagram of a design of a target vehicle according to an embodiment of the present application. As can be seen from fig. 4, the target vehicle may include a message parser, a synchronization program. The parser is used for classifying and grouping the fields according to the frequency according to the database configuration parsing message, namely, determining target data and other data according to a field configuration table launched by the cloud server; the analyzer is also used for reporting or storing the vehicle data in a built-in database, namely uploading the target data to the cloud server in real time and storing other data in the built-in database; the parser is further configured to receive data sent by the cloud server and forward the data to the vehicle, that is, receive the field configuration table and the calculation rule sent by the cloud server and forward the data to the target vehicle. The main functions of the synchronization program are as follows: periodically reporting the local analysis result to the cloud server, namely periodically reporting the calculation data to the cloud server; acquiring the latest configuration from the cloud server at regular time, and storing the latest configuration in a database or directly sending the latest configuration to the calculation and transmission analyzer, namely periodically receiving a field configuration table and calculation rules sent by the cloud server, and storing the latest configuration in the database or directly sending the latest configuration to the calculation and transmission analyzer; and acquiring vehicle analysis data from the cloud server according to the vehicle requirements.
The target vehicle may further include a built-in database for storing a field mapping table, i.e., a field configuration table; an algorithm configuration table, namely a calculation rule; the table is stored, as well as the analysis result table, i.e., the calculation data.
The target vehicle may also include an algorithm analyzer for acquiring and parsing configuration data, i.e., parsing other data, from the synchronization program or the built-in database; and analyzing the vehicle data of a period of time or a path to produce a vehicle portrait, storing the vehicle portrait in a database, calling a synchronization program and uploading the vehicle portrait to a cloud.
The target vehicle may also have a scheduler for coordinating the various components to provide on-board page presentations.
The cloud server is used for providing field analysis configuration, namely a field configuration table and algorithm configuration parameters, namely calculation rules; aggregating the image data of each vehicle to analyze big data; storing the vehicle representation for a period of time to prevent local loss of the vehicle; the original function of the internet of vehicles is maintained.
In order to better explain the data analysis method provided by the embodiment of the application, the embodiment of the application also provides a data analysis method. It should be noted that, in the method for data analysis provided by the embodiment of the present application, the execution body may be a data analysis device, and the data analysis device may be implemented in a manner of software, hardware, or a combination of software and hardware to form part or all of a cloud server. The cloud server can be a server or a terminal, wherein the server in the embodiment of the application can be one server or a server cluster consisting of a plurality of servers, and the terminal in the embodiment of the application can be other intelligent hardware devices such as a smart phone, a personal computer, a tablet personal computer, an intelligent robot and the like. In the following method embodiments, the execution subject is a cloud server as an example.
In one embodiment of the present application, as shown in fig. 5, a data analysis method is provided, and the method is applied to a cloud server for example, where the cloud server is connected to a target vehicle, and the method includes the following steps:
s41, transmitting the field configuration table to the target vehicle.
In an optional embodiment of the present application, the cloud server may generate the field configuration table according to data required when monitoring the target vehicle.
In another optional embodiment of the present application, the cloud server may further receive a field configuration table input by a user or receive a field configuration table sent by another device.
The method for acquiring the field configuration table by the cloud server is not particularly limited.
After the cloud server obtains the field configuration table, the field configuration table may be sent to the target vehicle based on the connection with the target vehicle.
S42, receiving target data uploaded by the target vehicle in real time based on the field configuration table.
Wherein the target data is generated according to the data analysis method of any one of the above embodiments.
Specifically, the cloud server may receive target data uploaded by the target vehicle in real time based on the field configuration table based on the connection with the target vehicle.
S43, analyzing the target data to determine whether dangerous driving behaviors exist in the target vehicle.
Specifically, after receiving the target data uploaded by the target vehicle in real time, the cloud server may analyze the target data, so as to determine whether the target vehicle has dangerous driving behaviors.
And S44, when dangerous driving behaviors exist in the target vehicle, sending alarm information to the target vehicle.
