CN109727334B - Method and device for identifying terrain where vehicle is located and vehicle - Google Patents

Abstract

The invention provides a method and a device for identifying the terrain where a vehicle is located and the vehicle, wherein the method comprises the following steps: acquiring a first driving parameter group of a vehicle running on the current terrain, wherein the first driving parameter group comprises at least one driving parameter of a steering wheel corner, a steering wheel angular rate, a longitudinal acceleration, a lateral acceleration and a yaw rate; determining terrain category probability that the current terrain belongs to each terrain in different terrains according to the first driving parameter group and a plurality of terrain identification interval sets respectively corresponding to different terrains; and determining the terrain to which the current terrain belongs according to the terrain class probability of the current terrain belonging to each terrain in different terrains. The method can identify the terrain where the vehicle is located by calculating and processing vehicle components collected during the running of the vehicle and driving parameters related to the vehicle action and accurately classifying the terrain where the vehicle may be located.

Description

Method and device for identifying terrain where vehicle is located and vehicle

Technical Field

The disclosure relates to the technical field of automatic driving, in particular to a method and a device for identifying a terrain where a vehicle is located and the vehicle.

Background

With the rise of artificial intelligence technology, more and more automobile manufacturers set an automatic driving function in a vehicle, wherein a terrain-based automatic driving device is used for selecting different automatic driving strategies according to the terrain or weather environment of the current form of the vehicle. In the prior art, a terrain-based automatic driving device generally adopts a non-contact sensor, such as a visual sensor, to collect image information related to terrain, and classifies and identifies the corresponding terrain by extracting colors and textures in the image information. However, the image information collected by the visual sensor is susceptible to external environmental factors, such as light conditions and weather, thereby causing inaccurate terrain classification and recognition conditions.

Disclosure of Invention

In view of this, the present invention provides a method and an apparatus for identifying a terrain where a vehicle is located, and a vehicle, so as to reduce the influence of external environmental factors on terrain identification and improve accuracy of terrain identification.

In order to achieve the purpose, the technical scheme of the invention is realized as follows:

a method of identifying a terrain in which a vehicle is located, the method comprising:

acquiring a first driving parameter group of a vehicle running on the current terrain, wherein the first driving parameter group comprises at least one driving parameter of a steering wheel corner, a steering wheel angular rate, a longitudinal acceleration, a lateral acceleration and a yaw rate;

determining terrain category probability that the current terrain belongs to each terrain in different terrains according to the first driving parameter group and a plurality of terrain identification interval sets respectively corresponding to the different terrains;

and determining the terrain to which the current terrain belongs according to the terrain category probability of the current terrain belonging to each terrain in the different terrains.

Further, before obtaining the first set of driving parameters for the vehicle to travel over the current terrain, the method further comprises:

collecting a plurality of groups of second driving parameter groups which are driven by vehicles on different shapes respectively, wherein the types of driving parameters contained in each group of driving parameter groups in the plurality of groups of second driving parameter groups are consistent with the types of driving parameters contained in the first driving parameter group;

determining a terrain information projection matrix corresponding to each driving parameter according to the plurality of groups of second driving parameter groups;

and aiming at any terrain in different terrains, acquiring a terrain identification interval corresponding to each driving parameter under the terrain according to the terrain information projection matrix corresponding to each driving parameter, wherein all terrain identification intervals corresponding to all driving parameters under the terrain form a terrain identification interval set corresponding to the terrain.

Further, the determining a terrain information projection matrix corresponding to each driving parameter according to the plurality of second driving parameter sets includes:

for any one of the driving parameters acquired on any one of the different terrains:

acquiring a peak value and a valley value included by the driving parameter to form a peak value array and a valley value array of the driving parameter;

calculating a first peak value average value and a first valley value average value of the driving parameter according to the peak value array and the valley value array;

constructing a first driving parameter matrix of the driving parameter according to the peak value array, the valley value array, the first peak value average value and the first valley value average value;

acquiring a discrete matrix of the first driving parameter matrix according to the first peak average value, the first valley average value and the first driving parameter matrix;

after obtaining the discrete matrix corresponding to the driving parameter under each terrain, determining the terrain information projection matrix corresponding to the driving parameter according to all the obtained discrete matrices.

Further, the method for acquiring the terrain identification interval corresponding to the first driving parameter under the first terrain according to the terrain information projection matrix corresponding to the first driving parameter includes:

determining first projection information of the first driving parameter under the first terrain according to a terrain information projection matrix corresponding to the first driving parameter, wherein the first projection information is a product of a transposed matrix of the terrain information projection matrix of the first driving parameter and a first driving parameter matrix corresponding to the first driving parameter;

taking the maximum value, the minimum value, the average value, the variance and the adjustment average of the first projection information as the input of a terrain identification formula to obtain first terrain identification data of the first driving parameter, wherein the terrain identification formula is as follows:

therein, Sig_1iFirst terrain identification data, Y, representing the i-th driving parameter of a second set of driving parameters acquired over terrain 1_1imaxMaximum value, Y, of first projection information representing the ith driving parameter_1iminMinimum value, SD, of first projection information representing the ith driving parameter_y1iA variance, mu, of first projection information representing the ith driving parameter_{y1i_adj}An adjusted average of first projection information representing the ith driving parameter; when Y is_1imaxTaking the maximum value and Y of the first projection information of the first driving parameter_1iminTaking the minimum value and SD of the first projection information of the first driving parameter_y1iTaking the variance and mu of the first projection information of the first driving parameter_{y1i_adj}Sig is taken as the average of the first projection information of the first driving parameter_1iFirst terrain identification data for said first driving parameter;

and determining a terrain identification interval corresponding to the first driving parameter under the first terrain according to the first terrain identification data of the first driving parameter.

Further, the determining, according to the first driving parameter group and a plurality of terrain identification interval sets respectively corresponding to different terrains, a terrain category probability that the current terrain belongs to each of the different terrains includes:

acquiring a terrain information projection matrix corresponding to each driving parameter in the first driving parameter group;

determining second terrain identification data corresponding to each driving parameter under the current terrain according to each driving parameter and the terrain information projection matrix corresponding to each driving parameter;

and determining the terrain category probability according to the second terrain identification data corresponding to each driving parameter under the current terrain and the plurality of terrain identification interval sets.

Further, the determining, according to the each driving parameter and the terrain information projection matrix corresponding to the each driving parameter, second terrain identification data corresponding to the each driving parameter under the current terrain includes:

for any one of the first set of driving parameters:

acquiring a peak value and a valley value included by the driving parameter to form a peak value array and a valley value array of the driving parameter;

calculating a second peak value average value and a second valley value average value of the driving parameter according to the peak value array and the valley value array;

constructing a second driving parameter matrix of the driving parameter according to the peak value array, the valley value array, the second peak value average value and the second valley value average value;

acquiring second projection information of the driving parameters under the current terrain according to the second driving parameter matrix and a terrain information projection matrix corresponding to the driving parameters;

taking the maximum value, the minimum value, the average value, the variance and the adjusted average value of the second projection information as the input of a terrain identification formula to obtain second terrain identification data of the driving parameter under the current terrain, wherein the terrain identification formula is as follows:

therein, Sig_xiSecond terrain identification data, Y, representing the i-th driving parameter of the first set of driving parameters acquired over terrain x_ximaxMaximum value, Y, of second projection information representing the ith driving parameter_ximinMinimum value, SD, of second projection information representing the ith driving parameter_yxiA variance, mu, of second projection information representing the ith driving parameter_{yxi_adj}An adjusted average of second projection information representing the ith driving parameter; when Y is_ximaxTaking the maximum value and Y of the second projection information of the driving parameter_ximinTaking the minimum value and SD of the second projection information of the driving parameter_yxiThe variance and mu of the second projection information of the driving parameter are taken_{yxi_adj}When the adjusted average of the second projection information of the driving parameter is taken, Sig_1iAnd identifying data for the second terrain of the driving parameter.

Furthermore, each driving parameter is respectively corresponding to a terrain identification interval under each terrain in different terrains, all terrain identification intervals corresponding to all driving parameters under the same terrain form a terrain identification interval set of the terrain,

determining the terrain category probability through the second terrain identification data corresponding to each driving parameter under the current terrain and the plurality of terrain identification interval sets, including:

for any driving parameter in the first driving parameter group, determining whether second terrain identification data of the driving parameter under the current terrain belongs to any terrain identification interval corresponding to the driving parameter under different terrains;

when the second terrain identification data of the driving parameter under the current terrain belongs to any terrain identification section corresponding to the driving parameter under different terrains, determining that the similarity probability of the terrain corresponding to the terrain identification section to which the driving parameter belongs is 1, and determining that the similarity probability of the terrain corresponding to other terrain identification sections except the terrain identification section to which the driving parameter belongs is 0; alternatively, the first and second electrodes may be,

when the second terrain identification data of the driving parameter under the current terrain does not belong to any terrain identification interval respectively corresponding to the driving parameter under different terrains, calculating the similarity probability of the terrain corresponding to each terrain identification interval respectively corresponding to the second terrain identification data and the driving parameter under different terrains according to the distance between the second terrain identification data and each terrain identification interval in the terrain identification interval set;

and after all the similar probabilities corresponding to all the driving parameters included in the first driving parameter group are obtained, taking the average value of all the similar probabilities corresponding to all the driving parameters of the same terrain in different terrains as the terrain class probability of the current terrain.

Further, the determining the terrain to which the current terrain belongs according to the terrain category probability that the current terrain belongs to each of the different terrains includes:

and determining the terrain with the maximum terrain probability value of the terrain category as the terrain to which the current terrain belongs.

Compared with the prior art, the method for identifying the terrain where the vehicle is located has the following advantages:

(1) the method can acquire a first driving parameter group of the vehicle running on the current terrain, wherein the first driving parameter group comprises at least one driving parameter of a steering wheel corner, a steering wheel angular rate, a longitudinal acceleration, a lateral acceleration and a yaw rate; determining terrain category probability that the current terrain belongs to each terrain in different terrains according to the first driving parameter group and a plurality of terrain identification interval sets respectively corresponding to different terrains; and determining the terrain to which the current terrain belongs according to the terrain class probability of the current terrain belonging to each terrain in different terrains. The invention provides a novel terrain recognition method, which can be used for recognizing the terrain where a vehicle is located by calculating and processing vehicle components collected during the running of the vehicle and driving parameters related to vehicle actions and classifying the terrain where the vehicle is likely to be located.

(2) The method can collect a plurality of groups of second driving parameter groups of which the vehicles respectively drive on different shapes, wherein the types of the driving parameters contained in each group of the second driving parameter groups are consistent with the types of the driving parameters contained in the first driving parameter group; determining a terrain information projection matrix corresponding to each driving parameter according to the plurality of groups of second driving parameter groups; and aiming at any terrain in different terrains, acquiring a terrain identification interval corresponding to each driving parameter under the terrain according to a terrain information projection matrix corresponding to each driving parameter, wherein all terrain identification intervals corresponding to all driving parameters under the terrain form a terrain identification interval set corresponding to the terrain. The characteristic data indicating various driving parameters in different terrains can be obtained through a large number of collected driving parameters related to vehicle components and vehicle actions from different terrains, and the characteristic data is used for classifying and identifying the vehicle terrains.

Another object of the present invention is to provide a device for recognizing the terrain in which a vehicle is located, so as to reduce the influence of external environmental factors on the terrain-based automatic driving function.

In order to achieve the purpose, the technical scheme of the invention is realized as follows:

an apparatus for identifying the terrain in which a vehicle is located, the apparatus comprising:

the system comprises a parameter acquisition module, a data processing module and a data processing module, wherein the parameter acquisition module is used for acquiring a first driving parameter group of a vehicle driving on the current terrain, and the first driving parameter group comprises at least one driving parameter of a steering wheel corner, a steering wheel angular rate, a longitudinal acceleration, a lateral acceleration and a yaw rate;

a probability determination module, configured to determine, according to the first driving parameter set and a plurality of terrain identification interval sets respectively corresponding to different terrains, a terrain category probability that the current terrain belongs to each of the different terrains;

and the terrain determining module is used for determining the terrain to which the current terrain belongs according to the terrain category probability that the current terrain belongs to each terrain in the different terrains.

Compared with the prior art, the identification device for the terrain where the vehicle is located has the following advantages:

the device can acquire a first driving parameter group of the vehicle running on the current terrain, wherein the first driving parameter group comprises at least one driving parameter of a steering wheel angle, a steering wheel angular rate, a longitudinal acceleration, a lateral acceleration and a yaw rate; determining terrain category probability that the current terrain belongs to each terrain in different terrains according to the first driving parameter group and a plurality of terrain identification interval sets respectively corresponding to different terrains; and determining the terrain to which the current terrain belongs according to the terrain class probability of the current terrain belonging to each terrain in different terrains. The terrain where the vehicle is located can be identified by calculating and processing vehicle components and driving parameters related to vehicle actions collected during vehicle driving and classifying the terrain where the vehicle may be located.

Another object of the present invention is to provide a vehicle including the above-mentioned apparatus for recognizing a terrain in which the vehicle is located, so as to reduce an influence of an external environmental factor on a terrain-based automatic driving function.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate an embodiment of the invention and, together with the description, serve to explain the invention and not to limit the invention. In the drawings:

fig. 1 is a flowchart of a method for identifying a terrain in which a vehicle is located according to an embodiment of the present invention;

FIG. 2 is a flow chart illustrating another method for identifying the terrain in which a vehicle is located according to the embodiment of FIG. 1;

FIG. 3 is a flow chart of a method for determining a terrain projection matrix according to the embodiment shown in FIG. 2;

FIG. 4 is a flowchart illustrating a method for determining a set of terrain identification intervals according to the embodiment shown in FIG. 2;

FIG. 5 is a flow chart illustrating a method for determining a terrain category probability according to the embodiment shown in FIG. 1;

FIG. 6 is a flow chart illustrating a method of geo-identification data acquisition according to the embodiment shown in FIG. 5;

FIG. 7 is a flow chart illustrating a method for calculating a terrain category probability according to the embodiment shown in FIG. 5;

fig. 8 is a block diagram of an apparatus for identifying the terrain in which a vehicle is located according to an embodiment of the present invention;

FIG. 9 is a block diagram of an alternative vehicle terrain identification device according to the embodiment of FIG. 8;

FIG. 10 is a block diagram illustrating a probability determination module according to the embodiment shown in FIG. 8.

Detailed Description

It should be noted that the embodiments and features of the embodiments may be combined with each other without conflict.

The present invention will be described in detail below with reference to the embodiments with reference to the attached drawings.

Fig. 1 is a flowchart of a method for identifying a terrain in which a vehicle is located according to an embodiment of the present invention, and referring to fig. 1, the method for identifying a terrain in which a vehicle is located may include the following steps:

in step 101, a first set of driving parameters for a vehicle to travel over current terrain is obtained.

Wherein the first driving parameter group comprises at least one driving parameter of steering wheel angle, steering wheel angle speed, longitudinal acceleration, lateral acceleration and yaw rate.

In step 102, a terrain classification probability that the current terrain belongs to each of the different terrains is determined according to the first driving parameter group and a plurality of terrain identification interval sets respectively corresponding to the different terrains.

By way of example, the different terrains in the embodiments of the present disclosure include extreme terrains that can be explicitly described, such as sand, mud, snow, etc., or more complex terrains that may be a combination of a plurality of such extreme terrains.

The plurality of terrain recognition interval sets respectively corresponding to different terrains may be terrain recognition interval sets artificially set according to characteristics of different terrains, or preferably may be sets of classification intervals in a terrain classification model trained by a large amount of terrain-related data. The training process may be described in a subsequent step, after which the vehicle needs to receive and store the trained terrain classification model. It should be noted that each terrain identification interval set includes a plurality of terrain identification intervals, and each terrain identification interval corresponds to a driving parameter acquired on a terrain. When the terrain category is calculated, the similar probability of a certain driving parameter under the current terrain and the same driving parameter under each terrain can be calculated, and then the similar probabilities of a plurality of driving parameters are integrated to obtain the terrain category probability of each terrain of the different terrains to which the current terrain belongs.

In step 103, the terrain to which the current terrain belongs is determined according to the terrain classification probability of the current terrain belonging to each of the different terrains.

Illustratively, this step 103 may comprise: and determining the terrain to which the current terrain belongs as the terrain with the largest probability of the terrain category.

In summary, the method for identifying the terrain where the vehicle is located provided by the present disclosure can obtain a first driving parameter set of the vehicle driving on the current terrain, where the first driving parameter set includes at least one driving parameter of a steering wheel angle, a steering wheel angular velocity, a longitudinal acceleration, a lateral acceleration, and a yaw rate; determining terrain category probability that the current terrain belongs to each terrain in different terrains according to the first driving parameter group and a plurality of terrain identification interval sets respectively corresponding to different terrains; and determining the terrain to which the current terrain belongs according to the terrain class probability of the current terrain belonging to each terrain in different terrains. The terrain of the vehicle can be identified by calculating and processing vehicle components acquired during vehicle running and driving parameters related to vehicle actions and accurately classifying the terrain where the vehicle may be located.

Fig. 2 is a flowchart illustrating another method for identifying the terrain in which the vehicle is located according to the embodiment shown in fig. 1, and as shown in fig. 2, before acquiring the first driving parameter group in which the vehicle travels on the current terrain, the method for identifying the terrain in which the vehicle is located may further include the following steps.

In step 104, a plurality of sets of second driving parameter, in which the vehicles respectively drive on different shapes, are collected.

The type of the driving parameters included in each of the plurality of sets of second driving parameter sets is consistent with the type of the driving parameters included in the first driving parameter set.

For example, before acquiring a first driving parameter group in which the vehicle drives on the current terrain, a plurality of second driving parameter groups in which the vehicle drives on different terrains respectively need to be collected to establish correspondence between different values of each driving parameter in the second driving parameter groups and different terrains.

In step 105, a terrain information projection matrix corresponding to each driving parameter is determined according to the plurality of second driving parameter sets.

In step 106, for any one of the different terrains, a terrain identification interval corresponding to each driving parameter under the terrain is obtained according to the terrain information projection matrix corresponding to each driving parameter.

And all terrain identification intervals corresponding to all driving parameters under the terrain form a terrain identification interval set corresponding to the terrain.

For example, the steps 104 to 106 may be collectively referred to as a process of training a terrain classification model through a large amount of collected terrain data (a first driving parameter group), which may be performed on an off-board device or on an on-board device. When the method is carried out on an off-board device, the trained terrain classification model (namely the terrain information projection matrix and the terrain recognition interval) needs to be pushed to a vehicle storage device before the vehicle runs.

Fig. 3 is a flowchart illustrating a method for determining a topographic projection matrix according to the embodiment shown in fig. 2, and as shown in fig. 3, the step 105 may include the following steps.

For any one of the driving parameters acquired on any one of the different aforementioned terrains:

in step 1051, the peak value and the valley value included in the driving parameter are obtained to form a peak value array and a valley value array of the driving parameter.

Exemplarily, any one of the different terrains is represented by a terrain 1, any one of driving parameters acquired on the terrain 1 is represented by an ith driving parameter, and the driving parameters can include peaks and valleys calculated by the following method:

obtaining Δ i ═ di (k) -di (k-1) and β i ═ di (k-1) -di (k), wherein di (k-1) represents the k-1 th value of the i-th driving parameter, di (k) represents the k-th value of the i-th driving parameter, and Δ i and β i are the forward difference value and the reverse difference value of the k-th value and the k-1 th value of the i-th driving parameter respectively. When Δ i <0 and β i >0, determining di _ p (k) di (k), i.e. di (k), as one of the peaks of the i-th driving parameter; when Δ i >0 and β i <0, di _ v (k) di (k), i.e. di (k), is determined to be one of the valleys of the i-th driving parameter.

All the peak values and the valley values included in each driving parameter can be obtained by the method. For example, when the i-th driving parameter includes 6 peaks and 5 valleys, the obtained integrated values Sizei _ P _ V _ min (6,5) 5 of the number of peaks and valleys are obtained first, and then an array di _ P _ resized [ P (1) P (2) P (3) P (4) P (5) ] and di _ V _ resized [ V (1) V (2) V (3) V (4) V (5) ] are constructed, where di _ P _ resized is the peak value array of the i-th driving parameter and di _ V _ resized is the valley value array of the i-th driving parameter.

In step 1052, a first peak average and a first valley average of the driving parameter are calculated according to the peak array and the valley array.

For example, the first peak average value and the first valley average value of the driving parameter may be calculated by the following equations (1) and (2):

wherein Sizei _ p _ v is the number of elements in the peak value array and the valley value array of the ith driving parameter, and mu_{i_p}Is the first peak value average value, mu, of the ith driving parameter_{i_v}The first valley average value of the ith driving parameter.

In step 1053, a first driving parameter matrix of the driving parameter is constructed according to the peak value array, the valley value array, the first peak value average value and the first valley value average value.

For example, the first driving parameter matrix of the driving parameters may be constructed by the following formula:

wherein, X_1iA first driving parameter matrix representing the ith driving parameter under the terrain 1, a peak value array di _ v _ resized, which is the ith driving parameter, of the ith driving parameter is a valley value array of the ith driving parameter, and mu_{i_p}Is the first peak value average value, mu, of the ith driving parameter_{i_v}The average value of the first valley values of the ith driving parameters is Sizei _ p _ v, the number of elements in a peak value array and a valley value array of the ith driving parameters is Sizei _ p _ v, and the terrain 1 is any one of the terrains.

In step 1054, a discrete matrix of the first driving parameter matrix is obtained according to the first peak average value, the first valley average value, and the first driving parameter matrix.

For example, an average of the first peak average value and the first valley average value may be calculated as an average of all values in the driving parameter, and then, a first driving parameter matrix of the driving parameter may be constructed by:

S_1i＝(X_1i-μ_1i)(X_1i-μ_1i)^T (4)

wherein S is_1iA discrete matrix, X, representing a first matrix of driving parameters of the i-th vehicle under the terrain 1_1iIs a first driving parameter matrix, mu, of the ith driving parameter under the terrain 1_1iAverage of all values in the i-th driving parameter acquired over terrain 1.

In step 1055, after obtaining the discrete matrix corresponding to the driving parameter in each terrain, determining a terrain information projection matrix corresponding to the driving parameter according to all the obtained discrete matrices.

For example, after obtaining the discrete matrix corresponding to the driving parameter in each terrain, the sum of all the obtained discrete matrices needs to be calculated first. It should be noted that all the discrete matrices obtained are all discrete matrices corresponding to the same driving parameters obtained on all possible terrains. After that, determining a terrain information projection matrix corresponding to the driving parameters by the formula (5):

wherein, W_iRepresenting a terrain information projection matrix corresponding to the ith driving parameter,

is a transposed matrix, mu, of a discrete matrix corresponding to the ith driving parameter acquired on all possible terrains_1iAverage, mu, of all values of the i-th driving parameter acquired over terrain 1_2iAverage of all values in the i-th driving parameter acquired over terrain 2.

Fig. 4 is a flowchart of a method for determining a set of terrain identification intervals according to the embodiment shown in fig. 2, where, as shown in fig. 4, the first terrain is any one of the aforementioned different terrains, and the first driving parameter is any one of the second driving parameter sets, and the step 106 may include the following steps.

In step 1061, first projection information of the first driving parameter under the first terrain is determined according to the terrain information projection matrix corresponding to the first driving parameter.

The first projection information is the product of the transpose matrix of the terrain information projection matrix of the first driving parameter and the first driving parameter matrix corresponding to the first driving parameter.

In step 1062, the maximum value, the minimum value, the average value, the variance, and the adjusted average of the first projection information are used as inputs of a terrain identification formula (6) to obtain first terrain identification data of the first driving parameter, where the terrain identification formula (6) is:

therein, Sig_1iFirst terrain identification data, Y, representing the i-th driving parameter of a second set of driving parameters acquired over terrain 1_1imaxMaximum value, Y, of first projection information representing the i-th driving parameter_1iminMinimum value, SD, of the first projection information representing the i-th driving parameter_y1iThe variance, mu, of the first projection information representing the i-th driving parameter_{y1i_adj}An adjusted average of the first projection information representing the ith driving parameter; by way of illustration of the steps 1061 to 1063, the formula can be expressed as: when Y is_1imaxTaking the maximum value and Y of the first projection information of the first driving parameter_1iminTaking the minimum value and SD of the first projection information of the first driving parameter_y1iThe variance and mu of the first projection information of the first driving parameter are taken_{y1i_adj}When the adjusted average of the first projection information of the first driving parameter is taken, Sig_1iFirst terrain identification data for the first driving parameter.

In the formula, for example, the subscript i is used to indicate the driving parameter type corresponding to the first terrain identification data,m is the total number of driving parameter types, for example, if the second driving parameter group includes five driving parameters of steering wheel angle, steering wheel angular velocity, longitudinal acceleration, lateral acceleration and yaw rate, m is 5, Sig₁₁First topographic data, Sig, representing the steering wheel angle of a driving parameter₁₂First terrain identification data representing a driving parameter, steering wheel angular rate, and so on.

In step 1063, a terrain identification interval corresponding to the first driving parameter under the first terrain is determined according to the first terrain identification data of the first driving parameter.

For example, the maximum and minimum thresholds of the first terrain identification data may be obtained through multiple calculations on the first terrain identification data, and the terrain identification interval corresponding to the first driving parameter may be composed of the maximum and minimum thresholds. It should be understood that each driving parameter of each terrain corresponds to a terrain identification interval, and a set of terrain identification intervals corresponding to the terrain can be obtained by integrating the terrain identification intervals of all driving parameters of the terrain.

Fig. 5 is a flowchart illustrating a method for determining a terrain category probability according to the embodiment shown in fig. 1, and referring to fig. 5, the step 102 may include the following steps:

in step 1021, a terrain information projection matrix corresponding to each driving parameter in the first driving parameter set is obtained.

In step 1022, second terrain identification data corresponding to each driving parameter in the current terrain is determined according to each driving parameter and the terrain information projection matrix corresponding to each driving parameter.

In step 1023, the terrain classification probability is determined by the second terrain identification data corresponding to each driving parameter in the current terrain and the set of terrain identification intervals.

Fig. 6 is a flowchart illustrating a method for obtaining topographic identification data according to the embodiment shown in fig. 5, and as shown in fig. 6, the step 1022 may include the following steps.

For any one of the first set of driving parameters:

in step 10221, the peak value and the valley value included in the driving parameter are obtained to form a peak value array and a valley value array of the driving parameter.

In step 10222, a second peak average and a second valley average of the driving parameter are calculated according to the peak array and the valley array.

In step 10223, a second driving parameter matrix of the driving parameter is constructed according to the peak value array, the valley value array, the second peak value average value, and the second valley value average value.

For example, the calculation manner of steps 10221 to 10223 is similar to steps 1051 to 1053, and is not described herein again.

In step 10224, second projection information of the driving parameter under the current terrain is obtained according to the second driving parameter matrix and the terrain information projection matrix corresponding to the driving parameter.

For example, the second projection information of the driving parameter under the current terrain may be obtained through formula (7):

wherein, Y_xiSecond projection information of the ith driving parameter under the current terrain x is shown,

a projection matrix, X, of the topographic information corresponding to the 1 st driving parameter_xiAnd the second driving parameter matrix of the ith driving parameter under the current terrain x is obtained.

In step 10225, the maximum value, the minimum value, the average value, the variance and the adjusted average of the second projection information are used as the input of the terrain recognition formula (8) to obtain second terrain recognition data of the driving parameter under the current terrain.

Wherein the terrain recognition formula (8) is:

therein, Sig_xiSecond terrain identification data, Y, representing the i-th driving parameter of the first set of driving parameters acquired over terrain x_ximaxMaximum value, Y, of second projection information representing the i-th driving parameter_ximinMinimum value, SD, of second projection information representing the i-th driving parameter_yxiThe variance, mu, of the second projection information representing the i-th driving parameter_{yxi_adj}An adjusted average of second projection information representing the ith driving parameter; to illustrate the manner in which steps 10221 to 10225 are expressed, the formula can be expressed as: when Y is_ximaxTaking the maximum value and Y of the second projection information of the driving parameter_ximinTaking the minimum value and SD of the second projection information of the driving parameter_yxiThe variance and mu of the second projection information of the driving parameter are taken_{yxi_adj}When the adjusted average of the second projection information of the driving parameter is taken, Sig_1iAnd identifying data for the second terrain of the driving parameter. In addition, the function of the subscript i and the parameter m in the formula expression is the same as that in the step 1062, and is not described again.

Fig. 7 is a flowchart of a terrain category probability calculation method according to the embodiment shown in fig. 5, and the step 1023 includes the following steps as shown in fig. 7.

In step 10231, it is determined whether the second terrain identification data of any driving parameter in the current terrain belongs to any terrain identification interval corresponding to the driving parameter in different terrains, for any driving parameter in the first driving parameter group.

It should be noted that each driving parameter corresponds to a terrain identification interval in each of the different terrains, and all terrain identification intervals corresponding to all driving parameters in the same terrain form a terrain identification interval set of the terrain.

In step 10232, when the second terrain identification data of the driving parameter in the current terrain belongs to any terrain identification section corresponding to the driving parameter in different terrains, the similarity probability of the terrain corresponding to the terrain identification section to which the driving parameter belongs is determined to be 1, and the similarity probability of the terrain corresponding to other terrain identification sections except the terrain identification section to which the driving parameter belongs is determined to be 0.

For example, the similarity probability is used to indicate a degree of similarity between the driving parameter acquired under the current terrain and the same driving parameter acquired under different terrains, and the similarity probability may further reflect a degree of similarity between the current terrain and the different terrain under the driving parameter. When the similarity probability is 1, it may be determined that the current terrain and a certain terrain of the different terrains are completely consistent under the driving parameter, and when the similarity probability is 0, it may be determined that the current terrain and a certain terrain of the different terrains are completely inconsistent under the driving parameter.

In step 10233, when the second terrain identification data of the driving parameter under the current terrain does not belong to any terrain identification interval corresponding to the driving parameter under the different terrains, calculating the similarity probability of the terrain corresponding to each terrain identification interval corresponding to the second terrain identification data and the driving parameter under the different terrains according to the distance between the second terrain identification data and each terrain identification interval in the terrain identification interval set.

For example, when it is determined that the driving parameter is not within any terrain recognition interval of the set of terrain recognition intervals in the second terrain recognition data under the current terrain, first, a distance between the second terrain recognition data and each terrain recognition interval of the set of terrain recognition intervals is calculated, and in the following formula (9), the calculation process of the step 10234 is described by calculating a distance between the second terrain recognition data corresponding to the i-th driving parameter and a terrain recognition interval corresponding to the j-th terrain of the set of terrain recognition intervals, according to the second terrain recognition data corresponding to the i-th driving parameter:

wherein Dsig_xjiIndicates the ith rowThe distance between the second terrain profile identification data corresponding to the vehicle parameter and the terrain profile identification section corresponding to the jth terrain profile in the terrain profile identification section set may be Sig_xiAnd the Sig_xiThe threshold value of the terrain identification interval constructs the value space, Sig, of the second terrain data on an XY-axis plane_xXiIs Sig_xiCoordinates on the X axis, Sig_{_thrjXi}Is Sig_xiThe coordinate of the threshold value of (1), Sig, on the X-axis_xYiIs Sig_xiCoordinates on the Y-axis, Sig_{_thrjYi}Is Sig_xiIs the coordinate on the Y-axis.

In step 10234, after all the similarity probabilities corresponding to all the driving parameters included in the first driving parameter group are obtained, the average value of all the similarity probabilities corresponding to all the driving parameters of the same terrain in different terrains is used as the terrain category probability that the current terrain belongs to the terrain.

For example, after obtaining a plurality of the similarity probabilities corresponding to each driving parameter under the current terrain, an average value of the similarity probabilities corresponding to each driving parameter under the current terrain needs to be calculated, for example, the first parameter group collected under the current terrain includes: three driving parameters, namely a steering wheel angle, a steering wheel angular rate and a longitudinal acceleration, are calculated, three similar probabilities of the driving parameters, namely the steering wheel angle, the steering wheel angular rate and the longitudinal acceleration and a certain terrain under the current terrain are calculated respectively, and then the average value of the three similar probabilities can be calculated to obtain the similar probability of the current terrain and the certain terrain, namely the terrain category probability.

After the foregoing steps 1022 and 1023, the foregoing step 103 may include: and determining the terrain with the highest probability value of the terrain category as the terrain to which the current terrain belongs.

In summary, the method for identifying the terrain where the vehicle is located provided by the present disclosure can obtain a first driving parameter set of the vehicle driving on the current terrain, where the first driving parameter set includes at least one driving parameter of a steering wheel angle, a steering wheel angular velocity, a longitudinal acceleration, a lateral acceleration, and a yaw rate; determining terrain category probability that the current terrain belongs to each terrain in different terrains according to the first driving parameter group and a plurality of terrain identification interval sets respectively corresponding to different terrains; and determining the terrain to which the current terrain belongs according to the terrain class probability of the current terrain belonging to each terrain in different terrains. The terrain of the vehicle can be identified by calculating and processing vehicle components acquired during vehicle running and driving parameters related to vehicle actions and accurately classifying the terrain where the vehicle may be located.

Fig. 8 is a block diagram of an apparatus for identifying a terrain in which a vehicle is located 800 according to an embodiment of the present invention, which may be used to perform the method described in fig. 1. Referring to fig. 8, the apparatus 800 may include:

a parameter obtaining module 810, configured to obtain a first driving parameter set of a vehicle driving on a current terrain, where the first driving parameter set includes at least one driving parameter of a steering wheel angle, a steering wheel angular rate, a longitudinal acceleration, a lateral acceleration, and a yaw rate;

a probability determining module 820, configured to determine, according to the first driving parameter group and a plurality of terrain identification interval sets respectively corresponding to different terrains, a terrain category probability that the current terrain belongs to each of the different terrains;

a terrain determining module 830, configured to determine a terrain to which the current terrain belongs according to a terrain category probability that the current terrain belongs to each of the different terrains.

Further, fig. 9 is a block diagram of another device for identifying the terrain where the vehicle is located according to the embodiment shown in fig. 8, and the device 800 for identifying the terrain where the vehicle is located can be used for executing the method described in any one of fig. 2 to 4. Referring to fig. 9, the apparatus 800 may further include:

a parameter collecting module 840, configured to collect a plurality of second driving parameter sets that are different in shape and run by the vehicle, where a type of driving parameter included in each driving parameter set in the plurality of second driving parameter sets is consistent with a type of driving parameter included in the first driving parameter set;

a projection matrix determining module 850, configured to determine, according to the multiple second driving parameter sets, a terrain information projection matrix corresponding to each driving parameter;

and the section acquiring module 860 is configured to acquire, for any one of the different terrains, a terrain identification section corresponding to each driving parameter under the terrain according to the terrain information projection matrix corresponding to each driving parameter, where all terrain identification sections corresponding to all driving parameters under the terrain form a terrain identification section set corresponding to the terrain.

Further, the projection matrix determination module 850 is configured to:

for any one of the driving parameters acquired on any one of the different aforementioned terrains:

acquiring a peak value and a valley value included by the driving parameter to form a peak value array and a valley value array of the driving parameter;

calculating a first peak value average value and a first valley value average value of the driving parameter according to the peak value array and the valley value array;

constructing a first driving parameter matrix of the driving parameters according to the peak value array, the valley value array, the first peak value average value and the first valley value average value;

acquiring a discrete matrix of the first driving parameter matrix according to the first peak average value, the first valley average value and the first driving parameter matrix;

after obtaining the discrete matrix corresponding to the driving parameter under each terrain, determining the terrain information projection matrix corresponding to the driving parameter according to all the obtained discrete matrices.

Further, the first terrain is any one of the different terrains, the first driving parameter is any one of the second driving parameter sets, and the section acquiring module 860 is configured to:

determining first projection information of the first driving parameter under the first terrain according to a terrain information projection matrix corresponding to the first driving parameter, wherein the first projection information is a product of a transpose matrix of the terrain information projection matrix of the first driving parameter and a first driving parameter matrix corresponding to the first driving parameter;

taking the maximum value, the minimum value, the average value, the variance and the adjustment average of the first projection information as the input of a terrain identification formula to obtain first terrain identification data of the first driving parameter, wherein the terrain identification formula is as follows:

therein, Sig_1iFirst terrain identification data, Y, representing the i-th driving parameter of a second set of driving parameters acquired over terrain 1_1imaxMaximum value, Y, of first projection information representing the i-th driving parameter_1iminMinimum value, SD, of the first projection information representing the i-th driving parameter_y1iThe variance, mu, of the first projection information representing the i-th driving parameter_{y1i_adj}An adjusted average of the first projection information representing the ith driving parameter; when Y is_1imaxTaking the maximum value and Y of the first projection information of the first driving parameter_1iminTaking the minimum value and SD of the first projection information of the first driving parameter_y1iThe variance and mu of the first projection information of the first driving parameter are taken_{y1i_adj}When the adjusted average of the first projection information of the first driving parameter is taken, Sig_1iFirst terrain identification data for the first driving parameter;

and determining a terrain identification interval corresponding to the first driving parameter under the first terrain according to the first terrain identification data of the first driving parameter.

Optionally, fig. 10 is a block diagram of a probability determination module according to the embodiment shown in fig. 8, where the probability determination module 820 may be used to perform the method described in any one of fig. 4 to 7. Referring to fig. 10, the probability determination module 820 includes:

a projection matrix obtaining submodule 821, configured to obtain a terrain information projection matrix corresponding to each driving parameter in the first driving parameter set;

the identification data determining submodule 822 is configured to determine, according to each driving parameter and the terrain information projection matrix corresponding to each driving parameter, second terrain identification data corresponding to each driving parameter in the current terrain;

the probability determination submodule 823 is configured to determine the terrain classification probability according to the second terrain identification data corresponding to each driving parameter in the current terrain and the set of the plurality of terrain identification intervals.

Further, the identification data determination submodule 822 is configured to:

for any one of the first set of driving parameters:

acquiring a peak value and a valley value included by the driving parameter to form a peak value array and a valley value array of the driving parameter;

calculating a second peak value average value and a second valley value average value of the driving parameter according to the peak value array and the valley value array;

constructing a second driving parameter matrix of the driving parameters according to the peak value array, the valley value array, the second peak value average value and the second valley value average value;

acquiring second projection information of the driving parameter under the current terrain according to the second driving parameter matrix and the terrain information projection matrix corresponding to the driving parameter;

taking the maximum value, the minimum value, the average value, the variance and the adjusted average value of the second projection information as the input of a terrain identification formula to obtain second terrain identification data of the driving parameter under the current terrain, wherein the terrain identification formula is as follows:

therein, Sig_xiSecond terrain identification data, Y, representing the i-th driving parameter of the first set of driving parameters acquired over terrain x_ximaxMaximum value, Y, of second projection information representing the i-th driving parameter_ximinMinimum value, SD, of second projection information representing the i-th driving parameter_yxiThe variance, mu, of the second projection information representing the i-th driving parameter_{yxi_adj}An adjusted average of second projection information representing the ith driving parameter; when Y is_ximaxTaking the maximum value and Y of the second projection information of the driving parameter_ximinTaking the minimum value and SD of the second projection information of the driving parameter_yxiThe variance and mu of the second projection information of the driving parameter are taken_{yxi_adj}When the adjusted average of the second projection information of the driving parameter is taken, Sig_1iAnd identifying data for the second terrain of the driving parameter.

Further, each driving parameter corresponds to a terrain identification interval under each of the different terrains, all terrain identification intervals corresponding to all driving parameters under the same terrain form a terrain identification interval set of the terrain, and the probability determination submodule 823 is configured to:

for any driving parameter in the first driving parameter group, determining whether second terrain identification data of the driving parameter in the current terrain belongs to any terrain identification section respectively corresponding to the driving parameter in different terrains;

when the second terrain identification data of the driving parameter under the current terrain belongs to any terrain identification section corresponding to the driving parameter under different terrains, the similarity probability of the terrain corresponding to the terrain identification section is determined to be 1, and the similarity probability of the terrain corresponding to other terrain identification sections except the terrain identification section is determined to be 0; alternatively, the first and second electrodes may be,

when the second terrain identification data of the driving parameter under the current terrain does not belong to any terrain identification interval respectively corresponding to the driving parameter under different terrains, calculating the similarity probability of the terrain corresponding to each terrain identification interval respectively corresponding to the second terrain identification data and the driving parameter under different terrains according to the distance between the second terrain identification data and each terrain identification interval in the terrain identification interval set;

and after all the similar probabilities corresponding to all the driving parameters included in the first driving parameter group are obtained, taking the average value of all the similar probabilities corresponding to all the driving parameters of the same terrain in the different terrains as the terrain type probability of the current terrain.

Further, the terrain determining module 830 is configured to:

and determining the terrain with the highest probability value of the terrain category as the terrain to which the current terrain belongs.

In summary, the identification apparatus for a terrain where a vehicle is located provided by the present disclosure can obtain a first driving parameter set of the vehicle driving on the current terrain, where the first driving parameter set includes at least one driving parameter of a steering wheel angle, a steering wheel angular velocity, a longitudinal acceleration, a lateral acceleration, and a yaw rate; determining terrain category probability that the current terrain belongs to each terrain in different terrains according to the first driving parameter group and a plurality of terrain identification interval sets respectively corresponding to different terrains; and determining the terrain to which the current terrain belongs according to the terrain class probability of the current terrain belonging to each terrain in different terrains. The terrain where the vehicle is located can be identified by calculating and processing vehicle components and driving parameters related to vehicle actions collected during vehicle driving and classifying the terrain where the vehicle may be located.

The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.

Claims (8)

1. A method of identifying a terrain in which a vehicle is located, the method comprising:

acquiring a first driving parameter group of a vehicle running on the current terrain, wherein the first driving parameter group comprises at least one driving parameter of a steering wheel corner, a steering wheel angular rate, a longitudinal acceleration, a lateral acceleration and a yaw rate;

determining terrain category probability that the current terrain belongs to each terrain in different terrains according to the first driving parameter group and a plurality of terrain identification interval sets respectively corresponding to the different terrains;

determining a terrain to which the current terrain belongs based on a terrain category probability that the current terrain belongs to each of the different terrains,

determining a terrain category probability that the current terrain belongs to each of the different terrains according to the first set of driving parameters and a plurality of terrain identification interval sets respectively corresponding to the different terrains, comprising:

acquiring a terrain information projection matrix corresponding to each driving parameter in the first driving parameter group;

determining second terrain identification data corresponding to each driving parameter under the current terrain according to each driving parameter and the terrain information projection matrix corresponding to each driving parameter;

determining the terrain category probability according to the second terrain identification data corresponding to each driving parameter under the current terrain and the plurality of terrain identification interval sets,

the determining, according to the each driving parameter and the terrain information projection matrix corresponding to the each driving parameter, second terrain identification data corresponding to the each driving parameter under the current terrain includes:

for any one of the first set of driving parameters:

acquiring a peak value and a valley value included by the driving parameter to form a peak value array and a valley value array of the driving parameter;

calculating a second peak value average value and a second valley value average value of the driving parameter according to the peak value array and the valley value array;

constructing a second driving parameter matrix of the driving parameter according to the peak value array, the valley value array, the second peak value average value and the second valley value average value;

acquiring second projection information of the driving parameters under the current terrain according to the second driving parameter matrix and a terrain information projection matrix corresponding to the driving parameters;

taking the maximum value, the minimum value, the average value, the variance and the adjusted average value of the second projection information as the input of a terrain identification formula to obtain second terrain identification data of the driving parameter under the current terrain, wherein the terrain identification formula is as follows:

therein, Sig_xiSecond terrain identification data, Y, representing the i-th driving parameter of the first set of driving parameters acquired over terrain x_ximaxMaximum value, Y, of second projection information representing the ith driving parameter_ximinMinimum value, SD, of second projection information representing the ith driving parameter_yxiA variance, mu, of second projection information representing the ith driving parameter_{yxi_adj}An adjusted average of second projection information representing the ith driving parameter; when Y is_ximaxTaking the maximum value and Y of the second projection information of the driving parameter_ximinTaking the minimum value and SD of the second projection information of the driving parameter_yxiThe variance and mu of the second projection information of the driving parameter are taken_{yxi_adj}When the adjusted average of the second projection information of the driving parameter is taken, Sig_1iAnd identifying data for the second terrain of the driving parameter.

2. The method of claim 1, wherein prior to obtaining the first set of driving parameters for the vehicle to travel over the current terrain, the method further comprises:

collecting a plurality of groups of second driving parameter groups which are driven by vehicles on different shapes respectively, wherein the types of driving parameters contained in each group of driving parameter groups in the plurality of groups of second driving parameter groups are consistent with the types of driving parameters contained in the first driving parameter group;

determining a terrain information projection matrix corresponding to each driving parameter according to the plurality of groups of second driving parameter groups;

and aiming at any terrain in different terrains, acquiring a terrain identification interval corresponding to each driving parameter under the terrain according to the terrain information projection matrix corresponding to each driving parameter, wherein all terrain identification intervals corresponding to all driving parameters under the terrain form a terrain identification interval set corresponding to the terrain.

3. The method according to claim 2, wherein the determining a terrain information projection matrix corresponding to each driving parameter according to the plurality of sets of second driving parameters comprises:

for any one of the driving parameters acquired on any one of the different terrains:

acquiring a peak value and a valley value included by the driving parameter to form a peak value array and a valley value array of the driving parameter;

calculating a first peak value average value and a first valley value average value of the driving parameter according to the peak value array and the valley value array;

constructing a first driving parameter matrix of the driving parameter according to the peak value array, the valley value array, the first peak value average value and the first valley value average value;

acquiring a discrete matrix of the first driving parameter matrix according to the first peak average value, the first valley average value and the first driving parameter matrix;

after obtaining the discrete matrix corresponding to the driving parameter under each terrain, determining the terrain information projection matrix corresponding to the driving parameter according to all the obtained discrete matrices.

4. The method according to claim 3, wherein a first terrain is any one of the different terrains, a first driving parameter is any one of the second driving parameter sets, and a terrain identification zone corresponding to the first driving parameter under the first terrain is obtained according to a terrain information projection matrix corresponding to the first driving parameter, comprising:

determining first projection information of the first driving parameter under the first terrain according to a terrain information projection matrix corresponding to the first driving parameter, wherein the first projection information is a product of a transposed matrix of the terrain information projection matrix of the first driving parameter and a first driving parameter matrix corresponding to the first driving parameter;

taking the maximum value, the minimum value, the average value, the variance and the adjustment average of the first projection information as the input of a terrain identification formula to obtain first terrain identification data of the first driving parameter, wherein the terrain identification formula is as follows:

therein, Sig_1iFirst terrain identification data, Y, representing the i-th driving parameter of a second set of driving parameters acquired over terrain 1_1imaxMaximum value, Y, of first projection information representing the ith driving parameter_1iminMinimum value, SD, of first projection information representing the ith driving parameter_y1iA variance, mu, of first projection information representing the ith driving parameter_{y1i_adj}An adjusted average of first projection information representing the ith driving parameter; when Y is_1imaxTaking the maximum value and Y of the first projection information of the first driving parameter_1iminTaking the minimum value and SD of the first projection information of the first driving parameter_y1iTaking the variance and mu of the first projection information of the first driving parameter_y1i_{_adj}Obtaining first projection information of the first driving parameterWhen adjusting the mean, Sig_1iFirst terrain identification data for said first driving parameter;

and determining a terrain identification interval corresponding to the first driving parameter under the first terrain according to the first terrain identification data of the first driving parameter.

5. The method according to claim 1, wherein each driving parameter corresponds to a terrain identification interval in each of the different terrains, all terrain identification intervals corresponding to all driving parameters in the same terrain constitute a set of terrain identification intervals for the terrain,

determining the terrain category probability through the second terrain identification data corresponding to each driving parameter under the current terrain and the plurality of terrain identification interval sets, including:

for any driving parameter in the first driving parameter group, determining whether second terrain identification data of the driving parameter under the current terrain belongs to any terrain identification interval corresponding to the driving parameter under different terrains;

when the second terrain identification data of the driving parameter under the current terrain belongs to any terrain identification section corresponding to the driving parameter under different terrains, determining that the similarity probability of the terrain corresponding to the terrain identification section to which the driving parameter belongs is 1, and determining that the similarity probability of the terrain corresponding to other terrain identification sections except the terrain identification section to which the driving parameter belongs is 0; alternatively, the first and second electrodes may be,

when the second terrain identification data of the driving parameter under the current terrain does not belong to any terrain identification interval respectively corresponding to the driving parameter under different terrains, calculating the similarity probability of the terrain corresponding to each terrain identification interval respectively corresponding to the second terrain identification data and the driving parameter under different terrains according to the distance between the second terrain identification data and each terrain identification interval in the terrain identification interval set;

and after all the similar probabilities corresponding to all the driving parameters included in the first driving parameter group are obtained, taking the average value of all the similar probabilities corresponding to all the driving parameters of the same terrain in different terrains as the terrain class probability of the current terrain.

6. The method of claim 5, wherein determining the terrain to which the current terrain belongs based on terrain category probabilities of the current terrain belonging to each of the different terrains comprises:

and determining the terrain with the maximum terrain probability value of the terrain category as the terrain to which the current terrain belongs.

7. An apparatus for identifying the terrain in which a vehicle is located, the apparatus comprising:

the system comprises a parameter acquisition module, a data processing module and a data processing module, wherein the parameter acquisition module is used for acquiring a first driving parameter group of a vehicle driving on the current terrain, and the first driving parameter group comprises at least one driving parameter of a steering wheel corner, a steering wheel angular rate, a longitudinal acceleration, a lateral acceleration and a yaw rate;

a probability determination module, configured to determine, according to the first driving parameter set and a plurality of terrain identification interval sets respectively corresponding to different terrains, a terrain category probability that the current terrain belongs to each of the different terrains;

a terrain determination module for determining a terrain to which the current terrain belongs based on a terrain category probability that the current terrain belongs to each of the different terrains,

the probability determination module comprises:

the projection matrix acquisition submodule is used for acquiring a terrain information projection matrix corresponding to each driving parameter in the first driving parameter group;

the identification data determining submodule is used for determining second terrain identification data corresponding to each driving parameter under the current terrain according to each driving parameter and the terrain information projection matrix corresponding to each driving parameter;

a probability determination submodule for determining the terrain category probability according to the second terrain identification data corresponding to each driving parameter under the current terrain and the plurality of terrain identification interval sets,

the identification data determination submodule is configured to:

for any one of the first set of driving parameters:

acquiring a peak value and a valley value included by the driving parameter to form a peak value array and a valley value array of the driving parameter;

calculating a second peak value average value and a second valley value average value of the driving parameter according to the peak value array and the valley value array;

constructing a second driving parameter matrix of the driving parameter according to the peak value array, the valley value array, the second peak value average value and the second valley value average value;

acquiring second projection information of the driving parameters under the current terrain according to the second driving parameter matrix and a terrain information projection matrix corresponding to the driving parameters;

taking the maximum value, the minimum value, the average value, the variance and the adjusted average value of the second projection information as the input of a terrain identification formula to obtain second terrain identification data of the driving parameter under the current terrain, wherein the terrain identification formula is as follows:

therein, Sig_xiSecond terrain identification data, Y, representing the i-th driving parameter of the first set of driving parameters acquired over terrain x_ximaxMaximum value, Y, of second projection information representing the ith driving parameter_ximinMinimum value, SD, of second projection information representing the ith driving parameter_yxiA variance, mu, of second projection information representing the ith driving parameter_{yxi_adj}An adjusted average of second projection information representing the ith driving parameter; when Y is_ximaxTaking the maximum value and Y of the second projection information of the driving parameter_ximinTaking the minimum value and SD of the second projection information of the driving parameter_yxiThe variance and mu of the second projection information of the driving parameter are taken_{yxi_adj}When the adjusted average of the second projection information of the driving parameter is taken, Sig_1iAnd identifying data for the second terrain of the driving parameter.

8. A vehicle comprising an apparatus for identifying the terrain in which the vehicle of claim 7 is located.

Images