Driving behavior processing method and device, equipment and storage medium

Abstract

The application relates to the technical field of vehicles and discloses a driving behavior processing method, device and equipment and a storage medium, the method comprising the following steps: acquiring current driving data of a vehicle and current road data of a driving road of the vehicle; determining index data corresponding to each driving index according to the current driving data and the current road data; calculating index scores of the driving indexes according to the index data; when it is determined that a user has an abnormal driving behavior according to the index scores of the driving indexes, processing the abnormal driving behavior; in the above manner, the index scores of the driving indexes are calculated by using the index data, and it is determined whether the user has an abnormal driving behavior according to the index scores of the driving indexes; if yes, the abnormal driving behavior is processed, so that the accuracy of determining the abnormal driving behavior can be effectively improved, and the abnormal driving behavior can be processed in time, so that the driving safety is improved.

Description

Technical Field

[0001] This invention relates to the field of vehicle technology, and more particularly to driving behavior processing methods, devices, equipment, and storage media. Background Technology

[0002] With the continuous development of vehicle-to-everything (V2X) technology, vehicles have become one of the best means of transportation for people. However, with the increase in vehicles, violations and traffic accidents have emerged one after another. A large amount of traffic data shows that traffic accidents are closely related to driving behavior, such as abnormal driving behavior. Currently, the method for identifying abnormal driving behavior is based on a rough judgment using single-index data collected by sensor devices. However, single-index data is prone to errors, resulting in low accuracy in identifying abnormal driving behavior and untimely warnings.

[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 processing method, apparatus, device, and storage medium, aiming to solve the technical problem that the accuracy of existing technologies in identifying abnormal driving behavior is low, resulting in untimely warnings.

[0005] To achieve the above objectives, the present invention provides a driving behavior processing method, which includes the following steps:

[0006] Obtain the vehicle's current driving data and the current road data of the road the vehicle is traveling on;

[0007] Determine the corresponding indicator data for each driving indicator based on the current driving data and the current road data;

[0008] Calculate the score for each driving indicator based on the aforementioned indicator data;

[0009] When it is determined that a user has abnormal driving behavior based on the comprehensive scores of the various driving indicators, the abnormal driving behavior will be processed.

[0010] Optionally, determining the indicator data corresponding to each driving indicator based on the current driving data and the current road data includes:

[0011] The mean of the current driving data and the current road data are aggregated separately.

[0012] The vehicle speed, drive motor speed, and charging status are obtained from the current driving data after the average aggregation.

[0013] The driving data with the vehicle speed at a preset vehicle speed threshold, the rotation speed less than a preset rotation speed threshold, and the charging state at a preset state are cleaned to obtain the target driving data.

[0014] The target driving data and the current road data after average aggregation are divided by preset driving index rules to obtain the index data corresponding to each driving index.

[0015] Optionally, the step of calculating the index score for each driving indicator based on the index data includes:

[0016] Establish benchmark values ​​for economic driving indicators, safety driving indicators, and standardized driving indicators;

[0017] Based on the aforementioned indicator data, we obtain economic driving indicator data, safe driving indicator data, and standardized driving indicator data;

[0018] Energy consumption data and the number of abnormal driving incidents are determined based on the aforementioned economic driving index data;

[0019] The economic driving index score is calculated based on the energy consumption data, the number of abnormal driving operations, and the baseline value of the economic driving index data.

[0020] Based on the aforementioned safe driving index data, determine the duration of abnormal driving, the number of abnormal pedaling incidents, and the abnormal transport data.

[0021] The safety driving index score is calculated based on the duration of abnormal driving, the number of abnormal steps, the abnormal transport data, and the baseline value of the safety driving index data.

[0022] The standard driving indicator score is calculated based on the standard driving indicator data and the standard driving indicator data benchmark value.

[0023] Optionally, determining energy consumption data and abnormal driving frequency based on the economic driving index data includes:

[0024] The speed difference and turning radius between adjacent time points are determined based on the aforementioned economic indicator data;

[0025] The number of abnormal driving incidents is determined based on the speed difference between adjacent moments and the turning radius.

[0026] The total recovered electricity and total consumed electricity are determined based on the aforementioned economic indicator data;

[0027] Energy consumption data is determined based on the total recovered electricity and the total consumed electricity.

[0028] Optionally, determining the duration of abnormal driving, the number of abnormal stampings, and the abnormal transport data based on the safety driving index data includes:

[0029] The vehicle's current gear, current speed, and power-on / off interval are obtained based on the aforementioned safe driving index data.

[0030] The duration of abnormal driving is determined based on the current gear, current vehicle speed, and vehicle power-on / off interval.

[0031] The pedal opening at adjacent moments is obtained based on the aforementioned safe driving index data;

[0032] The number of abnormal pedaling incidents is determined based on the pedal opening at adjacent moments.

[0033] The vehicle's current carrying data is obtained based on the aforementioned safe driving index data;

[0034] Abnormal transport data is determined based on the current transport data and the specified load data.

[0035] Optionally, the step of calculating the economic driving index score based on the energy consumption data, the number of abnormal driving trips, and the baseline value of the economic driving index data includes:

[0036] Based on the aforementioned benchmark values ​​for economic driving indicators, the mean and standard deviation of the economic driving indicators are obtained.

[0037] Calculate the differences between the energy consumption data, the number of abnormal driving times, and the average value of the economic driving index data for several quantities.

[0038] Calculate the multiple of the difference between the aforementioned quantities and the standard deviation of the economic driving index data;

[0039] The economic driving index score is calculated based on the multiplier.

[0040] Optionally, when it is determined that a user has abnormal driving behavior based on the comprehensive scores of the various driving indicators, the step of processing the abnormal driving behavior includes:

[0041] Based on the scores of each driving indicator, we obtain the scores for economic driving, safe driving, and standardized driving.

[0042] Based on the comparison results of the economic driving index score with the preset economic index average, the comparison results of the safe driving index score with the preset safety index average, and the comparison results of the standard driving index score with the preset standard index average, it is determined whether the user has abnormal driving behavior.

[0043] If so, the abnormal driving behavior will be processed.

[0044] Furthermore, to achieve the above objectives, the present invention also proposes a driving behavior processing device, the driving behavior processing device comprising:

[0045] The acquisition module is used to acquire the vehicle's current driving data and the current road data of the road the vehicle is traveling on;

[0046] The determination module is used to determine the indicator data corresponding to each driving indicator based on the current driving data and the current road data;

[0047] The calculation module is used to calculate the index score of each driving index based on the index data;

[0048] The processing module is used to process the abnormal driving behavior when it is determined that the user has abnormal driving behavior based on the comprehensive score of each driving indicator.

[0049] Furthermore, to achieve the above objectives, the present invention also proposes a driving behavior processing device, the driving behavior processing device comprising: a memory and a processor, wherein the memory stores a driving behavior processing program that can run on the processor, the driving behavior processing program being configured to implement the driving behavior processing method as described above.

[0050] In addition, to achieve the above objectives, the present invention also proposes a storage medium storing a driving behavior processing program, which, when executed by a processor, implements the driving behavior processing method as described above.

[0051] The driving behavior processing method proposed in this invention acquires the vehicle's current driving data and the current road data of the road the vehicle is traveling on; determines the indicator data corresponding to each driving indicator based on the current driving data and the current road data; calculates the indicator score of each driving indicator based on the indicator data; and processes the abnormal driving behavior when the indicator scores of each driving indicator are comprehensively used to determine whether the user has abnormal driving behavior. Through the above method, by determining the indicator data based on the vehicle's current driving data and the current road data of the road the vehicle is traveling on, calculating the indicator score of each driving indicator using the indicator data, and comprehensively judging whether the user has abnormal driving behavior based on the indicator scores of each driving indicator, and if so, processing the abnormal driving behavior, it can effectively improve the accuracy of determining abnormal driving behavior and promptly process abnormal driving behavior, thereby improving driving safety. Attached Figure Description

[0052] Figure 1 This is a schematic diagram of the structure of the driving behavior processing device in the hardware operating environment involved in the embodiments of the present invention;

[0053] Figure 2This is a flowchart illustrating the first embodiment of the driving behavior processing method of the present invention;

[0054] Figure 3 This is a schematic diagram of various indicator radars in an embodiment of the driving behavior processing method of the present invention;

[0055] Figure 4 This is a flowchart illustrating the second embodiment of the driving behavior processing method of the present invention;

[0056] Figure 5 This is a flowchart illustrating the third embodiment of the driving behavior processing method of the present invention;

[0057] Figure 6 This is a schematic diagram of the functional modules of the first embodiment of the driving behavior processing device of the present invention.

[0058] 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

[0059] It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the scope of the invention.

[0060] Reference Figure 1 , Figure 1 This is a schematic diagram of the driving behavior processing device structure in the hardware operating environment involved in the embodiments of the present invention.

[0061] like Figure 1 As shown, the driving behavior processing device may include: a processor 1001, such as a central processing unit (CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. The communication bus 1002 is used to enable communication between these components. The user interface 1003 may include a display screen or an input unit such as a keyboard; optionally, the user interface 1003 may also include a standard wired interface or a wireless interface. The network interface 1004 may optionally include a standard wired interface or a wireless interface (such as a Wireless-Fidelity (Wi-Fi) interface). The memory 1005 may be a high-speed random access memory (RAM) or a stable non-volatile memory (NVM), such as a disk drive. The memory 1005 may also optionally be a storage device independent of the aforementioned processor 1001.

[0062] Those skilled in the art will understand that Figure 1The structure shown does not constitute a limitation on the driving behavior processing device and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0063] like Figure 1 As shown, the memory 1005, which serves as a storage medium, may include an operating system, a network communication module, a user interface module, and a driving behavior processing program.

[0064] exist Figure 1 In the driving behavior processing device shown, the network interface 1004 is mainly used for data communication with the network integrated platform workstation; the user interface 1003 is mainly used for data interaction with the user; the processor 1001 and the memory 1005 in the driving behavior processing device of the present invention can be set in the driving behavior processing device, and the driving behavior processing device calls the driving behavior processing program stored in the memory 1005 through the processor 1001 and executes the driving behavior processing method provided in the embodiment of the present invention.

[0065] Based on the above hardware structure, an embodiment of the driving behavior processing method of the present invention is proposed.