Specifically, when the cloud server determines that the dangerous driving behavior exists in the target vehicle, the warning information can be sent to the target vehicle based on the connection with the target vehicle, so that the target vehicle can correct the dangerous driving behavior.
According to the data analysis method provided by the embodiment of the invention, the field configuration table is sent to the target vehicle, so that the target vehicle can determine the target data which needs to be uploaded in real time based on the field configuration table. Then, receiving target data uploaded by the target vehicle in real time based on the field configuration table, analyzing the target data, determining whether dangerous driving behaviors exist in the target vehicle, and ensuring the accuracy of a determination result. When the dangerous driving behavior exists in the target vehicle, alarm information is sent to the target vehicle, so that the target vehicle can receive the dangerous driving behavior information as soon as possible, and the driving safety of the target vehicle is ensured.
In one embodiment of the present application, as shown in fig. 6, there is provided a data analysis method as described above, further including:
and S51, sending the calculation rule to the target vehicle.
In an alternative embodiment of the present application, the cloud server may generate the calculation rule according to data required when monitoring the target vehicle.
In another optional embodiment of the present application, the cloud server may further receive a calculation rule input by a user or receive a calculation rule sent by another device.
The method for acquiring the calculation rule by the cloud server is not particularly limited.
After the cloud server obtains the calculation rule, the calculation rule may be sent to the target vehicle based on the connection with the target vehicle.
And S52, periodically receiving calculation data obtained by calculating other data by the target vehicle based on the calculation rule.
The other data are data which are determined by matching the driving data and the identification information of the environmental data with the field configuration table by the target vehicle and do not need to be reported to the cloud server in real time.
Specifically, the cloud server may periodically receive calculation data obtained by calculating other data by the target vehicle based on the calculation rule based on the connection with the target vehicle.
And S53, analyzing the driving behaviors of the target vehicle based on the calculated data and the target data, and visually outputting the driving behaviors corresponding to the target vehicle.
Specifically, the cloud server may analyze driving behavior of the target vehicle based on the calculation data and the target data after receiving the calculation data.
In an alternative embodiment, after the cloud server obtains the target data and other data uploaded by the target vehicle, the cloud server may continuously compare the target data and other data of the target vehicle with the target data and other data of other vehicles, and analyze the corresponding driving behavior of the target vehicle according to the comparison result.
After the driving behavior of the target vehicle is analyzed continuously, the cloud server can visually output the driving behavior corresponding to the target vehicle at the cloud server. Thus, the user can see the images of the excellent drivers corresponding to the target vehicle and other excellent drivers and know the average level in the computing device.
And S54, when the dangerous driving behavior of the target vehicle is determined based on the driving behavior, sending out alarm information.
Specifically, when the cloud server determines that the target vehicle has dangerous driving behaviors based on driving behaviors, alarm information is sent to the target vehicle based on connection with the target vehicle.
According to the data analysis method provided by the embodiment of the invention, the calculation rule is sent to the target vehicle, so that the target vehicle can calculate other data based on the calculation rule, and the calculated data is obtained. Then, calculation data obtained by calculating other data based on the calculation rule by the target vehicle is periodically received. And analyzing the driving behavior of the target vehicle based on the calculated data and the target data, and visually outputting the driving behavior corresponding to the target vehicle. The accuracy of the driving behaviors corresponding to the analyzed target vehicles is guaranteed, and the driving behaviors corresponding to the target vehicles are visually output, so that a user can see the driving behaviors, and the dangerous driving behaviors can be corrected conveniently. When the dangerous driving behavior of the target vehicle is determined based on the driving behavior, prompt information is sent out, so that a user can be reminded of correcting the dangerous driving behavior.
