CN115027485A

CN115027485A - Driving behavior analysis method and system

Info

Publication number: CN115027485A
Application number: CN202210506517.2A
Authority: CN
Inventors: 卢熠婷; 黄云飞; 疏腾飞; 陈洁; 汪洋
Original assignee: Zhejiang Geely Holding Group Co Ltd; Zhejiang Geely New Energy Commercial Vehicle Group Co Ltd; Zhejiang Remote Commercial Vehicle R&D Co Ltd
Current assignee: Zhejiang Geely Holding Group Co Ltd; Zhejiang Geely New Energy Commercial Vehicle Group Co Ltd; Zhejiang Remote Commercial Vehicle R&D Co Ltd
Priority date: 2022-05-09
Filing date: 2022-05-09
Publication date: 2022-09-09

Abstract

The invention discloses a driving behavior analysis method and system, and relates to the technical field of internet of vehicles. The driving behavior analysis method is applied to a driving behavior analysis system, the driving behavior analysis system comprises a vehicle-mounted terminal, a vehicle networking platform and a big data platform, and the method comprises the following steps: the vehicle-mounted terminal acquires vehicle driving data based on a preset national standard protocol and a preset Internet of vehicles protocol, and reports the vehicle driving data to an Internet of vehicles platform; the Internet of vehicles platform sends the reported vehicle driving data to a big data platform; and the big data platform performs data processing on the vehicle driving data, judges the vehicle driving data after the data processing according to a preset bad driving judgment rule and obtains the bad driving behavior information of the vehicle. The invention widens the application range of driving behavior analysis.

Description

Driving behavior analysis method and system

Technical Field

The invention relates to the technical field of vehicle networking, in particular to a driving behavior analysis method and system.

Background

With the advent of the internet of vehicles era, more and more commercial vehicle enterprises are focusing on the after-internet market service module. For the commercial vehicle, the vehicle use cost is emphasized by the vehicle owner, but the commercial vehicle is used as a business tool of the vehicle owner, the use frequency is high, the time is long, the utilization rate of the vehicle is high, and the loss is large. And for heavy vehicles applied to scenes such as trunk logistics, the heavy vehicles are mostly purchased by companies and driven by employees, because the heavy vehicles are not vehicles of oneself, the responsibility for vehicle use and safe driving is not strong, and the vehicle is driven in the trunk and is driven outside for a long time, a captain cannot follow the vehicle, and the condition of the vehicle cannot be really known. Therefore, a vehicle owner and a vehicle fleet manager need to know actual driving conditions, driving habits and the like of a driver, but driving behavior analysis generally needs data of a plurality of in-vehicle CAN (Controller Area Network) buses, and at present, a host factory generally performs data analysis, so that the application range of the existing driving behavior analysis is narrow.

The above is only for the purpose of assisting understanding of the technical solution of the present invention, and does not represent an admission that the above is the prior art.

Disclosure of Invention

The invention mainly aims to provide a driving behavior analysis method, and aims to solve the technical problem that the existing driving behavior analysis is narrow in application range.

In order to achieve the above object, the present invention provides a driving behavior analysis method applied to a driving behavior analysis system, where the driving behavior analysis system includes a vehicle-mounted terminal, a vehicle networking platform, and a big data platform, and the driving behavior analysis method includes the following steps:

the vehicle-mounted terminal acquires vehicle driving data based on a preset national standard protocol and a preset Internet of vehicles protocol, and reports the vehicle driving data to an Internet of vehicles platform;

the Internet of vehicles platform sends the reported vehicle driving data to a big data platform;

and the big data platform performs data processing on the vehicle driving data, judges the vehicle driving data after the data processing according to a preset bad driving judgment rule and obtains the bad driving behavior information of the vehicle.

Optionally, the step of the vehicle-mounted terminal acquiring vehicle driving data based on a preset national standard protocol and a preset internet of vehicles protocol includes:

the vehicle-mounted terminal acquires corresponding national standard driving data according to a preset national standard protocol;

the vehicle-mounted terminal collects corresponding vehicle networking driving data according to a preset vehicle networking protocol, and the national standard driving data and the vehicle networking driving data are used as the vehicle driving data.

Optionally, the preset internet of vehicles protocol includes a preset internet of vehicles base protocol and a preset internet of vehicles extension protocol, and the step of acquiring corresponding internet of vehicles driving data by the vehicle-mounted terminal according to the preset internet of vehicles protocol includes:

the vehicle-mounted terminal acquires corresponding vehicle networking basic driving data according to a preset vehicle networking basic protocol;

the vehicle networking platform issues a corresponding parameter setting instruction to the vehicle-mounted terminal according to a preset vehicle networking expansion protocol;

and the vehicle-mounted terminal collects the Internet of vehicles expanded driving data according to the received parameter setting instruction, and takes the Internet of vehicles basic driving data and the Internet of vehicles expanded driving data as the Internet of vehicles driving data.

Optionally, the car networking platform includes a first car networking platform and a second car networking platform, and the step of reporting the vehicle driving data to the car networking platform includes:

the vehicle-mounted terminal reports the national standard driving data to a first vehicle networking platform through a first communication link according to a preset national standard protocol;

and the vehicle-mounted terminal reports the vehicle networking driving data to a second vehicle networking platform through a second communication link according to a preset vehicle networking protocol.