[0066] Reference Figure 2 , Figure 2 This is a flowchart illustrating the first embodiment of the driving behavior processing method of the present invention.

[0067] In a first embodiment, the driving behavior processing method includes the following steps:

[0068] Step S10: Obtain the vehicle's current driving data and the current road data of the road the vehicle is traveling on.

[0069] It should be noted that the execution subject in this embodiment is a driving behavior processing device, but it can also be other devices that can achieve the same or similar functions, such as a driving behavior processing platform. This embodiment does not limit this, and in this embodiment, a driving behavior processing platform is used as an example for explanation.

[0070] It should be understood that current driving data refers to the vehicle's driving data at the current moment. This current driving data includes, but is not limited to, data such as vehicle speed, drive motor speed, charging status, energy consumption, and turning angle. Current road data refers to the road data that the vehicle travels on. This current road data includes, but is not limited to, data such as road elevation, gradient, and traffic congestion. In addition, the vehicle can be a new energy bus.

[0071] Step S20: Determine the indicator data corresponding to each driving indicator based on the current driving data and the current road data.

[0072] Understandably, the indicator data refers to the data used to calculate the scores of various driving indicators. This indicator data includes economic driving indicator data, safe driving indicator data, and standardized driving indicator data. The economic driving indicator data includes, but is not limited to, data on rapid acceleration and deceleration per kilometer, energy recovery rate, energy consumption per 100 kilometers, and sharp turns. The safe driving indicator data includes, but is not limited to, data on sudden acceleration, sudden braking, fatigue driving, and speeding. The standardized driving indicator data includes data on traffic congestion and lane-occupying, and data on lane changes on slopes. Moreover, the indicator data corresponding to each driving indicator is obtained by dividing the current driving data and the current road data.

[0073] Step S30: Calculate the index score for each driving index based on the index data.

[0074] It should be understood that the indicator score refers to the total score of the sum of the scores of all driving indicators. There are multiple driving indicators, and the score of each driving indicator is calculated by using the indicator data and the corresponding mean and standard deviation. Then, the score of each driving indicator is calculated by adding the corresponding weight value to each driving indicator score. For example, Among them, w i This represents the weight value of each driving indicator, Score. i This represents the score for each driving indicator, where i represents the sequence number of each driving indicator.

[0075] Step S40: When it is determined that the user has abnormal driving behavior based on the comprehensive score of each driving indicator, the abnormal driving behavior is processed.

[0076] Understandably, after obtaining the scores of each driving indicator, the system determines whether the user has engaged in abnormal driving behavior based on the scores of each driving indicator and the corresponding preset average. If so, the abnormal driving behavior is processed. This processing method includes, but is not limited to, issuing warnings, pushing low scores from the comprehensive indicator score, and pushing prompts to avoid abnormal driving behavior.

[0077] Furthermore, to effectively improve the accuracy of determining whether a user has abnormal driving behavior, step S40 includes: obtaining an economic driving index score, a safe driving index score, and a standardized driving index score based on the index scores of each driving index; comprehensively determining whether the user has abnormal driving behavior based on the comparison results of the economic driving index score with the preset average economic index, the comparison results of the safe driving index score with the preset average safety index, and the comparison results of the standardized driving index score with the preset average standardized index; if so, processing the abnormal driving behavior.

[0078] It should be understood that the scores for each driving indicator include scores for economic driving, safe driving, and standardized driving. The economic driving score is then compared to the preset average economic driving score, the safe driving score is compared to the preset average safe driving score, and the standardized driving score is compared to the preset average standardized driving score. Based on the combined results of these three comparisons, it is determined whether the user has engaged in abnormal driving behavior. If so, the abnormal driving behavior is addressed, referring to... Figure 3 , Figure 3 The radar diagrams for each indicator include the economic indicator radar diagram and the safety indicator radar diagram. The economic indicator radar diagram shows that the scores for energy recovery rate and the number of rapid accelerations per kilometer are both lower than the corresponding preset economic indicator averages. The safety indicator radar diagram shows that the scores for the number of abnormal accelerator pedal presses, the number of abnormal brake pedal presses, and the fatigue driving duration are all lower than the preset safety indicator averages. At this point, it is determined that the user has abnormal driving behavior, and the abnormal driving behavior will be dealt with in a timely manner.

[0079] This embodiment acquires the vehicle's current driving data and the current road data of the road the vehicle is traveling on; determines the indicator data corresponding to each driving indicator based on the current driving data and the current road data; calculates the indicator score for each driving indicator based on the indicator data; and processes the abnormal driving behavior when it is determined that the user is exhibiting abnormal driving behavior based on the comprehensive indicator scores of each driving indicator. Through the above method, indicator data is determined based on the vehicle's current driving data and the current road data of the road the vehicle is traveling on, and then the indicator scores for each driving indicator are calculated using the indicator data. The system then comprehensively judges whether the user is exhibiting abnormal driving behavior based on the indicator scores of each driving indicator. If so, the abnormal driving behavior is processed, thereby effectively improving the accuracy of identifying abnormal driving behavior and providing timely warnings when abnormal driving behavior is present, thus improving driving safety.

