Driving behavior analysis methods and systems

Abstract

This invention discloses a driving behavior analysis method and system, relating to the field of vehicle networking technology. The driving behavior analysis method is applied to a driving behavior analysis system, which includes an in-vehicle terminal, a vehicle networking platform, and a big data platform. The method includes the following steps: the in-vehicle terminal collects vehicle driving data based on a preset national standard protocol and a preset vehicle networking protocol, and reports the vehicle driving data to the vehicle networking platform; the vehicle networking platform sends the reported vehicle driving data to the big data platform; the big data platform processes the vehicle driving data and judges the processed vehicle driving data according to preset rules for judging poor driving behavior, thereby obtaining information on poor driving behavior of the vehicle. This invention broadens the applicability of driving behavior analysis.

Description

Technical Field

[0001] This invention relates to the field of vehicle networking technology, and in particular to a driving behavior analysis method and system. Background Technology

[0002] With the advent of the Internet of Vehicles (IoV) era, more and more commercial vehicle companies are focusing on IoV aftermarket service modules. For commercial vehicles, owners prioritize operating costs, but these vehicles, as their livelihood tools, are used frequently and for extended periods, resulting in high utilization and wear and tear. For heavy-duty vehicles used in long-haul logistics and other scenarios, many are purchased by companies and driven by employees. Because these vehicles are not owned by the drivers, there is often a lack of responsibility for vehicle use and safe driving. Furthermore, these vehicles operate on long routes and are frequently on the road, making it impossible for fleet managers to accompany them and gain a true understanding of the vehicles' condition. Therefore, vehicle owners and fleet managers need to understand the actual driving conditions and habits of drivers. However, driving behavior analysis typically requires data from multiple in-vehicle CAN (Controller Area Network) buses, which is currently usually analyzed by the OEM (Original Equipment Manufacturer), thus limiting the applicability of existing driving behavior analysis methods.

[0003] The above content is only used to help understand the technical solution of the present invention and does not represent an admission that the above content is prior art. Summary of the Invention

[0004] The main objective of this invention is to provide a driving behavior analysis method that addresses the technical problem of the narrow applicability of existing driving behavior analysis methods.

[0005] To achieve the above objectives, the present invention provides a driving behavior analysis method applied to a driving behavior analysis system, the driving behavior analysis system including an in-vehicle terminal, a vehicle networking platform, and a big data platform, the driving behavior analysis method comprising the following steps:

[0006] The vehicle terminal collects vehicle driving data based on a preset national standard protocol and a preset vehicle network protocol, and reports the vehicle driving data to the vehicle network platform.

[0007] The vehicle-to-everything (V2X) platform will send the reported vehicle driving data to the big data platform;

[0008] The big data platform processes the vehicle driving data and judges the processed vehicle driving data according to preset bad driving judgment rules to obtain information on bad driving behavior of the vehicle.

[0009] Optionally, the step of the vehicle-mounted terminal collecting vehicle driving data based on a preset national standard protocol and a preset vehicle networking protocol includes:

[0010] The vehicle-mounted terminal collects corresponding national standard driving data according to a preset national standard protocol;

[0011] The vehicle terminal collects corresponding vehicle network driving data according to a preset vehicle network protocol, and uses the national standard driving data and vehicle network driving data as the vehicle driving data.

[0012] Optionally, the preset vehicle-to-everything (V2X) protocol includes a preset basic V2X protocol and a preset extended V2X protocol. The steps for the on-board terminal to collect corresponding V2X driving data according to the preset V2X protocol include:

[0013] The vehicle terminal collects corresponding basic vehicle-to-everything (V2X) driving data according to the preset V2X basic protocol.

[0014] The vehicle-to-everything (V2X) platform sends corresponding parameter setting instructions to the vehicle terminal according to the preset V2X extended protocol;

[0015] The vehicle terminal collects extended driving data of the Internet of Vehicles according to the received parameter setting instructions, and uses the basic driving data of the Internet of Vehicles and the extended driving data of the Internet of Vehicles as the driving data of the Internet of Vehicles.

[0016] Optionally, the vehicle networking platform includes 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 includes:

[0017] The vehicle terminal reports the national standard driving data to the first vehicle network platform via the first communication link according to the preset national standard protocol;

[0018] The vehicle terminal reports the vehicle-to-everything (V2X) driving data to the second V2X platform via a second communication link according to a preset V2X protocol.

[0019] Optionally, the step of reporting the vehicle driving data to the vehicle network platform further includes:

[0020] The in-vehicle terminal determines whether the vehicle has engaged in any unsafe driving behavior events.

[0021] If an incident of improper driving behavior occurs, the on-board terminal will report the incident to the second vehicle network platform.

[0022] Optionally, the step of the vehicle networking platform sending the reported vehicle driving data to the big data platform includes:

[0023] The vehicle networking platform decrypts and deserializes the vehicle driving data and distributes it to a preset message queue, so that the big data platform can obtain the vehicle driving data in the preset message queue.

[0024] Optionally, the big data platform processes the vehicle driving data and judges the processed vehicle driving data according to preset bad driving judgment rules to obtain information on bad driving behavior of the vehicle, including the following steps:

[0025] The big data platform performs data analysis, data cleaning, and standardization on the vehicle driving data, and stores the processed vehicle driving data in a preset database;

[0026] The big data platform judges vehicle driving data in the preset database according to the preset bad driving judgment rules to obtain information on bad driving behavior of vehicles.

[0027] Optionally, the vehicle driving data includes vehicle type. Before the step of the big data platform judging the vehicle driving data in the preset database according to the preset bad driving judgment rules to obtain the vehicle's bad driving behavior information, the following steps are included:

[0028] The big data platform determines the preset bad driving judgment rules corresponding to the vehicle driving data based on the vehicle type.

[0029] Optionally, after the big data platform processes the vehicle driving data and judges the processed vehicle driving data according to preset bad driving judgment rules to obtain information on the vehicle's bad driving behavior, the following steps are included:

[0030] The big data platform obtains user query requests based on a preset interface, generates corresponding query results based on the bad driving behavior information and the query request, and feeds back the query results to the user through the preset interface.

[0031] To achieve the above objectives, the present invention also provides a driving behavior analysis system, the driving behavior analysis system comprising:

[0032] The vehicle-mounted terminal is used to collect vehicle driving data based on a preset national standard protocol and a preset vehicle network protocol, and to report the vehicle driving data to the vehicle network platform.

[0033] The vehicle-to-everything (V2X) platform is used to send the reported vehicle driving data to the big data platform.

[0034] The big data platform is used to process the vehicle driving data and judge the processed vehicle driving data according to preset bad driving judgment rules to obtain information on bad driving behavior of the vehicle.

[0035] This invention proposes a driving behavior analysis method applied to a driving behavior analysis system, which includes an in-vehicle terminal, a vehicle-to-everything (V2X) platform, and a big data platform. The in-vehicle terminal collects vehicle driving data based on preset national standard protocols and preset V2X protocols, and reports this data to the V2X platform. The V2X platform then sends the reported driving data to the big data platform. Finally, the big data platform processes the driving data and judges it according to preset rules for judging poor driving behavior, obtaining information on poor driving behavior. This invention, based on existing national standard requirements for vehicle driving data collection, combines vehicle driving data collected according to manufacturer-preset V2X protocol requirements, thereby increasing the richness of the collected driving data and providing more detailed driving behavior analysis. The big data platform then performs driving behavior analysis on this data. Compared to existing solutions for analyzing poor driving behavior, this invention eliminates the need for OEMs to analyze vehicle driving data, thus lowering the barrier to entry for users and improving the ease with which users can obtain information on poor driving behavior. Furthermore, the collected vehicle driving data is richer and more detailed, enabling a wider range of business scenarios for driving behavior analysis. Therefore, this embodiment significantly expands the applicability of driving behavior analysis. Attached Figure Description

[0036] Figure 1 This is a flowchart illustrating the first embodiment of the driving behavior analysis method of the present invention;

[0037] Figure 2 This is an example flowchart of the driving behavior analysis method of the present invention.

[0038] Figure 3 This is a flowchart illustrating the second embodiment of the driving behavior analysis method of the present invention;

[0039] Figure 4 This is a flowchart illustrating the third embodiment of the driving behavior analysis method of the present invention;

[0040] Figure 5 This is another example of the timing diagram of the driving behavior analysis method of the present invention;

[0041] Figure 6 This is a schematic diagram of the driving behavior analysis system involved in the embodiments of the present invention.

[0042] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0043] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0044] Since 2012, the concept of TCO (Total Cost of Ownership) has been introduced to China from Europe. Since then, the TCO concept has gradually spread and been promoted in the commercial vehicle sector. Currently, more and more commercial vehicle companies are focusing on connected vehicle aftermarket service modules, with the key to their success being reducing TCO costs. Taking Mercedes-Benz's Fleetboard fleet management system as an example, it helps large fleet customers monitor the transportation process, manage energy consumption, and train drivers on driving habits, ultimately helping customers reduce operating costs—this is the prototype of TCO.

[0045] Commercial vehicles, as tools for improving production efficiency, are highly sensitive to energy consumption. Analysis of total cost of ownership (TCO) shows that energy costs account for 31%. Market analysis reveals that driver habits have a significant impact on the energy consumption of commercial vehicles. Within the same statistical period, fuel consumption can vary by as much as 20 liters per 100 kilometers depending on the driving behavior of the vehicle. Against this backdrop, leveraging big data analysis and combining the results to optimize driver behavior and energy consumption management will undoubtedly greatly benefit product competitiveness.

[0046] However, driving behavior analysis requires data from multiple in-vehicle CAN bus systems, which ordinary aftermarket installations cannot provide, necessitating data analysis by OEMs. Currently, various OEMs have begun conducting multi-dimensional driving behavior analysis based on big data analytics to provide analytical data for drivers and fleet managers, enabling energy consumption reduction and vehicle damage reduction.

[0047] Reference Figure 1 , Figure 1 This is a flowchart illustrating the first embodiment of the driving behavior analysis method of the present invention.

[0048] The first embodiment of the present invention provides a driving behavior analysis method applied to a driving behavior analysis system, the driving behavior analysis system including an in-vehicle terminal, a vehicle networking platform, and a big data platform, the driving behavior analysis method including the following steps:

[0049] Step S100: The vehicle terminal collects vehicle driving data based on a preset national standard protocol and a preset vehicle network protocol, and reports the vehicle driving data to the vehicle network platform.

[0050] Specifically, the driving behavior analysis method in this embodiment is applied to a driving behavior analysis system, which includes an on-board terminal (i.e., an on-board T-BOX, Telematics BOX), a vehicle-to-everything (V2X) platform (i.e., a TSP platform, Telematics Service Provider), and a big data platform. The preset national standard protocol is the national standard protocol related to vehicle data collection. Taking heavy-duty diesel vehicles as an example, the corresponding national standard is GB 17691, which specifies the data items (such as engine status, engine fuel flow, GPS information, cumulative mileage, etc.) that the on-board terminal of a heavy-duty diesel vehicle must report to the V2X platform, as well as the communication protocol and data packet structure. Of course, this embodiment is not limited to heavy-duty diesel vehicles; the preset national standard protocol can also be GB / T 32960 "Technical Specification for Remote Service and Management System of Electric Vehicles," HJ 1239 "Technical Specification for Remote Monitoring of Emissions of Heavy-Duty Vehicles," or other relevant specifications. The on-board terminal can collect the corresponding data items of the vehicle according to the preset national standard protocol to obtain the corresponding vehicle driving data and report it to the V2X platform. The preset vehicle networking protocol is a protocol set by the manufacturer for data transmission between the in-vehicle terminal and the vehicle networking platform. It specifies the data items (such as fuel type, transmission type, vehicle ignition status, handbrake status, maximum speed, etc.) required by the manufacturer or user for the in-vehicle terminal to report to the vehicle networking platform, the communication protocol, and the data packet structure. Thus, the in-vehicle terminal can collect the corresponding data items according to the preset vehicle networking protocol to obtain the corresponding vehicle driving data and report it to the vehicle networking platform. The vehicle driving data includes vehicle data required by the preset national standard protocol and the preset vehicle networking protocol. The reporting frequency of the in-vehicle terminal to the vehicle networking platform can be set according to specific needs, such as 1 message / second, 1 message / 10 seconds, etc.

[0051] In this embodiment, based on the vehicle driving data collected according to existing national standards, the vehicle driving data collected is combined with the vehicle network protocol requirements preset by the manufacturer, thereby increasing the richness of the collected vehicle driving data and providing more detailed vehicle driving data for subsequent driving behavior analysis.

[0052] Furthermore, the steps by which the vehicle-mounted terminal collects vehicle driving data based on a preset national standard protocol and a preset vehicle networking protocol include the following steps:

[0053] Step S110: The vehicle terminal collects the corresponding national standard driving data according to the preset national standard protocol;

[0054] In step S120, the vehicle terminal collects the corresponding vehicle network driving data according to the preset vehicle network protocol, and uses the national standard driving data and the vehicle network driving data as the vehicle driving data.

[0055] Specifically, the national standard driving data refers to the vehicle data items required to be collected by the preset national standard protocol, and the vehicle-to-everything (V2X) driving data refers to the vehicle data items required to be collected by the preset V2X protocol. The vehicle driving data includes both the national standard driving data and the V2X driving data. The onboard terminal can collect the corresponding national standard driving data according to the preset national standard protocol and the corresponding V2X driving data according to the preset V2X protocol.

[0056] Furthermore, the vehicle-to-everything (V2X) platform includes a first V2X platform and a second V2X platform, and the step of reporting the vehicle driving data to the V2X platform includes:

[0057] Step S130: The vehicle terminal reports the national standard driving data to the first vehicle network platform via the first communication link according to the preset national standard protocol.

[0058] In step S131, the vehicle terminal reports the vehicle network driving data to the second vehicle network platform via the second communication link according to the preset vehicle network protocol.

[0059] Specifically, the vehicle-to-everything (V2X) platform includes a first V2X platform and a second V2X platform. The first V2X platform receives national standard driving data reported by in-vehicle terminals, and the second V2X platform receives connected vehicle-to-everything (V2X) driving data reported by in-vehicle terminals. In-vehicle terminals can report the national standard driving data to the first V2X platform via a first communication link according to a preset national standard protocol, and report the connected vehicle-to-everything (V2X) driving data to the second V2X platform via a second communication link according to a preset V2X protocol.

[0060] Furthermore, the step of reporting the vehicle driving data to the vehicle-to-everything (V2X) platform also includes:

[0061] Step S140: The vehicle terminal determines whether the vehicle has experienced any undesirable driving behavior events.

[0062] Step S141: If an undesirable driving behavior event occurs, the vehicle terminal reports the undesirable driving behavior event to the second vehicle network platform.

[0063] Specifically, the vehicle can also be equipped with the ability to detect specific undesirable driving behaviors (e.g., not wearing a seatbelt, turning without using turn signals, rapid acceleration, rapid deceleration, sharp turns, coasting in neutral, etc.). The types of specific undesirable driving behaviors that the vehicle can directly detect vary depending on the vehicle type. When the vehicle detects a specific undesirable driving behavior, it transmits the corresponding undesirable driving behavior event signal in the vehicle's CAN bus. The on-board terminal can determine whether an undesirable driving behavior event has occurred based on the undesirable driving behavior event signal in the CAN bus; if an undesirable driving behavior event has occurred, the on-board terminal can report the undesirable driving behavior event to the second vehicle networking platform. In this embodiment, by detecting specific undesirable driving behaviors by the vehicle itself, the on-board terminal can determine whether an undesirable driving behavior event has occurred, and when such an event occurs, it can report the undesirable driving behavior event. On the one hand, by detecting specific undesirable driving behaviors by the vehicle itself, the influence of other external factors is avoided, making the determination results of undesirable driving behaviors more accurate; on the other hand, no further judgment by a big data platform is required for this specific undesirable driving behavior, making the analysis of undesirable driving behaviors more convenient.

[0064] Furthermore, the preset vehicle-to-everything (V2X) protocol includes a preset basic V2X protocol and a preset extended V2X protocol. Step S120 also includes the following steps:

[0065] Step S121: The vehicle terminal collects the corresponding basic vehicle network driving data according to the preset vehicle network basic protocol;

[0066] Step S122: The vehicle network platform sends the corresponding parameter setting instructions to the vehicle terminal according to the preset vehicle network extended protocol;

[0067] In step S123, the vehicle terminal collects extended driving data of the Internet of Vehicles according to the received parameter setting instructions, and uses the basic driving data of the Internet of Vehicles and the extended driving data of the Internet of Vehicles as the driving data of the Internet of Vehicles.

[0068] Specifically, the preset vehicle-to-everything (V2X) protocol includes a preset basic V2X protocol and a preset extended V2X protocol. The preset basic V2X protocol can be used to specify the basic vehicle data items that need to be collected, such as air conditioning status, seat belt status, handbrake status, fault codes, turn signal status, and other basic information. The preset extended V2X protocol can be used to specify data items not available in the preset national standard protocol and the preset basic V2X protocol, such as engine model, accelerator pedal opening, brake pedal opening, steering wheel angle position, ACC (Adaptive Cruise Control) status, and other data items. The data items required by the preset extended V2X protocol can be set by the manufacturer or user according to specific business needs. The in-vehicle terminal collects the corresponding basic driving data according to the preset basic V2X protocol and reports the basic driving data to the second V2X platform. For data items not available in the preset national standard protocol and the preset basic V2X protocol, the V2X platform issues corresponding parameter setting instructions to the in-vehicle terminal according to the preset extended V2X protocol. Then, the on-board terminal collects CAN data items from the vehicle's CAN bus according to the received parameter setting instructions to obtain vehicle-to-everything (V2X) extended driving data. The on-board terminal then uses the basic V2X driving data and the extended V2X driving data as the V2X driving data. Specifically, the on-board terminal reports the basic V2X driving data to the second V2X platform using a preset basic V2X protocol, and also reports the extended V2X driving data to the second V2X platform using a preset extended V2X protocol.

[0069] Reference Figure 2 , Figure 2 This is an example flowchart illustrating the timing of the driving behavior analysis method of the present invention. The driving behavior analysis method of this embodiment is applied to a driving behavior analysis system, which may include an in-vehicle 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.

[0070] Figure 2 The Chinese standard protocol is based on GB 17691. When the vehicle is started or idling, the T-BOX is woken up and triggered to collect and report data from various components.

[0071] Among them, T-BOX uses a single communication link to report data according to the TSP basic protocol (i.e., the preset vehicle network basic protocol), and the data reporting frequency can be 1 report per 10 seconds in real time to TSP2.0;

[0072] When the T-BOX determines that a vehicle has engaged in unsafe driving behavior, it triggers an event reporting mechanism, reporting the unsafe driving behavior event to TSP2.0.

[0073] T-BOX uses another communication link to report data according to the GB 17691 protocol. The data reporting frequency can be 1 message / 1 second for real-time reporting to TSP1.0.

[0074] For data items not included in the GB 17691 protocol and the TSP basic protocol, parameter setting commands can be issued via TSP2.0 (i.e., Figure 3 The T-BOX receives CAN data reporting commands and transmits them to the T-BOX, enabling the T-BOX to collect and report the corresponding data items. The data reporting frequency can be replenished in real time at a rate of 1 data item per second to TSP2.0. Upon receiving parameter setting commands, the T-BOX reports data at a preset reporting frequency using the TSP extended protocol (i.e., the preset vehicle networking extended protocol).

[0075] Taking Table 1 below as an example, with the preset national standard protocol being GB 17691, the data obtained by the vehicle terminal is in the form of 17691 data items, the data obtained by the vehicle terminal based on the preset vehicle networking basic protocol is in the form of TSP data items, and the data obtained by the vehicle terminal based on the preset vehicle networking extended protocol is in the form of CAN data items.

[0076] Table 1 Vehicle driving data reported by the vehicle terminal

[0077]

[0078]

[0079] In step S200, the vehicle network platform sends the reported vehicle driving data to the big data platform;

[0080] Specifically, after receiving vehicle driving data reported by the in-vehicle terminal, the vehicle-to-everything (V2X) platform can process the data and distribute it to a message queue. This allows the big data platform to access the vehicle driving data in the message queue, thus enabling data transmission from the V2X platform to the big data platform. Of course, other data transmission methods can also be used, and it is not limited to the methods described above.

[0081] Further, step S200 may include the following steps:

[0082] In step S210, the vehicle networking platform decrypts and deserializes the vehicle driving data and distributes it to a preset message queue so that the big data platform can obtain the vehicle driving data in the preset message queue.

[0083] Specifically, the vehicle network platform performs data processing operations such as decrypting encrypted messages and deserializing protobuf format data on the vehicle driving data reported by the vehicle terminal. Then, it distributes the processed 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, thereby realizing the data transmission from the vehicle network platform to the big data platform.

[0084] Reference Figure 2 , Figure 2 This is an example flowchart illustrating the timing of the driving behavior analysis method of the present invention. The vehicle-to-everything (V2X) platform includes a first V2X platform (TSP1.0) and a second V2X platform (TSP2.0). TSP1.0 performs data processing operations such as encryption message decryption and protobuf format data deserialization on the data reported by T-BOX based on the GB 17961 protocol, and then distributes the processed data to a preset message queue. TSP2.0 similarly performs data processing operations such as encryption message decryption and protobuf format data deserialization on the data reported by T-BOX based on a preset V2X basic protocol and a preset V2X extended protocol, and then distributes the processed data to another preset message queue.

[0085] In step S300, the big data platform processes the vehicle driving data and judges the processed vehicle driving data according to preset bad driving judgment rules to obtain information on bad driving behavior of the vehicle.

[0086] Specifically, the data processing may include data parsing, data cleaning, standardization, and storage. The preset rules for judging poor driving behavior are those set by the manufacturer to determine such behavior. Taking dangerous speed driving as an example, the duration of driving at speeds greater than 100 km / h is counted; if the cumulative duration is greater than 5 seconds, it is counted as one instance of dangerous speed driving. If, during a single trip, the driving state changes but is maintained at a speed greater than 100 km / h for more than 3 seconds, it is again counted as one instance of dangerous speed driving. The trip is defined as engine ON → engine OFF, i.e., from the start of engine operation to the stop of engine operation is counted as one trip. After acquiring vehicle driving data, the big data platform performs data parsing, data cleaning, standardization, and storage to support subsequent data processing, querying, and analysis. Then, the big data platform uses the preset rules for judging poor driving behavior to determine the severity of the vehicle's poor driving behavior. The information on poor driving behavior may include the number of times poor driving behavior occurred, the type of poor driving behavior, the time when poor driving behavior occurred, the location when poor driving behavior occurred, and other information such as vehicle mileage, fuel consumption, failure rate, and average speed.

[0087] Furthermore, step S300 also includes the following steps:

[0088] Step S310: The big data platform performs data parsing, data cleaning and standardization on the vehicle driving data, and stores the processed vehicle driving data in a preset database.

[0089] In step S320, the big data platform judges the vehicle driving data in the preset database according to the preset bad driving judgment rules to obtain information on the vehicle's bad driving behavior.

[0090] Specifically, the big data platform performs data parsing, data cleaning, and standardization on the vehicle driving data, and stores the processed vehicle driving data in a preset database. In this embodiment, the big data platform restores the obtained vehicle driving data through data parsing, fills in missing values, deletes and corrects outliers and jump values ​​through data cleaning, and eliminates differences in the source, format, and data quality of the vehicle driving data through standardization. Thus, through data parsing, data cleaning, and standardization, the data processing operations support subsequent data processing, querying, analysis, and other further applications. The processed vehicle driving data is then stored in the preset database, which can be a MySQL database, HBase database, Oracle database, DB2 database, SQL Server database, etc. Finally, the big data platform judges and statistically analyzes the vehicle driving data in the preset database according to the preset bad driving judgment rules, forming a lightly aggregated data layer and data summary, thereby obtaining information on bad driving behavior of vehicles.

[0091] Reference Figure 2 , Figure 2 This is an example flowchart illustrating the driving behavior analysis method of the present invention. The big data platform consumes data from TSP1.0 and TSP2.0 in real time to obtain the vehicle driving data reported by the T-BOX to the vehicle networking platform. Then, it performs data processing operations such as data parsing, data cleaning, standardization, and storage on the vehicle driving data to support subsequent data processing, querying, and analysis. Furthermore, based on the actual analysis business scenario, the big data platform performs data calculations according to preset rules for judging poor driving behavior, forming a lightly aggregated data layer and data summary to obtain information on the vehicle's poor driving behavior. In addition, the big data platform also provides an interface for users to obtain the information on poor driving behavior.

[0092] The first embodiment of this invention proposes a driving behavior analysis method applied to a driving behavior analysis system, which includes an in-vehicle terminal, a vehicle-to-everything (V2X) platform, and a big data platform. The in-vehicle terminal collects vehicle driving data based on a preset national standard protocol and a preset V2X protocol, and reports the vehicle driving data to the V2X platform. The V2X platform then sends the reported vehicle driving data to the big data platform. Finally, the big data platform processes the vehicle driving data and judges the processed data according to preset rules for judging poor driving behavior, obtaining information on poor driving behavior. This embodiment, based on the vehicle driving data collected according to existing national standard requirements, combines vehicle driving data collected according to the manufacturer's preset V2X protocol requirements, thereby increasing the richness of the collected vehicle driving data and providing more detailed vehicle driving data for subsequent driving behavior analysis. The big data platform then performs driving behavior analysis on the vehicle driving data. Compared to existing solutions for analyzing poor driving behavior, this embodiment eliminates the need for OEMs to analyze vehicle driving data, thus lowering the barrier to entry for users and improving the ease with which users can obtain information on poor driving behavior. Furthermore, the collected vehicle driving data is richer and more detailed, enabling a wider range of business scenarios for driving behavior analysis. Therefore, this embodiment significantly expands the applicability of driving behavior analysis.

[0093] Furthermore, referring to Figure 3 The second embodiment of the present invention provides a driving behavior analysis method, based on the above. Figure 1 In the illustrated embodiment, the vehicle driving data includes the vehicle type, and the following steps are included before step S300:

[0094] Step S330: The big data platform determines the preset bad driving judgment rule corresponding to the vehicle driving data based on the vehicle type.

[0095] Specifically, before the big data platform judges the vehicle driving data, it can determine the preset bad driving judgment rules corresponding to the vehicle driving data based on the vehicle type. The vehicle type can be a vehicle classification (e.g., heavy truck, light truck, light bus, large bus, etc.) or the type of engine used in the vehicle (e.g., diesel engine, gasoline engine, electric motor, hybrid engine, etc.). Manufacturers can set corresponding preset bad driving judgment rules according to different vehicle types, so the big data platform can select the corresponding preset bad driving judgment rules according to the vehicle type. Therefore, this embodiment can select different preset bad driving judgment rules according to different vehicle types, so that the analysis of bad driving behavior can be adapted to different engines and different vehicle types, improving the accuracy and applicability of bad driving behavior analysis. As shown in Table 2 below, the preset bad driving judgment rules are as follows:

[0096] Table 2 Preset Rules for Judging Poor Driving

[0097]

[0098]

[0099]

[0100]

[0101]

[0102] It is understood that the above-mentioned preset bad driving judgment rules are only examples, and in actual applications, the preset bad driving judgment rules can be set according to specific needs.

[0103] Furthermore, referring to Figure 4 The third embodiment of the present invention provides a driving behavior analysis method, based on the above. Figure 1 In the embodiment shown, the following step is included after step S300:

[0104] In step S400, the big data platform obtains the user's query request based on a preset interface, generates corresponding query results based on the bad driving behavior information and the query request, and feeds back the query results to the user through the preset interface.

[0105] Specifically, the big data platform needs to provide pre-defined interfaces for users to access and retrieve data through the app and intelligent fleet management platform. The interface design must integrate the user center's token system (a token is a connection authentication method, often represented by a string, used for communication with the server). The pre-defined interface provided by the big data platform to the app is a single-vehicle driving behavior interface. The pre-defined interfaces provided by the big data platform to the intelligent fleet management platform are both single-vehicle driving behavior interfaces and multi-vehicle driving behavior interfaces.

[0106] The query request may include a user-specified time period. The query results may include cumulative vehicle driving data, vehicle trip driving data, and details of poor driving behavior within the specified time period; if there are multiple vehicles, it may also include multi-vehicle driving data. (See reference...) Figure 5 , Figure 5 This is another example diagram illustrating the timeline of the driving behavior analysis method of the present invention. Users can log in to the intelligent fleet management platform, obtain statistical results data through preset interfaces, and visualize the data. Based on the intelligent fleet management platform, users can obtain statistical results data for a single vehicle within a specified time period through the single-vehicle driving behavior interface, and obtain statistical results data for multiple vehicles within a specified time period through the multi-vehicle driving behavior interface. Then, the big data platform returns the corresponding query results data through preset interfaces, and the intelligent fleet management platform visualizes the returned query results for user viewing. Furthermore, users can log in to the APP and query driving data within a specified time period through preset interfaces; the APP visualizes the returned data results.

[0107] Users can query the cumulative driving data of selected vehicles within a specified time period through the APP or fleet management platform. This cumulative driving data can include the selected vehicle's cumulative mileage, total fuel consumption, and number of instances of improper driving behavior within the specified time period. The big data platform can calculate the daily mileage of a single vehicle based on the GB17691 data item "Cumulative Mileage"; calculate the daily fuel consumption of a single vehicle based on the GB17691 data item "Engine Fuel Flow"; and calculate the daily number of instances of improper driving behavior of a single vehicle based on a combination of the TSP data item and the GB17691 data item. The calculation method for the cumulative driving data is shown in Table 3 below.

[0108] Table 3 Explanation of Calculation of Cumulative Vehicle Driving Data

[0109]

[0110]

[0111] Users can use the app to query driving data for selected vehicles within a specified time period, segmented by trip. This driving data includes mileage, total fuel consumption, trip start and end points, trip start and end times, number of instances of undesirable driving behavior, average speed, fuel consumption per 100 kilometers, and trip duration for each segment of the journey within the specified time period. The big data platform can calculate the trip start and end times based on the GB17691 data item "Engine Status"; calculate the total fuel consumption based on the GB17691 data item "Engine Fuel Flow"; and statistically determine the number of undesirable driving behaviors during a single vehicle's trip based on a combination of TSP and GB17691 data items. It can also calculate and perform reverse geocoding based on the GB17691 data item "GPS Information" to obtain the trip start and end points; and calculate the mileage based on the GB17691 data items "Cumulative Mileage" and "Engine Status". The calculation of this vehicle driving data is explained in Table 4 below.

[0112] Table 4 Explanation of Vehicle Trip Driving Data Calculation

[0113]

[0114]

[0115] Users can query multi-vehicle driving data for their vehicles within a specified time period through the intelligent fleet management platform. This multi-vehicle driving data can include energy consumption per 100 kilometers, poor driving behavior, vehicle failure rate, and cumulative operating mileage for multiple vehicles under the user's name within the specified time period. The big data platform can calculate the single-vehicle failure rate based on the GB17691 data item [OBD failure]; calculate the energy consumption per 100 kilometers based on the GB17691 data items [engine fuel flow, operating mileage]; and statistically determine the number of poor driving behaviors per vehicle per day based on a combination of TSP and GB17691 data items. The cumulative operating mileage is calculated based on the GB17691 data item [cumulative mileage]. The calculation method for the multi-vehicle driving data is explained in Table 5 below.

[0116] Table 5 Explanation of Multi-Vehicle Driving Data Calculation

[0117]

[0118]

[0119] Users can use the app to query details of poor driving behavior for their vehicles within a specified time period. These details include records of poor driving behavior for the user's vehicles during that period, such as the number of instances, the type and time of each instance, and the location of the instance. The big data platform can use a combination of TSP and GB17691 data items to calculate and statistically determine the daily details of poor driving behavior for each vehicle. The calculation of these details is explained in Table 6 below.

[0120] Table 6. Calculation Instructions for Details of Undesirable Driving Behaviors

[0121]

[0122]

[0123] In addition, the preset interfaces provided by the big data platform to the APP may include: vehicle cumulative driving data interface, vehicle trip driving data interface, and poor driving behavior details interface; the preset interfaces provided to the intelligent fleet management platform include: vehicle cumulative driving data interface and multi-vehicle driving data interface. Detailed requirements for the above preset interfaces are shown in Tables 7, 8, 9, and 10 below:

[0124] Table 7. Vehicle Cumulative Driving Data Interface Requirements Fields

[0125]

[0126] Table 8. Vehicle Trip Driving Data Interface Requirements Fields

[0127]

[0128]

[0129] Table 9. Fields required for the multi-vehicle driving data interface

[0130]

[0131]

[0132] Table 10: Interface Requirements Fields for Details of Undesirable Driving Behaviors

[0133]

[0134]

[0135] Reference Figure 6 , Figure 6 This is a schematic diagram of the driving behavior analysis system involved in the embodiments of the present invention.

[0136] like Figure 6 As shown, one embodiment of the present invention provides a driving behavior analysis system, the driving behavior analysis system comprising:

[0137] The vehicle terminal 10 is used to collect vehicle driving data based on a preset national standard protocol and a preset vehicle network protocol, and to report the vehicle driving data to the vehicle network platform 20.

[0138] The vehicle networking platform 20 is used to send the reported vehicle driving data to the big data platform 30;

[0139] The big data platform 30 is used to process the vehicle driving data and judge the processed vehicle driving data according to preset bad driving judgment rules to obtain information on bad driving behavior of the vehicle.

[0140] Furthermore, the driving behavior analysis system also includes:

[0141] The vehicle-mounted terminal 10 is used to collect corresponding national standard driving data according to a preset national standard protocol;

[0142] The vehicle terminal 10 is used to collect corresponding vehicle network driving data according to a preset vehicle network protocol, and to use the national standard driving data and the vehicle network driving data as the vehicle driving data.

[0143] Furthermore, the preset vehicle-to-everything (V2X) protocol includes a preset basic V2X protocol and a preset extended V2X protocol, and the driving behavior analysis system also includes:

[0144] The vehicle terminal 10 is used to collect corresponding basic vehicle network driving data according to the preset vehicle network basic protocol;

[0145] The vehicle networking platform 20 is used to send corresponding parameter setting instructions to the vehicle terminal 10 according to the demand data;

[0146] The vehicle terminal 10 is used to collect vehicle-to-everything (V2X) extended driving data according to the received parameter setting instructions, and to use the V2X basic driving data and V2X extended driving data as V2X driving data.

[0147] Furthermore, the vehicle networking platform 20 includes a first vehicle networking platform 21 and a second vehicle networking platform 22, and the driving behavior analysis system further includes:

[0148] The vehicle terminal 10 is used to report the national standard driving data to the first vehicle network platform 21 via the first communication link according to the preset national standard protocol;

[0149] The vehicle terminal 10 is used to report the vehicle network driving data to the second vehicle network platform 22 via a second communication link according to a preset vehicle network protocol.

[0150] Furthermore, the driving behavior analysis system also includes:

[0151] The vehicle terminal 10 is used to determine whether the vehicle has experienced any undesirable driving behavior events.

[0152] If an incident of improper driving behavior occurs, the vehicle terminal 10 reports the incident to the second vehicle network platform 22.

[0153] Furthermore, the driving behavior analysis system also includes:

[0154] The vehicle networking platform 20 is used to decrypt and deserialize the vehicle driving data and distribute it to a preset message queue so that the big data platform 30 can obtain the vehicle driving data in the preset message queue.

[0155] Furthermore, the driving behavior analysis system also includes:

[0156] Big data platform 30 is used to perform data parsing, data cleaning and standardization processing on the vehicle driving data, and store the processed vehicle driving data in a preset database;

[0157] The big data platform 30 is used to judge vehicle driving data in a preset database according to the preset bad driving judgment rules, and obtain information on bad driving behavior of vehicles.

[0158] Furthermore, the vehicle driving data includes vehicle type, and the driving behavior analysis system also includes:

[0159] The big data platform 30 is used to determine the preset bad driving judgment rules corresponding to the vehicle driving data based on the vehicle type.

[0160] Furthermore, the driving behavior analysis system also includes:

[0161] The big data platform 30 is used to obtain user query requests based on a preset interface, generate corresponding query results based on the bad driving behavior information and the query requests, and feed back the query results to the user through the preset interface.

[0162] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity / operation / object from another, and do not necessarily require or imply any such actual relationship or order between these entities / operations / objects; the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or system. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or system that includes that element.

[0163] For the apparatus embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and relevant details can be found in the description of the method embodiments. The apparatus embodiments described above are merely illustrative, and the units 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 present invention. Those skilled in the art can understand and implement this without any creative effort.

[0164] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0165] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) as described above, and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, vehicle, or network device, etc.) to execute the methods described in the various embodiments of the present invention.

[0166] The above are merely preferred embodiments of the present invention and do not limit the scope of the patent. Any equivalent structural or procedural transformations made based on the description and drawings of the present invention, or direct or indirect applications in other related technical fields, are similarly included within the scope of patent protection of the present invention.

Claims

1. A driving behavior analysis method, applied to a driving behavior analysis system, the driving behavior analysis system comprising an in-vehicle terminal, a vehicle networking platform, and a big data platform, characterized in that, The driving behavior analysis method includes the following steps: The vehicle terminal collects vehicle driving data based on a preset national standard protocol and a preset vehicle network protocol, and reports the vehicle driving data to the vehicle network platform. The vehicle-to-everything (V2X) platform will send the reported vehicle driving data to the big data platform; The big data platform processes the vehicle driving data and judges the processed vehicle driving data according to preset bad driving judgment rules to obtain information on bad driving behavior of the vehicle. The steps for the in-vehicle terminal to collect vehicle driving data based on a preset national standard protocol and a preset vehicle networking protocol include: The vehicle terminal collects corresponding national standard driving data according to a preset national standard protocol, wherein the preset national standard protocol is the national standard protocol related to data collection for the vehicle. The vehicle terminal collects corresponding vehicle network driving data according to a preset vehicle network protocol, and uses the national standard driving data and the vehicle network driving data as the vehicle driving data. The preset vehicle network protocol is a protocol set by the manufacturer for data transmission between the vehicle terminal and the vehicle network platform. The preset vehicle network protocol includes a preset vehicle network basic protocol and a preset vehicle network extended protocol. The preset vehicle network basic protocol is used to specify the basic data items of the vehicle to be collected, and the preset vehicle network extended protocol is used to specify data items not available in the preset national standard protocol and the preset vehicle network basic protocol. The steps for the in-vehicle terminal to collect corresponding vehicle-to-everything (V2X) driving data according to a preset vehicle-to-everything (V2X) protocol include: The vehicle terminal collects corresponding basic vehicle-to-everything (V2X) driving data according to the preset V2X basic protocol. The vehicle-to-everything (V2X) platform sends corresponding parameter setting instructions to the vehicle terminal according to the preset V2X extended protocol; The vehicle terminal collects extended driving data of the Internet of Vehicles according to the received parameter setting instructions, and uses the basic driving data of the Internet of Vehicles and the extended driving data of the Internet of Vehicles as the driving data of the Internet of Vehicles.

2. The driving behavior analysis method as described in claim 1, characterized in that, The vehicle-to-everything (V2X) platform includes a first V2X platform and a second V2X platform. The step of reporting the vehicle driving data to the V2X platform includes: The vehicle terminal reports the national standard driving data to the first vehicle network platform via the first communication link according to the preset national standard protocol; The vehicle terminal reports the vehicle-to-everything (V2X) driving data to the second V2X platform via a second communication link according to a preset V2X protocol.

3. The driving behavior analysis method as described in claim 2, characterized in that, The step of reporting the vehicle driving data to the vehicle network platform also includes: The in-vehicle terminal determines whether the vehicle has engaged in any unsafe driving behavior events. If an incident of improper driving behavior occurs, the on-board terminal will report the incident to the second vehicle network platform.

4. The driving behavior analysis method as described in claim 1, characterized in that, The steps by which the vehicle networking platform sends the reported vehicle driving data to the big data platform include: The vehicle networking platform decrypts and deserializes the vehicle driving data and distributes it to a preset message queue, so that the big data platform can obtain the vehicle driving data in the preset message queue.

5. The driving behavior analysis method as described in claim 1, characterized in that, The big data platform processes the vehicle driving data and judges the processed vehicle driving data according to preset bad driving judgment rules to obtain information on bad driving behavior of the vehicle. The steps include: The big data platform performs data analysis, data cleaning, and standardization on the vehicle driving data, and stores the processed vehicle driving data in a preset database; The big data platform judges vehicle driving data in the preset database according to the preset bad driving judgment rules to obtain information on bad driving behavior of vehicles.

6. The driving behavior analysis method as described in claim 5, characterized in that, The vehicle driving data includes vehicle type. Before the step of obtaining information on poor driving behavior of a vehicle by judging the vehicle driving data in the preset database according to the preset poor driving judgment rules, the big data platform includes: The big data platform determines the preset bad driving judgment rules corresponding to the vehicle driving data based on the vehicle type.

7. The driving behavior analysis method as described in any one of claims 1 to 6, characterized in that, The big data platform processes the vehicle driving data and judges the processed vehicle driving data according to preset bad driving judgment rules to obtain information on bad driving behavior of the vehicle. Following this step, the platform includes: The big data platform obtains user query requests based on a preset interface, generates corresponding query results based on the bad driving behavior information and the query request, and feeds back the query results to the user through the preset interface.

8. A driving behavior analysis system, characterized in that, The driving behavior analysis system includes: The vehicle-mounted terminal is used to collect vehicle driving data based on a preset national standard protocol and a preset vehicle network protocol, and to report the vehicle driving data to the vehicle network platform. The vehicle-to-everything (V2X) platform is used to send the reported vehicle driving data to the big data platform. The big data platform is used to process the vehicle driving data and judge the processed vehicle driving data according to the preset bad driving judgment rules to obtain information on bad driving behavior of the vehicle. Among them, the vehicle terminal is also used to collect corresponding national standard driving data according to the preset national standard protocol, collect corresponding vehicle network driving data according to the preset vehicle network protocol, and use the national standard driving data and vehicle network driving data as the vehicle driving data. The preset national standard protocol is the national standard protocol related to data collection for the vehicle, and the preset vehicle network protocol is the protocol set by the manufacturer for data transmission between the vehicle terminal and the vehicle network platform. The preset vehicle network protocol includes a preset vehicle network basic protocol and a preset vehicle network extended protocol. The preset vehicle network basic protocol is used to specify the basic data items of the vehicle to be collected, and the preset vehicle network extended protocol is used to specify data items not available in the preset national standard protocol and the preset vehicle network basic protocol. The vehicle-mounted terminal is also used to collect corresponding basic vehicle-to-everything (V2X) driving data according to the preset V2X basic protocol; The vehicle networking platform is also used to send corresponding parameter setting instructions to the vehicle terminal according to the preset vehicle networking extended protocol; The vehicle-mounted terminal is also used to collect vehicle-to-everything (V2X) extended driving data according to the received parameter setting instructions, and to use the V2X basic driving data and V2X extended driving data as V2X driving data.

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