CN117465474A

CN117465474A - Method, device, equipment and storage medium for detecting vehicle driving

Info

Publication number: CN117465474A
Application number: CN202311182179.2A
Authority: CN
Inventors: 张效鹏; 刘婷; 丁庆港
Original assignee: Chery Automobile Co Ltd
Current assignee: Chery Automobile Co Ltd
Priority date: 2023-09-13
Filing date: 2023-09-13
Publication date: 2024-01-30

Abstract

The application discloses a vehicle driving detection method, device, equipment and storage medium, and belongs to the technical field of vehicle control. The method comprises the following steps: acquiring running data of a vehicle and weather data during driving; determining influence data of vehicle driving based on driving data of the vehicle and weather data when driving, wherein the influence data of the vehicle driving comprises at least one of driving safety data, driving speed data, average fuel consumption data, trip habit data or driving mileage data; first-level index data of vehicle driving is acquired based on the influence data of vehicle driving, second-level index data and total index data are determined based on the first-level index data of vehicle driving, and driving advice for the vehicle is determined based on the second-level index data and the total index data. Through detecting the multi-aspect data of the driving trip, the characteristics of the driving trip can be obtained, driving advice aiming at the vehicle is obtained based on the characteristics of the driving trip, and driving safety is improved.

Description

Method, device, equipment and storage medium for detecting vehicle driving

Technical Field

The embodiment of the application relates to the technical field of vehicle control, in particular to a vehicle driving detection method, device and equipment and a storage medium.

Background

With the popularization of vehicles, driving vehicles are increasingly normalized, and data analysis is performed on each driving trip of a driver, so that the driving safety is improved and the driving expense is saved.

In the related art, a certain aspect of driving travel is detected, the characteristics of the driving travel are obtained based on the detection result, and the driving habit is improved according to the characteristics of the driving travel.

In the related art, due to the fact that a certain aspect of driving travel is detected, characteristics of the driving travel obtained based on detection results have limitations, and after driving habit is improved according to the characteristics of the driving travel, driving safety is not high.

Disclosure of Invention

The embodiment of the application provides a vehicle driving detection method, device, equipment and storage medium, which can be used for solving the problems in the related art. The technical scheme is as follows:

in one aspect, an embodiment of the present application provides a method for detecting driving of a vehicle, where the method includes:

acquiring running data of a vehicle and weather data during driving;

determining influence data of vehicle driving based on the driving data of the vehicle and the weather data during driving, wherein the influence data of vehicle driving comprises at least one of driving safety data, driving speed data, average fuel consumption data, trip habit data or driving mileage data;

Acquiring primary index data of the vehicle driving based on the influence data of the vehicle driving, determining secondary index data and total index data based on the primary index data of the vehicle driving, and determining driving advice for the vehicle based on the secondary index data and the total index data.

In another aspect, there is provided a detection apparatus for vehicle driving, the apparatus comprising:

the acquisition module is used for acquiring running data of the vehicle and weather data during driving;

a first determining module, configured to determine, based on driving data of the vehicle and weather data during driving, impact data of driving of the vehicle, where the impact data of driving of the vehicle includes at least one of driving safety data, driving speed data, average fuel consumption data, trip habit data, or driving mileage data;

and the second determining module is used for acquiring primary index data of the vehicle driving based on the influence data of the vehicle driving, determining secondary index data and total index data based on the primary index data of the vehicle driving, and determining driving advice aiming at the vehicle based on the secondary index data and the total index data.

In another aspect, a computer device is provided, where the computer device includes a processor and a memory, where at least one computer program is stored in the memory, where the at least one computer program is loaded and executed by the processor, so that the computer device implements the method for detecting driving of a vehicle described in any of the foregoing.

In another aspect, there is provided a computer readable storage medium having stored therein at least one computer program loaded and executed by a processor to cause a computer to implement any of the above methods for detecting vehicle driving.

In another aspect, a computer program product or computer program is provided, the computer program product or computer program comprising computer instructions stored in a computer readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions so that the computer device performs any of the above-described methods of detecting vehicle driving.

The technical scheme provided by the embodiment of the application at least brings the following beneficial effects:

The driving safety data, the driving speed data, the average fuel consumption data, the trip habit data or the driving mileage data are determined according to the driving data of the vehicle and the weather data during driving. And the control data service platform processes the influence data of the vehicle driving to obtain first-level index data of the vehicle driving. And determining second-level index data and total index data based on the first-level index data, and determining advice for driving the vehicle based on the second-level index data and the total index data. According to the method and the device, the characteristics of the driving trip can be obtained by detecting the multi-aspect data of the driving trip, the driving advice aiming at the vehicle is obtained based on the characteristics of the driving trip, and the driving safety is improved.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.

FIG. 1 is a schematic illustration of an implementation environment provided by embodiments of the present application;

fig. 2 is a flowchart of a method for detecting vehicle driving according to an embodiment of the present application;

FIG. 3 is a graph of the correspondence between the primary index data, the secondary index data, the primary weights and the secondary weights according to the embodiment of the present application;

fig. 4 is a five-dimensional radar chart of two-level index data according to an embodiment of the present application;

fig. 5 is a schematic structural diagram of a vehicle driving detection device according to an embodiment of the present application;

FIG. 6 is a schematic diagram of a communication for detecting vehicle driving according to an embodiment of the present application;

fig. 7 is a schematic structural diagram of a server according to an embodiment of the present application;

fig. 8 is a schematic structural diagram of a vehicle driving detection apparatus provided in an embodiment of the present application.

Detailed Description

For the purpose of making the objects, technical solutions and advantages of the present application more apparent, the embodiments of the present application will be described in further detail below with reference to the accompanying drawings.

An embodiment of the application provides a method for detecting driving of a vehicle, please refer to fig. 1, which shows a schematic diagram of an implementation environment of the method provided in the embodiment of the application. The implementation environment may include: a vehicle 11, a vehicle control system 12 and a data service platform 13.

Wherein the vehicle control system 12 acquires the traveling data of the vehicle 11 and the weather data when the vehicle 11 is driven, the vehicle control system 12 determines the influence data of the driving of the vehicle 11 based on the traveling data of the vehicle 11 and the weather data when the vehicle 11 is driven.

Thereafter, the vehicle control system 12 uploads the influence data of the driving of the vehicle 11 to the data service platform 13, the data service platform 13 processes the influence data of the driving of the vehicle 11 to obtain primary index data of the driving of the vehicle 11, secondary index data and total index data are determined based on the primary index data of the driving of the vehicle 11, and driving advice for the vehicle 11 is determined based on the secondary index data and the total index data.

The vehicle control system 12 receives the primary index data, the secondary index data, the total index data, and the driving advice for the vehicle 11, which are transmitted by the data service platform 13.

Among them, the vehicle 11 is mounted with an instrument control system capable of exhibiting primary index data, secondary index data, total index data, and driving advice for the vehicle 11. The vehicle control system 12 may store the primary index data, the secondary index data, the total index data, and the driving advice for the vehicle 11, and the vehicle 11 may acquire the primary index data, the secondary index data, the total index data, and the driving advice for the vehicle 11 from the vehicle control system 12. Of course, the primary index data, the secondary index data, the total index data, and the driving advice for the vehicle 11 may be stored on the vehicle 11.

Alternatively, the vehicle control system 12 may be a terminal, which may be an in-vehicle terminal or the like. The vehicle 11 establishes a communication connection with the vehicle control system 12 through a wired or wireless network.

Based on the implementation environment shown in fig. 1, the embodiment of the present application provides a method for detecting driving of a vehicle, as shown in fig. 2, and the method is applied to a vehicle control system, for example, and the method includes steps 201 to 203.

In step 201, traveling data of a vehicle and weather data at the time of driving are acquired.

The running data of the vehicle includes, as examples, at least one of the number of unbelted times, the degree of fatigue driving, the number of collision warning, the number of emergency braking requests, the number of tire pressure warning, the number of lane departure warning, the number of high-speed overbending, the number of speed limit warning, the speed of the vehicle running, the acceleration of the vehicle running, the degree of overspeed, the number of rapid acceleration, the speed limit of the road where the vehicle is located, the period of non-start, the number of reference weather driving, the period of driving, the fuel consumption of hundred kilometers per month, or the total mileage per month running.

Next, an example of the manner of acquiring each travel data will be described.

(1) Obtaining number of unbelted times

Illustratively, obtaining the number of unbelted times includes: after the vehicle starts for a first reference period, the wearing condition of the safety belt of the driver's seat, the co-driver's seat or the rear passenger seat is identified, and the number of times of unbelting the safety belt is obtained based on the wearing condition of any one of the safety belts of the driver's seat, the co-driver's seat or the rear passenger seat. For example, the wearing condition of any one of the seat belts based on the driver's seat, the passenger's seat, or the rear passenger's seat is the unbuckled seat belt, and the wearing condition of any two of the seat belts is the unbuckled seat belt.

The method for judging the starting of the vehicle comprises the steps of but not limited to acquiring the power-on state of a key of the vehicle, and if the key of the vehicle is in the power-on state, then the vehicle is in the starting state; the vehicle is not in a start state based on the key of the vehicle not being in a power-on state. In addition, the embodiment of the application does not limit the first reference duration, and the first reference duration may be set empirically or may be adjusted according to actual situations.

After determining that the vehicle starts the first reference time length, the wearing condition of the safety belt is acquired, and the method for acquiring the wearing condition of the safety belt is not limited in the embodiment of the application, for example, the wearing condition of the safety belt can be acquired through an air bag controller, and the vehicle control system can acquire the wearing condition of the safety belt of a driving position, a copilot position or a rear passenger position through the air bag controller. For another example, an image of the driver's seat, the passenger seat, or the passenger seat of the rear passenger may be captured, and the wearing condition of the seat belt may be acquired by image recognition.

(2) Obtaining the degree of fatigue driving

Alternatively, the degree of fatigue driving is classified as non-fatigue, first reference degree fatigue, second reference degree fatigue, or third reference degree fatigue. The embodiment of the application does not limit the manner of obtaining the degree of fatigue driving, and can obtain the degree of fatigue driving of the driver through an OPENCV (Open Source Computer Vision Library ) fatigue detection system by way of example.

Illustratively, the obtaining the driver fatigue driving degree through the OPENCV fatigue detection system comprises: the method comprises the steps of acquiring at least one of blink frequency of a driver or yawing frequency of the driver through an OPENCV fatigue detection system, and determining the degree of fatigue driving based on the acquired at least one of blink frequency of the driver or yawing frequency of the driver.

Wherein determining the extent of the fatigue driving based on the obtained at least one of the blink frequency of the driver or the yawning frequency of the driver comprises: the fatigue driving degree of the driver is not tired based on the fact that the blink frequency of the driver is larger than a first blink threshold value or the yawning frequency of the driver is smaller than the first yawning threshold value; based on the fact that the blink frequency of the driver is smaller than the first blink threshold value and larger than the second blink threshold value, or the yawing frequency of the driver is larger than the first yawing threshold value and smaller than the second yawing threshold value, the fatigue driving degree of the driver is fatigue of the first reference degree; based on the fact that the blink frequency of the driver is smaller than the second blink threshold value and larger than the third blink threshold value, or the yawing frequency of the driver is larger than the second yawing threshold value and smaller than the third yawing threshold value, the fatigue driving degree of the driver is fatigue of the second reference degree; and based on the fact that the blink frequency of the driver is smaller than a third blink threshold value or the yawing frequency of the driver is larger than the third yawing threshold value, the fatigue driving degree of the driver is fatigue of a third reference degree.

The embodiment of the application does not limit the first reference degree of fatigue, the second reference degree of fatigue and the third reference degree of fatigue, and exemplarily, the fatigue degree required to meet the third reference degree of fatigue is greater than the second reference degree of fatigue; the second reference degree of fatigue is greater than the first reference degree of fatigue. The first blink threshold value, the second blink threshold value and the third blink threshold value are not limited, and the first blink threshold value, the second blink threshold value and the third blink threshold value can be set based on experience, and the first blink threshold value is required to be larger than the second blink threshold value, and the second blink threshold value is larger than the third blink threshold value. The embodiment of the application also does not limit the first yawing threshold value, the second yawing threshold value and the third yawing threshold value, and can be set based on experience, wherein the first yawing threshold value is required to be smaller than the second yawing threshold value, and the second yawing threshold value is smaller than the third yawing threshold value.

(3) Acquiring the number of collision alarms

The embodiment of the application does not limit the collision warning device, and can warn collision behaviors through a vehicle collision warning system installed in a vehicle by way of example. Illustratively, the number of collision alarms is acquired, including that the vehicle control system acquires the collision visual alarm and the collision sound alarm from the vehicle collision avoidance early warning system, and a result obtained by adding the acquired number of collision visual alarms and the acquired number of collision sound alarms is taken as the number of collision alarms.

Wherein, when the time interval between occurrence of the collision visual alarm and the collision sound alarm is smaller than the second reference time period, the collision alarm is recorded as one time. The second reference time length is not limited, and may be set based on experience, or may be adjusted according to actual conditions, and the second reference time length may be set to 5 minutes, for example.

(4) Acquiring the number of emergency brake requests

In one possible implementation, an AEB (Autonomous Emergency Braking, automatic emergency braking system), EBA (Electronic Brake Assist, electronically controlled brake assist system) and AWB (Autonomous Warning Braking, automatic warning braking system) are installed in the vehicle. Optionally, the step of acquiring the number of emergency braking requests includes acquiring a first deceleration control request issued by the AEB, a second deceleration control request issued by the EBA, and a third deceleration control request issued by the AWB, and adding the acquired number of first deceleration control requests, the acquired number of second deceleration control requests, and the acquired number of third deceleration control requests to each other to obtain the acquired number of emergency braking requests.

For example, each time the vehicle control system obtains a third deceleration control request, the third deceleration control request is recorded as a first reference degree emergency braking; every time the vehicle control system acquires a second deceleration control request, recording the second deceleration control request as a second reference degree emergency braking; each time the vehicle control system acquires a first deceleration control request, the first deceleration control request is recorded as a third reference degree emergency braking. The result of adding the number of times of the first reference degree emergency brake, the second reference degree emergency brake, and the third reference degree emergency brake is taken as the acquired number of times of the emergency brake request.

(5) Obtaining the number of tire pressure alarms

In one possible implementation, a tire pressure monitoring system is installed in a vehicle that can monitor tire pressures of a front left wheel, a rear left wheel, a front right wheel, and a rear right wheel of the vehicle. Optionally, the number of tire pressure alarms is acquired, including that the vehicle control system monitors the tire pressures of the left front wheel, the left rear wheel, the right front wheel and the right rear wheel of the vehicle through the tire pressure monitoring system, and in the third reference time period, the tire pressure alarm is triggered when the tire pressure of at least one of the left front wheel, the left rear wheel, the right front wheel and the right rear wheel of the vehicle is recorded as one tire pressure alarm. And taking the total tire pressure alarming times in the third reference time period as the times of tire pressure alarming in the acquired running data. The embodiment of the application does not limit the third reference time length, the third reference time length can be set based on experience, and the third reference time length can be adjusted according to actual conditions.

(6) Obtaining the number of lane departure warning

In one possible implementation, an LDW (Lane Departure Warning, lane departure warning system) is installed in the vehicle, which can warn whether a lane departure of the vehicle has occurred. Illustratively, obtaining the number of lane departure alerts includes: the vehicle control system acquires a line pressing alarm signal and an intervention alarm signal sent by the LDW. The frequency of sending out the line pressing alarm signal and the frequency of sending out the intervention alarm signal by the LDW are obtained. And taking the result of adding the times of the LDW sending out the line pressing alarm signal and the times of the LDW sending out the intervention alarm signal as the acquired times of lane departure alarm.

(7) Acquiring the number of times of high-speed over-bending and the running speed of the vehicle

In one possible implementation, a lateral acceleration sensor and a speed sensor are mounted on the vehicle, the lateral acceleration sensor can acquire a lateral acceleration during running of the vehicle, and the speed sensor can acquire a running speed of the vehicle. Optionally, acquiring the number of times the vehicle is over-bent at a high speed includes: the vehicle control system acquires the transverse acceleration of the vehicle in the running process through a transverse acceleration sensor arranged on the vehicle, and acquires the running speed of the vehicle through a speed sensor arranged on the vehicle; determining that the vehicle is over-bent at a high speed based on the absolute value of the lateral acceleration being greater than the reference value and the speed of the vehicle being greater than the reference speed; and acquiring the number of times of high-speed over-bending of the vehicle.

(8) Acquiring the number of speed limit alarms and the speed limit of the road where the vehicle is located

In one possible implementation, an SLA (Speed Limit Assist, intelligent speed limit assist) is installed on the vehicle, which SLA can take the speed limit of the road on which the vehicle is located and can signal the speed limit when the vehicle exceeds a second reference speed. Illustratively, obtaining the number of rate limiting alarms includes: the vehicle control system acquires the speed limiting signal sent by the SLA, and records as a primary speed limiting alarm based on the acquired primary speed limiting signal.

(9) Obtaining overspeed degree of vehicle

Illustratively, obtaining the overspeed degree of the vehicle includes: comparing the running speed of the vehicle with the speed limit of the road where the vehicle is located, and if the running speed of the vehicle exceeds the first reference percentage of the speed limit of the road where the vehicle is located and is smaller than the second reference percentage, overspeed is carried out on the vehicle to a first reference degree; based on the running speed of the vehicle exceeding the second reference percentage of the speed limit of the road where the vehicle is located and being smaller than the third reference percentage, the vehicle is overspeed at a second reference degree; the vehicle is overspeed to a third reference degree based on the travel speed of the vehicle exceeding a third reference percentage of the speed limit of the road on which the vehicle is located.

The first reference percentage, the second reference percentage, or the third reference percentage are not limited in the embodiments of the present application, and the first reference percentage is smaller than the second reference percentage, and the second reference percentage is smaller than the third reference percentage.

(10) Obtaining the number of rapid acceleration and the acceleration of the vehicle

In one possible implementation, an accelerometer is mounted on the vehicle, and the accelerometer can acquire the acceleration of the vehicle running.

Illustratively, obtaining the number of rapid accelerations of the vehicle includes: acquiring acceleration of vehicle running through an accelerometer arranged on the vehicle; based on the acquired acceleration being greater than the reference acceleration, a sudden acceleration of the vehicle is noted.

The embodiment of the application does not limit the reference acceleration, can be set based on experience, and can also adjust the reference acceleration according to actual conditions.

(11) Acquiring a time length of non-start

Optionally, acquiring the duration of non-startup includes: and acquiring the time when the key of the vehicle is in the power-on state, and taking the time gap of the power-on state of the key of the vehicle twice as the non-starting time length. Determining that the vehicle is not started for a first long term based on the fact that the time gap of the key of the vehicle in the two-time power-on state exceeds a fourth reference time length and is smaller than a fifth reference time length; determining that the vehicle is not started for a second long term based on the fact that the time gap of the key of the vehicle in the power-on state twice exceeds a fifth reference time length and is smaller than a sixth reference time length; and determining that the vehicle is not started for a three-stage long term based on the fact that the time gap between the two power-on states of the key of the vehicle exceeds a sixth reference duration.

When the occurrence time of the first-stage long-term non-starting, the second-stage long-term non-starting or the third-stage long-term non-starting is coincident, determining that the vehicle is not started at a higher level.

(12) Acquiring a period of driving

In one possible implementation, obtaining the period of driving includes: the vehicle control system acquires a time of vehicle driving from an instrument control system of the vehicle, and determines a period of vehicle driving based on the time of vehicle driving.

For example, the period in which the vehicle is driven includes a daytime period, a night time period, and a late night time period. The present embodiments do not limit the time divisions of the daytime period, the night time period, and the late night time period, and the time divisions of the daytime period, the night time period, and the late night time period may be set based on experience, for example.

(13) Obtaining the oil consumption of hundred kilometers per month

Illustratively, obtaining the fuel consumption of hundred kilometers per month includes: the vehicle control system obtains the oil consumption of the vehicle in the current month from the instrument control system of the vehicle, divides the oil consumption in the current month by the number of driving kilometers and multiplies the number of driving kilometers by one hundred to obtain the oil consumption in the current month.

(14) Acquiring a monthly total mileage

Optionally, acquiring the monthly total mileage includes: the vehicle control system obtains the total mileage of the vehicle on the last day of the last month and the total mileage of the vehicle on the last day of the month from the instrument control system of the vehicle, and subtracts the total mileage on the last day of the last month from the total mileage on the last day of the month to obtain the total mileage of the month.

(15) Obtaining the driving times of the reference weather (the reference weather comprises rainy days or snowy days, namely, the situation that the vehicle travels on the rainy and snowy days)

In one possible implementation, the vehicle control system obtains weather data for the vehicle while driving from an instrument control system of the vehicle, the weather data for the vehicle while driving including at least one of a rainy day, a snowy day, a foggy day, a sunny day, a cloudy day, or a sand storm. Optionally, acquiring the driving times of the reference weather includes: the weather data is obtained as the number of driving times in rainy, snowy, foggy or sand storm days.

In step 202, impact data of vehicle driving is determined based on the driving data of the vehicle and weather data at the time of driving, the impact data of vehicle driving including at least one of driving safety data, driving speed data, average fuel consumption data, trip habit data, or driving mileage data.

In one possible implementation, determining impact data for driving of the vehicle based on travel data of the vehicle and weather data while driving includes: determining driving safety data based on the number of unbelted times, the degree of fatigue driving, the number of collision warning times, the number of emergency braking requests, the number of tire pressure warning times, the number of lane departure warning times and the number of high-speed over-bends; determining running speed data based on the number of speed limit alarms, the overspeed degree and the number of sudden acceleration; determining travel habit data based on the duration of non-start, the number of times of driving in a reference period, and the number of times of driving in a reference weather, the number of times of driving in the reference period being determined based on the period of driving; determining average fuel consumption data based on fuel consumption index, wherein the fuel consumption index is determined based on hundred kilometers of fuel consumption on a month basis; the range data is determined based on the monthly total range.

For example, when the reference period is a late-night period, the number of times the reference period is driven is determined based on the period of driving, that is, the number of times the driver is driven in the late-night period is acquired. The embodiment of the application does not limit the time range of the late night period, and can exemplarily define 23 to 5 points of the next day as the late night period, and the driver drives the vehicle when 23 to 5 points of the next day, which is recorded as one-time driving in the late night period.

Illustratively, the fuel consumption index is determined based on the fuel consumption of hundred kilometers on a month basis, including: and carrying the fuel consumption of the hundred kilometers per month into a fuel consumption index formula to obtain a fuel consumption index corresponding to the fuel consumption of the hundred kilometers per month.

Wherein, the formula of the fuel consumption index is as follows: oil consumption index= (month average hundred kilometers oil consumption/standard hundred kilometers oil consumption-1) x 100%.

Based on the fuel consumption index being greater than the fourth reference percentage, the vehicle consumes fuel to a first reference degree; based on the fuel consumption index being less than the fourth reference percentage and greater than the fifth reference percentage, the vehicle is consuming fuel to a second reference level; based on the fuel consumption index being less than the fifth reference percentage and greater than the sixth reference percentage, the vehicle is consuming fuel to a third reference level; based on the fuel consumption index being less than the sixth reference percentage and greater than the seventh reference percentage, the vehicle is a fourth reference level of fuel consumption; based on the fuel consumption index being less than the seventh reference percentage and greater than the eighth reference percentage, the vehicle is a fifth reference level of fuel consumption; the vehicle is fuel-consuming to a sixth reference degree based on the fuel consumption index being less than the eighth reference percentage and greater than the negative eighth reference percentage.

Based on the fuel consumption index being less than the negative eighth reference percentage and greater than the negative seventh reference percentage, the vehicle is fuel efficient for the fifth reference level; based on the fuel consumption index being less than the negative seventh reference percentage and greater than the negative eighth reference percentage, the vehicle is fuel efficient for the fourth reference level; based on the fuel consumption index being less than the negative sixth reference percentage and greater than the negative fifth reference percentage, the vehicle is fuel efficient for the third reference level; based on the fuel consumption index being less than the negative fifth reference percentage and greater than the negative fourth reference percentage, the vehicle is fuel efficient for the second reference degree; based on the fuel consumption index being less than the negative fourth reference percentage, the vehicle is fuel efficient for the first reference level.

The fourth reference percentage, the fifth reference percentage, the sixth reference percentage, the seventh reference percentage and the eighth reference percentage are not limited, can be set based on experience, and can be adjusted according to actual conditions.

Based on the monthly total mileage being greater than 0 and less than the first reference mileage, the monthly total mileage of the vehicle is the first reference mileage; based on the fact that the total monthly mileage is greater than the first reference mileage and less than the second reference mileage, the total monthly mileage of the vehicle is the second reference mileage; and based on that the total monthly mileage is greater than the second reference mileage and less than the third reference mileage, the total monthly mileage of the vehicle is the fourth reference mileage.

The first reference mileage, the second reference mileage, the third reference mileage and the fourth reference mileage are not limited, can be set based on experience, and can be adjusted according to actual conditions.

In step 203, primary index data of the vehicle driving is acquired based on the influence data of the vehicle driving, secondary index data and total index data are determined based on the primary index data of the vehicle driving, and driving advice for the vehicle is determined based on the secondary index data and the total index data.

In one possible implementation, obtaining primary index data of vehicle driving based on impact data of vehicle driving, determining secondary index data and total index data based on the primary index data of vehicle driving, determining driving advice for the vehicle based on the secondary index data and the total index data, includes: uploading the influence data of the vehicle driving to a data service platform, and processing the influence data of the vehicle driving by the data service platform to obtain primary index data of the vehicle driving, determining secondary index data and total index data based on the primary index data of the vehicle driving, and determining driving advice for the vehicle based on the secondary index data and the total index data; and receiving the primary index data, the secondary index data and the total index data sent by the data service platform and the driving advice aiming at the vehicle.

Wherein uploading the impact data of vehicle driving to the data service platform comprises: controlling the remote communication terminal to send the influence data of the vehicle driving to a vehicle remote service provider, wherein the remote communication terminal is positioned on the vehicle; the control vehicle remote service provider uploads the influence data of the vehicle driving to the data service platform.

The embodiment of the application does not limit the remote communication terminal, and for example, a TBOX (remote BOX) is taken as an example, and one TBOX is installed below an instrument panel of a vehicle, and the TBOX has a wireless communication function. The embodiment of the application also does not limit the vehicle remote service provider, alternatively, a TSP (telematics service provider ) platform may be used as the vehicle remote service provider, and the impact data of the vehicle driving uploaded by the remote communication terminal may be forwarded to the data service platform.

Illustratively, the vehicle control system controls the TBOX to upload impact data of vehicle driving to the TSP, which is forwarded to the data service platform.

After the data service platform receives the influence data of the vehicle driving, acquiring first-level index data of the vehicle driving based on the influence data of the vehicle driving, wherein the first-level index data of the vehicle driving comprises: the number of times of unbelting, the degree of fatigue driving, the number of times of collision alarming, the number of times of emergency braking requests, the number of times of tire pressure alarming, the number of times of lane departure alarming and the number of times of high-speed over-bending in the driving safety data are respectively corresponding to one-level index data; the first-level index data respectively corresponding to the number of speed limit alarms, the overspeed degree and the number of rapid acceleration in the running speed data; the first-level index data respectively correspond to the non-starting time length, the driving times of the reference time period and the driving times of the reference weather in the trip habit data; primary index data corresponding to the fuel consumption index in the average fuel consumption data; and the first-level index data corresponds to the monthly total mileage in the mileage data.

In one possible implementation, determining primary index data for a number of unbelted times includes: before the vehicle starts, setting the primary index data of the number of times of unbelting the safety belt as 100; after the vehicle starts for a first reference time period, subtracting a first reference value from primary index data of times of unbuckling the safety belt for one time, wherein the times correspond to the unbuckling times; when the primary index data of the number of times of unbuckling is less than or equal to 0, the primary index data of the number of times of unbuckling is recorded as 0.

Illustratively, determining primary index data of the extent of fatigue driving includes: before the vehicle is started, setting the first-level index data of the fatigue driving degree as 100; after the vehicle is started, the second reference value is subtracted from the first-level index data of the degree of fatigue corresponding to the fatigue driving of the first reference degree, the third reference value is subtracted from the first-level index data of the degree of fatigue corresponding to the fatigue driving of the first reference degree, and the fourth reference value is subtracted from the first-level index data of the degree of fatigue corresponding to the fatigue driving of the first reference degree; when the first-order index data of the degree of fatigue driving is less than or equal to 0, the first-order index data of the degree of fatigue driving is recorded as 0.

Optionally, setting the primary index data of the number of collision alarms as 100 before starting the vehicle; after the vehicle is started, subtracting a fifth reference value from the primary index data of the times of collision alarm corresponding to the collision alarm of one time; when the first-order index data of the number of collision alarms is less than or equal to 0, the first-order index data of the number of collision alarms is recorded as 0.

In one possible implementation, determining primary index data for a number of emergency brake requests includes: setting the primary index data of the number of emergency braking requests as 100 before starting the vehicle; after the vehicle is started, the sixth reference value is deducted from the primary index data of the times of the emergency braking requests of the first reference degree, the seventh reference value is deducted from the primary index data of the times of the emergency braking requests of the second reference degree, and the eighth reference value is deducted from the primary index data of the times of the emergency braking requests of the third reference degree; when the primary index data of the number of emergency brake requests is less than or equal to 0, the primary index data of the number of emergency brake requests is recorded as 0.

Illustratively, the primary index data of the number of tire pressure alarms is set to 100 before the vehicle starts; after the vehicle is started, the ninth reference value is deducted from the primary index data of the times of the tire pressure alarm corresponding to the tire pressure alarm; when the first-level index data of the number of tire pressure alarms is less than or equal to 0, the first-level index data of the number of tire pressure alarms is recorded as 0.

Optionally, setting the primary index data of the number of lane departure warning to 100 before starting the vehicle; after the vehicle is started, the tenth reference value is deducted from the primary index data of the number of times of lane departure warning corresponding to the primary line pressing warning signal, and the eleventh reference value is deducted from the primary index data of the number of times of lane departure warning corresponding to the primary intervention warning signal; when the first-order index data of the number of lane departure warning is less than or equal to 0, the first-order index data of the number of lane departure warning is recorded as 0.

In one possible implementation, the first-level index data of the number of times of high-speed over-bending is set to be 100 before the vehicle starts; after the vehicle is started, subtracting a twelfth reference value from the first-level index data of the times of the first high-speed over-bending corresponding to the times of the first high-speed over-bending; when the first-order index data of the number of high-speed overstretches is less than or equal to 0, the first-order index data of the number of high-speed overstretches is recorded as 0.

Illustratively, the primary index data of the number of speed limit alarms is set to 100 before the vehicle starts; after the vehicle is started, the thirteenth reference value is deducted from the primary index data of the times of the primary speed limit alarm corresponding to the speed limit alarm; when the first-level index data of the number of speed limit alarms is smaller than or equal to 0, the first-level index data of the number of speed limit alarms is recorded as 0.

In one possible implementation, determining primary indicator data of an overspeed degree includes: setting the first-level index data of overspeed degree as 100 before starting the vehicle; after the vehicle is started, the fourteenth reference value is deducted from the first-level index data of the first reference degree overspeed corresponding to the overspeed degree, the fifteenth reference value is deducted from the first-level index data of the second reference degree overspeed corresponding to the overspeed degree, and the sixteenth reference value is deducted from the first-level index data of the third reference degree overspeed corresponding to the overspeed degree; when the first-level index data of the overspeed degree is less than or equal to 0, the first-level index data of the overspeed degree is recorded as 0.

Illustratively, the primary index data of the number of rapid acceleration is set to 100 before the vehicle is started; after the vehicle is started, deducting a seventeenth reference value from the primary index data of the number of times of the first sudden acceleration corresponding to the sudden acceleration; when the first-order index data of the number of rapid acceleration is less than or equal to 0, the first-order index data of the number of rapid acceleration is recorded as 0.

Illustratively, the first-level index data of the number of times of driving in the reference period is set to 100 before the vehicle starts; after the vehicle is started, the eighteenth reference value is deducted from the first-level index data of the driving times of the first reference period corresponding to the driving times of the reference period; when the first-level index data of the number of times of driving in the reference period is less than or equal to 0, the first-level index data of the number of times of driving in the reference period is recorded as 0.

Illustratively, the first-level index data of the number of times of driving with reference to weather is set to 100 before the vehicle is started; after the vehicle is started, subtracting a nineteenth reference value from the first-level index data of the times of driving in the primary reference weather corresponding to the driving in the reference weather; when the first-order index data of the number of times of reference weather driving is less than or equal to 0, the first-order index data of the number of times of reference weather driving is recorded as 0.

Illustratively, the primary index data of the fuel consumption index is set to 100 before the vehicle starts; after the vehicle is started, subtracting a twentieth reference value from first-level index data of the oil consumption index corresponding to the first reference degree; subtracting a twenty-first reference value from the first-level index data of the oil consumption index corresponding to the second reference degree oil consumption; subtracting a twenty-second reference value from the first-level index data of the oil consumption index corresponding to the third reference degree oil consumption; subtracting a twenty-third reference value from the first-level index data of the oil consumption index corresponding to the fourth reference degree oil consumption; subtracting a twenty-fourth reference value from the first-level index data of the oil consumption index corresponding to the fifth reference degree oil consumption; the first-level index data of the oil consumption index corresponding to the oil consumption of the sixth reference degree is unchanged; the first-order index data of the fuel consumption index corresponding to the first reference degree fuel saving is increased by a twenty-fourth reference value; the first level index data of the fuel consumption index corresponding to the fuel saving of the first reference degree is increased by a twenty-third reference value; the first level index data of the fuel consumption index corresponding to the fuel saving of the third reference degree is increased by a twenty-second reference value; the first level index data of the fuel consumption index corresponding to the fuel saving of the fourth reference degree is increased by a twenty-first reference value; and the first-order index data of the fuel consumption index corresponding to the fifth reference degree fuel saving is increased by a twentieth reference value. When the first-order index data of the fuel consumption index is less than or equal to 0, the first-order index data of the fuel consumption index is recorded as 0.

Illustratively, the first-level index data of the total monthly mileage is set to 100 before the vehicle is started; after the vehicle is started, the first-order index data of the first reference mileage corresponding to the monthly total mileage is increased by a twenty-fifth reference value; the first-order index data of the total monthly driving mileage corresponding to the first second reference mileage is increased by a twenty-sixth reference value; the twenty-seventh reference value is added to the first-level index data of the monthly total driving mileage corresponding to the first third reference mileage; and the first-order index data of the total monthly driving mileage corresponding to the fourth reference mileage is increased by a twenty-eighth reference value. When the first-order index data of the monthly total mileage is less than or equal to 0, the first-order index data of the monthly total mileage is recorded as 0.

Illustratively, the primary index data of the period of non-start-up is set to 100 before the vehicle starts up; after the vehicle is started, subtracting a twenty-ninth reference value from the first-level index data of the first-level long-term non-starting time period corresponding to the non-starting time period; the thirty-first index data corresponding to the non-start time length is deducted from the primary secondary long-term non-start time length; the thirty-first reference value is subtracted from the primary index data of the duration corresponding to the non-start time of the primary three-stage long-term non-start.

The embodiments of the present application do not limit the first reference value, the second reference value, the third reference value, the fourth reference value, the fifth reference value, the sixth reference value, the seventh reference value, the eighth reference value, the ninth reference value, the tenth reference value, the eleventh reference value, the twelfth reference value, the thirteenth reference value, the fourteenth reference value, the fifteenth reference value, the sixteenth reference value, the seventeenth reference value, the eighteenth reference value, the nineteenth reference value, the twentieth reference value, the twenty first reference value, the twenty second reference value, the twenty third reference value, the twenty fourth reference value, the twenty fifth reference value, the twenty sixth reference value, the twenty seventh reference value, the twenty eighth reference value, the twenty ninth reference value, the thirty-first reference value, and are exemplary, and are all less than 100.

In one possible implementation, after obtaining the first-level index data of the vehicle driving, determining the second-level index data and the total index data based on the first-level index data of the vehicle driving includes: determining secondary index data of the driving safety data based on primary index data and primary weight corresponding to the number of unbelted safety belts, the degree of fatigue driving, the number of collision alarming, the number of emergency braking requests, the number of tire pressure alarming, the number of lane departure alarming and the number of high-speed over-bending in the driving safety data respectively; determining secondary index data of the running speed data based on primary index data and primary weight respectively corresponding to the speed limit alarming times, the overspeed degree and the rapid acceleration times in the running speed data; determining secondary index data of the travel habit data based on primary index data and primary weight which correspond to the non-starting time length, the driving times of the reference time period and the driving times of the reference weather in the travel habit data respectively; determining secondary index data corresponding to the average fuel consumption data based on the primary index data and the primary weight of the fuel consumption index in the average fuel consumption data; determining secondary index data corresponding to the driving mileage data based on the primary index data and the primary weight of the monthly driving total mileage in the driving mileage data; and determining the total index data based on the secondary index data and the secondary weight of the driving safety data, the driving speed data, the average fuel consumption data, the trip habit data and the driving mileage data in the influence data of the driving of the vehicle.

The number of unbelted times, the degree of fatigue driving, the number of collision alarms, the number of emergency braking requests, the number of tire pressure alarms, the number of lane departure alarms and the first-order weight of the number of high-speed overstretched times in driving safety data are not limited, and the first-order weight of the number of unbelted times, the degree of fatigue driving, the number of collision alarms, the number of emergency braking requests, the number of tire pressure alarms, the number of lane departure alarms and the number of high-speed overstretched times is required to be added to be equal to 1.

For example, the correspondence between each level of index data and the level of weight in the driving safety data is shown in fig. 3, in which 30% of the level of unbelted time, 15% of the level of fatigue driving, 15% of the level of collision warning, 10% of the level of emergency braking request, 10% of the level of tire pressure warning, 10% of the level of lane departure warning, and 10% of the level of high-speed overbending are taken as examples.

After the number of unbelted times, the degree of fatigue driving, the number of collision alarms, the number of emergency braking requests, the number of tire pressure alarms, the number of lane departure alarms and the number of high-speed overturns are determined in the driving safety data, the number of unbelted times is multiplied by the number of high-speed overturns, the degree of fatigue driving is multiplied by the number of fatigue driving, the number of collision alarms is multiplied by the number of collision alarms, the number of emergency braking requests is multiplied by the number of emergency braking requests, the number of tire pressure alarms is multiplied by the number of lane departure alarms, the number of high-speed overturns is multiplied by the number of speed limit alarms, the number of overspeed is multiplied by the number of speed limit alarms, the degree of overspeed is multiplied by the number of overspeed acceleration is multiplied by the number of speed limit alarms, and the number of rapid driving is multiplied by the number of emergency driving results of the number of emergency braking is added to obtain the safety data.

The present embodiment does not limit the primary weights of the number of speed limit alarms, the degree of overspeed, and the number of rapid acceleration in the running speed data, and illustratively, the primary weights of the number of speed limit alarms, the degree of overspeed, and the number of rapid acceleration need to be added to be equal to 1.

For example, taking 50% of the primary weights of the number of speed limit alarms, 30% of the primary weights of the overspeed degree and 20% of the primary weights of the number of rapid acceleration as an example, the correspondence between the primary index data and the primary weights in the travel speed data is shown in fig. 3.

After the number of speed limit alarms, the overspeed degree and the sudden acceleration degree are determined as the first-level weight in the running speed data, the first-level weight of the number of speed limit alarms is multiplied by the first-level index data of the number of speed limit alarms, the first-level weight of the overspeed degree is multiplied by the first-level index data of the overspeed degree, and the result of the first-level weight of the number of sudden acceleration times is multiplied by the first-level index data of the number of sudden acceleration is added to obtain the second-level index data of the running speed data.

The embodiment of the application does not limit the primary weights of the non-starting time length, the number of times driven in the reference time period and the number of times driven in the reference weather in the trip habit data, and by way of example, the primary weight addition of the non-starting time length, the number of times driven in the reference time period and the number of times driven in the reference weather is required to be 1.

For example, taking the case that the primary weight of the non-starting duration is 60%, the primary weight of the number of times of driving in the reference period is 20% and the primary weight of the number of times of driving in the reference weather is 20%, the corresponding relationship between the primary index data and the primary weight in the travel habit data is shown in fig. 3.

After determining the non-starting time length, the number of times of driving in the reference time period and the first-level weight of the number of times of driving in the reference weather, the first-level weight of the non-starting time length is multiplied by the first-level index data of the non-starting time length, the first-level weight of the number of times of driving in the reference time period is multiplied by the first-level index data of the number of times of driving in the reference time period, and the first-level index data of the number of times of driving in the reference weather is multiplied by the second-level index data of the travel habit data are obtained through addition.

In one possible implementation manner, the primary weight of the fuel consumption index in the average fuel consumption data is determined to be 1, the primary index data of the fuel consumption index is used as the secondary index data of the average fuel consumption data, and the corresponding relationship between the primary index data of the fuel consumption index and the primary weight is shown in fig. 3.

Similarly, the first-level weight of the total monthly mileage in the mileage data is also 1, the first-level index data of the total monthly mileage is used as the second-level index data of the average fuel consumption data, and the corresponding relationship between the first-level index data of the total monthly mileage and the first-level weight is shown in fig. 3.

The embodiment of the application does not limit the secondary weights of the driving safety data, the driving speed data, the average fuel consumption data, the travel habit data and the driving mileage data in the influence data of the driving of the vehicle, and by way of example, the sum of the secondary weights of the driving safety data, the driving speed data, the average fuel consumption data, the travel habit data and the driving mileage data is required to be equal to 1.

For example, taking driving safety data with a secondary weight of 40%, driving speed data with a secondary weight of 20%, average fuel consumption data with a secondary weight of 15%, travel habit data with a secondary weight of 15% and driving mileage data with a secondary weight of 10% as examples, the correspondence between each secondary index data and the secondary weight in the influence data of vehicle driving is shown in fig. 3.

After the primary weights of the driving safety data, the driving speed data, the average fuel consumption data, the travel habit data and the driving mileage data are determined, the secondary weights of the driving safety data are multiplied by the secondary index data of the driving safety data, the secondary weights of the driving speed data are multiplied by the secondary index data of the driving speed data, the secondary weights of the average fuel consumption data are multiplied by the secondary index data of the average fuel consumption data, the secondary weights of the travel habit data are multiplied by the secondary index data of the travel habit data, and the secondary weights of the travel mileage data are multiplied by the secondary index data of the travel mileage data, so that the total index data of the vehicle driving is obtained.

In one possible implementation, after determining the primary index data, the secondary index data, and the total index data for driving the vehicle, determining the driving advice for the vehicle based on the secondary index data and the total index data includes: comparing the total index data with the reference total index data, and based on the total index data being less than the reference total index data, the advice for driving the vehicle may include: the total index data of the vehicle driving is low, and the driving behavior is normalized. Based on the total indicator data being greater than the reference total indicator data, the advice for driving the vehicle may include: the total index data of the vehicle driving is higher and the vehicle is kept.

For example, comparing the secondary index data of the driving safety data with the reference driving safety secondary index data, the secondary index data based on the driving safety data being less than or equal to the reference driving safety secondary index data, the advice for driving safety may include: the second level index data of the driving safety data is lower, and please pay attention to the driving safety. The second level index data based on the driving safety data is greater than the reference driving safety second level index data, and the advice for driving safety may include: the second level index data of the driving safety data is higher and is kept.

For example, comparing the secondary index data of the travel speed data with the reference travel speed secondary index data, the secondary index data based on the travel speed data being less than or equal to the reference travel speed secondary index data, the advice for the travel speed may include: the second level index data of the running speed data is low, and the running speed is noted. The advice for the travel speed may include: the second level index data of the running speed data is higher and is kept.

For example, comparing the second-level index data of the average fuel consumption data with the reference average fuel consumption second-level index data, the second-level index data based on the average fuel consumption data being less than or equal to the reference average fuel consumption second-level index data, the suggestion for the average fuel consumption may include: the secondary index data of the average fuel consumption data is lower, and attention is paid to reducing fuel consumption. The second-level index data based on the average fuel consumption data is greater than the reference average fuel consumption second-level index data, and the suggestion for the average fuel consumption may include: the secondary index data of the average fuel consumption data is higher, and the average fuel consumption data is kept continuously.

For example, comparing the second level index data of the travel habit data with the reference travel habit second level index data, the second level index data based on the travel habit data is less than or equal to the reference travel habit second level index data, and the suggestion for the travel habit may include: the second-level index data of the travel habit data is lower, and please pay attention to the travel habit. The second-level index data based on the travel habit data is greater than the reference travel habit second-level index data, and the suggestion for the travel habit may include: the second-level index data of the travel habit data is higher and is kept continuously.

For example, comparing the secondary index data of the driving range data with the reference driving range secondary index data, the suggestion for the driving range may include: the secondary index data of the driving distance data is lower, and attention is paid to the improvement of the driving distance. The advice for the range may include: the secondary index data of the driving mileage data is higher and is kept.

In one possible implementation, after the data service platform receives the impact data of vehicle driving, the positions of the charging post and the power exchange station in the reference range around the vehicle can be determined based on the positions of the vehicle in the impact data of vehicle driving and the positions of the charging post and the power exchange station.

The embodiment of the application does not limit the reference range, and the reference range can be determined based on experience and can be adjusted according to actual conditions. The embodiment of the application also does not limit the manner of acquiring the positions of the charging pile and the power exchange station, and for example, the data service platform can be controlled to acquire a map containing the positions of the charging pile and the power exchange station, and the positions of the charging pile and the power exchange station are determined based on the map containing the positions of the charging pile and the power exchange station.

In one possible implementation, after determining the primary index data, the secondary index data, the total index data, and the driving advice for the vehicle, the control data service platform transmits the primary index data, the secondary index data, the total index data, and the advice for driving the vehicle to the device of the vehicle remote service provider; the control vehicle remote service provider transmits the primary index data, the secondary index data, the total index data and the suggestion for driving the vehicle to the remote communication terminal for displaying the primary index data, the secondary index data, the total index data and the suggestion for driving the vehicle by the real-time remote communication terminal.

The embodiment of the application does not limit the remote communication terminal, and for example, TBOX may be used as the remote communication terminal. The embodiments of the present application are also not limited to vehicle remote service providers, and alternatively, TSP platforms may be used as devices of the vehicle remote service providers.

Illustratively, the control data service platform transmits the primary index data, the secondary index data, the total index data, and the driving advice for the vehicle to the TSP platform; the TSP platform is controlled to transmit the primary index data, the secondary index data, the total index data, and the driving advice for the vehicle to the TBOX.

After the vehicle control system acquires the primary index data, the secondary index data, the total index data and the driving advice for the vehicle from the TBOX, the primary index data, the secondary index data, the total index data and the driving advice for the vehicle are sent to the instrument control system of the vehicle for display.

The embodiment of the application does not limit the manner in which the meter control system displays the secondary index data, and for example, the secondary index data may be displayed through a five-dimensional radar chart, where the five-dimensional radar chart of the secondary index data is shown in fig. 4.

The present application is not limited in the manner in which the total index data and the driving advice for the vehicle are displayed, and the total index data and the driving advice for the vehicle may be displayed by text, for example.

The method for displaying the primary index data by the instrument control system is not limited, and the primary index data of the number of unbelted times, the degree of fatigue driving, the number of collision alarming, the number of emergency braking requests, the number of tire pressure alarming, the number of lane departure alarming and the number of high-speed overstretched times in the driving safety data can be displayed through a seven-dimensional radar chart.

For example, the first-level index data of the number of speed limit alarms, the degree of overspeed, and the number of rapid acceleration in the running speed data may be displayed by a three-dimensional radar map.

For example, the first-level index data of the duration of non-start, the number of times of driving in the reference period, and the number of times of driving in the reference weather in the travel habit data may be displayed through a three-dimensional radar map.

For example, the first-order index data of the fuel consumption index and the first-order index data of the total mileage of the month may be displayed by text.

In the embodiment of the application, the driving data of the vehicle and the weather data during driving are used for determining the driving influence data of the vehicle, wherein the driving influence data of the vehicle comprises at least one of driving safety data, driving speed data, average fuel consumption data, travel habit data or driving mileage data. And the control data service platform processes the influence data of the vehicle driving to obtain first-level index data of the vehicle driving. And determining second-level index data and total index data based on the first-level index data, and determining advice for driving the vehicle based on the second-level index data and the total index data. According to the method and the device for detecting the driving travel, the characteristics of the driving travel can be obtained through detecting the multi-aspect data of the driving travel, driving advice aiming at the vehicle is obtained based on the characteristics of the driving travel, and driving safety is improved.

For ease of understanding, the above-described detection method of vehicle driving is exemplified in the following example. For example, the driver goes from the A-site to the B-site at 23, when the weather condition is snowy, the time interval from the last start of the vehicle has exceeded the fourth reference time period and is less than the fifth reference time period, i.e., the vehicle is not started for a first period of time. The driver gets on the vehicle alone and then wears the safety belt, and the driver is in a fatigue state of the first reference degree. In the process that the driver goes from the ground A to the ground B, a first reference degree emergency braking request and a speed limiting alarm occur, and the running speed of the vehicle exceeds the first reference percentage of the speed limiting of the road where the vehicle is located and is smaller than the second reference percentage when the speed limiting alarm occurs, namely the vehicle is overspeed at the first reference degree. The fuel consumption index of the vehicle in the month is smaller than the negative fourth reference percentage, namely the vehicle saves fuel for the first reference degree. The monthly total mileage of the vehicle in the present month is greater than 0 and less than the first reference mileage, i.e., the monthly total mileage of the vehicle is the first reference mileage.

Taking the second reference value, the sixth reference value, the thirteenth reference value, the fourteenth reference value, the eighteenth reference value, the nineteenth reference value, the twenty fourth reference value, the twenty fifth reference value and the twenty ninth reference value as examples, the calculation process of the first-level index data, the second-level index data and the total index data of the current journey of the driver includes: based on the travel time of the driver being 23 points, namely driving once in the reference period, the primary index data of the driving times in the reference period is 100 deducted by 10, namely 90; based on the fact that the driver travels on snow, the primary index data of the driving times of the reference weather is 100 deducted by 10, namely 90; based on the fact that the vehicle is not started for a first-stage long term, the first-stage index data of the time length of the non-starting is 100 deducted by 10, namely 90; based on the state that the driver is in the fatigue state of the first reference degree at the moment, the first-level index data of the fatigue driving degree is 100 deducted by 10, namely 90; based on the first reference degree emergency braking sent once in the driving process, the primary index data of the number of emergency braking requests is 100 deducted by 10, namely 90; based on the fact that one speed limiting alarm is sent in the driving process, the primary index data of the frequency of the speed limiting alarm is 100 deducted by 10, namely 90; based on the overspeed of the vehicle at the first reference degree during speed limiting alarm, the first-level index data of the overspeed degree is 100 minus 10, namely 90. Oil is saved based on the first reference degree of the oil consumption index of the vehicle in the month, and the first-level index data of the oil consumption index is increased by 10 and is 110; and on the basis that the monthly total driving mileage of the vehicle in the month is the first reference mileage, the first-level index data of the monthly total driving mileage is 100, and the first-level index data is 110.

The second level index data of the driving safety data is 100 times 30%, 90 times 15%, 100 times 15%, 90 times 10%, 100 times 10% and 100 times 10% based on the first level weight of the unbelted number, the first level weight of the fatigue driving degree being 15%, the first level weight of the number of the collision warning being 10%, the first level weight of the number of the tire pressure warning being 10%, the first level weight of the number of the lane departure warning being 10%, and the first level weight of the number of the high-speed overbending being 10%, that is, 97.5.

The primary weight based on the number of speed limit alarms is 50%, the primary weight of overspeed degree is 30% and the primary weight of the number of sudden acceleration is 20%, and the secondary index data of the running speed data is 90 times 50%, 90 times 30% and 100 times 20%, namely 92.

And if the primary weight based on the non-starting time period is 60%, the primary weight of the number of times of driving in the reference time period is 20% and the primary weight of the number of times of driving in the reference weather is 20%, the secondary index data of the travel habit data is 90 times 60%, 90 times 20% and 90 times 20% are added, and then 90 is obtained.

And if the primary weight of the fuel consumption index in the average fuel consumption data is 1, the secondary index data of the average fuel consumption data is 110.

And the primary weight of the total monthly mileage in the mileage data is also 1, and the secondary index data of the mileage data is 110.

Based on that the secondary weight of the driving safety data is 40%, the secondary weight of the driving speed data is 20%, the secondary weight of the average fuel consumption data is 15%, the secondary weight of the travel habit data is 15% and the secondary weight of the driving mileage data is 10%, the total index data is 97.5 multiplied by 40%, 92 multiplied by 20%, 90 multiplied by 15%, 110 multiplied by 15% and 110 multiplied by 10% and added, namely 98.4.

After the total index data is obtained, comparing the total index data with the reference total index data, taking the reference total index data as 90 as an example, and based on the total index data being greater than the reference total index data, the suggestion for driving the vehicle may include: the total index data of the vehicle driving is higher and the vehicle is kept.

Taking 90 as an example, the reference driving safety secondary index data, the reference driving speed secondary index data, the reference average fuel consumption secondary index data, the reference travel habit secondary index data and the reference driving mileage secondary index data are all the reference driving safety secondary index data, the secondary index data based on the driving safety data is larger than the reference driving safety secondary index data, and the suggestion for driving safety may include: the second level index data of the driving safety data is higher and is kept. The advice for the travel speed may include: the second level index data of the running speed data is higher and is kept. The second-level index data based on the average fuel consumption data is greater than the reference average fuel consumption second-level index data, and the suggestion for the average fuel consumption may include: the secondary index data of the average fuel consumption data is higher, and the average fuel consumption data is kept continuously. The second-level index data based on the travel habit data is equal to the reference travel habit second-level index data, and the suggestion for the travel habit may include: the second level index data of the driving safety data is lower, and please pay attention to the driving safety. The advice for the range may include: the secondary index data of the driving mileage data is higher and is kept.

Referring to fig. 5, an embodiment of the present application provides a detection apparatus for vehicle driving, including:

an acquisition module 501 for acquiring travel data of a vehicle and weather data at the time of driving;

a first determining module 502, configured to determine, based on driving data of the vehicle and weather data during driving, impact data of driving of the vehicle, where the impact data of driving of the vehicle includes at least one of driving safety data, driving speed data, average fuel consumption data, trip habit data, or driving mileage data;

a second determining module 503, configured to obtain primary index data of the vehicle driving based on the impact data of the vehicle driving, determine secondary index data and total index data based on the primary index data of the vehicle driving, and determine driving advice for the vehicle based on the secondary index data and the total index data.

In a possible implementation manner, the second determining module 503 is configured to upload the impact data of vehicle driving to the data service platform, and process the impact data of vehicle driving by the data service platform to obtain primary index data of vehicle driving, determine secondary index data and total index data based on the primary index data of vehicle driving, and determine driving advice for the vehicle based on the secondary index data and the total index data; and receiving the primary index data, the secondary index data and the total index data sent by the data service platform and the driving advice aiming at the vehicle.

In a possible implementation manner, the second determining module 503 is configured to control the remote communication terminal to send the vehicle driving impact data to the vehicle remote service provider, where the remote communication terminal is located on the vehicle; the control vehicle remote service provider uploads the influence data of the vehicle driving to the data service platform.

In one possible implementation, the driving data of the vehicle includes at least one of a number of unbelted times, a degree of fatigue driving, a number of collision warning times, a number of emergency braking requests, a number of tire pressure warning times, a number of lane departure warning times, a number of high-speed over-curves, a number of speed limit warning times, a speed of the vehicle driving, an acceleration of the vehicle driving, a degree of overspeed, a number of rapid acceleration times, a speed limit of a road where the vehicle is located, a period of non-start, a period of driving, a fuel consumption of hundred kilometers per month, or a total mileage of month driving; a first determining module 502, configured to determine driving safety data based on a number of unbelted times, a degree of fatigue driving, a number of collision warnings, a number of emergency braking requests, a number of tire pressure warnings, a number of lane departure warnings, and a number of high-speed overstretches; determining running speed data based on the number of speed limit alarms, the overspeed degree and the number of sudden acceleration; determining travel habit data based on the duration of non-start, the number of times of driving in a reference period, and the number of times of driving in a reference weather, the number of times of driving in the reference period being determined based on the period of driving; determining average fuel consumption data based on fuel consumption index, wherein the fuel consumption index is determined based on hundred kilometers of fuel consumption on a month basis; the range data is determined based on the monthly total range.

In one possible implementation, first level index data for vehicle driving includes: the number of times of unbelting, the degree of fatigue driving, the number of times of collision alarming, the number of times of emergency braking requests, the number of times of tire pressure alarming, the number of times of lane departure alarming and the number of times of high-speed over-bending in the driving safety data are respectively corresponding to one-level index data; the first-level index data respectively corresponding to the number of speed limit alarms, the overspeed degree and the number of rapid acceleration in the running speed data; the first-level index data respectively correspond to the non-starting time length, the driving times of the reference time period and the driving times of the reference weather in the trip habit data; primary index data corresponding to the fuel consumption index in the average fuel consumption data; and the first-level index data corresponds to the monthly total mileage in the mileage data.

In one possible implementation manner, the second determining module 503 is configured to determine the second level index data of the driving safety data based on the first level index data and the first level weight, where the first level index data and the first level weight correspond to the number of times the driving safety data is not fastened with the safety belt, the degree of fatigue driving, the number of times of collision warning, the number of times of emergency braking request, the number of times of tire pressure warning, the number of times of lane departure warning, and the number of times of high-speed over-bending, respectively; determining secondary index data of the running speed data based on primary index data and primary weight respectively corresponding to the speed limit alarming times, the overspeed degree and the rapid acceleration times in the running speed data; determining secondary index data of the travel habit data based on primary index data and primary weight which correspond to the non-starting time length, the driving times of the reference time period and the driving times of the reference weather in the travel habit data respectively; determining secondary index data corresponding to the average fuel consumption data based on the primary index data and the primary weight of the fuel consumption index in the average fuel consumption data; determining secondary index data corresponding to the driving mileage data based on the primary index data and the primary weight of the monthly driving total mileage in the driving mileage data; and determining total index data based on secondary index data and secondary weight which respectively correspond to the driving safety data, the driving speed data, the average fuel consumption data, the trip habit data and the driving mileage data in the influence data of the driving of the vehicle.

In one possible implementation, the apparatus further includes: the first control module is used for controlling the data service platform to send the primary index data, the secondary index data, the total index data and the suggestion for vehicle driving to the vehicle remote service provider; and the second control module is used for controlling the vehicle remote service provider to transmit the primary index data, the secondary index data, the total index data and the suggestion for driving the vehicle to the remote communication terminal, and displaying the primary index data, the secondary index data, the total index data and the suggestion for driving the vehicle by the real-time remote communication terminal.

The device determines the influence data of vehicle driving according to the driving data of the vehicle and the weather data during driving, wherein the influence data of vehicle driving comprises at least one of driving safety data, driving speed data, average fuel consumption data, trip habit data or driving mileage data. And the control data service platform processes the influence data of the vehicle driving to obtain first-level index data of the vehicle driving. And determining second-level index data and total index data based on the first-level index data, and determining advice for driving the vehicle based on the second-level index data and the total index data. The device can obtain the characteristics of the driving trip by detecting the multi-aspect data of the driving trip, and the driving advice aiming at the vehicle is obtained based on the characteristics of the driving trip, so that the driving safety is improved.

It should be noted that, when the apparatus provided in the foregoing embodiment performs the functions thereof, only the division of the foregoing functional modules is used as an example, in practical application, the foregoing functional allocation may be performed by different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules, so as to perform all or part of the functions described above. In addition, the apparatus and the method embodiments provided in the foregoing embodiments belong to the same concept, and specific implementation processes of the apparatus and the method embodiments are detailed in the method embodiments and are not repeated herein.

Fig. 6 is a schematic diagram of detection communication of vehicle driving provided in an embodiment of the present application, in which a vehicle control system 601 sends data of influence of vehicle driving to a remote communication terminal 602, the remote communication terminal 602 sends the data of influence of vehicle driving to a vehicle remote service provider 603, and the vehicle remote service provider 603 sends the data of influence of vehicle driving to a data service platform 604.

Fig. 7 is a schematic structural diagram of a server provided in the embodiment of the present application, where the server may have a relatively large difference due to different configurations or performances, and may include one or more processors 701 and one or more memories 702, where at least one computer program is stored in the one or more memories 702, and the at least one computer program is loaded and executed by the one or more processors 701, so that the server implements the vehicle driving detection method provided in each method embodiment described above. Of course, the server may also have a wired or wireless network interface, a keyboard, an input/output interface, and other components for implementing the functions of the device, which are not described herein.

Fig. 8 is a schematic structural diagram of a vehicle driving detection device according to an embodiment of the present application. The device may be a terminal, for example: vehicle-mounted terminal, smart phone, tablet computer, player, notebook computer or desktop computer. Terminals may also be referred to by other names as user equipment, portable terminals, laptop terminals, desktop terminals, etc.

Generally, the terminal includes: a processor 1501 and a memory 1502.

The processor 1501 may include one or more processing cores, such as a 4-core processor, an 8-core processor, or the like. The processor 1501 may be implemented in at least one hardware form of DSP (Digital Signal Processing ), FPGA (Field-Programmable Gate Array, field programmable gate array), PLA (Programmable Logic Array ). The processor 1501 may also include a main processor, which is a processor for processing data in an awake state, also called a CPU (Central Processing Unit ), and a coprocessor; a coprocessor is a low-power processor for processing data in a standby state. In some embodiments, the processor 1501 may be integrated with a GPU (Graphics Processing Unit, image processor) for taking care of rendering and rendering of content to be displayed by the display screen. In some embodiments, the processor 1501 may also include an AI (Artificial Intelligence ) processor for processing computing operations related to machine learning.

Memory 1502 may include one or more computer-readable storage media, which may be non-transitory. Memory 1502 may also include high-speed random access memory, as well as non-volatile memory, such as one or more magnetic disk storage devices, flash memory storage devices. In some embodiments, a non-transitory computer readable storage medium in memory 1502 is configured to store at least one instruction for execution by processor 1501 to cause the terminal to implement the method of detecting vehicle driving provided by the method embodiments in the present application.

In some embodiments, the terminal may further optionally include: a peripheral interface 1503 and at least one peripheral device. The processor 1501, memory 1502 and peripheral interface 1503 may be connected by a bus or signal lines. The individual peripheral devices may be connected to the peripheral device interface 1503 via a bus, signal lines, or circuit board. Specifically, the peripheral device includes: at least one of radio frequency circuitry 1504, a display 1505, a camera assembly 1506, audio circuitry 1507, and a power supply 1508.

A peripheral interface 1503 may be used to connect I/O (Input/Output) related at least one peripheral device to the processor 1501 and the memory 1502. In some embodiments, processor 1501, memory 1502, and peripheral interface 1503 are integrated on the same chip or circuit board; in some other embodiments, either or both of the processor 1501, the memory 1502, and the peripheral interface 1503 may be implemented on separate chips or circuit boards, which is not limited in this embodiment.

The Radio Frequency circuit 1504 is configured to receive and transmit RF (Radio Frequency) signals, also known as electromagnetic signals. The radio frequency circuit 1504 communicates with a communication network and other communication devices via electromagnetic signals. The radio frequency circuit 1504 converts an electrical signal into an electromagnetic signal for transmission, or converts a received electromagnetic signal into an electrical signal. Optionally, the radio frequency circuit 1504 includes: antenna systems, RF transceivers, one or more amplifiers, tuners, oscillators, digital signal processors, codec chipsets, subscriber identity module cards, and so forth. The radio frequency circuit 1504 may communicate with other terminals via at least one wireless communication protocol. The wireless communication protocol includes, but is not limited to: metropolitan area networks, various generations of mobile communication networks (2G, 3G, 4G, and 5G), wireless local area networks, and/or WiFi (Wireless Fidelity ) networks. In some embodiments, the radio frequency circuit 1504 may also include NFC (Near Field Communication, short range wireless communication) related circuits, which are not limited in this application.

Display 1505 is used to display a UI (User Interface). The UI may include graphics, text, icons, video, and any combination thereof. When display screen 1505 is a touch display screen, display screen 1505 also has the ability to collect touch signals at or above the surface of display screen 1505. The touch signal may be input to the processor 1501 as a control signal for processing. At this point, display 1505 may also be used to provide virtual buttons and/or a virtual keyboard, also referred to as soft buttons and/or a soft keyboard. In some embodiments, the display 1505 may be one, disposed on the front panel of the terminal; in other embodiments, the display 1505 may be at least two, respectively disposed on different surfaces of the terminal or in a folded design; in other embodiments, the display 1505 may be a flexible display disposed on a curved surface or a folded surface of the terminal. Even more, the display 1505 may be arranged in a non-rectangular irregular pattern, i.e., a shaped screen. The display screen 1505 may be made of LCD (Liquid Crystal Display ), OLED (Organic Light-Emitting Diode) or other materials.

The camera assembly 1506 is used to capture images or video. Optionally, the camera assembly 1506 includes a front camera and a rear camera. Typically, the front camera is disposed on the front panel of the terminal and the rear camera is disposed on the rear surface of the terminal. In some embodiments, the at least two rear cameras are any one of a main camera, a depth camera, a wide-angle camera and a tele camera, so as to realize that the main camera and the depth camera are fused to realize a background blurring function, and the main camera and the wide-angle camera are fused to realize a panoramic shooting and Virtual Reality (VR) shooting function or other fusion shooting functions. In some embodiments, the camera assembly 1506 may also include a flash. The flash lamp can be a single-color temperature flash lamp or a double-color temperature flash lamp. The dual-color temperature flash lamp refers to a combination of a warm light flash lamp and a cold light flash lamp, and can be used for light compensation under different color temperatures.

The audio circuitry 1507 may include a microphone and a speaker. The microphone is used for collecting sound waves of users and the environment, converting the sound waves into electric signals, inputting the electric signals to the processor 1501 for processing, or inputting the electric signals to the radio frequency circuit 1504 for voice communication. For the purpose of stereo acquisition or noise reduction, a plurality of microphones can be respectively arranged at different parts of the terminal. The microphone may also be an array microphone or an omni-directional pickup microphone. The speaker is used to convert electrical signals from the processor 1501 or the radio frequency circuit 1504 into sound waves. The speaker may be a conventional thin film speaker or a piezoelectric ceramic speaker. When the speaker is a piezoelectric ceramic speaker, not only the electric signal can be converted into a sound wave audible to humans, but also the electric signal can be converted into a sound wave inaudible to humans for ranging and other purposes. In some embodiments, the audio circuit 1507 may also include a headphone jack.

The power supply 1508 is used to power the various components in the terminal. The power source 1508 may be alternating current, direct current, disposable battery, or rechargeable battery. When the power source 1508 includes a rechargeable battery, the rechargeable battery may support wired or wireless charging. The rechargeable battery may also be used to support fast charge technology.

In some embodiments, the terminal further includes one or more sensors 1509. The one or more sensors 1509 include, but are not limited to: an acceleration sensor 1510, a gyro sensor 1511, a pressure sensor 1512, an optical sensor 1513, and a proximity sensor 1514.

The acceleration sensor 1510 may detect the magnitudes of accelerations on three coordinate axes of a coordinate system established with a terminal. For example, the acceleration sensor 1510 may be used to detect components of gravitational acceleration in three coordinate axes. The processor 1501 may control the display screen 1505 to display the user interface in either a landscape view or a portrait view based on the gravitational acceleration signal collected by the acceleration sensor 1510. The acceleration sensor 1510 may also be used for acquisition of motion data of a game or user.

The gyro sensor 1511 may detect a body direction and a rotation angle of the terminal, and the gyro sensor 1511 may collect a 3D motion of the user to the terminal in cooperation with the acceleration sensor 1510. The processor 1501, based on the data collected by the gyro sensor 1511, may implement the following functions: motion sensing (e.g., changing UI according to a tilting operation by a user), image stabilization at shooting, game control, and inertial navigation.

The pressure sensor 1512 may be disposed on a side frame of the terminal and/or below the display 1505. When the pressure sensor 1512 is disposed on a side frame of the terminal, a grip signal of the terminal by the user may be detected, and the processor 1501 performs a left-right hand recognition or a quick operation according to the grip signal collected by the pressure sensor 1512. When the pressure sensor 1512 is disposed at the lower layer of the display screen 1505, the processor 1501 controls the operability control on the UI interface according to the pressure operation of the user on the display screen 1505. The operability controls include at least one of a button control, a scroll bar control, an icon control, and a menu control.

The optical sensor 1513 is used to collect the ambient light intensity. In one embodiment, processor 1501 may control the display brightness of display screen 1505 based on the intensity of ambient light collected by optical sensor 1513. Specifically, when the ambient light intensity is high, the display brightness of the display screen 1505 is turned up; when the ambient light intensity is low, the display luminance of the display screen 1505 is turned down. In another embodiment, the processor 1501 may also dynamically adjust the shooting parameters of the camera assembly 1506 based on the ambient light intensity collected by the optical sensor 1513.

A proximity sensor 1514, also referred to as a distance sensor, is typically provided on the front panel of the terminal. The proximity sensor 1514 is used to collect the distance between the user and the front face of the terminal. In one embodiment, when the proximity sensor 1514 detects a gradual decrease in the distance between the user and the front face of the terminal, the processor 1501 controls the display 1505 to switch from the on-screen state to the off-screen state; when the proximity sensor 1514 detects that the distance between the user and the front face of the terminal gradually increases, the processor 1501 controls the display screen 1505 to switch from the off-screen state to the on-screen state.

Those skilled in the art will appreciate that the structure shown in fig. 8 is not limiting of the terminal and may include more or fewer components than shown, or may combine certain components, or may employ a different arrangement of components.

In an exemplary embodiment, a computer device is also provided, the computer device comprising a processor and a memory, the memory having at least one computer program stored therein. The at least one computer program is loaded and executed by one or more processors to cause the computer arrangement to implement any of the methods of detecting vehicle driving described above.

In an exemplary embodiment, there is also provided a computer-readable storage medium having stored therein at least one computer program loaded and executed by a processor of a computer device to cause the computer to implement any one of the above-described methods of detecting vehicle driving.

In one possible implementation, the computer readable storage medium may be a Read-Only Memory (ROM), a random-access Memory (Random Access Memory, RAM), a compact disc Read-Only Memory (CD-ROM), a magnetic tape, a floppy disk, an optical data storage device, and the like.

In an exemplary embodiment, a computer program product or a computer program is also provided, the computer program product or computer program comprising computer instructions stored in a computer readable storage medium. The processor of the computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions so that the computer device performs any of the above-described methods of detecting vehicle driving.

It should be noted that, information (including but not limited to user equipment information, user personal information, etc.), data (including but not limited to data for analysis, stored data, presented data, etc.), and signals referred to in this application are all authorized by the user or are fully authorized by the parties, and the collection, use, and processing of relevant data is required to comply with relevant laws and regulations and standards of relevant countries and regions. For example, the running data of the vehicle and the weather data at the time of driving referred to in the present application are acquired with sufficient authorization.

It should be understood that references herein to "a plurality" are to two or more. "and/or", describes an association relationship of an association object, and indicates that there may be three relationships, for example, a and/or B, and may indicate: a exists alone, A and B exist together, and B exists alone. The character "/" generally indicates that the context-dependent object is an "or" relationship.

It should be noted that the terms "first," "second," and the like in the description and in the claims of this application (if any) are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that embodiments of the present application described herein may be implemented in sequences other than those illustrated or otherwise described herein. The implementations described in the following exemplary examples are not representative of all implementations consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with some aspects of the present application as detailed in the accompanying claims.

The foregoing description of the exemplary embodiments of the present application is not intended to limit the invention to the particular embodiments of the present application, but to limit the scope of the invention to any modification, equivalents, or improvements made within the principles of the present application.

Claims

1. A method of detecting vehicle driving, the method comprising:

acquiring running data of a vehicle and weather data during driving;

2. The method of claim 1, wherein the obtaining primary index data for the vehicle drive based on the impact data for the vehicle drive, determining secondary index data and total index data based on the primary index data for the vehicle drive, determining a driving recommendation for the vehicle based on the secondary index data and the total index data, comprises:

uploading the influence data of the vehicle driving to a data service platform, and processing the influence data of the vehicle driving by the data service platform to obtain primary index data of the vehicle driving, determining secondary index data and total index data based on the primary index data of the vehicle driving, and determining driving advice for the vehicle based on the secondary index data and the total index data;

And receiving the primary index data, the secondary index data, the total index data and the driving advice for the vehicle, which are sent by the data service platform.

3. The method of claim 2, wherein uploading the impact data of vehicle driving to a data service platform comprises:

controlling a remote communication terminal to transmit the influence data of the driving of the vehicle to a vehicle remote service provider, wherein the remote communication terminal is positioned on the vehicle;

and controlling the vehicle remote service provider to upload the influence data of the vehicle driving to the data service platform.

4. The method of claim 1, wherein the vehicle travel data includes at least one of a number of unbelted times, a degree of tired driving, a number of collision warnings, a number of emergency braking requests, a number of tire pressure warnings, a number of lane departure warnings, a number of high speed over-curves, a number of speed limit warnings, a speed of the vehicle travel, an acceleration of the vehicle travel, an overspeed degree, a number of rapid acceleration, a speed limit of a road on which the vehicle is located, a period of inactivity, a number of reference weather driving, a period of driving, a hundred kilometers per month fuel consumption, or a total monthly travel distance;

The determining of the influence data of the vehicle driving based on the running data of the vehicle and the weather data at the time of driving includes:

determining the driving safety data based on the number of unbelted times, the degree of fatigue driving, the number of collision warnings, the number of emergency braking requests, the number of tire pressure warnings, the number of lane departure warnings, and the number of high-speed overstretches;

determining the driving speed data based on the number of speed limit alarms, the overspeed degree and the number of rapid acceleration;

determining the travel habit data based on the non-start time length, the number of times of driving in a reference period and the number of times of driving in a reference weather, wherein the number of times of driving in the reference period is determined based on the driving period;

determining the average fuel consumption data based on a fuel consumption index, the fuel consumption index being determined based on the average hundred kilometers fuel consumption;

the range data is determined based on the monthly total range.

5. The method of claim 4, wherein the primary index data of vehicle driving comprises: the number of times of unbelting, the degree of fatigue driving, the number of times of collision warning, the number of times of emergency braking request, the number of times of tire pressure warning, the number of times of lane departure warning and the number of times of high-speed over-bending in the driving safety data are respectively corresponding to one-level index data;

The first-level index data respectively corresponding to the frequency of speed limit alarming, the overspeed degree and the frequency of rapid acceleration in the running speed data;

the non-starting time length, the number of driving times in the reference time period and the number of driving times in the reference weather in the travel habit data are respectively corresponding to first-level index data;

primary index data corresponding to the fuel consumption index in the average fuel consumption data;

and the first-level index data corresponding to the monthly total mileage in the mileage data.

6. The method of claim 5, wherein the determining secondary and total index data based on the primary index data of the vehicle drive comprises:

determining secondary index data of the driving safety data based on the primary index data and the primary weight corresponding to the number of unbelted times, the fatigue driving degree, the collision alarming times, the emergency braking request times, the tire pressure alarming times, the lane departure alarming times and the high-speed over-bending times in the driving safety data respectively;

determining secondary index data of the running speed data based on the primary index data and the primary weight, which correspond to the speed limit alarming times, the overspeed degree and the sudden acceleration times in the running speed data respectively;

Determining secondary index data of the travel habit data based on the primary index data and the primary weight which correspond to the non-starting time length, the number of times of driving in the reference time period and the number of times of driving in the reference weather respectively in the travel habit data;

determining secondary index data corresponding to the average fuel consumption data based on the primary index data and the primary weight of the fuel consumption index in the average fuel consumption data;

determining secondary index data corresponding to the driving mileage data based on the primary index data and the primary weight of the month driving total mileage in the driving mileage data;

and determining the total index data based on secondary index data and secondary weights respectively corresponding to the driving safety data, the driving speed data, the average fuel consumption data, the trip habit data and the driving mileage data in the influence data of the driving of the vehicle.

7. The method according to any one of claims 1-6, further comprising:

controlling the data service platform to send the primary index data, the secondary index data, the total index data and the advice for driving the vehicle to the vehicle remote service provider;

And controlling the vehicle remote service provider to transmit the primary index data, the secondary index data, the total index data and the suggestion for vehicle driving to the remote communication terminal, wherein the primary index data, the secondary index data, the total index data and the suggestion for vehicle driving are displayed by the real-time remote communication terminal.

8. A vehicle driving detection apparatus, characterized in that the apparatus comprises:

9. A computer device, characterized in that it comprises a processor and a memory, in which at least one computer program is stored, which is loaded and executed by the processor, in order to carry out the method for detecting the driving of a vehicle according to any one of claims 1 to 6.

10. A computer-readable storage medium, wherein at least one computer program is stored in the computer-readable storage medium, and the at least one computer program is loaded and executed by a processor, so that the computer implements the method for detecting driving of a vehicle according to any one of claims 1 to 6.