[0080] In one embodiment, such as Figure 4 The second embodiment of the driving behavior processing method of the present invention, based on the first embodiment, includes step S20, which includes:

[0081] Step S201: Perform mean aggregation on the current driving data and the current road data respectively.

[0082] It should be understood that both the current driving data and the current road data are time series data. After obtaining the current driving data and the current road data, it is necessary to perform mean aggregation on the current driving data and the current road data respectively to obtain the feature values ​​of the current driving data and the current road data within the time period. For example, the second-level data is aggregated into minute-level data according to the mean. With a sampling rate of 1Hz, 60 seconds of data at a certain measuring point will be calculated as 1 record, and the corresponding value is the average value of the 60 seconds of data at that measuring point.

[0083] Step S202: Obtain the vehicle speed, drive motor speed, and charging status based on the current driving data after the average aggregation.

[0084] Understandably, vehicle speed refers to the vehicle's speed at the current moment, rotational speed refers to the rotational speed of the motor that drives the vehicle at the current moment, and charging status refers to the vehicle's charging status, which corresponds to the data recorded by the State of Charge (SOC).

[0085] Step S203: Clean the driving data where the vehicle speed is a preset vehicle speed threshold, the rotation speed is less than a preset rotation speed threshold, and the charging state is a preset state to obtain the target driving data.

[0086] It should be understood that after obtaining the current driving data, it is necessary to remove abnormal data from the current driving data. Abnormal data refers to driving data where the vehicle speed is at a preset speed threshold, the engine speed is less than a preset engine speed threshold, or the charging status is a preset status. The preset speed threshold can be 200 km / h, the preset engine speed threshold can be -500 rpm and 5000 rpm, and the preset status refers to the charging status corresponding to negative data. Abnormal data in the current driving data is removed by using data cleaning methods to obtain the target driving data.

[0087] Step S204: The target driving data and the current road data after average aggregation are divided by preset driving index rules to obtain the index data corresponding to each driving index.

[0088] Understandably, the preset driving indicator rules refer to the rules for dividing different driving indicator data. After obtaining the target driving data and the current road data after aggregating the average, the preset driving indicator rules are used to divide the target driving data and the current road data after aggregating the average into indicator data corresponding to each driving indicator.

[0089] This embodiment achieves mean aggregation on the current driving data and the current road data respectively; based on the mean-aggregated current driving data, the vehicle speed, drive motor speed, and charging status are obtained; driving data with speeds at preset speed thresholds, speeds below preset speed thresholds, and charging statuses at preset states are cleaned to obtain target driving data; the target driving data and the mean-aggregated current road data are divided using preset driving indicator rules to obtain indicator data corresponding to each driving indicator; through the above method, after obtaining the current driving data and the current road data, mean aggregation is performed on both, then abnormal data in the current driving data is removed, and then the target driving data and the mean-aggregated current road data are divided using preset driving indicator rules, thereby effectively improving the accuracy of obtaining indicator data corresponding to each driving indicator.

[0090] In one embodiment, such as Figure 5 The third embodiment of the driving behavior processing method of the present invention, based on the first embodiment, includes step S30, which includes:

[0091] Step S301: Determine the baseline values ​​for economic driving indicators, safe driving indicators, and standardized driving indicators.

[0092] It is understood that the benchmark values ​​for economic driving indicators, safe driving indicators, and standardized driving indicators can be calculated from the daily indicator data of vehicles of the same type as the vehicle, or they can be obtained through customization or other methods. This embodiment does not impose any restrictions on this. The benchmark values ​​for economic driving indicators, safe driving indicators, and standardized driving indicators are used to calculate the final scores of each driving indicator.

[0093] Step S302: Obtain economic driving index data, safe driving index data, and standardized driving index data based on the index data.

[0094] Step S303: Determine energy consumption data and abnormal driving frequency based on the economic driving index data.

[0095] It should be understood that energy consumption data refers to data related to energy consumption during vehicle operation. This energy consumption data includes, but is not limited to, energy recovery rate and energy consumption per 100 kilometers. The number of abnormal driving operations includes, but is not limited to, the number of sharp turns and the number of times of rapid acceleration and deceleration per kilometer.

[0096] Furthermore, in order to effectively improve the accuracy of determining the number of abnormal trips and energy consumption data, step S303 includes: determining the speed difference and turning radius between adjacent time points based on the economic index data; determining the number of abnormal trips based on the speed difference and turning radius between adjacent time points; determining the total recovered electricity and total consumed electricity based on the economic index data; and determining the energy consumption data based on the total recovered electricity and total consumed electricity.

[0097] It is understandable that the velocity difference between adjacent moments refers to the difference between the velocities at adjacent moments. For example, the velocity at moment A is v. t The velocity at time B is v t-1 And A and B are adjacent moments, at which point the velocity difference between adjacent moments is v. t -v t-1 Then, the vehicle's current acceleration is calculated based on the speed difference between adjacent moments and the time taken to turn. When the current acceleration is greater than the positive acceleration threshold, it indicates that the vehicle is accelerating rapidly. When the current acceleration is less than the negative acceleration threshold, it indicates that the vehicle is decelerating rapidly. The number of rapid accelerations and decelerations per kilometer is obtained by counting the number of times the current acceleration is greater than the positive acceleration threshold or less than the negative acceleration threshold.