Optionally, the step of reporting the vehicle driving data to a vehicle networking platform further includes:

the vehicle-mounted terminal judges whether the vehicle has an adverse driving behavior event or not;

and if the adverse driving behavior event occurs, the vehicle-mounted terminal reports the adverse driving behavior event to the second vehicle networking platform.

Optionally, the step of sending the reported vehicle driving data to a big data platform by the internet of vehicles platform includes:

and the vehicle networking platform decrypts and deserializes the vehicle driving data and distributes the vehicle driving data to a preset message queue so that the big data platform can acquire the vehicle driving data in the preset message queue.

Optionally, the big data platform performs data processing on the vehicle driving data, and determines the vehicle driving data after the data processing according to a preset bad driving determination rule, and the step of obtaining the bad driving behavior information of the vehicle includes:

the big data platform carries out data analysis, data cleaning and standardization processing on the vehicle driving data, and stores the processed vehicle driving data to a preset database;

and the big data platform judges the vehicle driving data in a preset database according to the preset bad driving judgment rule to obtain the bad driving behavior information of the vehicle.

Optionally, the vehicle driving data includes a vehicle type, the big data platform determines the vehicle driving data in a preset database according to the preset bad driving determination rule, and the step of obtaining the bad driving behavior information of the vehicle includes:

and the big data platform determines a preset bad driving judgment rule corresponding to the vehicle driving data according to the vehicle type.

Optionally, the step of obtaining the bad driving behavior information of the vehicle by the big data platform performing data processing on the vehicle driving data and determining the vehicle driving data after the data processing according to a preset bad driving determination rule includes:

the big data platform acquires a query request of a user based on a preset interface, generates a corresponding query result according to the bad driving behavior information and the query request, and feeds the query result back to the user through the preset interface.

In order to achieve the above object, the present invention also provides a driving behavior analysis system, including:

the vehicle-mounted terminal is used for collecting vehicle driving data based on a preset national standard protocol and a preset Internet of vehicles protocol and reporting the vehicle driving data to an Internet of vehicles platform;

the vehicle networking platform is used for sending the reported vehicle driving data to the big data platform;

and the big data platform is used for carrying out data processing on the vehicle driving data, judging the vehicle driving data after the data processing according to a preset bad driving judgment rule and obtaining the bad driving behavior information of the vehicle.

The driving behavior analysis method is applied to a driving behavior analysis system, and the driving behavior analysis system comprises a vehicle-mounted terminal, a vehicle networking platform and a big data platform. The vehicle-mounted terminal acquires vehicle driving data based on a preset national standard protocol and a preset Internet of vehicles protocol, and reports the vehicle driving data to an Internet of vehicles platform; and then the vehicle networking platform sends the reported vehicle driving data to a big data platform, and finally, the big data platform performs data processing on the vehicle driving data, judges the vehicle driving data after data processing according to a preset bad driving judgment rule, and obtains the bad driving behavior information of the vehicle. The invention combines the vehicle driving data acquired by the vehicle networking protocol requirement preset by a manufacturer on the basis of the vehicle driving data acquired by the existing national standard requirement, thereby improving the abundance degree of the acquired vehicle driving data, providing more detailed vehicle driving data for subsequent driving behavior analysis, and then carrying out driving behavior analysis on the vehicle driving data through a big data platform. Compared with the existing adverse driving behavior analysis scheme, the method and the device have the advantages that on one hand, the driving behavior analysis of the driving data of the vehicle by a host manufacturer is not needed, the use threshold of the user can be reduced, and the convenience of the user for acquiring the adverse driving behavior information is improved, on the other hand, the collected driving data of the vehicle is richer and more detailed, so that the service scene of the driving behavior analysis can be richer, and therefore, the application range of the driving behavior analysis is greatly widened.

Drawings

FIG. 1 is a schematic flow chart diagram of a driving behavior analysis method according to a first embodiment of the present invention;

FIG. 2 is a diagram illustrating an exemplary process sequence of a driving behavior analysis method according to the present invention;

FIG. 3 is a schematic flow chart of a driving behavior analysis method according to a second embodiment of the present invention;

FIG. 4 is a schematic flow chart of a driving behavior analysis method according to a third embodiment of the present invention;

FIG. 5 is a diagram illustrating another example of a flow sequence of a driving behavior analysis method according to the present invention;

fig. 6 is a schematic view of a driving behavior analysis system according to an embodiment of the present invention.

The implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.

Detailed Description

It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

Since 2012, the concept of TCO (Total Cost of Ownership, full life cycle Cost) was introduced from europe into china. Since then, the concept of TCO is gradually spread and generalized in the field of commercial vehicles. Up to now, more and more commercial vehicle enterprises are focusing on the after-market service module of the internet of vehicles, and the trouble point is to reduce the cost of the TCO. Taking a running Fleetboard fleet management system as an example, the system can help large fleet customers to perform work such as transportation process monitoring, energy consumption management, driver driving habit training and the like, and finally help the customers to reduce the operation cost, namely the prototype of the TCO.

Commercial vehicles are very sensitive to energy consumption as a production efficiency tool. From the analysis of the proportion of TCO cost, the proportion of energy consumption cost reaches 31%. Through market condition analysis, the influence of the driving habits of drivers on the energy consumption of commercial vehicles is very obvious. Within the same statistical period, the vehicle runs according to different driving behaviors, and the difference of the oil consumption per hundred kilometers of the fuel vehicle can reach as much as 20L. Based on the background, if the driver driving behavior and energy consumption management can be optimized in a targeted manner by big data analysis and analysis results, the competitiveness of the product is promoted to a certain extent.