Fig. 7 is a cloud flowchart provided in an embodiment of the present application. As shown in fig. 7, the cloud server may send a message to the vehicle-mounted terminal of the target vehicle through the cache queue and the gateway, where the message may include a field configuration table and a calculation rule. The target vehicle collects driving data and environment data, and transmits the collected driving data and environment data to a vehicle-mounted terminal of the target vehicle. And the vehicle-mounted terminal generates a message, wherein the message can comprise target data or calculation data. And transmitting through the gateway device. And then the cloud server decompresses the message, transmits the message through the message queue, continuously analyzes the decompressed message data again, and transmits the decompressed message data to the cloud server based on the big data platform.
Fig. 8 is a schematic diagram of the whole embodiment of the present application. As can be seen from fig. 8, the vehicle-mounted terminal of the target vehicle may store other collected data in a built-in database. The terminal equipment can convert the target data into a unified message and send the unified message to the cloud server processor. The cloud server can display all vehicle images on the cloud, and synchronize and compare all vehicle images of the cloud with the target vehicle local image and the like.
It should be understood that, although the steps in the flowcharts of fig. 1-3 and 5-6 are shown in order as indicated by the arrows, these steps are not necessarily performed in order as indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps of FIGS. 1-3, and 5-6 may include multiple steps or stages that are not necessarily performed at the same time, but may be performed at different times, nor does the order in which the steps or stages are performed necessarily occur sequentially, but may be performed alternately or alternately with other steps or at least a portion of the steps or stages in other steps.
As shown in fig. 9, the present embodiment provides a data analysis device applied to a target vehicle, including:
An acquisition module 61 for acquiring driving data and environmental data of the target vehicle;
The determining module 62 is configured to match the driving data and the identification information of the environmental data with the field configuration table, and determine target data that needs to be reported to the cloud server in real time and other data that does not need to be reported to the cloud server in real time; the field configuration table includes identification information of the target data;
The reporting module 63 is configured to report the target data to the cloud server in real time, so that the cloud server analyzes the target data;
64 for calculating other data to monitor the driving behaviour of the target vehicle.
In one embodiment of the present application, the reporting module 63 is specifically configured to convert the target data into target format data; and uploading the target format data to the cloud server in real time.
In one embodiment of the present application, the reporting module 63 is specifically configured to obtain a data structure of the target data; extracting all data in each layer of structure according to the data structure of the target data, and adding the extracted all data into the structure identification; and splicing all the data added with the structure identifier to generate target format data.
In one embodiment of the present application, the calculation module 64 is specifically configured to obtain a calculation rule sent by the cloud server; calculating other data based on the calculation rule to obtain calculation data; based on the calculation data, analyzing the driving behaviors corresponding to the target vehicle, and visually outputting the driving behaviors corresponding to the target vehicle; and when the dangerous driving behavior of the target vehicle is determined based on the driving behavior, sending out prompt information.
In one embodiment of the present application, the computing module 64 is further configured to periodically upload the computing data to the cloud server.
As shown in fig. 10, the present embodiment provides a data analysis device applied to a cloud server, where the cloud server is connected with a target vehicle, the device includes:
a first transmitting module 71 for transmitting the field configuration table to the target vehicle;
a first receiving module 72, configured to receive target data uploaded in real time by a target vehicle based on a field configuration table; the target data being generated according to the data analysis method of any one of claims 1 to 5;
A determining module 73, configured to parse the target data and determine whether the target vehicle has dangerous driving behavior;
The second sending module 74 is configured to send alarm information to the target vehicle when there is dangerous driving behavior of the target vehicle.
As shown in fig. 10, the data analysis device provided in this embodiment further includes:
a third transmitting module 75 for transmitting the calculation rule to the target vehicle;
A second receiving module 76 for periodically receiving calculation data obtained by calculating other data based on the calculation rule by the target vehicle; the other data are data which are determined by matching the driving data and the identification information of the environmental data with the field configuration table by the target vehicle and do not need to be reported to the cloud server in real time;
An analysis module 77, configured to analyze driving behaviors of the target vehicle based on the calculation data and the target data, and visually output driving behaviors corresponding to the target vehicle;
And a fourth sending module 78, configured to send out alarm information when it is determined that the target vehicle has dangerous driving behavior based on driving behavior.