[0098] It should be understood that total recovered current refers to the current recovered during vehicle operation, with the current being negative during the energy recovery process. Total consumed energy refers to the energy consumed by the vehicle during operation, with the current being negative during the energy consumption process. The energy recovery rate is then calculated based on the total recovered energy and the total consumed energy, specifically as follows:

[0099]

[0100] Among them, C hs C represents the energy recovery rate. recycle C represents the total amount of electricity recovered. cost This indicates the total power consumption.

[0101]

[0102] Among them, C recycle C represents the total amount of electricity recovered. cost C represents the total power consumption, and C represents the total power consumption per charge.

[0103]

[0104] Where C represents the total amount of electricity charged in a single charge, and I t U represents the current in the cross section at time t. t The voltage across the cross section at time t, where T represents the sampling time interval.

[0105] Understandably, after obtaining the total recovered electricity and the total consumed electricity, the energy consumption per 100 kilometers is calculated based on the vehicle's total mileage driven that day, specifically:

[0106]

[0107] Where N represents energy consumption per 100 kilometers, C recycle C represents the total amount of electricity recovered. cost S represents the total power consumption. day This indicates the total mileage traveled on that day.

[0108] It is understandable that the turning radius refers to the radius of a vehicle when turning. After obtaining the economic index data, the turning angle of the vehicle within the corresponding time period is calculated using the trajectory vector angle method. The turning radius is then calculated based on the vehicle speed and turning angle. Finally, a sharp turn is determined based on the vehicle speed and turning radius. Specifically, a sharp turn is determined when the vehicle speed exceeds a preset speed threshold and the turning radius exceeds a preset value. The number of sharp turns that occurred that day is then counted. If neither of the above conditions is met, the vehicle is determined not to have made a sharp turn. It should also be noted that turns with a turning angle less than 24 / π are not considered. This turning radius is calculated based on the vehicle speed and turning angle, specifically:

[0109]

[0110] Where r represents the turning radius, v t "Angle" indicates vehicle speed, and "angel" indicates turning angle.

[0111] angel=arcoss(V1*V2 / |V1|*|V2|) / 2*180 / π;

[0112] Where angel represents the turning angle, V1 represents the direction vector between the position point corresponding to the index data at time t and the position point corresponding to the index data at time t-1, and V2 represents the direction vector between the position point corresponding to the index data at time t and the position point corresponding to the index data at time t+1.

[0113]

[0114] Where x1 represents the x-coordinate of the index data point at time t-1 in the Cartesian coordinate system, y1 represents the y-coordinate of the index data point at time t-1 in the Cartesian coordinate system, z1 represents the y-coordinate of the index data point at time t-1 in the Cartesian coordinate system, x2 represents the x-coordinate of the index data point at time t in the Cartesian coordinate system, y2 represents the y-coordinate of the index data point at time t in the Cartesian coordinate system, z2 represents the y-coordinate of the index data point at time t in the Cartesian coordinate system, x3 represents the x-coordinate of the index data point at time t+1 in the Cartesian coordinate system, y3 represents the y-coordinate of the index data point at time t+1 in the Cartesian coordinate system, and z3 represents the y-coordinate of the index data point at time t+1 in the Cartesian coordinate system.

[0115]

[0116] Where lat1 represents the longitude of the sampled longitude at time t-1 in the polar coordinate system, lat2 represents the longitude of the sampled longitude at time t in the polar coordinate system, lat3 represents the longitude of the sampled longitude at time t+1 in the polar coordinate system, lon1 represents the latitude of the sampled longitude at time t-1 in the polar coordinate system, lon2 represents the latitude of the sampled longitude at time t in the polar coordinate system, and lon3 represents the latitude of the sampled longitude at time t+1 in the polar coordinate system.

[0117] Step S304: Calculate the economic driving index score based on the energy consumption data, the number of abnormal driving trips, and the baseline value of the economic driving index data.

[0118] Furthermore, in order to effectively improve the accuracy of calculating the economic driving index score, step S304 includes: obtaining the economic driving index data mean and economic driving index data standard deviation based on the economic driving index data benchmark; calculating a number of differences between the energy consumption data, the number of abnormal driving times and the economic driving index data mean; calculating the multiple of the number of differences and the economic driving index data standard deviation; and calculating the economic driving index score based on the multiple.

[0119] It should be understood that the mean of the economic driving indicator data refers to the mean of each indicator data in the economic driving indicator data benchmark value. Similarly, the standard deviation of the economic driving indicator data refers to the standard deviation of each indicator data in the economic driving indicator data benchmark value. Then, calculate a number of differences between the energy consumption data, the number of abnormal driving times and the mean of the economic driving indicator data. Calculate the multiple of these differences to the standard deviation of the economic driving indicator data. For example, for the energy recovery rate, for every 0.1 times the standard deviation above the mean, the score is increased by 1 point, with a maximum of 100 points; for every 0.1 times the standard deviation below the mean, the score is decreased by 1 point, with a maximum of 0 points. Then, multiply the economic driving indicator score by the corresponding weight value, and then sum the scores of each multiplied indicator to obtain the total indicator score.

[0120] Step S305: Determine the duration of abnormal driving, the number of abnormal pedaling incidents, and the abnormal transport data based on the safety driving index data.