However, the driving behavior analysis needs a plurality of items of data of the CAN bus in the vehicle, and the common after-loading CAN not meet the requirements, so that the data analysis needs to be carried out by a host factory. At present, each host factory already performs various dimensional driving behavior analysis based on big data analysis, provides analysis data for drivers and fleet managers, and reduces energy consumption and vehicle damage.

Referring to fig. 1, fig. 1 is a schematic flow chart of a driving behavior analysis method according to a first embodiment of the present invention.

The first embodiment of the invention provides a driving behavior analysis method, which is applied to a driving behavior analysis system, wherein the driving behavior analysis system comprises a vehicle-mounted terminal, a vehicle networking platform and a big data platform, and the driving behavior analysis method comprises the following steps:

step S100, the vehicle-mounted terminal collects vehicle driving data based on a preset national standard protocol and a preset Internet of vehicles protocol, and reports the vehicle driving data to an Internet of vehicles platform;

specifically, the driving behavior analysis method of the embodiment is applied to a driving behavior analysis system, and the driving behavior analysis system includes a vehicle-mounted terminal (i.e., a vehicle-mounted T-BOX, Telematics BOX), a vehicle networking platform (i.e., a TSP platform, Telematics Service Provider) and a big data platform. The preset national standard protocol is a national standard protocol related to data acquisition corresponding to the vehicle, for example, a heavy-duty diesel vehicle, and the corresponding national standard is GB17691, in which contents such as data items (such as information of an engine state, an engine fuel flow, GPS information, an accumulated mileage, and the like), a communication protocol, a data packet structure, and the like, which require a vehicle-mounted terminal of the heavy-duty diesel vehicle to report data to a vehicle networking platform are specified. Of course, the present embodiment is not limited to heavy-duty diesel vehicles, and the predetermined national standard protocol may also be GB/T32960 technical specification for remote service and management system for electric vehicles, HJ 1239 technical specification for remote monitoring of emissions of heavy-duty vehicles, and other relevant specifications. The vehicle-mounted terminal can acquire corresponding data items of the vehicle according to a preset national standard protocol so as to acquire corresponding vehicle driving data and report the corresponding vehicle driving data to the Internet of vehicles platform. The preset Internet of vehicles protocol is a protocol set by a manufacturer for data transmission between the vehicle-mounted terminal and the Internet of vehicles platform, and specifies the data items (such as information of fuel type, gearbox type, vehicle ignition and flameout state, hand brake state, maximum vehicle speed and the like), communication protocol, data packet structure and the like which are required by the manufacturer or a user and reported by the vehicle-mounted terminal to the Internet of vehicles platform. Therefore, the vehicle-mounted terminal can acquire the corresponding data items according to the preset vehicle networking protocol, so that the corresponding vehicle driving data can be acquired and reported to the vehicle networking platform. The vehicle driving data comprises vehicle data acquired according to the requirements of a preset national standard protocol and a preset Internet of vehicles protocol. The reporting frequency of the data reported by the vehicle-mounted terminal to the internet of vehicles platform can be set according to specific requirements, such as 1/second, 1/10 second and the like.

In this embodiment, on the basis of the vehicle driving data that the current national standard required to gather, the vehicle driving data that the car networking agreement that combines the preset of manufacturer required to gather to improve the abundance of the vehicle driving data who gathers, provide more detailed vehicle driving data for subsequent driving behavior analysis.

Furthermore, the step of the vehicle-mounted terminal collecting the vehicle driving data based on the preset national standard protocol and the preset internet of vehicles protocol comprises the following steps:

step S110, the vehicle-mounted terminal collects corresponding national standard driving data according to a preset national standard protocol;

and step S120, the vehicle-mounted terminal acquires corresponding vehicle networking driving data according to a preset vehicle networking protocol, and the national standard driving data and the vehicle networking driving data are used as the vehicle driving data.

Specifically, the national standard driving data is a data item of the vehicle required to be acquired by the preset national standard protocol, and the internet of vehicles driving data is a data item of the vehicle required to be acquired by the preset internet of vehicles protocol. The vehicle driving data comprises national standard driving data and internet of vehicles driving data. The vehicle-mounted terminal can acquire corresponding national standard driving data according to a preset national standard protocol and acquire corresponding Internet of vehicles driving data according to a preset Internet of vehicles protocol.

Furthermore, the vehicle networking platform comprises a first vehicle networking platform and a second vehicle networking platform, and the step of reporting the vehicle driving data to the vehicle networking platform comprises:

step S130, the vehicle-mounted terminal reports the national standard driving data to a first vehicle networking platform through a first communication link according to a preset national standard protocol;

and S131, the vehicle-mounted terminal reports the vehicle networking driving data to a second vehicle networking platform through a second communication link according to a preset vehicle networking protocol.

Specifically, the vehicle networking platform comprises a first vehicle networking platform and a second vehicle networking platform, wherein the first vehicle networking platform is used for receiving national standard driving data reported by the vehicle-mounted terminal, and the second vehicle networking platform is used for receiving vehicle networking driving data reported by the vehicle-mounted terminal. The vehicle-mounted terminal can report the national standard driving data to a first vehicle networking platform through a first communication link according to a preset national standard protocol, and report the vehicle networking driving data to a second vehicle networking platform through a second communication link according to a preset vehicle networking protocol.

Further, the step of reporting the vehicle driving data to the vehicle networking platform further includes:

step S140, the vehicle-mounted terminal judges whether the vehicle has an adverse driving behavior event;

and step S141, if the adverse driving behavior event occurs, the vehicle-mounted terminal reports the adverse driving behavior event to the second vehicle networking platform.

Specifically, the vehicle may be provided with a function of detecting a specific undesirable driving behavior (for example, a non-belted vehicle, a non-cornering turn signal, a sudden acceleration, a sudden deceleration, a sudden turn, a neutral coasting, or the like) which is different in type depending on the type of the vehicle and which can be directly detected by the vehicle. When the vehicle detects the specific undesirable driving behavior, a corresponding undesirable driving behavior event signal is transmitted in the CAN bus of the vehicle. The vehicle-mounted terminal CAN judge whether the vehicle has an adverse driving behavior event or not according to the adverse driving behavior event signal in the CAN bus; if the vehicle has an adverse driving behavior event, the vehicle-mounted terminal can report the adverse driving behavior event to the second vehicle networking platform. In this embodiment, the vehicle-mounted terminal may determine whether the vehicle has an adverse driving behavior event by detecting a specific adverse driving behavior of the vehicle, and report the adverse driving behavior event when the vehicle has the adverse driving behavior event. On the one hand, the influence of other external factors is avoided through the detection of the vehicle to the specific bad driving behavior, so that the obtained judgment result of the bad driving behavior is more accurate, on the other hand, the specific bad driving behavior is not required to be further judged by a large data platform, and the analysis of the bad driving behavior is more convenient.

Further, the preset car networking protocol includes a preset car networking base protocol and a preset car networking extension protocol, and step S120 further includes the following steps:

step S121, the vehicle-mounted terminal collects corresponding vehicle networking basic driving data according to a preset vehicle networking basic protocol;

step S122, the Internet of vehicles platform issues a corresponding parameter setting instruction to the vehicle-mounted terminal according to a preset Internet of vehicles extension protocol;

and S123, acquiring the Internet of vehicles extended driving data by the vehicle-mounted terminal according to the received parameter setting instruction, and taking the Internet of vehicles basic driving data and the Internet of vehicles extended driving data as the Internet of vehicles driving data.

Specifically, preset car networking protocol includes preset car networking basic protocol and preset car networking extension protocol, preset car networking basic protocol can be used for stipulating the basic data item of the vehicle that requires to gather, basic information such as air conditioner open state, safety belt state, manual brake state, fault code, indicator state. The preset internet of vehicles extension protocol may be used to specify data items that are not included in the preset national standard protocol and the preset internet of vehicles base protocol, such as data items of an engine model, an accelerator pedal opening, a brake pedal opening, a steering wheel angle position, an ACC (Adaptive Cruise Control) state, and the like, where the data items required to be collected by the preset internet of vehicles extension protocol may be set by a manufacturer or a user according to specific service requirements. The vehicle-mounted terminal collects corresponding vehicle networking basic driving data according to a preset vehicle networking basic protocol and reports the vehicle networking basic driving data to a second vehicle networking platform. And for data items which are not contained in the preset national standard protocol and the preset Internet of vehicles basic protocol, the Internet of vehicles platform issues a corresponding parameter setting instruction to the vehicle-mounted terminal according to the preset Internet of vehicles extension protocol. And then, the vehicle-mounted terminal collects CAN data items in a CAN bus of the vehicle according to the received parameter setting instruction to obtain the Internet of vehicles extended driving data, and the Internet of vehicles basic driving data and the Internet of vehicles extended driving data are used as the Internet of vehicles driving data. The vehicle-mounted terminal reports the vehicle networking basic driving data to a second vehicle networking platform according to a preset vehicle networking basic protocol, and reports the vehicle networking extended driving data to the second vehicle networking platform according to a preset vehicle networking extended protocol.

Referring to fig. 2, fig. 2 is a diagram illustrating an exemplary process sequence of the driving behavior analysis method according to the present invention. The driving behavior analysis method of the embodiment is applied to a driving behavior analysis system, and the driving behavior analysis system may include a vehicle-mounted terminal (i.e., T-BOX), a first vehicle networking platform (i.e., TSP1.0), a second vehicle networking platform (i.e., TSP2.0), and a big data platform.

In the preset national standard protocol in fig. 2, for example, GB17691, when a vehicle is started or powered on at idle speed, the T-BOX is woken up, and is triggered to acquire data of each component and to report it.

The T-BOX reports data according to a TSP basic protocol (namely a preset Internet of vehicles basic protocol) by using a communication link, and the reporting frequency of the data can be reported to TSP2.0 in real time by taking 1/10 second as a period;

when the T-BOX judges that the vehicle has an adverse driving behavior event, triggering event reporting, and reporting the adverse driving behavior event to the TSP 2.0:

the T-BOX reports data according to a GB17691 protocol by using another communication link, and the reporting frequency of the data can be reported to TSP1.0 in real time by taking 1/1 second as a period;

for data items which are not provided in the GB17691 protocol and the TSP basic protocol, the T-BOX may collect and report corresponding data items in a manner that the TSP2.0 issues a parameter setting instruction (i.e., a CAN data reporting instruction in fig. 3) to the T-BOX, and the reporting frequency of the data may be supplemented and reported to the TSP2.0 in real time in a period of 1 piece/1 second. After receiving the parameter setting instruction, the T-BOX reports data according to a preset reporting frequency in a form of a TSP (short message service) extended protocol (namely, a preset Internet of vehicles extended protocol).