For specific limitations and beneficial effects of the data analysis device, reference may be made to the limitations of the data analysis method hereinabove, and no further description is given here. The respective modules in the above-described data analysis apparatus may be implemented in whole or in part by software, hardware, and combinations thereof. The modules can be embedded in a vehicle-mounted computing platform of the target vehicle or independent of the vehicle-mounted computing platform in a hardware mode, and can also be stored in a memory in the vehicle-mounted computing platform in a software mode, so that the processor can call and execute operations corresponding to the modules.
The embodiment of the invention also provides a target vehicle, which comprises a vehicle-mounted computing platform, wherein the vehicle-mounted computing platform is provided with the data analysis device shown in the figure 9.
FIG. 11 is a schematic structural diagram of a vehicle-mounted computing platform according to an alternative embodiment of the present invention, as shown in FIG. 11, where the vehicle-mounted computing platform may include: at least one processor 81, such as a CPU (Central Processing Unit ), at least one communication interface 83, a memory 84, at least one communication bus 82. Wherein the communication bus 82 is used to enable connected communication between these components. The communication interface 83 may include a Display screen (Display) and a Keyboard (Keyboard), and the optional communication interface 83 may further include a standard wired interface and a wireless interface. The memory 84 may be a high-speed RAM memory (Random Access Memory, volatile random access memory) or a non-volatile memory (non-volatile memory), such as at least one disk memory. The memory 84 may also optionally be at least one memory device located remotely from the aforementioned processor 81. Wherein the processor 81 may be in conjunction with the apparatus described in fig. 9, the application program is stored in the memory 84, and the processor 81 invokes the program code stored in the memory 84 for performing any of the method steps described above.
The communication bus 82 may be a peripheral component interconnect standard (PERIPHERAL COMPONENT INTERCONNECT, PCI) bus or an extended industry standard architecture (extended industry standard architecture, EISA) bus, among others. The communication bus 82 may be divided into an address bus, a data bus, a control bus, and the like. For ease of illustration, only one thick line is shown in FIG. 11, but not only one bus or one type of bus.
Wherein the memory 84 may include volatile memory (English) such as random-access memory (RAM); the memory may also include a nonvolatile memory (English: non-volatile memory), such as a flash memory (English: flash memory), a hard disk (English: HARD DISK DRIVE, abbreviation: HDD) or a solid state disk (English: solid-STATE DRIVE, abbreviation: SSD); the memory 84 may also include a combination of the types of memory described above.
The processor 81 may be a central processor (english: central processing unit, abbreviated: CPU), a network processor (english: network processor, abbreviated: NP) or a combination of CPU and NP.
The processor 81 may further include a hardware chip. The hardware chip may be an application-specific integrated circuit (ASIC), a Programmable Logic Device (PLD), or a combination thereof (English: programmable logic device). The PLD may be a complex programmable logic device (English: complex programmable logic device, abbreviated: CPLD), a field-programmable gate array (English: field-programmable GATE ARRAY, abbreviated: FPGA), a general-purpose array logic (English: GENERIC ARRAY logic, abbreviated: GAL), or any combination thereof.
Optionally, the memory 84 is also used for storing program instructions. Processor 81 may invoke program instructions to implement the data analysis methods as shown in the embodiments of the present application in fig. 1-3 and fig. 5-6.
The embodiment of the invention also provides a data analysis system, which comprises:
The target vehicle in the above embodiment, for performing the data analysis method of any one of the above embodiments;
the cloud server is connected with the target vehicle and used for executing the data analysis method in any one of the above embodiments.
The embodiment of the invention also provides a non-transitory computer storage medium, wherein the computer storage medium stores computer executable instructions, and the computer executable instructions can execute the data analysis method in any of the method embodiments. The storage medium may be a magnetic disk, an optical disk, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), a Flash Memory (Flash Memory), a hard disk (HARD DISK DRIVE, abbreviated as HDD), a Solid state disk (Solid-STATE DRIVE, SSD), or the like; the storage medium may also comprise a combination of memories of the kind described above.
Although embodiments of the present invention have been described in connection with the accompanying drawings, various modifications and variations may be made by those skilled in the art without departing from the spirit and scope of the invention, and such modifications and variations fall within the scope of the invention as defined by the appended claims.
Claims (8)
1. A data analysis method applied to a target vehicle, comprising:
acquiring driving data and environment data of the target vehicle;
Matching the driving data and the identification information of the environmental data with a field configuration table to determine target data which needs to be reported to a cloud server in real time and other data which does not need to be reported to the cloud server in real time; the field configuration table comprises identification information of the target data;
reporting the target data to the cloud server in real time so that the cloud server analyzes the target data;
calculating the other data to monitor the driving behavior of the target vehicle;
the step of reporting the target data to the cloud server in real time includes:
converting the target data into target format data;
Uploading the target format data to the cloud server in real time;
The converting the target data into target format data includes:
Acquiring a data structure of the target data;
Extracting all data in each layer of structure according to the data structure of the target data, and adding the extracted all data into a structure identifier;
and splicing all the data added with the structure identifier to generate the target format data.
2. The method of claim 1, wherein the calculating the other data to monitor driving behavior of the target vehicle comprises:
acquiring a calculation rule sent by the cloud server;
Calculating the other data based on the calculation rule to obtain calculation data;
Based on the calculated data, analyzing the driving behavior corresponding to the target vehicle, and visually outputting the driving behavior corresponding to the target vehicle;
and sending prompt information when the dangerous driving behavior of the target vehicle is determined based on the driving behavior.
3. The method according to claim 2, wherein after calculating the other data based on the calculation rule, the method further comprises:
and periodically uploading the calculated data to the cloud server.
4. A data analysis method, which is applied to a cloud server, wherein the cloud server is connected with a target vehicle, the method comprising:
Transmitting a field configuration table to the target vehicle;
Receiving target data uploaded by the target vehicle in real time based on the field configuration table; the target data being generated according to the data analysis method of any one of claims 1 to 3;
analyzing the target data to determine whether dangerous driving behaviors exist in the target vehicle;
And when dangerous driving behaviors exist in the target vehicle, sending alarm information to the target vehicle.
5. The method according to claim 4, wherein the method further comprises:
sending a calculation rule to the target vehicle;
Periodically receiving calculation data obtained by calculating other data by the target vehicle based on the calculation rule; the other data are data which are determined by matching the driving data and the environment data of the target vehicle with the field configuration table and do not need to be reported to the cloud server in real time;
Based on the calculated data and the target data, analyzing the driving behavior of the target vehicle, and visually outputting the driving behavior corresponding to the target vehicle;
And sending out alarm information when the dangerous driving behavior of the target vehicle is determined based on the driving behavior.
6. A target vehicle comprising an on-board computing platform, the on-board computing platform comprising a memory and a processor, the memory having stored therein computer instructions, the processor executing the computer instructions to perform the data analysis method of any of claims 1-5.
7. A data analysis system, comprising:
the target vehicle of claim 6 for performing the data analysis method of any one of claims 1-3;
The cloud server is connected with the target vehicle and used for executing the data analysis method of any one of claims 4-5.
8. A computer-readable storage medium storing computer instructions for causing a computer to perform the data analysis method of any one of claims 1 to 5.
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| CN112235195B (en) * | 2020-09-30 | 2022-10-11 | 博泰车联网科技(上海)股份有限公司 | Method for processing reported data and related equipment |
| CN113691888A (en) * | 2021-05-28 | 2021-11-23 | 中汽研（天津）汽车工程研究院有限公司 | A method for collection, transmission and processing of test data for unmanned vehicles |
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| CN104077819A (en) * | 2014-06-17 | 2014-10-01 | 深圳前向启创数码技术有限公司 | Remote monitoring method and system based on driving safety |
| CN111459415A (en) * | 2020-04-15 | 2020-07-28 | 腾讯科技（深圳）有限公司 | Cross-cloud data migration method, device, equipment and storage medium |
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