[0121] Furthermore, to effectively improve the accuracy of determining the duration of abnormal driving, the number of abnormal pedal strokes, and the abnormal load data, step S305 includes: obtaining the vehicle's current gear, current speed, and power-on / off interval based on the safety driving index data; determining the duration of abnormal driving based on the current gear, current speed, and power-on / off interval; obtaining the pedal opening at adjacent moments based on the safety driving index data; determining the number of abnormal pedal strokes based on the pedal opening at adjacent moments; obtaining the vehicle's current load data based on the safety driving index data; and determining the abnormal load data based on the current load data and the specified load data.

[0122] It is understood that the duration of abnormal driving includes, but is not limited to, the duration of fatigued driving, the duration of speeding, and the duration of coasting in neutral. When the vehicle's current gear is neutral and the current vehicle speed is greater than a preset vehicle speed threshold, the vehicle is determined to be coasting in neutral. At this time, the duration of coasting in neutral is counted. Then, the travel value of the accelerator pedal is determined based on the accelerator pedal opening at adjacent moments. When the travel value of the accelerator pedal is greater than a preset accelerator pedal travel threshold, abnormal accelerator pedal depressing is determined. At this time, the number of abnormal accelerator pedal depressings is counted. The preset accelerator pedal opening threshold can be 70. Similarly, the travel value of the brake pedal is determined based on the brake pedal opening at adjacent moments. When the travel value of the brake pedal is greater than a preset brake pedal travel threshold, abnormal brake pedal depressing is determined. At this time, the number of abnormal brake pedal depressings is counted. The preset brake pedal travel threshold can be 40.

[0123] It should be understood that the regulation requires a 20-minute rest for every 4 hours of driving. Considering the special circumstances of this vehicle having a large number of vehicles that are powered on but not driven, based on the interval between power on and off of the vehicle, driving behavior that exceeds 4 hours of continuous driving and has a rest time of less than 1000 seconds is judged as fatigue driving. At this time, the duration of fatigue driving is counted, and then abnormal load data is determined based on the current load data and the prescribed load data. This abnormal load data can be the vehicle's overload.

[0124] Step S306: Calculate the safety driving index score based on the duration of abnormal driving, number of abnormal pedaling incidents, abnormal transport data, and the baseline value of the safety driving index data.

[0125] Understandably, after obtaining the baseline value of the safe driving index data, the mean value and standard deviation of the safe driving index data are obtained based on the baseline value. Then, the differences between the duration of abnormal driving, the number of abnormal stampings, the abnormal load data and the mean value of the safe driving index data are calculated. Finally, the multiples of the differences between the duration of abnormal driving, the number of abnormal stampings, the abnormal load data and the mean value of the safe driving index data and the standard deviation of the safe driving index data are calculated. The index score of the safe driving index is calculated based on this multiple.

[0126] Step S307: Calculate the index score of the standardized driving index based on the standardized driving index data and the benchmark value of the standardized driving index data.

[0127] It should be understood that after obtaining the baseline value of the standardized driving indicator data, the mean and standard deviation of the standardized driving indicator data are obtained based on the baseline value. Several differences between the standardized driving indicator data and the mean of the standardized driving indicator data are calculated respectively. Then, the multiples of the several differences between the standardized driving indicator data and the mean of the standardized driving indicator data and the standard deviation of the standardized driving indicator data are calculated. The indicator score of the standardized driving indicator is calculated based on this multiple.

[0128] This embodiment determines the baseline values ​​for economic driving indicators, safe driving indicators, and standardized driving indicators. Then, based on the economic driving indicator data, it determines energy consumption data and the number of abnormal driving incidents. Next, it calculates the economic driving indicator score based on the energy consumption data, the number of abnormal driving incidents, and the baseline value for economic driving indicators. Similarly, it determines the duration of abnormal driving incidents, the number of abnormal pedaling incidents, and abnormal load data based on the safe driving indicator data, and calculates the safety driving indicator score based on these parameters. Finally, it calculates the standardized driving indicator score based on the standardized driving indicator data and its baseline value. This approach effectively improves the accuracy of calculating the scores for each driving indicator.

[0129] Furthermore, embodiments of the present invention also propose a storage medium storing a driving behavior processing program, which, when executed by a processor, implements the steps of the driving behavior processing method described above.

[0130] Since this storage medium adopts all the technical solutions of all the above embodiments, it has at least all the beneficial effects brought about by the technical solutions of the above embodiments, which will not be repeated here.

[0131] In addition, refer to Figure 6 The present invention also proposes a driving behavior processing device, the driving behavior processing device comprising:

[0132] The acquisition module 10 is used to acquire the current driving data of the vehicle and the current road data of the road on which the vehicle is traveling.

[0133] The determining module 20 is used to determine the indicator data corresponding to each driving indicator based on the current driving data and the current road data.

[0134] The calculation module 30 is used to calculate the index score of each driving index based on the index data.

[0135] The processing module 40 is used to process the abnormal driving behavior when it is determined that the user has abnormal driving behavior based on the comprehensive score of each driving indicator.

[0136] This embodiment acquires the vehicle's current driving data and the current road data of the road the vehicle is traveling on; determines the indicator data corresponding to each driving indicator based on the current driving data and the current road data; calculates the indicator score for each driving indicator based on the indicator data; and processes the abnormal driving behavior when it is determined that the user is exhibiting abnormal driving behavior based on the comprehensive indicator scores of each driving indicator. Through the above method, indicator data is determined based on the vehicle's current driving data and the current road data of the road the vehicle is traveling on, and then the indicator scores for each driving indicator are calculated using the indicator data. The system then comprehensively judges whether the user is exhibiting abnormal driving behavior based on the indicator scores of each driving indicator. If so, the abnormal driving behavior is processed, thereby effectively improving the accuracy of identifying abnormal driving behavior and providing timely warnings when abnormal driving behavior is present, thus improving driving safety.

[0137] It should be noted that the workflow described above is merely illustrative and does not limit the scope of protection of this invention. In practical applications, those skilled in the art can select some or all of the workflow to achieve the purpose of this embodiment according to actual needs, and no restrictions are imposed here.

[0138] In addition, for technical details not described in detail in this embodiment, please refer to the driving behavior processing method provided in any embodiment of the present invention, which will not be repeated here.

[0139] In one embodiment, the determining module 20 is further configured to perform mean aggregation on the current driving data and the current road data respectively; obtain the vehicle speed, drive motor speed and charging status based on the mean-aggregated current driving data; clean the driving data whose speed is a preset speed threshold, whose speed is less than a preset speed threshold, and whose charging status is a preset status to obtain target driving data; and divide the target driving data and the mean-aggregated current road data according to preset driving index rules to obtain index data corresponding to each driving index.

[0140] In one embodiment, the calculation module 30 is further configured to: determine the baseline values ​​for economic driving index data, safe driving index data, and standardized driving index data; obtain economic driving index data, safe driving index data, and standardized driving index data based on the index data; determine energy consumption data and abnormal driving frequency based on the economic driving index data; calculate the index score for the economic driving index based on the energy consumption data, abnormal driving frequency, and the baseline value for the economic driving index data; determine the duration of abnormal driving, abnormal pedaling frequency, and abnormal load data based on the safe driving index data; calculate the index score for the safe driving index based on the duration of abnormal driving, abnormal pedaling frequency, abnormal load data, and the baseline value for the safe driving index data; and calculate the index score for the standardized driving index based on the standardized driving index data and the baseline value for the standardized driving index data.

[0141] In one embodiment, the calculation module 30 is further configured to determine the speed difference and turning radius between adjacent time points based on the economic index data; determine the number of abnormal driving operations based on the speed difference and turning radius between adjacent time points; determine the total recovered electricity and total consumed electricity based on the economic index data; and determine energy consumption data based on the total recovered electricity and total consumed electricity.

[0142] In one embodiment, the calculation module 30 is further configured to: obtain the vehicle's current gear, current speed, and power-on / off interval time based on the safe driving index data; determine the duration of abnormal driving based on the current gear, current speed, and power-on / off interval time; obtain the pedal opening at adjacent moments based on the safe driving index data; determine the number of abnormal pedal presses based on the pedal opening at adjacent moments; obtain the vehicle's current load data based on the safe driving index data; and determine abnormal load data based on the current load data and the specified load data.

[0143] In one embodiment, the calculation module 30 is further configured to obtain the mean and standard deviation of the economic driving index data based on the benchmark value of the economic driving index data; calculate a number of differences between the energy consumption data, the number of abnormal driving times and the mean of the economic driving index data; calculate the multiple of the number of differences and the standard deviation of the economic driving index data; and calculate the index score of the economic driving index based on the multiple.

[0144] In one embodiment, the processing module 40 is further configured to obtain an economic driving index score, a safe driving index score, and a standardized driving index score based on the index scores of each driving index; to comprehensively determine whether the user has abnormal driving behavior based on the comparison results of the economic driving index score with the preset economic index average, the comparison results of the safe driving index score with the preset safety index average, and the comparison results of the standardized driving index score with the preset standardized index average; and if so, to process the abnormal driving behavior.

[0145] Other embodiments or implementation methods of the driving behavior processing device described in this invention can be found in the above-described method embodiments, and will not be repeated here.

[0146] Furthermore, it should be noted that, in this document, 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.

[0147] 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.

[0148] 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, 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 read-only memory (ROM) / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal device (which may be a mobile phone, computer, all-in-one platform workstation, or network device, etc.) to execute the methods described in the various embodiments of the present invention.

[0149] 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 method for processing driving behavior, characterized in that, The driving behavior processing method includes the following steps: Obtain the vehicle's current driving data and the current road data of the road the vehicle is traveling on; Determine the corresponding indicator data for each driving indicator based on the current driving data and the current road data; Calculate the score for each driving indicator based on the aforementioned indicator data; When it is determined that a user has abnormal driving behavior based on the comprehensive scores of the various driving indicators, the abnormal driving behavior will be processed. The calculation of the index scores for each driving indicator based on the index data includes: Establish benchmark values ​​for economic driving indicators, safety driving indicators, and standardized driving indicators; Based on the aforementioned indicator data, we obtain economic driving indicator data, safe driving indicator data, and standardized driving indicator data; Energy consumption data and the number of abnormal driving incidents are determined based on the aforementioned economic driving index data; The economic driving index score is calculated based on the energy consumption data, the number of abnormal driving operations, and the baseline value of the economic driving index data. Based on the aforementioned safe driving index data, determine the duration of abnormal driving, the number of abnormal pedaling incidents, and the abnormal transport data. The safety driving index score is calculated based on the duration of abnormal driving, the number of abnormal steps, the abnormal transport data, and the baseline value of the safety driving index data. The standard driving indicator score is calculated based on the standard driving indicator data and the standard driving indicator data benchmark value.

2. The driving behavior processing method as described in claim 1, characterized in that, The step of determining the indicator data corresponding to each driving indicator based on the current driving data and the current road data includes: The mean of the current driving data and the current road data are aggregated separately. The vehicle speed, drive motor speed, and charging status are obtained from the current driving data after the average aggregation. The driving data with the vehicle speed at a preset vehicle speed threshold, the rotation speed less than a preset rotation speed threshold, and the charging state at a preset state are cleaned to obtain the target driving data. The target driving data and the current road data after average aggregation are divided by preset driving index rules to obtain the index data corresponding to each driving index.

3. The driving behavior processing method as described in claim 1, characterized in that, The step of determining energy consumption data and abnormal driving frequency based on the economic driving index data includes: The speed difference and turning radius between adjacent moments are determined based on the aforementioned economic driving index data; The number of abnormal driving incidents is determined based on the speed difference between adjacent moments and the turning radius. The total recovered electricity and total consumed electricity are determined based on the aforementioned economic driving index data; Energy consumption data is determined based on the total recovered electricity and the total consumed electricity.

4. The driving behavior processing method as described in claim 1, characterized in that, The process of determining the duration of abnormal driving, the number of abnormal stampings, and the abnormal transport data based on the safety driving index data includes: The vehicle's current gear, current speed, and power-on / off interval are obtained based on the aforementioned safe driving index data. The duration of abnormal driving is determined based on the current gear, current vehicle speed, and vehicle power-on / off interval. The pedal opening at adjacent moments is obtained based on the aforementioned safe driving index data; The number of abnormal pedaling incidents is determined based on the pedal opening at adjacent moments. The vehicle's current carrying data is obtained based on the aforementioned safe driving index data; Abnormal transport data is determined based on the current transport data and the specified load data.

5. The driving behavior processing method as described in claim 1, characterized in that, The calculation of the economic driving index score based on the energy consumption data, abnormal driving frequency, and economic driving index benchmark value includes: Based on the aforementioned benchmark values ​​for economic driving indicators, the mean and standard deviation of the economic driving indicators are obtained. Calculate several differences between the energy consumption data, the number of abnormal driving times, and the average value of the economic driving index data; Calculate the multiple of the difference between the aforementioned quantities and the standard deviation of the economic driving index data; The economic driving index score is calculated based on the multiplier.

6. The driving behavior processing method as described in claim 1, characterized in that, When it is determined that a user has engaged in abnormal driving behavior based on the comprehensive scores of the various driving indicators, the process of handling the abnormal driving behavior includes: Based on the scores of each driving indicator, we obtain the scores for economic driving, safe driving, and standardized driving. Based on the comparison results of the economic driving index score with the preset economic index average, the comparison results of the safe driving index score with the preset safety index average, and the comparison results of the standard driving index score with the preset standard index average, it is determined whether the user has abnormal driving behavior. If so, the abnormal driving behavior will be processed.

7. A driving behavior processing device, characterized in that, The driving behavior processing device includes: The acquisition module is used to acquire the vehicle's current driving data and the current road data of the road the vehicle is traveling on; The determination module is used to determine the indicator data corresponding to each driving indicator based on the current driving data and the current road data; The calculation module is used to calculate the index score of each driving index based on the index data; The processing module is used to process the abnormal driving behavior when it is determined that the user has abnormal driving behavior based on the comprehensive score of each driving indicator. The calculation module is further configured to: determine the baseline values ​​for economic driving indicators, safe driving indicators, and standardized driving indicators; obtain economic driving indicator data, safe driving indicator data, and standardized driving indicator data based on the indicator data; determine energy consumption data and the number of abnormal driving occurrences based on the economic driving indicator data; calculate the indicator score for the economic driving indicator based on the energy consumption data, the number of abnormal driving occurrences, and the baseline values ​​for the economic driving indicator data; determine the duration of abnormal driving, the number of abnormal pedaling occurrences, and abnormal load data based on the safe driving indicator data; calculate the indicator score for the safe driving indicator based on the duration of abnormal driving, the number of abnormal pedaling occurrences, the abnormal load data, and the baseline values ​​for the safe driving indicator data; and calculate the indicator score for the standardized driving indicator based on the standardized driving indicator data and the baseline values ​​for the standardized driving indicator data.

8. A driving behavior processing device, characterized in that, The driving behavior processing device includes: a memory and a processor, wherein the memory stores a driving behavior processing program that can run on the processor, and the driving behavior processing program is configured to implement the driving behavior processing method as described in any one of claims 1 to 6.

9. A storage medium, characterized in that, The storage medium stores a driving behavior processing program, which, when executed by a processor, implements the driving behavior processing method as described in any one of claims 1 to 6.

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