Driving data collection and analysis method, system, readable storage medium and vehicle

Abstract

The application provides a driving data collection and analysis method, system, readable storage medium and vehicle. The method comprises the following steps: obtaining a wake-up request sent by a CAN network of a whole vehicle, and making the vehicle wake up according to the wake-up request; actively obtaining driving data of a target vehicle every first preset time, obtaining driving behaviors of a driver in a current period according to a vehicle speed, an engine speed, a throttle pedal stroke value, a brake pedal stroke value, a steering wheel rotation angle and a steering wheel rotation angle acceleration; generating a trip report of the target vehicle according to driving behaviors corresponding to multiple continuous periods respectively, and uploading the trip report to a cloud service platform. The driving data collection and analysis method can intuitively reflect existing bad driving behaviors of a customer by collecting real-time data, and can help the customer to improve the existing bad driving habits, so that the behaviors of the customer are more standardized and economical.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of vehicle Internet, in particular to a driving data acquisition and analysis method and system, a readable storage medium and a vehicle. BACKGROUND

[0002] With the rapid development and popularization of intelligent networking technology in the automotive industry, many technological functions can be brought to users who purchase vehicles, which also narrows the distance between customers and automobile manufacturers. Through the intelligent networking APP, customers can clearly know the real-time situation and health status of their vehicles, and a communication bridge is established between customers and automobile manufacturers. Customers' questions and needs can be quickly answered and satisfied, and automobile manufacturers can directly obtain customers' needs to carry out function iteration and new product research and development.

[0003] In the prior art, the driving behavior of customers is often evaluated through intelligent networking to obtain a score and ranking of the driving behavior of customers, so as to play a certain feedback role. However, in the actual evaluation process, due to the lack of collection and use of real-time data of the vehicle, the driving behavior analysis is one-sided, the specific driving situation cannot be accurately understood, and the customer cannot intuitively understand the defects in driving habits, so that the customer's driving behavior cannot be effectively improved. SUMMARY

[0004] Therefore, the purpose of the present application is to provide a driving data acquisition and analysis method, system, readable storage medium and vehicle to solve the problem that the traditional customer driving behavior evaluation method cannot intuitively reflect the defects in customer driving behavior due to the lack of collection and use of real-time data, and to help customers improve their bad driving habits, so that the customer's behavior is more standardized and economical.

[0005] According to the driving data acquisition and analysis method provided by the present application, the method is applied to a vehicle terminal, and the method comprises the following steps:

[0006] An awakening request sent by a whole vehicle CAN network is acquired, and the vehicle terminal is in an awakening state according to the awakening request, wherein the awakening request is triggered by the CAN network receiving an external unlocking request;

[0007] After being in the awakening state, the vehicle terminal actively acquires a plurality of driving data of a target vehicle every first preset time, wherein the driving data comprises vehicle speed, engine speed, throttle pedal stroke value, brake pedal stroke value, steering wheel rotation angle and steering wheel rotation angle acceleration;

[0008] According to the vehicle speed, the engine speed, the throttle pedal stroke value, the brake pedal stroke value, the steering wheel angle and the steering wheel angle acceleration, the driving behavior of the driver in the current period is obtained, and the driving behavior at least includes over-long idle driving, rapid acceleration driving, rapid braking driving and rapid turning driving;

[0009] According to the driving behavior corresponding to each of the plurality of consecutive periods, a driving report of the target vehicle is generated, and the driving report is uploaded to a cloud service platform, the driving report including the cumulative number of each driving behavior corresponding to the driver in this driving.

[0010] In summary, according to the above driving data acquisition and analysis method, the user driving data is collected and used in real time to obtain the driving report corresponding to the customer in each driving, so as to intuitively reflect the specific bad driving habits of the customer in actual driving, and facilitate the customer to improve. Specifically, first, the vehicle terminal will obtain the wake-up request in real time, so as to make itself in a wake-up state according to the wake-up request, and then know that the customer is using the target vehicle, so as to start data collection and analysis work, and then collect various driving data of the target vehicle every first preset time, so as to analyze the current driving behavior of the customer according to the driving data collected each time. The driving behavior at least includes over-long idle driving, rapid acceleration driving, rapid braking driving and rapid turning driving, so as to generate a driving report containing the cumulative number of various driving behaviors, and then send the driving report to the cloud service platform, so that the customer can check at any time. Through intuitive and accurate display of the bad driving habits of the customer in actual driving, the problem of being unable to intuitively reflect the driving behavior defects of the customer in the traditional customer driving behavior evaluation method due to lack of real-time data collection and use is solved, and the customer can be effectively helped to improve the bad driving behavior.

[0011] Further, the step of actively acquiring the plurality of driving data of the target vehicle every first preset time includes:

[0012] According to the driving data of the last period and the driving data of the current period, the error value of each driving data is calculated;

[0013] It is judged whether there is an error value of driving data greater than a first preset error threshold value;

[0014] If there is an error value of driving data greater than the first preset error threshold value, the driving data with the error value greater than the first preset error threshold value is deleted, and the driving data with the error value greater than the first preset error threshold value is collected again within a sixth preset time;

[0015] The error value of the driving data collected in the sixth preset time is repeatedly calculated until the error value corresponding to all the driving data is less than or equal to the first preset error threshold.

[0016] Further, the step of determining that the target vehicle is in the idle state for too long includes:

[0017] If the current vehicle speed of the target vehicle is zero and the transmitter speed is greater than the first preset speed, the timing is started to obtain the first duration of the target vehicle in the current state;

[0018] It is determined whether the first duration is greater than the first preset time threshold.

[0019] If the first duration is greater than the first preset time threshold, it is determined that the target vehicle is in the idle state for too long.

[0020] Further, the step of determining that the target vehicle is in the rapid acceleration driving includes:

[0021] If the current vehicle speed of the target vehicle is greater than zero and the accelerator pedal stroke value is greater than the first preset accelerator pedal threshold, a plurality of vehicle speeds are obtained every second preset time, and the average longitudinal acceleration of the target vehicle is obtained according to the vehicle speeds at a plurality of adjacent time points.

[0022] It is determined whether the average longitudinal acceleration is greater than the first preset longitudinal acceleration threshold.

[0023] If the average longitudinal acceleration is greater than the first preset longitudinal acceleration threshold, it is determined that the target vehicle is in the rapid acceleration driving.

[0024] Further, the step of determining that the target vehicle is in the rapid acceleration driving and the rapid turning driving includes:

[0025] If the current vehicle speed of the target vehicle is greater than zero and the brake pedal stroke value is greater than the first preset brake pedal threshold, a plurality of vehicle speeds are obtained every third preset time, and the average longitudinal deceleration of the target vehicle is obtained according to the vehicle speeds at a plurality of adjacent time points.

[0026] It is determined whether the average longitudinal deceleration is greater than the first preset longitudinal deceleration threshold.

[0027] If the average longitudinal deceleration threshold is greater than the first preset longitudinal deceleration threshold, it is determined that the target vehicle is in the rapid deceleration state.

[0028] If the vehicle speed of the target vehicle is greater than the first preset vehicle speed and the steering wheel angle is greater than the first preset steering wheel angle, it is determined whether the current steering wheel angle acceleration of the target vehicle is greater than the first preset steering wheel angle acceleration.

[0029] If the current steering wheel angle acceleration of the target vehicle is greater than a first preset steering wheel angle acceleration, it is determined that the target vehicle is in a sharp turning driving.

[0030] Further, the method further comprises:

[0031] Engine state data of the target vehicle is acquired every fifth preset time, the engine state data comprising a preset message defining a current state of the engine;

[0032] It is determined whether the target vehicle is in a starting state or an off state according to field information in the preset message;

[0033] When it is monitored that the target vehicle is in the starting state, initial fuel data, initial mileage data and initial travel time of the target vehicle are acquired;

[0034] When it is monitored that the target vehicle is in the off state, final fuel data, final mileage data and final travel time of the target vehicle are acquired.

[0035] Further, the step of generating a travel report of the target vehicle according to the driving behaviors corresponding to a plurality of continuous periods respectively and uploading the travel report to a cloud service platform comprises:

[0036] All the driving behaviors of the target vehicle determined are summarized to obtain a cumulative number of times of the target vehicle in various driving states;

[0037] The travel data of the target vehicle is acquired according to the following formula:

[0038] H0=(Z1-Z2)·L / (S2-S1)

[0039] V0=(S2-S1) / (t2-t1)

[0040] Wherein, H0 represents average fuel consumption of this driving, Z2 represents the final fuel data, Z1 represents the initial fuel data, S2 represents the final mileage data, S1 represents the initial mileage data, L represents a fuel tank volume of the target vehicle, V0 represents an average speed of this driving, t2 represents the final travel time, and t1 represents the initial travel time;

[0041] The travel report is made according to the cumulative number of times of the target vehicle in various driving states and the travel data in this driving.

[0042] A driving data acquisition and analysis system according to an embodiment of the present application is applied to a vehicle terminal, and the system comprises:

[0043] a wake-up module configured to acquire a wake-up request sent by a whole vehicle CAN network and to be in a wake-up state according to the wake-up request, the wake-up request being triggered by the CAN network receiving an external unlock request;

[0044] a driving data acquisition module configured to actively acquire driving data of a target vehicle every first preset time when in the wake-up state, the driving data including vehicle speed, engine speed, throttle pedal stroke value, brake pedal stroke value, steering wheel angle and steering wheel angle acceleration;

[0045] a driving data analysis module configured to acquire driving behavior of a driver in a current period according to the vehicle speed, the engine speed, the throttle pedal stroke value, the brake pedal stroke value, the steering wheel angle and the steering wheel angle acceleration, the driving behavior including at least prolonged idling driving, rapid acceleration driving, rapid braking driving and rapid turning driving;

[0046] a trip report construction module configured to generate a trip report of the target vehicle according to driving behavior corresponding to a plurality of continuous periods respectively, and to upload the trip report to a cloud service platform, the trip report including cumulative number of each driving behavior of the driver in the current driving.

[0047] Another aspect of the present application also provides a readable storage medium, including one or more programs stored in the readable storage medium, the program being executed to implement the driving data acquisition and analysis method as described above.

[0048] Another aspect of the present application also provides a vehicle, including a memory and a processor, wherein:

[0049] the memory is configured to store a computer program;

[0050] the processor is configured to execute the computer program stored in the memory to implement the driving data acquisition and analysis method as described above.

[0051] Additional aspects and advantages of the present application will be given in part in the following description, become apparent from the following description, or be understood by those skilled in the art from the embodiments of the present application. BRIEF DESCRIPTION OF DRAWINGS

[0052] Figure 1 a flow chart of the driving data acquisition and analysis method for the first embodiment of the present application;

[0053] Figure 2 a flow chart of the driving data acquisition and analysis method for the second embodiment of the present application;

[0054] Figure 3A structure schematic diagram of a driving data collection and analysis system for a third embodiment of the present application.

[0055] The following detailed description will further describe the present application in conjunction with the above-mentioned drawings. DETAILED DESCRIPTION

[0056] In order to facilitate the understanding of the present application, the present application will be described more fully below in conjunction with the related drawings. The drawings show several embodiments of the present application. However, the present application can be implemented in many different forms and is not limited to the embodiments described herein. On the contrary, the purpose of providing these embodiments is to make the disclosure of the present application more thorough and comprehensive.

[0057] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the present application belongs. The terminology used in the description of the present application herein is only for the purpose of describing the specific embodiments and is not intended to limit the present application. The term "and / or" used herein includes any and all combinations of one or more of the associated listed items.

[0058] Please refer to Figure 1 , which is a flowchart of a driving data collection and analysis method in a first embodiment of the present application. The method is applied to a vehicle terminal. The method comprises steps S01 to S02, wherein:

[0059] Step S01: obtaining a wake-up request sent by a whole vehicle CAN network and making itself in a wake-up state according to the wake-up request, wherein the wake-up request is triggered by the CAN network receiving an external unlock request;

[0060] In this step, when a customer needs to start using a target vehicle, a corresponding unlock request will be sent to the CAN bus of the target vehicle. The CAN bus will further send a wake-up message to the vehicle terminal according to the obtained unlock request, so that the vehicle terminal can be actively woken up according to the received wake-up message, and thus the vehicle terminal can start monitoring the real-time state of the target vehicle.

[0061] Step S02: actively obtaining driving data of the target vehicle every first preset time after being in the wake-up state, wherein the driving data includes vehicle speed, engine speed, throttle pedal stroke value, brake pedal stroke value, steering wheel angle and steering wheel angle acceleration;

[0062] It should be noted that in order to accurately analyze the bad driving behavior of the customer, the vehicle terminal will collect the corresponding related driving data of the customer in the actual driving process in real time.

[0063] Further, since the bad driving behaviors of the customer generally exist in a certain moment, in order to accurately obtain the bad driving behaviors of the customer existing in a certain moment, it is necessary to set the first preset time, and the purpose is to frequently monitor the driving data of the target vehicle, so as to accurately analyze whether there is a bad driving behavior in the first preset time.

[0064] Specifically, the first preset time is generally set to 30-120s, and if it is too short, the complete process of the entire bad driving behavior cannot be monitored, and if it is too long, there is a large amount of data of normal driving or other driving behaviors in the collected data, which is easy to cause inaccurate analysis results.

[0065] Step S03: obtaining the driving behavior of the driver in the current period according to the vehicle speed, the engine speed, the throttle pedal stroke value, the brake pedal stroke value, the steering wheel angle and the steering wheel angle acceleration, the driving behavior at least including long-idle driving, rapid acceleration driving, rapid braking driving and rapid turning driving;

[0066] It should be noted that collecting various driving data corresponds to a period, and after collecting various driving data at appropriate time intervals, the corresponding bad driving behavior is analyzed according to the various driving data in the current period, and the bad driving behavior specifically includes long-idle driving, rapid acceleration driving, rapid braking driving and rapid turning driving.

[0067] Step S04: generating a trip report of the target vehicle according to the driving behaviors corresponding to a plurality of continuous periods respectively, and uploading the trip report to a cloud service platform, the trip report including the cumulative number of the long-idle driving, the rapid acceleration driving, the rapid braking driving and the rapid turning driving of the driver in the current driving respectively.

[0068] It should be noted that in this step, the plurality of continuous periods generally include all time from when the vehicle is started to when the vehicle is turned off, and each period corresponds to a specific driving behavior. By summarizing the driving behaviors corresponding to each period of the customer in the entire driving time, the cumulative number of each driving behavior in the current driving is obtained to generate the trip report of the current driving, and then the trip report is uploaded to the cloud service platform. When the customer ends the current driving, the cloud service platform can push the trip report to the customer, so that the customer can accurately know all the bad driving behavior records in the current driving, which is beneficial to the customer to improve the driving habit.

[0069] In summary, according to the driving data collection and analysis method, the user driving data is collected and used in real time to obtain the corresponding trip report of the customer in each driving, so that the specific bad driving habits of the customer in actual driving are intuitively embodied, and the customer can be targeted to improve. Specifically, first, the vehicle terminal acquires the wake-up request in real time, so as to make itself in a wake-up state according to the wake-up request, and then knows that the customer is using the target vehicle, so as to start the data collection and analysis work, and then collects the various driving data of the target vehicle every first preset time, so as to analyze the current driving behavior of the customer according to the driving data collected each time, the driving behavior at least including long idling driving, high-speed driving, sudden braking driving and sudden turning driving, so as to generate a trip report containing the cumulative number of various driving behaviors, and then send the trip report to the cloud service platform, so that the customer can check at any time, and the bad driving habits of the customer in actual driving are intuitively and accurately displayed, thereby solving the problem that the traditional customer driving behavior evaluation method cannot intuitively reflect the driving behavior defects of the customer due to lack of real-time data collection and use, and effectively helping the customer to improve the bad driving behavior.

[0070] Referring to Figure 2 , the driving data collection and analysis method in the second embodiment of the application is shown, which comprises steps S101 to S107, wherein:

[0071] Step S101: acquiring the communication request sent by the user terminal, and establishing a connection with the user terminal according to the communication request;

[0072] It should be noted that there are mainly two ways to wake up the vehicle terminal, one is that the user remotely sends a communication request to the CAN bus of the target vehicle through the mobile terminal, so that the mobile terminal and the CAN bus establish a connection.

[0073] Step S102: after successfully establishing a connection with the user terminal, acquiring the wake-up message issued by the user through the CAN network;

[0074] It can be understood that after the mobile terminal establishes communication with the CAN bus, the CAN bus sends a wake-up message to the vehicle terminal to wake up the vehicle terminal.

[0075] Step S103: actively acquiring the various driving data of the target vehicle every first preset time, the driving data including vehicle speed, engine speed, throttle pedal stroke value, brake pedal stroke value, steering wheel angle and steering wheel angle acceleration.

[0076] It should be noted that, in the process of data acquisition, in order to prevent the existence of wireless data caused by signal and other reasons, and avoid the influence of low accuracy on subsequent data processing, when the various driving data of the current period are obtained, the error values of the various driving data are calculated according to the driving data of the last period and the driving data of the current period; it is judged whether the error value of the driving data is greater than the first preset error threshold value; if the error value of the driving data is greater than the first preset error threshold value, the driving data with the error value greater than the first preset error threshold value is deleted, and the driving data with the error value greater than the first preset error threshold value is collected again within the sixth preset time; the error values of the driving data collected within the sixth preset time are repeatedly calculated until the error values corresponding to all the driving data are less than or equal to the first preset error threshold value. Thus, it is ensured that the various driving data in the current period are all valid data.

[0077] For example but not limited to, when the customer is driving normally, the vehicle speed is stable at about 80KM / H, and if the data collected in the current period suddenly appears a message with vehicle speed of 0, it is determined that the error of the collected vehicle speed data is large, that is, the vehicle speed data is abnormal data, which is automatically discarded, and is collected again within the sixth preset time. It should be noted that the sixth preset time is generally within 30ms to respond quickly and avoid long collection time interval.

[0078] Step S103: obtaining the driving behavior of the driver in the current period according to the vehicle speed, the engine speed, the accelerator pedal stroke value, the brake pedal stroke value, the steering wheel angle and the steering wheel angle acceleration, the driving behavior at least including idling for too long, rapid acceleration driving, rapid braking driving and rapid turning driving;

[0079] It should be noted that the step of judging that the target vehicle is idling for too long includes:

[0080] If the current vehicle speed of the target vehicle is zero and the engine speed is greater than the first preset speed, the first duration of the target vehicle in the current state is obtained by starting timing; at the same time, it is judged whether the first duration is greater than the first preset time threshold value; if the first duration is greater than the first preset time threshold value, it is determined that the target vehicle is in the idling for too long state.

[0081] For example but not limited to, engine speed > 0 and vehicle speed = 0, then start timing, and form an idling for too long event when the condition is maintained for 5 minutes, trigger an idling for too long event message to record the driving behavior once according to the idling for too long event message.

[0082] The step of judging that the target vehicle is rapid acceleration driving includes:

[0083] If the current vehicle speed of the target vehicle is greater than zero and the accelerator pedal stroke value is greater than a first preset accelerator pedal threshold, a plurality of vehicle speeds are acquired every second preset time, and an average longitudinal acceleration of the target vehicle is acquired according to the vehicle speeds at a plurality of adjacent time points; it is judged whether the average longitudinal acceleration is greater than a first preset longitudinal acceleration threshold; if the average longitudinal acceleration is greater than the first preset longitudinal acceleration threshold, it is determined that the target vehicle is in the rapid acceleration driving.

[0084] By way of example but not limitation, in the present embodiment, it needs to be pointed out that when the accelerator pedal stroke value is greater than 0, it can be preliminarily judged that the vehicle is accelerating, at this time, the vehicle speed of a plurality of time periods is continuously monitored, so as to calculate the longitudinal acceleration according to the vehicle speeds of the continuous time periods, and then it is judged whether the longitudinal acceleration value is greater than 5 m / s 2 , if it is greater, it is determined to be rapid acceleration driving. The second preset time is set to be less than the first preset time, that is, if it is judged that the accelerator pedal stroke is greater than 0 within the period corresponding to the first preset time, the vehicle terminal will collect the vehicle speed multiple times within the period, so as to accurately analyze the current longitudinal acceleration value.

[0085] The steps of judging that the target vehicle is in the rapid braking driving and the rapid turning driving are as follows:

[0086] If the current vehicle speed of the target vehicle is greater than zero and the brake pedal stroke value is greater than a first preset brake pedal threshold, a plurality of vehicle speeds are acquired every third preset time, and an average longitudinal deceleration of the target vehicle is acquired according to the vehicle speeds at a plurality of adjacent time points; it is judged whether the average longitudinal deceleration is greater than a first preset longitudinal deceleration threshold; if the average longitudinal deceleration threshold is greater than the first preset longitudinal deceleration threshold, it is determined that the target vehicle is in the rapid deceleration state; that is, the principles of judging the rapid acceleration and the rapid deceleration are basically the same, except that the rapid acceleration is triggered by the accelerator pedal stroke, and the rapid deceleration is triggered by the brake pedal stroke.

[0087] It also needs to be pointed out that if the vehicle speed of the target vehicle is greater than a first preset vehicle speed and the steering wheel angle is greater than a first preset steering wheel angle, it is judged whether the current steering wheel angle acceleration of the target vehicle is greater than a first preset steering wheel angle acceleration; if the current steering wheel angle acceleration of the target vehicle is greater than the first preset steering wheel angle acceleration, it is determined that the target vehicle is in the rapid turning driving.

[0088] By way of example but not limitation, when it is detected that the vehicle is running (vehicle speed > 30 km / h) and the steering wheel angle > 90 deg, it is judged whether the steering wheel angle acceleration is greater than 100 deg / s, if the steering wheel angle is greater than 100 deg / s at this time, the rapid turning event is triggered to record the rapid turning driving once.

[0089] Step S104: acquiring engine state data of the target vehicle every fifth preset time, the engine state data including a preset message defining the current state of the engine;

[0090] It should be further noted that the bad driving behavior of the driver is easy to cause the fuel consumption of the vehicle to increase, and thus there is a problem of high driving fuel consumption. Based on this, before generating the trip report, the vehicle terminal will also continuously detect engine state data to monitor the real-time state of the engine according to the engine state data.

[0091] Step S105: determining whether the target vehicle is in a start state or an off state according to field information in the preset message;

[0092] For example, but not limited to, Table 1 is a preset message corresponding to the record of the current state of the engine in this embodiment, which includes function items and bytes associated with the function items. For example, for the engine state in the function item, there are four kinds of byte information, according to which the current state of the engine can be clearly determined to be start, off or abnormal, etc.

[0093] Table 1

[0094]

[0095] Further, when it is monitored that the target vehicle is in the start state, the initial data of the oil quantity, the initial data of the mileage and the initial time of the trip of the target vehicle are acquired;

[0096] When it is monitored that the target vehicle is in the off state, the final data of the oil quantity, the final data of the mileage and the final time of the trip of the target vehicle are acquired.

[0097] Step S106: aggregating all the driving behaviors of the target vehicle determined to obtain the cumulative number of the target vehicle in various driving states;

[0098] Step S107: generating the trip report according to the cumulative number of the target vehicle in various driving states in this driving and the trip data.

[0099] It should be noted that the trip data of the target vehicle is acquired according to the following formula:

[0100] H0 = (Z1-Z2)·L / (S2-S1)

[0101] V0 = (S2-S1) / (t2-t1)

[0102] Wherein, H0 represents the average fuel consumption of this driving, Z2 represents the oil final data, Z1 represents the oil initial data, S2 represents the mileage final data, S1 represents the mileage initial data, L represents the fuel tank volume of the target vehicle, V0 represents the average speed of this driving, t2 represents the trip final time, and t1 represents the trip initial time.

[0103] That is, by judging the starting state of the engine, the initial data of the oil, mileage, etc. of the target vehicle before driving is obtained, by monitoring the engine off state, the final data of the oil, mileage, etc. of the target vehicle after driving is obtained, and then the average speed and the oil consumption of this driving are accurately calculated according to the above formula, and then combined with various bad driving behavior data in this driving, so that the customer can intuitively judge the bad driving habits he has and the oil consumption of this driving. Since the customer purchases from the factory, the manufacturer will generally give the fuel consumption rate, so the customer can clearly know that the high oil consumption caused by bad driving behavior causes the problem of uneconomical driving, so as to be more conducive to the customer to actively improve the bad driving behavior.

[0104] It should be noted that the trip report obtained above is a daily trip report, and the attendance rate, vehicle use time and vehicle use cost of the customer in the month, quarter and year are calculated according to the content contained in the daily trip report. The attendance rate is obtained by dividing the number of days with daily trip reports by the total number of days in the month, quarter and year, the vehicle use time is the total driving time of each driving, and the single driving time is obtained by subtracting the initial driving time from the final driving time. The vehicle use cost is calculated according to the fuel consumption value generated by each driving. Specifically, the vehicle use cost is the sum of the fuel consumption cost and the maintenance cost, wherein the maintenance cost is obtained by the customer actively uploading through the mobile terminal. By generating daily, monthly, quarterly and annual trip reports, various trip reports are pushed to the customer through the cloud service platform, so that the customer can timely understand the use of his own vehicle.

[0105] In summary, according to the driving data collection and analysis method, the user driving data is collected and used in real time to obtain the corresponding trip report of the customer in each driving, so that the specific bad driving habits of the customer in actual driving are intuitively embodied, and the customer can be targeted to improve. Specifically, first, the vehicle terminal can obtain the wake-up request in real time, so as to make itself in a wake-up state according to the wake-up request, and then know that the customer is using the target vehicle, so as to start the data collection and analysis work, and then collect the driving data of the target vehicle every first preset time, so as to analyze the current driving behavior of the customer according to the driving data collected each time, the driving behavior at least including long idling driving, high-speed driving, sudden braking driving and sudden turning driving, so as to generate a trip report containing the cumulative number of various driving behaviors, and then send the trip report to the cloud service platform, so that the customer can check at any time, and the bad driving habits of the customer in actual driving are intuitively and accurately displayed, thereby solving the problem that the traditional customer driving behavior evaluation method cannot intuitively reflect the driving behavior defects of the customer due to lack of collection and use of real-time data, and effectively helping the customer to improve the bad driving behavior.

[0106] Please refer to Figure 3 , which is a structure schematic diagram of the driving data collection and analysis system in the third embodiment of the present application, and the system comprises:

[0107] The wake-up module 10 is used for obtaining the wake-up request sent by the CAN network of the whole vehicle, and making itself in a wake-up state according to the wake-up request, and the wake-up request is triggered by the CAN network receiving an external unlock request;

[0108] Further, the wake-up module 10 further comprises:

[0109] The communication connection unit is used for obtaining the communication request sent by the user terminal, and establishing a connection with the user terminal according to the communication request;

[0110] The wake-up message receiving unit is used for obtaining the wake-up message issued by the user through the CAN network after successfully establishing a connection with the user terminal

[0111] The driving data collection module 20 is used for actively obtaining the driving data of the target vehicle every first preset time after being in a wake-up state, and the driving data includes vehicle speed, engine speed, throttle pedal stroke value, brake pedal stroke value, steering wheel angle and steering wheel angle acceleration;

[0112] Further, the driving data collection module further comprises:

[0113] The error value calculation unit is used for calculating the error value of various driving data according to the driving data of the last period and the driving data of the current period.​

[0114] an error value monitoring unit configured to determine whether an error value of the driving data is greater than a first preset error threshold value;

[0115] a driving data repeated collection unit configured to, if the error value of the driving data is greater than the first preset error threshold value, delete the driving data with the error value greater than the first preset error threshold value and repeatedly collect the driving data with the error value greater than the first preset error threshold value within a sixth preset time;

[0116] a driving data repeated monitoring unit configured to repeatedly calculate the error value of the driving data collected within the sixth preset time until the error values corresponding to all the driving data are less than or equal to the first preset error threshold value.

[0117] a driving data analysis module 30 configured to obtain a driving behavior of a driver in a current period according to the vehicle speed, the engine speed, the throttle pedal stroke value, the brake pedal stroke value, the steering wheel angle and the steering wheel angle acceleration, the driving behavior at least including an idle driving for too long, an urgent acceleration driving, an urgent braking driving and an urgent turning driving;

[0118] Further, the driving data analysis module 30 further includes:

[0119] an idle driving for too long monitoring unit configured to, if the current vehicle speed of the target vehicle is zero and the engine speed is greater than a first preset engine speed, start timing to obtain a first duration of the target vehicle in a current state;

[0120] determine whether the first duration is greater than a first preset time threshold value;

[0121] if the first duration is greater than the first preset time threshold value, determine that the target vehicle is in the idle driving for too long state.

[0122] an urgent acceleration driving monitoring unit configured to, if the current vehicle speed of the target vehicle is greater than zero and the throttle pedal stroke value is greater than a first preset throttle pedal threshold value, obtain a plurality of vehicle speeds every second preset time and obtain an average longitudinal acceleration of the target vehicle according to the vehicle speeds at a plurality of adjacent time points;

[0123] determine whether the average longitudinal acceleration is greater than a first preset longitudinal acceleration threshold value;

[0124] if the average longitudinal acceleration is greater than the first preset longitudinal acceleration threshold value, determine that the target vehicle is in the urgent acceleration driving.

[0125] The sudden braking driving monitoring unit, if the current speed of the target vehicle is greater than zero, and the brake pedal stroke value is greater than a first preset brake pedal threshold, then a plurality of speeds are obtained every third preset time, and an average longitudinal deceleration of the target vehicle is obtained according to the speeds at adjacent times;

[0126] It is judged whether the average longitudinal deceleration is greater than a first preset longitudinal deceleration threshold;

[0127] If the average longitudinal deceleration threshold is greater than the first preset longitudinal deceleration threshold, it is determined that the target vehicle is in a sudden deceleration state.

[0128] The sudden turn driving monitoring unit, if the speed of the target vehicle is greater than a first preset speed, and the steering wheel angle is greater than a first preset steering wheel angle, it is judged whether the current steering wheel angle acceleration of the target vehicle is greater than a first preset steering wheel angle acceleration;

[0129] If the current steering wheel angle acceleration of the target vehicle is greater than the first preset steering wheel angle acceleration, it is determined that the target vehicle is in a sudden turn driving.

[0130] The trip report construction module 40 is configured to generate a trip report of the target vehicle according to the driving behaviors corresponding to a plurality of consecutive periods respectively, and upload the trip report to a cloud service platform, the trip report including the cumulative number of times of the prolonged idling driving, the sudden acceleration driving, the sudden braking driving and the sudden turn driving of the driver in this driving.

[0131] Further, the trip report construction module 40 further includes:

[0132] The driving state statistical unit is configured to aggregate all the driving behaviors of the target vehicle determined to obtain the cumulative number of times of the target vehicle in various driving states;

[0133] The trip data acquisition unit is configured to obtain the trip data of the target vehicle according to the following formula:

[0134] H0=(Z1-Z2)·L / (S2-S1)

[0135] V0=(S2-S1) / (t2-t1)

[0136] Wherein, H0 represents the average fuel consumption of this driving, Z2 represents the final oil data, Z1 represents the initial oil data, S2 represents the final mileage data, S1 represents the initial mileage data, L represents the fuel tank volume of the target vehicle, V0 represents the average speed of this driving, t2 represents the final trip time, and t1 represents the initial trip time;

[0137] a trip report generation unit configured to generate the trip report according to the cumulative number of various driving states of the target vehicle in the current driving and the trip data.

[0138] Further, in some optional embodiments of the present application, the system further comprises:

[0139] an engine state data acquisition module configured to acquire engine state data of the target vehicle every fifth preset time, the engine state data comprising a preset message defining the current state of the engine;

[0140] an engine state data analysis module configured to determine whether the target vehicle is in a starting state or an off state according to the field information in the preset message;

[0141] an initial data acquisition module configured to acquire initial fuel data, initial mileage data and initial trip time of the target vehicle when it is monitored that the target vehicle is in the starting state;

[0142] a final data acquisition module configured to acquire final fuel data, final mileage data and final trip time of the target vehicle when it is monitored that the target vehicle is in the off state.

[0143] In summary, according to the driving data acquisition and analysis method described above, the user driving data is collected and used in real time to obtain the corresponding trip report of the customer in each driving, so as to intuitively reflect the specific bad driving habits of the customer in actual driving, and facilitate the customer to improve targetedly. Specifically, first, the vehicle terminal will acquire a wake-up request in real time, so as to make itself in a wake-up state according to the wake-up request, and then know that the customer is using the target vehicle, so as to start the data acquisition and analysis work. Then, various driving data of the target vehicle is collected every first preset time, so as to analyze the current driving behavior of the customer according to the driving data collected each time, which at least includes long-idle driving, high-speed driving, sudden braking driving and sudden turning driving, so as to generate a trip report containing the cumulative number of various driving behaviors, and then send the trip report to the cloud service platform, so that the customer can check at any time. Through intuitive and accurate display of the bad driving habits of the customer in actual driving, the problem that the traditional customer driving behavior evaluation method cannot intuitively reflect the driving behavior defects of the customer due to lack of real-time data collection and use is solved, and the customer can be effectively helped to improve the bad driving behavior.

[0144] In another aspect, the present application also provides a readable storage medium having one or more programs stored thereon, which programs, when executed by a processor, implement the driving data acquisition and analysis method described above.

[0145] Another aspect of the present application also provides a vehicle comprising a memory and a processor, wherein the memory is configured to store a computer program, and the processor is configured to execute the computer program stored in the memory to implement the driving data collection and analysis method described above.

[0146] Those skilled in the art will appreciate that the logic and / or steps represented in the flow diagrams, or otherwise described herein, can be embodied in one or more computer-readable media, executed by an instruction execution system, apparatus, or device, such as a computer-based system, a processor- based system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions, or in conjunction with which the instructions may be executed. For purposes of this specification, a "computer-readable medium" can be any apparatus that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. The computer-readable medium can be a computer- readable storage medium or a computer-readable signal medium.

[0147] More specific examples (a non-exhaustive list) of the computer-readable medium include the following: an electrical connection (electronic) having one or more wires, a portable computer diskette (magnetic), a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium can also be paper or other suitable medium upon which the program is printed, as the program can be electronically captured, for example, via an optical scanner, then compiled, interpreted, or otherwise processed, and stored in a computer memory in a form that can be later executed by a computer. In some embodiments, the computer-readable medium can be a computer program product that can be traded or sold, for example, a floppy disk, a CD-ROM, an optical disk, and the like.

[0148] It should be understood that aspects of the present application can be implemented in hardware, software, firmware, or combinations thereof. In the above embodiments, various steps or methods can be implemented in software or firmware that is stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, and in another embodiment, any of the following technologies, known in the art, or combinations thereof, can be used: discrete logic circuitry having logic gates for implementing logic functions upon data signals, application specific integrated circuits having appropriate combinational logic gates, programmable gate arrays (PGA), field programmable gate arrays (FPGA), and so forth.

[0149] In the description of the present specification, the description of the terms "one embodiment", "some embodiments", "an example", "a specific example", or "some examples" and the like means that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. In the present specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0150] The above-described embodiments only express several implementation manners of the present application, which are described in a more specific and detailed manner, but cannot be understood as a limitation on the patent scope of the present application. It should be noted that, for those skilled in the art, several modifications and improvements can be made without departing from the concept of the present application, which are all within the protection scope of the present application. Therefore, the protection scope of the patent of the present application should be subject to the appended claims.

Claims

1. A driving data collection and analysis method applied to a vehicle terminal, characterized in that, The method comprises: acquiring a wake-up request sent by a whole vehicle CAN network and making itself in a wake-up state according to the wake-up request, the wake-up request being triggered by the CAN network receiving an external unlock request; acquiring multiple driving data of a target vehicle every first preset time after being in the wake-up state, the driving data comprising vehicle speed, engine speed, throttle pedal stroke value, brake pedal stroke value, steering wheel angle and steering wheel angle acceleration; acquiring driving behavior of a driver in a current period according to the vehicle speed, the engine speed, the throttle pedal stroke value, the brake pedal stroke value, the steering wheel angle and the steering wheel angle acceleration, the driving behavior at least comprising long-idle driving, rapid acceleration driving, rapid brake driving and rapid turning driving; generating a driving report of the target vehicle according to driving behavior corresponding to multiple continuous periods respectively and uploading the driving report to a cloud service platform, the driving report comprising cumulative number of each driving behavior corresponding to the driver in the current driving; generating corresponding monthly, quarterly and annual reports according to the driving report of different time periods according to a preset period and sending the reports to a customer; the step of generating the driving report of the target vehicle according to the driving behavior corresponding to multiple continuous periods respectively and uploading the driving report to the cloud service platform comprises: summarizing all the driving behavior of the target vehicle to obtain cumulative number of the target vehicle in various driving states; acquiring driving data of the target vehicle according to the following formula: H0= (Z1-Z2)·L / (S2-S1) V0=(S2-S1) / (t2-t1) wherein, H0 represents average fuel consumption of the current driving, Z2 represents final oil data, Z1 represents initial oil data, S2 represents final mileage data, S1 represents initial mileage data, L represents tank volume of the target vehicle, V0 represents average speed of the current driving, t2 represents final driving time and t1 represents initial driving time; manufacturing the driving report according to the cumulative number of the target vehicle in various driving states in the current driving and the driving data.

2. The method of claim 1, wherein, the step of acquiring multiple driving data of the target vehicle every first preset time after being in the wake-up state, the driving data comprising vehicle speed, engine speed, throttle pedal stroke value, brake pedal stroke value, steering wheel angle and steering wheel angle acceleration comprises: calculating error values of various driving data according to driving data of a previous period and driving data of the current period; judging whether there is an error value of driving data greater than a first preset error threshold value; if there is an error value of driving data greater than the first preset error threshold value, deleting the driving data with the error value greater than the first preset error threshold value and repeatedly collecting the driving data with the error value greater than the first preset error threshold value once within a sixth preset time; repeatedly calculating error values of the driving data collected within the sixth preset time until error values of all the driving data are less than or equal to the first preset error threshold value.

3. The method of claim 1, wherein, The step of judging that the target vehicle is in the state of the idle driving for too long comprises: If the current vehicle speed of the target vehicle is zero and the engine speed is greater than a first preset engine speed, start timing to obtain a first duration of the target vehicle in the current state; Judge whether the first duration is greater than a first preset time threshold; If the first duration is greater than the first preset time threshold, determine that the target vehicle is in the state of the idle driving for too long.

4. The driving data collection and analysis method of claim 3, wherein, The step of judging that the target vehicle is in the state of the rapid acceleration driving further comprises: If the current vehicle speed of the target vehicle is greater than zero and the accelerator pedal stroke value is greater than a first preset accelerator pedal threshold, obtain a plurality of vehicle speeds every second preset time, and obtain the average longitudinal acceleration of the target vehicle according to the vehicle speeds at a plurality of adjacent time points; Judge whether the average longitudinal acceleration is greater than a first preset longitudinal acceleration threshold; If the average longitudinal acceleration is greater than the first preset longitudinal acceleration threshold, determine that the target vehicle is in the state of the rapid acceleration driving.

5. The driving data collection and analysis method of claim 4, wherein, The step of judging that the target vehicle is in the state of the rapid braking driving and the rapid turning driving comprises: If the current vehicle speed of the target vehicle is greater than zero and the brake pedal stroke value is greater than a first preset brake pedal threshold, obtain a plurality of vehicle speeds every third preset time, and obtain the average longitudinal deceleration of the target vehicle according to the vehicle speeds at a plurality of adjacent time points; Judge whether the average longitudinal deceleration is greater than a first preset longitudinal deceleration threshold; If the average longitudinal deceleration is greater than the first preset longitudinal deceleration threshold, determine that the target vehicle is in the state of the rapid deceleration; If the vehicle speed of the target vehicle is greater than a first preset vehicle speed and the steering wheel angle is greater than a first preset steering wheel angle, judge whether the current steering wheel angle acceleration of the target vehicle is greater than a first preset steering wheel angle acceleration; If the current steering wheel angle acceleration of the target vehicle is greater than the first preset steering wheel angle acceleration, determine that the target vehicle is in the state of the rapid turning driving.

6. The driving data collection and analysis method of claim 5, wherein, The method further comprises: Obtain the engine state data of the target vehicle every fifth preset time, the engine state data comprising a preset message defining the current state of the engine; Judge whether the target vehicle is in the state of starting or the state of turning off according to the field information in the preset message; When it is monitored that the target vehicle is in the state of starting, obtain the initial data of fuel consumption, the initial data of mileage and the initial time of travel of the target vehicle; When it is monitored that the target vehicle is in the state of turning off, obtain the final data of fuel consumption, the final data of mileage and the final time of travel of the target vehicle.

7. A driving data collection and analysis system applied to a vehicle terminal, characterized in that, The system for implementing the driving data acquisition and analysis method according to any one of claims 1 to 6 comprises: An awakening module, configured to obtain an awakening request sent by a CAN network of the whole vehicle, and make itself in an awakening state according to the awakening request, the awakening request being triggered by the CAN network receiving an external unlocking request; The driving data collection module is configured to actively acquire driving data of the target vehicle every first preset time after the target vehicle is in the wake-up state, the driving data including vehicle speed, engine speed, throttle pedal stroke value, brake pedal stroke value, steering wheel rotation angle, and steering wheel rotation angle acceleration; The driving data analysis module is configured to acquire driving behavior of the driver in the current period according to the vehicle speed, the engine speed, the throttle pedal stroke value, the brake pedal stroke value, the steering wheel rotation angle, and the steering wheel rotation angle acceleration, the driving behavior including at least over-long-idling driving, rapid-acceleration driving, rapid-braking driving, and rapid-turning driving. The trip report construction module is configured to generate a trip report of the target vehicle according to the driving behavior corresponding to each of the plurality of continuous periods, and upload the trip report to a cloud service platform, the trip report including the cumulative number of each driving behavior of the driver in the current driving.

8. A readable storage medium, characterized by, The computer program is stored in the readable storage medium and executed by the processor to implement the driving data collection and analysis method according to any one of claims 1-6. The vehicle includes a memory and a processor, wherein:

9. A vehicle characterized by comprising: The memory is configured to store a computer program; The processor is configured to execute the computer program stored in the memory to implement the driving data collection and analysis method according to any one of claims 1-6. ​

Images