Taking the following table 1 as an example, taking the preset national standard protocol as GB17691 as an example, the data format obtained by the vehicle-mounted terminal is 17691 data items, the data format obtained by the vehicle-mounted terminal based on the preset internet of vehicles basic protocol is TSP data items, and the data format obtained by the vehicle-mounted terminal based on the preset internet of vehicles extended protocol is CAN data items.

TABLE 1 vehicle driving data reported by the vehicle-mounted terminal

Step S200, the Internet of vehicles platform sends the reported vehicle driving data to a big data platform;

specifically, after the vehicle networking platform obtains the vehicle driving data reported by the vehicle-mounted terminal, the vehicle driving data can be processed and then distributed to the message queue, so that the big data platform can obtain the vehicle driving data in the message queue, and data transmission from the vehicle networking platform to the big data platform is realized. Of course, other data transmission methods can be adopted, and are not limited to the above method.

Further, step S200 may include the steps of:

and step S210, the vehicle networking platform decrypts and deserializes the vehicle driving data and distributes the vehicle driving data to a preset message queue so that the big data platform can obtain the vehicle driving data in the preset message queue.

Specifically, the vehicle networking platform performs data processing operations such as encrypted message decryption and protobuf format data deserialization on the vehicle driving data reported by the vehicle-mounted terminal, and then distributes the processed vehicle driving data to a preset message queue, so that the big data platform obtains the vehicle driving data in the preset message queue, and data transmission from the vehicle networking platform to the big data platform is realized.

Referring to fig. 2, fig. 2 is a diagram illustrating an exemplary flow sequence of the driving behavior analysis method according to the present invention. The internet of vehicles platform comprises a first internet of vehicles platform (namely TSP1.0) and a second internet of vehicles platform (namely TSP 2.0). TSP1.0 carries out data processing operations such as encrypted message decryption and protobuf format data deserialization on data reported by the T-BOX based on a GB 17961 protocol, and then the processed data are distributed to a preset message queue. The TSP2.0 also performs data processing operations such as encrypted message decryption and protobuf format data deserialization on the T-BOX based on data reported by a preset Internet of vehicles basic protocol and a preset Internet of vehicles extended protocol, and then distributes the processed data to another preset message queue.

And step S300, the big data platform performs data processing on the vehicle driving data, and judges the vehicle driving data after the data processing according to a preset bad driving judgment rule to obtain the bad driving behavior information of the vehicle.

Specifically, the data processing may include processing operations such as data analysis, data cleaning, standardization processing, storage and warehousing. The bad driving determination rule is preset as a rule set by a manufacturer for determining bad driving behavior. Taking the example that the bad driving behavior is dangerous speed driving, the number of times is counted according to the duration of the driving state with the vehicle speed more than 100km/h, and the number is accumulated for more than 5 seconds to count one dangerous speed driving. After the driving state is changed in a single trip, the driving state with the vehicle speed of more than 100km/h is maintained for more than 3 seconds, and the driving is repeated to be the dangerous speed driving, wherein the trip is determined as engine ON → engine OFF, namely the driving from the start of the engine to the stop of the engine is recorded as a trip. After the big data platform obtains the vehicle driving data, the big data platform performs data processing operations such as data analysis, data cleaning, standardization processing and storage and warehousing on the obtained vehicle driving data so as to support further application such as subsequent data processing, query and analysis. And then, the big data platform judges the vehicle driving data after data processing through a preset bad driving judgment rule, so as to obtain the bad driving behavior information of the vehicle. The bad driving behavior information may include information such as the number of bad driving behaviors, the type of the bad driving behavior, the occurrence time of the bad driving behavior, and the occurrence location of the bad driving behavior, and may also include other information such as the driving mileage, the driving fuel consumption, the failure rate, and the average speed of the vehicle.

Further, step S300 further includes the steps of:

step S310, the big data platform carries out data analysis, data cleaning and standardization processing on the vehicle driving data, and stores the processed vehicle driving data into a preset database;

and step S320, the big data platform judges the vehicle driving data in a preset database according to the preset bad driving judgment rule to obtain the bad driving behavior information of the vehicle.

Specifically, the big data platform performs data analysis, data cleaning and standardization processing on the vehicle driving data, and stores the processed vehicle driving data in a preset database. In the embodiment, the big data platform restores the acquired vehicle driving data through data analysis, fills up missing values and deletes and corrects abnormal values and jump values of the acquired vehicle driving data through data cleaning, and eliminates differences of the vehicle driving data in the aspects of sources, formats, data quality and the like through standardization. And the vehicle driving data are subjected to data processing operations such as data analysis, data cleaning and standardization processing, so that further application of subsequent data processing, query, analysis and the like is supported. And then storing the data processed vehicle driving data into a preset database, wherein the preset database can be a MySQL database, an HBase database, an Oracle database, a DB2 database, an SQL Server database and the like. And finally, the big data platform judges and counts the vehicle driving data in a preset database according to the preset bad driving judgment rule to form a mild aggregate data layer and data summarization, so as to obtain the bad driving behavior information of the vehicle.

Referring to fig. 2, fig. 2 is a diagram illustrating an exemplary flow sequence of the driving behavior analysis method according to the present invention. The big data platform obtains the vehicle driving data reported to the vehicle networking platform by the T-BOX through real-time consumption of the data of the TSP1.0 and the TSP2.0, and then carries out data processing operations such as data analysis, data cleaning, standardized processing, storage and warehousing on the vehicle driving data so as to support further application of subsequent data processing, query, analysis and the like. And then the big data platform carries out data calculation according to the actual analysis service scene and the preset bad driving behavior judgment rule to form a light aggregation data layer and data summarization so as to obtain the bad driving behavior information of the vehicle. In addition, the big data platform also provides an interface for acquiring data for a user to acquire the bad driving behavior information.

The invention provides a driving behavior analysis method which is applied to a driving behavior analysis system. The vehicle-mounted terminal acquires vehicle driving data based on a preset national standard protocol and a preset Internet of vehicles protocol, and reports the vehicle driving data to an Internet of vehicles platform; and then the vehicle networking platform sends the reported vehicle driving data to a big data platform, and finally, the big data platform performs data processing on the vehicle driving data, judges the vehicle driving data after data processing according to a preset bad driving judgment rule, and obtains the bad driving behavior information of the vehicle. On the basis of the vehicle driving data acquired according to the national standard, the vehicle driving data acquired according to the preset vehicle networking protocol requirements of manufacturers are combined, so that the abundance of the acquired vehicle driving data is improved, more detailed vehicle driving data are provided for subsequent driving behavior analysis, and the vehicle driving data are subjected to driving behavior analysis through a big data platform. Compared with the existing adverse driving behavior analysis scheme, the method and the device have the advantages that on one hand, the host manufacturer is not required to analyze the driving behavior of the driving data of the vehicle, the use threshold of the user can be reduced, and the convenience of the user for acquiring the adverse driving behavior information is improved, on the other hand, the collected driving data of the vehicle is richer and more detailed, so that the service scene of the driving behavior analysis can be richer, and therefore the application range of the driving behavior analysis is greatly widened.

Further, referring to fig. 3, a second embodiment of the present invention provides a driving behavior analysis method, based on the above embodiment shown in fig. 1, where the vehicle driving data includes a vehicle type, and before step S300, the method further includes the following steps:

and S330, determining a preset bad driving judgment rule corresponding to the vehicle driving data by the big data platform according to the vehicle type.

Specifically, before the big data platform determines the vehicle driving data, a preset bad driving determination rule corresponding to the vehicle driving data may be determined according to the vehicle type. The vehicle type may be a classification of the vehicle (e.g., heavy duty truck, light passenger car, large bus, etc.) or may be an engine type employed by the vehicle (e.g., diesel engine, gasoline engine, electric motor, hybrid engine, etc.). A manufacturer can set corresponding preset bad driving judgment rules according to different vehicle types, so that the big data platform can select the corresponding preset bad driving judgment rules according to the vehicle types. Therefore, different preset bad driving judgment rules can be selected according to different vehicle types, so that analysis of bad driving behaviors can be adapted to different engines and different vehicle types, and the accuracy and the applicability of analysis of the bad driving behaviors are improved. Taking the following table 2 as an example, the preset bad driving determination rule is as follows:

table 2 Preset bad Driving decision rules

It is to be understood that the preset bad driving determination rule is only an example, and the preset bad driving determination rule may be set according to specific requirements in practical applications.

Further, referring to fig. 4, a third embodiment of the present invention provides a driving behavior analysis method, based on the above embodiment shown in fig. 1, further including the following steps after step S300:

and S400, the big data platform acquires a query request of a user based on a preset interface, generates a corresponding query result according to the bad driving behavior information and the query request, and feeds the query result back to the user through the preset interface.

Specifically, the big data platform needs to provide a preset interface for a user to call and acquire data through the APP and the intelligent fleet management platform. The interface design needs to integrate a token (token is a kind of connection identification, often represented by a string of characters, and is a token for communicating with the server) system of the user center. The preset interface provided by the big data platform for the APP is a driving behavior interface of the bicycle. The preset interfaces provided by the big data platform to the intelligent fleet management platform are a single-vehicle driving behavior interface and a multi-vehicle driving behavior interface.

The query request may include a specified time period for the user. The query result may include the vehicle accumulated driving data, the vehicle trip driving data, and the details of the bad driving behavior in the specified time period, and if there are multiple vehicles, the query result may further include multiple vehicle driving data. Referring to fig. 5, fig. 5 is another exemplary diagram of the flow timing sequence of the driving behavior analysis method of the present invention. The user can log in the intelligent fleet management platform, and statistical result data are obtained through a preset interface and visually presented. The user can acquire statistical result data of a single vehicle in a specified time period through the single vehicle driving behavior interface and acquire statistical result data of a plurality of vehicles in the specified time period through the multi-vehicle driving behavior interface based on the intelligent fleet management platform. And then the big data platform returns corresponding query result data through a preset interface, and the intelligent fleet management platform performs visual presentation according to the returned query data result for a user to check. In addition, a user can log in the APP to inquire the driving data in the appointed time period through a preset interface, and the APP performs visual presentation according to the returned data result.

The user can inquire the vehicle accumulated driving data of the selected vehicle in a specified time period through the APP or the fleet management platform, wherein the vehicle accumulated driving data can comprise the accumulated driving mileage, the accumulated total fuel consumption, the accumulated times of bad driving behaviors and the like of the selected vehicle in the specified time period. The big data platform can obtain the daily driving mileage of the bicycle by statistics based on GB17691 data items (accumulated mileage); based on a GB17691 data item [ engine fuel flow ], the daily oil consumption of the single vehicle is obtained through statistics; and (4) counting the times of the bad driving behaviors of the bicycle every day based on the combined judgment of the TSP data item and the GB17691 data item. The calculation of the vehicle accumulated driving data is explained as shown in the following table 3,

TABLE 3 vehicle cumulative Driving data calculation description

The user can inquire the vehicle travel driving data divided according to the travel of the selected vehicle in the specified time period through the APP. The vehicle trip driving data may include a mileage, a total oil consumption, a trip start point, a trip end point, a trip start time, a trip end time, a number of bad driving behaviors, a trip average speed, a fuel consumption per hundred kilometers trip, a trip duration, etc. for each trip of the selected vehicle within a specified time period. The big data platform can obtain the travel starting time and the travel ending time through calculation based on a GB17691 data item (engine state); based on a GB17691 data item [ engine fuel flow ], the total oil consumption in driving is obtained through calculation; and (4) counting the times of bad driving behaviors in the single-vehicle journey based on the combined judgment of the TSP data item and the GB17691 data item. Based on a GB17691 data item (GPS information), a travel starting point and a travel end point are obtained by calculating and carrying out inverse geocoding; and calculating to obtain the driving mileage based on GB17691 data items (accumulated mileage and engine state). The calculation of the vehicle trip driving data is illustrated in table 4 below,

table 4 vehicle trip driving data calculation description

A user can inquire the multi-vehicle driving data of the named vehicle in a specified time period through the intelligent fleet management platform. The multi-vehicle driving data may include hundreds of kilometers of energy consumption, bad driving behavior, vehicle failure rate, accumulated operating mileage, etc. of a plurality of vehicles under the user name within a specified time period. The big data platform can obtain the fault rate of the single vehicle through calculation based on GB17691 data items (OBD fault); based on GB17691 data items [ engine fuel flow and operation mileage ], the hundred kilometers of energy consumption is obtained through calculation; and (4) counting the times of the bad driving behaviors of the bicycle every day based on the combined judgment of the TSP data item and the GB17691 data item. Based on GB17691 data item [ accumulated mileage ], the accumulated operation mileage is obtained through calculation. The calculation of the multi-vehicle driving data is described in table 5 below,

TABLE 5 Multi-vehicle Driving data calculation description

The user can inquire the details of the bad driving behaviors of the named vehicle in the specified time period through the APP, wherein the details of the bad driving behaviors can comprise the record details of the bad driving behaviors of the named vehicle in the specified time period, such as the frequency of the bad driving behaviors, the type and the occurrence time of the bad driving behaviors, the occurrence place of the bad driving behaviors and the like. The big data platform can be judged based on the combination of the TSP data item and the GB17691 data item, and statistics is carried out to obtain the detail of the daily bad driving behaviors of the bicycle. The detailed calculation of the bad driving behavior is shown in table 6 below,

TABLE 6 detailed description of bad driving behavior

In addition, the preset interface provided by the big data platform to the APP may include: the system comprises a vehicle accumulated driving data interface, a vehicle travel driving data interface and a bad driving behavior detail interface; the preset interface provided for the intelligent motorcade management platform comprises: the vehicle driving data interface comprises a vehicle accumulated driving data interface and a multi-vehicle driving data interface. The detailed requirements for the above-mentioned preset interface are shown in tables 7, 8, 9 and 10 below:

TABLE 7 cumulative driving data interface requirements field for vehicle

TABLE 8 vehicle trip driving data interface requirements field

TABLE 9 Multi-vehicle Driving data interface requirement field

TABLE 10 interface requirements for bad driving behavior details field

Referring to fig. 6, fig. 6 is a schematic diagram of a driving behavior analysis system according to an embodiment of the present invention.

As shown in fig. 6, an embodiment of the present invention provides a driving behavior analysis system, including:

the vehicle-mounted terminal 10 is used for acquiring vehicle driving data based on a preset national standard protocol and a preset internet of vehicles protocol, and reporting the vehicle driving data to the internet of vehicles platform 20;

the vehicle networking platform 20 is used for sending the reported vehicle driving data to the big data platform 30;

and the big data platform 30 is used for carrying out data processing on the vehicle driving data, judging the vehicle driving data after the data processing according to a preset bad driving judgment rule and obtaining the bad driving behavior information of the vehicle.

Still further, the driving behavior analysis system further includes:

the vehicle-mounted terminal 10 is used for acquiring corresponding national standard driving data according to a preset national standard protocol;

and the vehicle-mounted terminal 10 is used for acquiring corresponding vehicle networking driving data according to a preset vehicle networking protocol, and taking the national standard driving data and the vehicle networking driving data as the vehicle driving data.

Still further, the preset internet of vehicles protocol includes a preset internet of vehicles base protocol and a preset internet of vehicles extension protocol, and the driving behavior analysis system further includes:

the vehicle-mounted terminal 10 is used for acquiring corresponding vehicle networking basic driving data according to a preset vehicle networking basic protocol;

the vehicle networking platform 20 is used for issuing a corresponding parameter setting instruction to the vehicle-mounted terminal 10 according to the demand data;

and the vehicle-mounted terminal 10 is used for acquiring the Internet of vehicles expanded driving data according to the received parameter setting instruction, and taking the Internet of vehicles basic driving data and the Internet of vehicles expanded driving data as the Internet of vehicles driving data.

Still further, the internet of vehicles platform 20 includes a first internet of vehicles platform 21 and a second internet of vehicles platform 22, and the driving behavior analysis system further includes:

the vehicle-mounted terminal 10 is used for reporting the national standard driving data to a first vehicle networking platform 21 through a first communication link according to a preset national standard protocol;

and the vehicle-mounted terminal 10 is configured to report the vehicle networking driving data to the second vehicle networking platform 22 through the second communication link according to a preset vehicle networking protocol.

Still further, the driving behavior analysis system further includes:

the vehicle-mounted terminal 10 is used for judging whether the vehicle has an adverse driving behavior event or not;

if an adverse driving behavior event occurs, the vehicle-mounted terminal 10 reports the adverse driving behavior event to the second vehicle networking platform 22.

Still further, the driving behavior analysis system further includes:

and the vehicle networking platform 20 is configured to decrypt and deserialize the vehicle driving data, and distribute the vehicle driving data to a preset message queue, so that the big data platform 30 acquires the vehicle driving data in the preset message queue.

Still further, the driving behavior analysis system further includes:

the big data platform 30 is used for performing data analysis, data cleaning and standardization processing on the vehicle driving data and storing the processed vehicle driving data into a preset database;

and the big data platform 30 is used for judging the vehicle driving data in the preset database according to the preset bad driving judgment rule to obtain the bad driving behavior information of the vehicle.

Still further, the vehicle driving data includes a vehicle type, and the driving behavior analysis system further includes:

and the big data platform 30 is used for determining a preset bad driving judgment rule corresponding to the vehicle driving data according to the vehicle type.

Still further, the driving behavior analysis system further includes:

and the big data platform 30 is used for acquiring a query request of a user based on a preset interface, generating a corresponding query result according to the bad driving behavior information and the query request, and feeding the query result back to the user through the preset interface.

It should be noted that, in this document, relational terms such as first and second, and the like are only used for distinguishing one entity/operation/object from another entity/operation/object, and do not necessarily require or imply any actual relationship or order between these entities/operations/objects; the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in the process, method, article, or system in which the element is included.

For the apparatus embodiment, since it is substantially similar to the method embodiment, it is described relatively simply, and reference may be made to some descriptions of the method embodiment for relevant points. The above-described apparatus embodiments are merely illustrative, in that elements described as separate components may or may not be physically separate. Some or all of the modules can be selected according to actual needs to achieve the purpose of the scheme of the invention. One of ordinary skill in the art can understand and implement it without inventive effort.

The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.

Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solution of the present invention or the portions contributing to the prior art may be embodied in the form of a software product, which is stored in a storage medium (such as ROM/RAM, magnetic disk, optical disk) as described above and includes several instructions for enabling a terminal device (which may be a mobile phone, a computer, a server, a vehicle, or a network device, etc.) to execute the method according to the embodiments of the present invention.

The above description is only a preferred embodiment of the present invention, and is not intended to limit the scope of the present invention, and all equivalent structures or equivalent processes performed by the present invention or directly or indirectly applied to other related technical fields are also included in the scope of the present invention.

Claims

1. A driving behavior analysis method is applied to a driving behavior analysis system, the driving behavior analysis system comprises a vehicle-mounted terminal, a vehicle networking platform and a big data platform, and the driving behavior analysis method is characterized by comprising the following steps:

2. The driving behavior analysis method according to claim 1, wherein the step of the vehicle-mounted terminal acquiring the driving data of the vehicle based on a preset national standard protocol and a preset internet of vehicles protocol comprises:

3. The driving behavior analysis method according to claim 2, wherein the preset internet of vehicles protocol includes a preset internet of vehicles base protocol and a preset internet of vehicles extension protocol, and the step of the vehicle-mounted terminal acquiring corresponding internet of vehicles driving data according to the preset internet of vehicles protocol includes:

4. The driving behavior analysis method of claim 2, wherein the vehicle networking platform comprises a first vehicle networking platform and a second vehicle networking platform, and the step of reporting the vehicle driving data to the vehicle networking platform comprises:

5. The driving behavior analysis method of claim 4, wherein reporting the vehicle driving data to a vehicle networking platform further comprises:

6. The driving behavior analysis method of claim 1, wherein the step of the internet of vehicles platform sending the reported vehicle driving data to a big data platform comprises:

7. The driving behavior analysis method according to claim 1, wherein the big data platform performs data processing on the vehicle driving data, and determines the data-processed vehicle driving data according to a preset bad driving determination rule, and the step of obtaining the bad driving behavior information of the vehicle comprises:

8. The driving behavior analysis method according to claim 7, wherein the vehicle driving data includes a vehicle type, the big data platform determines the vehicle driving data in a preset database according to the preset bad driving determination rule, and the step of obtaining the bad driving behavior information of the vehicle is preceded by:

9. The driving behavior analysis method according to any one of claims 1 to 8, wherein the big data platform performs data processing on the vehicle driving data, and determines the data-processed vehicle driving data according to a preset bad driving determination rule, and the step of obtaining the bad driving behavior information of the vehicle is followed by:

10. A driving behavior analysis system, characterized in that the driving behavior analysis system comprises: