CN111724505A

CN111724505A - Method and device for constructing driving condition

Info

Publication number: CN111724505A
Application number: CN202010589834.6A
Authority: CN
Inventors: 崔海龙; 王书庆; 金作梁; 李莉; 俞海洋
Original assignee: Beiqi Foton Motor Co Ltd
Current assignee: Beiqi Foton Motor Co Ltd
Priority date: 2020-06-24
Filing date: 2020-06-24
Publication date: 2020-09-29

Abstract

The embodiment of the invention provides a method and a device for constructing a running condition, wherein the method comprises the following steps: collecting driving record data of a target vehicle, and segmenting the driving record data to obtain working condition segments; acquiring characteristic parameters corresponding to the working condition fragments, and grouping the working condition fragments according to the characteristic parameters to obtain working condition groups; and calculating the evaluation value of each working condition segment in the working condition group, determining a target working condition segment according to the evaluation value, and constructing the driving working condition corresponding to the working condition group through the target working condition segment. In the embodiment of the invention, the driving record data is acquired in a test without artificially specifying conditions, so that the cost is low and the artificial interference is less; secondly, the evaluation value calculated according to the characteristic parameters of the working condition segment can actually reflect the quality of the working condition segment, so that the target working condition segment selected according to the evaluation value can construct a more accurate driving working condition; finally, grouping of different road types can be carried out on the working condition segments according to the characteristic parameters, and the method is suitable for wider actual scenes.

Description

Method and device for constructing driving condition

Technical Field

The invention relates to the technical field of automobiles, in particular to a method and a device for constructing a driving condition.

Background

The driving Cycle refers to the working condition of the vehicle during transportation and driving, and can be used for research, authentication, inspection and the like of the vehicle. The driving condition of the vehicle is affected by the model of the vehicle, the brand of the vehicle, the use of the vehicle, the driving environment and the like.

At present, a tester usually drives a vehicle with a specified model and brand, a specified purpose mode is realized in a specified driving environment, and an additional data acquisition device is arranged on the vehicle to acquire data of the vehicle in transportation and driving, so that a corresponding driving working condition is constructed. However, when the driving condition is constructed by the method, the data with large artificial interference factors are used, so that the constructed driving condition is not accurate enough and is difficult to reflect the actual condition; moreover, testing personnel, additional data acquisition devices, designated experimental sites or areas and the like which are recruited in advance are required to perform testing, so that the cost is high; and finally, the driving working condition is constructed by data acquired under specified conditions, so that the constructed driving working condition can only be suitable for limited vehicle types, scenes and the like, and the application range is small.

Disclosure of Invention

In view of the above problems, embodiments of the present invention are provided to provide a method and an apparatus for constructing a driving condition, so as to overcome the problems of high cost and poor accuracy in constructing a driving condition in the prior art.

According to a first aspect of the present invention, there is provided a driving condition construction method, which may include:

acquiring driving record data of a target vehicle;

dividing the driving record data into working condition segments according to a preset segmentation rule;

acquiring characteristic parameters of the working condition segments according to the running characteristics of the target vehicle;

grouping the working condition segments according to the road types corresponding to the characteristic parameters to obtain working condition groups;

determining the evaluation value of each working condition segment in the working condition group according to the characteristic parameters;

determining at least one target working condition segment in the working condition group according to the evaluation value;

and constructing the driving working conditions corresponding to the working condition groups based on the at least one target working condition segment.

Optionally, the determining, according to the characteristic parameter, an evaluation value of each operating condition segment in the operating condition group includes:

calculating the average value of the characteristic parameters of the same characteristic parameters corresponding to the working condition segments in the working condition group;

calculating weight vector coefficients of different characteristic parameters corresponding to the working condition groups according to the characteristic parameter average value;

and calculating the evaluation value of each working condition segment in the working condition group according to the characteristic parameter average value, the weight vector coefficient, the characteristic parameter and the number of the characteristic parameter.

Optionally, the calculating, according to the feature parameter average value, weight vector coefficients of different feature parameters corresponding to the working condition groups includes:

performing principal component analysis on the characteristic parameters according to the characteristic parameter average value to obtain principal components, principal component characteristic values corresponding to the principal components and component values corresponding to the characteristic parameters;

and determining the weight vector coefficient corresponding to the characteristic parameter according to the principal component characteristic value corresponding to the principal component and the component value.

Optionally, the feature parameters include vehicle speed distribution, and calculating feature parameter average values for the same feature parameters corresponding to each operating condition segment in the operating condition group includes:

calculating the vehicle speed distribution of each working condition segment in the working condition group in a preset vehicle speed interval;

and calculating the vehicle speed distribution average value corresponding to the preset vehicle speed interval in the working condition group according to the vehicle speed distribution.

Optionally, the calculating the characteristic parameter average value includes:

calculating the acceleration distribution of each working condition segment in the working condition group in a preset acceleration interval;

and calculating the average value of the acceleration distribution corresponding to the preset acceleration interval in the working condition group according to the acceleration distribution.

Optionally, the dividing the driving record data into working condition segments according to a preset segmentation rule includes:

dividing driving record data with a record time interval greater than or equal to a preset time interval from the record time interval to obtain at least two working condition segments; and/or the presence of a gas in the gas,

carrying out interpolation on the driving recording data with the recording time interval smaller than the preset time interval at the recording time interval to obtain at least one working condition segment; and/or the presence of a gas in the gas,

and dividing the driving record data with the record accumulated time length being greater than or equal to the preset accumulated time length at the preset accumulated time length to obtain at least two working condition segments.

determining an idle speed position of an idle speed section in the driving record data, wherein the idle speed section comprises driving record data of which the speed is in an idle speed interval and the acceleration is in an idle acceleration interval;

and dividing the driving record data at the idle speed position to obtain at least two working condition segments.

Optionally, the characteristic parameter includes a vehicle speed, and the grouping the operating condition segments according to the road category corresponding to the characteristic parameter to obtain the operating condition group includes:

calculating the average vehicle speed value of each working condition segment;

determining the road type corresponding to the working condition segment according to the vehicle speed average value;

and grouping the working condition segments according to the road type to obtain at least one working condition group.

According to a second aspect of the present invention, there is provided a driving condition constructing apparatus, which may include:

the data acquisition module is used for acquiring the driving record data of the target vehicle;

the segment dividing module is used for dividing the driving record data into working condition segments according to a preset segmentation rule;

the characteristic acquisition module is used for acquiring characteristic parameters of the working condition segments according to the running characteristics of the target vehicle;

the segment grouping module is used for grouping the working condition segments according to the road types corresponding to the characteristic parameters to obtain working condition groups;

the evaluation determining module is used for determining the evaluation value of each working condition segment in the working condition group according to the characteristic parameters;

the target determining module is used for determining at least one target working condition segment in the working condition group according to the evaluation value;

and the working condition construction module is used for constructing the driving working conditions corresponding to the working condition groups based on the at least one target working condition segment.

Optionally, the evaluation determination module comprises:

the characteristic average value calculation submodule is used for calculating the characteristic parameter average value of the same characteristic parameters corresponding to the working condition segments in the working condition group;

the weight vector coefficient calculation submodule is used for calculating weight vector coefficients of different characteristic parameters corresponding to the working condition groups according to the characteristic parameter average value;

and the evaluation value calculation submodule is used for calculating the evaluation value of each working condition segment in the working condition group according to the characteristic parameter average value, the weight vector coefficient, the characteristic parameter and the number of the characteristic parameter.

Optionally, the weight vector coefficient calculation sub-module includes:

the principal component analysis unit is used for performing principal component analysis on the characteristic parameters according to the characteristic parameter average value to obtain principal components, principal component characteristic values corresponding to the principal components and component values corresponding to the characteristic parameters;

and the weight vector coefficient calculation unit is used for determining the weight vector coefficient corresponding to the characteristic parameter according to the principal component characteristic value corresponding to the principal component and the component value.

Optionally, the feature average value calculating sub-module includes:

the vehicle speed distribution calculating unit is used for calculating the vehicle speed distribution of each working condition segment in the working condition group in a preset vehicle speed interval;

and the vehicle speed distribution average value calculating unit is used for calculating the vehicle speed distribution average value corresponding to the preset vehicle speed interval in the working condition group according to the vehicle speed distribution.

Optionally, the feature average value calculating sub-module includes:

the acceleration distribution calculating unit is used for calculating the acceleration distribution of each working condition segment in the working condition group in a preset acceleration interval;

and the acceleration distribution average value calculating unit is used for calculating the acceleration distribution average value corresponding to the preset acceleration interval in the working condition group according to the acceleration distribution.

Optionally, the segment dividing module includes:

the recording time interval segmentation submodule is used for dividing driving recording data with a recording time interval larger than or equal to a preset time interval from the recording time interval to obtain at least two working condition segments;

the recording time interval interpolation submodule is used for interpolating driving recording data with a recording time interval smaller than the preset time interval at the recording time interval to obtain at least one working condition segment;

and the recording accumulated time length segmenting submodule is used for dividing the driving record data with the recording accumulated time length being greater than or equal to the preset accumulated time length at the preset accumulated time length to obtain at least two working condition segments.

Optionally, the segment dividing module includes:

the idle position determining submodule is used for determining an idle position of an idle section in the driving record data, wherein the idle section comprises driving record data of which the speed is in an idle speed interval and the acceleration is in an idle acceleration interval;

and the idle position division submodule is used for dividing the driving record data at the idle position to obtain at least two working condition segments.

Optionally, the fragment grouping module includes:

the vehicle speed average value calculation submodule is used for calculating the vehicle speed average value of each working condition segment;

the road type determining submodule is used for determining the road type corresponding to the working condition segment according to the vehicle speed average value;

and the working condition segment grouping submodule is used for grouping the working condition segments according to the road type to obtain at least one working condition group.

The embodiment of the invention has the following advantages:

in the embodiment of the invention, the driving record data of the target vehicle can be collected, and the driving record data is segmented to obtain the working condition segments; acquiring characteristic parameters corresponding to the working condition fragments, and grouping the working condition fragments according to the characteristic parameters to obtain working condition groups; and calculating the evaluation value of each working condition segment in the working condition group, determining a target working condition segment according to the evaluation value, and constructing the driving working condition corresponding to the working condition group through the target working condition segment. In the embodiment of the invention, firstly, the driving record data can be directly collected from the target vehicle without testing and collecting the target vehicle in a test scene with specified conditions, the collection cost is low, the artificial interference factors are less, and the collected driving record data is more in line with the actual driving condition; secondly, the evaluation values of the working condition segments calculated according to the characteristic parameters of the working condition segments can reflect the quality of the working condition segments actually, and the target working condition segments are selected from the working condition groups according to the evaluation values, so that the driving working conditions constructed according to the target working condition segments are more consistent with the actual driving conditions and more accurate; finally, grouping of different road types can be carried out on the working condition segments according to the characteristic parameters, so that the working condition groups corresponding to the different road types can be directly obtained in the driving record data, the driving working conditions constructed according to the target working condition segments in the working condition groups can correspond to the different road types, the driving conditions are not limited to specified test conditions, and the driving scene is more suitable.

Drawings

FIG. 1 is a flow chart of a method for constructing a driving condition according to an embodiment of the present invention;

FIG. 2 is a flow chart of another driving condition construction method provided by the embodiment of the invention;

fig. 3 is a schematic diagram of a recording time interval in driving record data according to an embodiment of the present invention;

FIG. 4 is a schematic diagram of interpolation of driving record data at a recording time interval according to an embodiment of the present invention;

FIG. 5 is a histogram of vehicle speed distribution of driving data in one form provided by an embodiment of the present invention;

FIG. 6 is a histogram of vehicle speed distribution of vehicle data according to another form provided by the embodiment of the invention;

FIG. 7 is a schematic representation of a vehicle speed acceleration distribution matrix provided by an embodiment of the present invention;

FIG. 8 is a histogram of principal component-contribution ratios provided by an embodiment of the present invention;

FIG. 9 is a histogram of principal component-principal component eigenvalues provided by an embodiment of the present invention;

FIG. 10 is a diagram illustrating an exemplary driving condition provided by an embodiment of the present invention;

fig. 11 is a block diagram of a driving condition constructing apparatus according to an embodiment of the present invention.

Detailed Description

In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in further detail below.

Before the embodiments of the present application are explained in detail, an application scenario of the embodiments of the present application is introduced.

Example one

Referring to fig. 1, a flowchart of a driving condition construction method is shown, and the method may specifically include the following steps:

step 101: and acquiring the driving record data of the target vehicle.

In the embodiment of the present invention, the target vehicle may be a vehicle capable of recording the driving record data during the driving process, for example, the target vehicle may be equipped with a driving recorder, an on-board computer, an on-board T-Box (Telematics Box), and the like, so that the driving record data such as position information, time information, speed information, trajectory information, and the like of the driving of the target vehicle may be recorded during the driving process. The vehicle-mounted computer is connected with the vehicle-mounted T-Box, and vehicle-mounted data recorded by the target vehicle in the driving process can be acquired. The driving record data is generated by the target vehicle according to the autonomous driving behavior of the driver, and the limitation of specified driving conditions set artificially (such as the condition that the driver drives only on a specified route, drives at a specified speed and the like set artificially) is not generated, so that the driving record data acquired at one time can cover various driving conditions in the actual driving process, and can reflect the real situation of the target vehicle in the actual driving process, and the driving record data is more accurate. In addition, in order to obtain the driving record data in a targeted manner, the target Vehicle may be determined according to a requirement for constructing a driving condition, and optionally, the Vehicle model, the VIN (Vehicle Identification Number), the use, the power transmission system configuration, and the like of the target Vehicle may be different.

Step 102: and dividing the driving record data into working condition segments according to a preset segmentation rule.

In the embodiment of the invention, the collected driving record data can be divided into the working condition segments according to the preset segmentation rule, so that a large amount of driving record data are scattered integrally, and the analysis and calculation are convenient. Optionally, the preset segmentation rule may be that the driving record data is divided according to the generation time of the driving record data, for example, the driving record data in a fixed time period is divided into a working condition segment; alternatively, the preset segmentation rule may also be to divide the driving record data according to the generated coordinates of the driving record data, for example, to divide the driving record data between a fixed origin and a fixed destination into a working condition segment. A person skilled in the art may select a preset segmentation rule according to actual requirements to segment the driving record data, which is not specifically limited in the embodiment of the present invention.

Step 103: and acquiring the characteristic parameters of the working condition segments according to the running characteristics of the target vehicle.

In the embodiment of the invention, the characteristic parameters of the working condition segments can be obtained according to the running characteristics of the target vehicle, wherein the running characteristics of the target vehicle in the working condition segments can be directly obtained as the characteristic parameters, such as the total distance, the total time, the uniform speed time, the acceleration time and the like of the working condition segments; the driving characteristics may also be converted according to a preset calculation rule to obtain characteristic parameters, such as a running time percentage, a constant speed time percentage, an acceleration time percentage, an average speed, a speed standard deviation, and the like in the working condition segment according to the driving characteristics of the target vehicle, and those skilled in the art may select different types and quantities of characteristic parameters according to actual requirements.

Step 104: and grouping the working condition segments according to the road types corresponding to the characteristic parameters to obtain working condition groups.

In the embodiment of the invention, the working condition segments can be grouped according to the road type corresponding to the characteristic parameter, so that the obtained same working condition group comprises the working condition segments corresponding to the same road type, wherein the road type can be distinguished according to the average vehicle speed in the characteristic parameter, such as the correspondence between the road type and the average speed value, the average speed interval and the like; alternatively, the road type may be distinguished according to the travel track in the characteristic parameter, such as the road type corresponding to a straight travel track, a curved travel track, an upward travel track, a downward travel track, and the like. In addition, when the working condition segments are grouped according to the road category corresponding to the characteristic parameter, one road category may correspond to one characteristic parameter, or one road category may also correspond to multiple characteristic parameters, which is not specifically limited in the embodiment of the present invention.

Step 105: and determining the evaluation value of each working condition segment in the working condition group according to the characteristic parameters.

In the embodiment of the invention, the evaluation value of each working condition segment in the working condition group can be calculated according to the characteristic parameters, wherein the characteristic parameters are obtained according to the driving characteristics in the driving record data and reflect the characteristics of the actual driving working condition of the target vehicle, and the working condition group is obtained by classifying the working condition segments according to the characteristic parameters, so that the evaluation value of each working condition segment obtained according to the characteristic parameters can reflect the relation between the characteristic parameters of the working condition segment and the driving characteristics of the actual driving working condition, and the approach degree between the working condition segment and the actual driving working condition is determined.

Step 106: and determining at least one target working condition segment in the working condition group according to the evaluation value.

In the embodiment of the invention, according to the calculation method of the evaluation value, the smaller the evaluation value is, the greater the proximity degree of the working condition segment to the actual driving working condition is; the larger the evaluation value is, the smaller the proximity degree of the working condition segments to the actual driving working condition is, on this basis, according to the evaluation value, the working condition segments with the greater proximity degree to the actual driving working condition can be selected as target working condition segments in the working condition groups, for example, the working condition segments with the evaluation value smaller than or equal to a preset evaluation value threshold value are selected as target segments in the working condition groups, or the working condition segments are sorted according to the evaluation value in the working condition groups, and a preset number of target segments are selected. In addition, according to the calculation method of the evaluation value, the larger the evaluation value is, the larger the proximity degree of the condition segment to the actual driving condition is, the smaller the evaluation value is, and the smaller the proximity degree of the condition segment to the actual driving condition is, which is not specifically limited in the embodiment of the present invention.

Step 107: and constructing the driving working conditions corresponding to the working condition groups based on the at least one target working condition segment.

In the embodiment of the invention, the driving conditions corresponding to the working condition groups are constructed according to the target working condition segments, and the target working condition segments can be spliced, so that the driving conditions according with the road types corresponding to the working condition groups are obtained.

In the embodiment of the invention, the driving record data of the target vehicle can be collected, and the driving record data is segmented to obtain the working condition segments; acquiring characteristic parameters corresponding to the working condition fragments, and grouping the working condition fragments according to the characteristic parameters to obtain working condition groups; and calculating the evaluation value of each working condition segment in the working condition group, determining a target working condition segment according to the evaluation value, and constructing the driving working condition corresponding to the working condition group through the target working condition segment. In the embodiment of the invention, firstly, the driving record data can be directly collected from the target vehicle without testing and collecting the target vehicle in a test scene with specified conditions, the collection cost is low, the artificial interference factors are less, and the collected driving record data is more in line with the actual driving condition; secondly, the evaluation value of the working condition segment calculated according to the characteristic parameters of the working condition segment can actually reflect the quality of the working condition segment, and the target working condition segment is selected from the working condition group according to the evaluation value, so that the driving working condition constructed according to the target working condition segment is more consistent with the actual driving condition and more accurate; finally, grouping of different road types can be carried out on the working condition segments according to the characteristic parameters, so that the working condition groups corresponding to the different road types can be directly obtained in the driving record data, the driving working conditions constructed according to the target working condition segments in the working condition groups can correspond to the different road types, the driving conditions are not limited to specified test conditions, and the driving scene is more suitable.

Referring to fig. 2, a flow chart of another driving condition construction method is shown, and as shown in fig. 2, the method may include the steps of:

step 201: and acquiring the driving record data of the target vehicle.

In the embodiment of the invention, the driving record data of the target vehicle can be acquired for a period of time, such as one month, one week, one day and the like; the driving record data of the unlimited route between the origin and the destination may also be obtained, and the specific obtaining manner may refer to the related description of step 101, and is not described herein again to avoid repetition.

For example, at the acquisition frequency of 1Hz, the T-Box can acquire the driving record data of not less than 20 target vehicles and 1 month through the connection of a mobile network, a wireless broadband, bluetooth and the like, so that the number of lines of the effective driving record data is more than 1000 ten thousand lines. The driving record data collected from the T-Box includes data sent by a Controller Area Network (CAN) bus of the entire vehicle, and is stored in a CAN file, where the data includes data of time, vehicle speed, rotational speed, load, mileage, clutch pedal signal, brake pedal signal, accumulated fuel consumption, and the like, and driving record data recorded in a location file by a navigation device integrated in the T-Box, such as longitude, latitude, altitude, and the like. The mobile network may be a 2G (2-Generation wireless telephone technology, second-Generation mobile phone communication specification), a 3G (3rd-Generation, third-Generation mobile communication technology), a 4G (the 4th Generation mobile communication technology, fourth-Generation mobile communication technology), a 5G (5th-Generation, fifth-Generation mobile communication technology), and the like.

Step 202: and dividing the driving record data into working condition segments according to a preset segmentation rule.

In the embodiment of the present invention, step 202 may correspond to the related description of step 102, and is not repeated herein to avoid repetition.

Optionally, the step 202 may include:

substep S11: and dividing the driving recording data with the recording time interval larger than or equal to the preset time interval from the recording time interval to obtain at least two working condition segments.

In the embodiment of the invention, when the driving record data is acquired, the driving record data recorded by the passing time of the target vehicle can be acquired, for example, the driving record data comprises the driving speed corresponding to the recording time, the driving distance corresponding to the recording time and the like.

In the embodiment of the invention, the recording time in the driving record data is discontinuous due to data loss, restart after flameout of a vehicle and the like, so that the recording time interval appears in the driving record data. Alternatively, a preset time interval may be set, for example, 20 seconds, 30 seconds, 40 seconds, and the like, and when the recording time interval is greater than or equal to the preset time interval, the driving recording data before the recording time interval and after the recording time interval are considered to be discontinuous. At this time, the recording time interval may be divided, and optionally, the start of the recording time interval may be used as the end point of the condition segment before the recording time interval, and the end of the recording time interval may be used as the start point of the condition segment after the recording time interval, so as to segment the driving record data, and avoid the influence of data loss on the construction of the driving condition.

For example, when the recording time interval is greater than 30 seconds, the last second before the 1 st second of the 30 seconds is taken as the end point of the condition segment before the 1 st second, and the first second after the 30 th second of the 30 seconds is taken as the start point of the condition segment after the 30 th second.

Substep S12: and interpolating the driving recording data with the recording time interval smaller than the preset time interval at the recording time interval to obtain at least one working condition segment.

In the embodiment of the invention, when the recording time is less than the preset time interval, the data can be considered to be not lost much, and the recording time, namely the recording time, can be interpolated by analyzing the driving recording data before and after the recording time interval, so that the driving recording data is continuous.

FIG. 3 is a schematic diagram of a recording time interval in driving record data according to an embodiment of the present invention, as shown in FIG. 3, the driving record data includes a vehicle speed corresponding to the recording time at t_iSecond to t_jData loss in secondsThus, t_iSecond to t_jSeconds is the recording time interval 301. V_i，V_jAre respectively t_iSecond and t_jVehicle speed in seconds. The interpolation curve can be calculated by the following equations (1) and (2):

k＝(V_j-V_i)/(t_i-t_j) (1)

V_m＝k*i_m+(V_i-k*t_i) (2)

in the formulas (1) and (2), 0<i<j; j-i is less than or equal to 30; i, j are positive integers; i is not less than m not more than j, m is a positive integer; k is a coefficient in km/h.s (km/h.s); v_j,V_i,V_mThe unit is km/h (kilometer/hour) as vehicle speed.

Fig. 4 is a schematic diagram of interpolation of driving record data at a recording time interval according to an embodiment of the present invention, as shown in fig. 4, on the basis of fig. 3, an interpolation curve 401 is inserted at the recording time interval, i.e., a dashed box, according to formula (2), so that the driving record data is continuous.

Substep S13: and dividing the driving record data with the record accumulated time length being greater than or equal to the preset accumulated time length at the preset accumulated time length to obtain at least two working condition segments.

In the embodiment of the invention, the recording accumulated time can be the accumulated time of the recording time under the condition that the driving record data is continuous, and in order to avoid the loss of details due to overlong working condition segments, the driving record data of which the recording accumulated time is greater than or equal to the preset accumulated market can be divided at the recording accumulated time. Optionally, the preset accumulated time duration may be any time duration between 150 seconds and 300 seconds, such as 150 seconds, 180 seconds, 210 seconds, 240 seconds, 270 seconds, 300 seconds, and the like, and the divided operating condition segment record accumulated time durations may be the same or may be any time duration between 150 seconds and 300 seconds.

For example, when the recording accumulated time length of the driving record data is 450 seconds, the driving record data may be divided into two operating condition segments of 150 seconds and 300 seconds, or may be divided into two operating condition segments of 200 seconds and 250 seconds, or may be divided into three operating condition segments of which the recording accumulated time length is 150 seconds.

Optionally, the step 202 includes:

substep S21: and determining the idle speed position of an idle speed section in the driving record data, wherein the idle speed section comprises the driving record data of which the speed is in an idle speed interval and the acceleration is in an idle acceleration interval.

In the embodiment of the invention, the driving record data can be segmented by removing the idle section from the driving record data, wherein the idle section comprises the driving record data of which the speed is in the idle speed interval and the acceleration is in the idle acceleration interval, and the idle position comprises the starting position to the ending position of the idle section, such as the starting record time to the ending record time of the idle section or the starting record coordinate to the ending record coordinate of the idle section. The idle vehicle speed interval and the idle acceleration interval may be a vehicle speed interval or an acceleration interval when the vehicle is operated with the engine being unloaded.

Optionally, the driving condition may be divided into an acceleration condition, a deceleration condition, a constant speed condition and an idle condition, wherein the acceleration condition may be that the acceleration a of the vehicle in the driving process is greater than or equal to 0.15m/s²(m/s) operating conditions; the deceleration working condition can be that the acceleration a is less than or equal to-0.15 m/s in the running process of the vehicle²The working condition of (1); the constant speed working condition can be that the absolute value of the acceleration a in the running process of the vehicle is less than 0.15m/s²I.e., -0.15m/s²<a<0.15m/s²And the running speed v of the vehicle is more than or equal to 1 km/h; the idle condition can be that the absolute value of the acceleration a during the running of the vehicle is less than 0.15m/s²I.e., -0.15m/s²<a<0.15m/s²And the running speed v of the vehicle is less than 1 km/h. At the moment, the idle speed interval is that the running speed v is less than 1km/h, and the idle acceleration interval is that the acceleration is minus 0.15m/s²<a<0.15m/s². The idle speed interval and the idle acceleration interval may be appropriately adjusted according to the road type, the vehicle speed distribution of the driving record data, the acceleration distribution of the driving record data, and the like, which is not particularly limited in the embodiment of the present invention.

Substep S22: and dividing the driving record data at the idle speed position to obtain at least two working condition segments.

In the embodiment of the invention, in the driving record data, the front of the start position in the idle position is divided into one working condition segment, and the rear of the end position is divided into one working condition segment, so that at least two working condition segments are obtained, and the idle section is removed from the driving record data. Alternatively, the driving record data segmentation methods of the substeps S11 to S13 and the substeps 21 to S22 may be used separately, or may be used in combination according to the actual segmentation requirements, which is not specifically limited in the embodiment of the present invention.

Step 203: and acquiring the characteristic parameters of the working condition segments according to the running characteristics of the target vehicle.

In the embodiment of the present invention, step 203 may refer to the related description of step 103, and is not described herein again to avoid repetition. Optionally, in the embodiment of the present invention, part of characteristic parameters of the operating condition segment 1, the operating condition segment 2, and the operating condition segment 3 are as shown in table 1 below:

table 1 table of characteristic parameters of part of the operating condition section 1, the operating condition section 2 and the operating condition section 3

The characteristic parameters in table 1 are only used as examples, and the embodiment of the present invention does not specifically limit the number and the type of the characteristic parameters of the operating condition segments.

Step 204: and grouping the working condition segments according to the road types corresponding to the characteristic parameters to obtain working condition groups.

In the embodiment of the present invention, step 204 may correspond to the related description of step 104, and is not repeated herein to avoid repetition.

Optionally, the step 204 may include:

substep S31: and calculating the average value of the vehicle speed of each working condition segment.

Substep S32: and determining the road type corresponding to the working condition segment according to the average vehicle speed value.

Substep S33: and grouping the working condition segments according to the road type to obtain at least one working condition group.

In the embodiment of the invention, the average vehicle speed of the working condition segments can be calculated firstly, and then the road type to which the working condition segments belong can be determined according to the average vehicle speed, for example, different working condition segments of which the average vehicle speed is equal to the preset average vehicle speed are divided into the same working condition group, or the working condition segments of which the average vehicle speed belongs to the same average vehicle speed interval are divided into the same working condition group; or, the road category may also be determined according to the driving track of the condition segment, for example, the driving track of the target vehicle in the condition segment is determined according to the driving direction, the driving distance, the driving position, and the like of the condition segment, and the driving track is compared with the actual map information, so as to determine the road category corresponding to the driving track.

In the embodiment of the present invention, the preset average vehicle speed may be determined according to the vehicle speed distribution, the driving track, and the like of the driving record data, for example, in the driving record data of the target vehicle, the proportion of the vehicle speed operation time of different vehicle speeds in the total operation time, or the proportion of the vehicle speed operation distance of different vehicle speeds in the total operation distance is calculated, so as to determine the high speed average speed, the medium speed average speed, the low speed average speed, and the like corresponding to the driving record data, further determine the corresponding high speed road, the medium speed road, the low speed road, and the like, or further determine the corresponding high speed road, the suburban road, the urban road, and the like. Alternatively, it may be determined that the high speed average speed is 75km/h, and the corresponding link category is an expressway; the medium-speed average speed is 45km/h, and the corresponding road category is suburban roads; the low-speed average speed is 20km/h, and the corresponding road category is urban road.

FIG. 5 is a histogram of vehicle speed distribution of vehicle record data in one form provided by an embodiment of the present invention, where the abscissa is a vehicle speed interval, and Idle Stall represents an Idle vehicle speed interval; the ordinate is the vehicle speed-time ratio, i.e. the running time ratio of the vehicle speed in the vehicle speed interval in the total running time of the target vehicle in the running record data. From the contents shown in fig. 5, it can be seen that the target vehicle is comparatively large at the low-speed running time.

Fig. 6 is another form of a histogram of vehicle speed distribution of the driving record data, where the abscissa is a vehicle speed interval and the ordinate is a vehicle speed-distance ratio, that is, the ratio of the vehicle speed to the distance traveled by the target vehicle in the vehicle speed interval is the total distance traveled by the target vehicle in the driving record data. From the contents shown in fig. 6, it can be seen that the target vehicle has a large operating distance ratio at a medium speed and a high speed and a small operating distance ratio at a low speed.

In the embodiment of the invention, on the basis of the vehicle speed distribution in the driving record data shown in fig. 5 and 6, the vehicle speed at 25% of sites is determined as the quantile V by calculating the quantile corresponding to the vehicle speed, namely dividing the vehicle speed into four equal parts after sorting from small to large, and determining the vehicle speed at the 25% sites as the quantile V_25％The vehicle speed corresponding to 50% of the sites is quantile V_medianThe vehicle speed corresponding to 75% of the sites is quantile V_75％And determining V in FIGS. 5 and 6_25％、V_median、V_75％The vehicle speed interval. Alternatively, V may be set in FIG. 5 because of the large low speed run time ratio in FIG. 5_25％Comparing with the low-speed average speed of 20 km/h; since the medium-speed and high-speed operation distances are relatively large in fig. 6, V may be set in fig. 6_medianAt an average speed of 45km/h, V_75％Compared with the high-speed average speed of 75 km/h. Optionally, the low-speed average speed of 20km/h, the medium-speed average speed of 45km/h and the high-speed average speed of 75km/h may be corrected according to the principle that the low speed ratio is lower, the medium speed ratio is average and the high speed ratio is higher, so as to finally determine the low-speed average speed, the medium speed average speed and the high-speed average speed, thereby determining the average speeds corresponding to the urban road, the suburban road and the expressway.

Step 205: and calculating the average value of the characteristic parameters of the same characteristic parameters corresponding to the working condition segments in the working condition group.

In the embodiment of the invention, the average value of the characteristic parameters corresponding to the working condition groups, such as the average value of the working condition group running time, the average value of the uniform running time, the average value of the accelerated running time, the average value of the average vehicle speed, the average value of the average acceleration and the like, can be calculated through the same characteristic parameters corresponding to the working condition segments in the working condition groups.

For example, the average value of the characteristic parameter can be calculated by equation (3), as follows:

in the above formula (3), A_iThe average value of the characteristic parameters is taken; nc is the total number of working condition fragments in the working condition group; d_iIs the characteristic parameter of the ith segment. Taking the example that the working condition segment 1, the working condition segment 2 and the working condition segment 3 in the above table 1 belong to the same working condition group, the average running time of the working condition group is 299.3 seconds calculated by 299 seconds, 299 seconds and 300 seconds, the average constant-speed running time of the working condition group is 98 seconds calculated by 17 seconds, 76 seconds and 201 seconds, and the like.

Optionally, the characteristic parameter includes a vehicle speed distribution, and the step 205 includes:

substep S41: and calculating the vehicle speed distribution of each working condition segment in the working condition group in a preset vehicle speed interval.

In the embodiment of the present invention, the characteristic parameter may be vehicle speed distribution, at this time, a vehicle speed distribution average value of each working condition segment in the preset vehicle speed interval may be calculated, and optionally, the vehicle speed distribution may be a ratio of an operation time corresponding to the preset vehicle speed interval in the working condition segments in a total operation time; or the vehicle speed distribution may be a ratio of a travel distance corresponding to a preset vehicle speed interval in the working condition segment to a total travel distance. The number of preset vehicle speed intervals divided in the working condition segments can be used for obtaining the number of vehicle speed distributions, and the vehicle speed distributions corresponding to different preset vehicle speed intervals can be different characteristic parameters of the working condition segments.

Substep S42: and calculating the vehicle speed distribution average value corresponding to the preset vehicle speed interval in the working condition group according to the vehicle speed distribution.

In the embodiment of the invention, the vehicle speed distribution average value of the preset vehicle speed interval in the working condition group can be obtained by calculating the vehicle speed distribution corresponding to the same preset vehicle speed interval according to different working condition segments, and the vehicle speed distribution average value can be calculated by dividing the working condition segments into a plurality of preset vehicle speed intervals, so that the characteristic parameter average value corresponding to the characteristic parameter vehicle speed distribution is obtained.

Optionally, the characteristic parameter includes an acceleration profile, and the step 205 includes:

substep S51: and calculating the acceleration distribution of each working condition segment in the working condition group in a preset acceleration interval.

Substep S52: and calculating the average value of the acceleration distribution corresponding to the preset acceleration interval in the working condition group according to the acceleration distribution.

In the embodiment of the invention, the acceleration of the working condition segment can be obtained by calculating the vehicle speed, as shown in formula (4):

Acceleration＝(V_i+1-V_i)/3.6 (4)

in the above formula (4), Accelation is Acceleration in m/s²；V_i+1The vehicle speed is the i +1 second vehicle speed, and the unit is km/h; v_iThe vehicle speed is the ith second and the unit is km/h.

After the acceleration is obtained through calculation, the acceleration distribution of the working condition segments in the preset acceleration interval and the average value of the acceleration distribution of the preset acceleration intervals in the working condition group may be calculated, and the calculation process may refer to the related description of the substep S41 to the substep S42, and is not described herein again to avoid repetition. In addition, in the embodiment of the present invention, the substeps S41 to the substep S42, and the substeps S51 to the substep S52 may also be jointly calculated, for example, calculating the operation time ratio of the acceleration in the preset acceleration interval when the vehicle speed is in the preset vehicle speed interval; or, when the acceleration is within the preset acceleration interval, calculating an operating time ratio of the vehicle speed within the preset vehicle speed interval, and obtaining a vehicle speed acceleration distribution.

FIG. 7 is a schematic diagram of a vehicle speed and acceleration distribution matrix according to an embodiment of the present inventionAs shown in FIG. 7, the preset vehicle speed section includes 12 sections, for example, one preset vehicle speed section is set every 10km/h within 0km/h to 100km/h, and one preset vehicle speed section is set every 0km/h and more than 100 km/h. The preset acceleration interval includes 13 acceleration intervals, such as (-9 m/s)²,-2m/s²]，(-2m/s²,1.6m/s²]，(-1.6m/s²,1.2m/s²]，(-1.2m/s²,0.8m/s²]，(-0.8m/s²,0.4m/s²]，(-0.4m/s²,-0.15m/s²]，(-0.15m/s²,0.15m/s²]，(0.15m/s²,0.4m/s²]，(0.4m/s²,0.8m/s²]，(0.8m/s²,1.2m/s²]，(1.2m/s²,1.6m/s²]，(1.6m/s²,2.0m/s²]，(2m/s²,9m/s²]. And obtaining the vehicle speed acceleration matrix of different working condition segments according to calculation, thereby obtaining the vehicle speed acceleration distribution average value corresponding to the preset vehicle speed interval and the preset acceleration in the working condition group through calculation according to the formula (3).

Step 206: and calculating the weight vector coefficients of different characteristic parameters corresponding to the working condition groups according to the characteristic parameter average value.

In the embodiment of the invention, because the characteristic parameters of the working condition segments have different influences on the actual working condition, the weight vector coefficients corresponding to different characteristic parameters can be determined by determining the contribution degrees of the different characteristic parameters to the actual working condition, and the condition parameters with large contribution degrees are prevented from being ignored or the characteristic parameters with small contribution degrees are prevented from being excessively emphasized in the subsequent calculation to cause the inaccuracy of the calculation result.

Optionally, the step 206 may include:

substep S61: and performing principal component analysis on the characteristic parameters according to the characteristic parameter average value to obtain principal components, principal component characteristic values corresponding to the principal components and component values corresponding to the characteristic parameters.

PCA (Principal Component Analysis) is a statistical method, in which a group of original variables that may have correlation are converted into a group of linearly uncorrelated variables by orthogonal transformation, and the converted variables are Principal components. Optionally, the contribution rate of the principal component to the original variables can also be determined through PCA, and the contribution rate indicates the degree of information quantity in all the original variables contained in each principal component; the principal component characteristic value corresponding to each principal component can be determined through PCA, and the principal component characteristic value represents the characteristic of the information content contained in the principal component, so that different principal components can be distinguished; the component value of each original variable corresponding to the principal component can also be determined by PCA, and the component value represents the degree of information amount corresponding to different original variables contained in each principal component, i.e. the load of the original variables on the principal component.

In the embodiment of the invention, the feature parameter average value can be used as a bit original variable to carry out PCA, so as to obtain the principal component, the contribution rate and the feature value corresponding to the principal component, and the component value of each principal component corresponding to each feature parameter. Optionally, the principal components may be sorted according to the contribution rates from large to small, the sum of the contribution rates is accumulated and calculated sequentially from large to small, and the principal component with the sum of the contribution rates being greater than or equal to the preset contribution rate is determined as the principal component corresponding to the characteristic parameter. The predetermined contribution rate is not limited, and may be 90%, 85%, 80%, or the like.

Fig. 8 is a principal component-contribution ratio histogram provided by an embodiment of the present invention, and as shown in fig. 8, the contribution degrees of the

principal components

1, 2, 3, 4, and 5 have reached 92.73%, and in the case where the preset contribution ratio is 90%, it is considered that the information amount of the characteristic parameters included in the

principal components

1, 2, 3, 4, and 5 can approximately represent the total information amount of the characteristic parameters, so that the

principal components

1, 2, 3, 4, and 5 are taken as the principal components corresponding to the characteristic parameters.

Fig. 9 is a histogram of principal component-principal component eigenvalues provided by the embodiment of the present invention, and as shown in fig. 9, principal component eigenvalues corresponding to

principal components

1, 2, 3, 4, and 5, respectively, can be obtained.

Substep S62: and determining the weight vector coefficient corresponding to the characteristic parameter according to the principal component characteristic value corresponding to the principal component and the component value.

In the embodiment of the invention, the weight corresponding to each characteristic parameter can be determined through the principal component characteristic value and the component value of each characteristic parameter in the corresponding principal component, and if the component value of the characteristic parameter in the principal component with the larger principal component characteristic value is larger, the weight is larger; the smaller the feature parameter is, the smaller the component value is in the principal component, the smaller the weight is, and the like. Optionally, after determining the weight of each feature parameter, normalization processing may be performed on the feature parameter, so as to obtain a weight vector coefficient corresponding to each feature parameter.

Step 207: and calculating the evaluation value of each working condition segment in the working condition group according to the characteristic parameter average value, the weight vector coefficient, the characteristic parameter and the number of the characteristic parameter.

In the embodiment of the present invention, the evaluation value corresponding to the working condition segment may be calculated by the average value of the characteristic parameters, the weight vector coefficient, the characteristic parameters, and the number of the characteristic parameters, and optionally, may be calculated by equation (5) according to a weighted quadratic criterion:

in the above formula (5), E is an evaluation value; m is the number of characteristic parameters; w_iIs a weight vector coefficient; d_iCharacteristic parameters of the working condition segments; a. the_iAverage value of characteristic parameters; abs () represents the absolute value of the value in parentheses.

Taking the average value of the characteristic parameters as the expected value of the actual working condition, the smaller the evaluation value calculated by the above formula (5), the closer the characteristic parameters of each working condition segment are to the expected value of the actual working condition, and the closer the working condition segment is to the actual working condition.

One skilled in the art may also determine the proximity of the characteristic parameter of each operating condition segment to the expected value of the actual operating condition by calculating a difference between the characteristic parameter and the average value of the characteristic parameter, or by other methods, which is not limited in this embodiment of the present invention.

Step 208: and determining at least one target working condition segment in the working condition group according to the evaluation value.

In the embodiment of the present invention, step 208 may correspond to the related description of step 106, and is not described herein again to avoid repetition.

In the embodiment of the invention, the working condition segments can be sequenced according to the evaluation values, the sequenced working condition segments are displayed on the window interface, the selection operation of different working condition segments in the window interface is received, the corresponding evaluation values and the working condition segment curves can be displayed, and the working condition segments corresponding to the selection operation are confirmed as the target working condition segments. According to the method in the prior art, after the working condition segments are analyzed, the working condition segments with the minimum chi-square value in different speed intervals need to be selected through chi-square test to be constructed, the working condition segments are displayed in a disorder mode, the programming complexity of the window interface is high, the working condition segments can be directly displayed in a sequencing mode according to the evaluation values, the programming complexity of the corresponding window interface is reduced, and the construction efficiency of the working condition segments is improved. Wherein the window interface may be a Microsoft Windows (Microsoft Windows) window interface.

Step 209: and constructing the driving working conditions corresponding to the working condition groups based on the at least one target working condition segment.

In the embodiment of the present invention, step 209 may correspond to the related description referring to step 107, and is not described herein again to avoid repetition.

FIG. 10 is a schematic diagram of a driving condition according to an embodiment of the present invention, and as shown in FIG. 10, a driving condition with a recorded cumulative duration of about 1800 seconds is constructed by recording a plurality of target condition segments with cumulative durations of 150 seconds to 300 seconds.

In the embodiment of the present invention, the characteristic parameters of the driving condition constructed in the embodiment of the present invention are obtained, and the characteristic parameters of the driving condition are compared with the characteristic parameters of the actual condition, as shown in table 2 below:

TABLE 2 running condition characteristic parameter and actual condition characteristic parameter comparison list

Characteristic parameter	Actual conditions	Running condition
			Maximum speed (km/h)	96	93.8
Maximum acceleration (m/s)²)	1.21	1.19
			Maximum deceleration (m/s)²)	-1.56	-1.64
Average speed (km/h)	24.65	25.24
			Relative positive acceleration (m/s)²)	0.12	0.13
Acceleration ratio (%)	20.54	20.93
			Deceleration ratio (%)	19.12	19.88
Uniform ratio (%)	42.12	39.03
			Idling ratio (%)	18.22	20.16

As can be seen from the above table 2, the driving condition obtained by the embodiment of the invention is close to the actual condition, and more conforms to the actual driving characteristics of the target vehicle.

The embodiment of the invention has the following advantages:

It should be noted that, for simplicity of description, the method embodiments are described as a series of acts or combination of acts, but those skilled in the art will recognize that the present invention is not limited by the illustrated order of acts, as some steps may occur in other orders or concurrently in accordance with the embodiments of the present invention. Further, those skilled in the art will appreciate that the embodiments described in the specification are presently preferred and that no particular act is required to implement the invention.

Example two

Referring to fig. 11, a block diagram of a driving condition constructing apparatus 500 is shown, which may specifically include:

the data acquisition module 501 is used for acquiring driving record data of a target vehicle;

a segment dividing module 502, configured to divide the driving record data into working condition segments according to a preset segmentation rule;

a characteristic obtaining module 503, configured to obtain a characteristic parameter of the working condition segment according to a driving characteristic of the target vehicle;

the segment grouping module 504 is configured to group the working condition segments according to the road category corresponding to the characteristic parameter, so as to obtain a working condition group;

an evaluation determining module 505, configured to determine, according to the characteristic parameter, an evaluation value of each working condition segment in the working condition group;

a target determining module 506, configured to determine at least one target operating condition segment in the operating condition group according to the evaluation value;

and a working condition constructing module 507, configured to construct a driving working condition corresponding to the working condition group based on the at least one target working condition segment.

Optionally, the evaluation determination module 505 comprises:

Optionally, the weight vector coefficient calculation sub-module includes:

Optionally, the feature average value calculating sub-module includes:

Optionally, the fragment dividing module 502 includes:

Optionally, the fragment grouping module 504 includes:

The embodiment of the invention has the following advantages:

For the device embodiment, since it is basically similar to the method embodiment, the description is simple, and for the relevant points, refer to the partial description of the method embodiment.

The embodiments in the present specification are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other.

As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, apparatus, or computer program product. Accordingly, embodiments of the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, embodiments of the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.

In a typical configuration, the computer device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory. The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium. Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include non-transitory computer readable media (fransitory media), such as modulated data signals and carrier waves.

Embodiments of the present invention are described with reference to flowchart illustrations and/or block diagrams of methods, terminal devices (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing terminal to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing terminal, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing terminal to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing terminal to cause a series of operational steps to be performed on the computer or other programmable terminal to produce a computer implemented process such that the instructions which execute on the computer or other programmable terminal provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

While preferred embodiments of the present invention have been described, additional variations and modifications of these embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including preferred embodiments and all such alterations and modifications as fall within the scope of the embodiments of the invention.

Finally, it should also be noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or terminal that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or terminal. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or terminal that comprises the element.

The method for constructing the driving condition and the device for constructing the driving condition provided by the invention are described in detail, specific examples are applied in the description to explain the principle and the implementation mode of the invention, and the description of the examples is only used for helping to understand the method and the core idea of the invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present invention.

Claims

1. A driving condition construction method, characterized by comprising:

acquiring driving record data of a target vehicle;

2. The method according to claim 1, wherein the determining the evaluation value of each condition segment in the condition group according to the characteristic parameter comprises:

3. The method according to claim 2, wherein the calculating the weight vector coefficients of the working condition groups corresponding to different feature parameters according to the feature parameter average value comprises:

4. The method of claim 2, wherein the characteristic parameter comprises a vehicle speed distribution, and the calculating a characteristic parameter average value for the same characteristic parameter corresponding to each operating condition segment in the operating condition group comprises:

5. The method of claim 2, wherein the characteristic parameter comprises an acceleration distribution, and the calculating a characteristic parameter average value for the same characteristic parameter corresponding to each condition segment in the condition group comprises:

6. The method according to claim 1, wherein the dividing the driving record data into working condition segments according to a preset segmentation rule comprises:

7. The method according to claim 1, wherein the dividing the driving record data into working condition segments according to a preset segmentation rule comprises:

8. The method according to claim 1, wherein the characteristic parameter includes a vehicle speed, and the grouping of the working condition segments according to the road category corresponding to the characteristic parameter to obtain a working condition group comprises:

calculating the average vehicle speed value of each working condition segment;

9. A running condition constructing apparatus characterized by comprising:

10. The apparatus of claim 9, wherein the evaluation determination module comprises: