CN116817955A - Vehicle path planning method, device, electronic equipment and storage medium - Google Patents
Vehicle path planning method, device, electronic equipment and storage medium Download PDFInfo
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Abstract
The disclosure provides a vehicle path planning method, a vehicle path planning device, electronic equipment and a storage medium. The vehicle path planning method of the embodiment of the disclosure comprises the following steps: acquiring wheelbase, current state information and target state information of a vehicle; and generating a planned path of the vehicle according to a preset heuristic path length threshold value, current state information and target state information of the vehicle, wherein the positions of all track points on the planned path are represented by coordinates in a Cartesian coordinate system. The method and the device can directly complete path planning under the Cartesian coordinate system without coordinate conversion, meanwhile, the current steering wheel angle change rate of the vehicle is considered in the path planning, and the safety, the comfort and the stability of the path planning under a high-speed scene are improved.
Description
Technical Field
The disclosure relates to a vehicle path planning method, a vehicle path planning device, electronic equipment and a storage medium.
Background
With the development of automatic driving technology, the automatic driving capability of a high-speed scene has become an advanced embodiment of the vehicle automatic driving technology. The path planning is a key part of the automatic driving technology, and planning of a safe and comfortable path is the basis of stable operation of an automatic driving system.
In the prior art, path planning of a high-speed scene is generally completed under Frenet coordinates, on one hand, path planning under the Frenet coordinates is required to be performed with mutual conversion between Cartesian coordinates and Frenet coordinates, and calculation power consumption is caused; on the other hand, the current steering wheel angle change rate of the vehicle cannot be considered in the path planning under the Frenet coordinate. This can result in a discontinuous planned path start from the current rate of change of steering wheel angle, thereby burdening the lateral control of the vehicle while reducing the comfort and stability of the vehicle.
Disclosure of Invention
In order to solve at least one of the above technical problems, the present disclosure provides a vehicle path planning method, a device, an electronic apparatus, and a storage medium.
According to a first aspect of the present disclosure, there is provided a vehicle path planning method, comprising:
acquiring wheelbase, current state information and target state information of a vehicle, wherein the current state information comprises Cartesian coordinate system coordinates of a current position, a current course angle, a current running speed, a current steering wheel angle and a current steering wheel rotating speed; the target state information comprises Cartesian coordinate system coordinates of a target end point position, a course angle of the target end point and road curvature of the target end point;
And generating a planned path of the vehicle according to a preset heuristic path length threshold value, current state information and target state information of the vehicle, wherein the positions of all track points on the planned path are represented by coordinates in a Cartesian coordinate system.
In some embodiments of the present disclosure, the vehicle path planning method further includes: respectively constructing seven-degree polynomials aiming at all coordinate axes of a Cartesian coordinate system, wherein the seven-degree polynomials take heuristic path length as independent variables and coordinate of the corresponding coordinate axes as function values; the generating a planned path of the vehicle according to the preset heuristic path length threshold value, the current state information and the target state information of the vehicle comprises the following steps: and determining coefficients of seven-degree polynomials based on the heuristic path length threshold value, the current state information of the vehicle and the target state information, and performing polynomial fitting to determine coordinates of corresponding coordinate axes of the track points on the planned path in a Cartesian coordinate system.
In some embodiments of the disclosure, the cartesian coordinate system is a two-dimensional rectangular coordinate system parallel to the ground, and coordinate axes of the cartesian coordinate system include an x-axis and a y-axis; seven-degree polynomials are respectively constructed for each coordinate axis of a Cartesian coordinate system, and the seven-degree polynomials comprise: a first polynomial for calculating the X-axis coordinates of a Cartesian coordinate system of each track point in a planning path and a second polynomial for calculating the Y-axis coordinates of a Cartesian coordinate system of each track point in the planning path are constructed, wherein the first polynomial and the second polynomial are seven-degree polynomials and take heuristic path length as independent variables.
In some embodiments of the disclosure, the coefficients of the seven-degree polynomial are determined according to the coordinates of the cartesian coordinate system of the path start point and its derivative with respect to the heuristic path length, the coordinates of the cartesian coordinate system of the path end point and its derivative with respect to the heuristic path length, and the heuristic path length threshold; the Cartesian coordinate system of the path starting point corresponds to the coordinate axis coordinate and the derivative thereof about the inspired path length are determined according to the wheelbase of the vehicle, the Cartesian coordinate system of the current position of the vehicle corresponds to the coordinate axis coordinate, the current course angle of the vehicle, the current running speed of the vehicle, the current steering wheel angle of the vehicle and the current steering wheel rotating speed of the vehicle; and the Cartesian coordinate system of the path end point corresponds to the coordinate axis coordinate and the derivative of the Cartesian coordinate system of the path end point relative to the heuristic path length is determined according to the Cartesian coordinate system of the target end point corresponds to the coordinate axis coordinate, the course angle and the road curvature.
In some embodiments of the present disclosure, further comprising: determining the current curvature and the curvature change rate of the vehicle according to the wheelbase of the vehicle, the current steering wheel angle and the current steering wheel rotating speed; the Cartesian coordinate system of the path starting point corresponds to coordinate axis coordinates and derivatives thereof related to the heuristic path length are determined according to the wheelbase of the vehicle, the Cartesian coordinate system of the current position of the vehicle corresponds to coordinate axis coordinates, the current course angle of the vehicle, the current running speed of the vehicle, the current curvature of the vehicle and the curvature change rate.
In some embodiments of the present disclosure, the target state information is obtained by:
acquiring reference path information of a vehicle, wherein the reference path information comprises Cartesian coordinate system coordinates, course angles and road curvatures of all track points on a reference path; and searching a track point with the path length between track points closest to the current position of the vehicle as the heuristic path length threshold on the reference path as a target destination of the vehicle, and extracting information of the target destination from the reference path information as target state information of the vehicle.
According to a second aspect of the present disclosure, there is provided a vehicle path planning apparatus comprising:
the information acquisition unit is used for acquiring the wheelbase, the current state information and the target state information of the vehicle, wherein the current state information comprises Cartesian coordinate system coordinates of a current position, a current course angle, a current running speed, a current steering wheel rotation angle and a current steering wheel rotation speed; the target state information comprises Cartesian coordinate system coordinates of a target end point position, a course angle of the target end point and road curvature of the target end point;
the path generation unit is used for generating a planning path of the vehicle according to a preset heuristic path length threshold value, current state information of the vehicle and target state information, and the positions of all track points on the planning path are represented by coordinates in a Cartesian coordinate system.
According to a third aspect of the present disclosure, there is provided an electronic device comprising:
a memory storing execution instructions; the method comprises the steps of,
and the processor executes the execution instructions stored in the memory, so that the processor executes the vehicle path planning method.
According to a fourth aspect of the present disclosure, there is provided a readable storage medium having stored therein execution instructions which when executed by a processor are for implementing the vehicle path planning method described above.
The vehicle path planning of the embodiment of the disclosure is directly completed under a Cartesian coordinate system, coordinate conversion is not needed, and the vehicle path planning method is small in calculation force consumption, simple, reliable and smooth and easy to realize. Meanwhile, the current steering wheel angle change rate of the vehicle is added in path planning, so that the safety, comfort and stability of a planned path can be effectively improved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the disclosure and are incorporated in and constitute a part of this specification, illustrate exemplary embodiments of the disclosure and together with the description serve to explain the principles of the disclosure.
Fig. 1 is a flow diagram of a vehicle path planning method according to some embodiments of the present disclosure.
Fig. 2 is a schematic diagram of heuristic path-length selection in accordance with some embodiments of the present disclosure.
Fig. 3 is a schematic diagram of heuristic path length increments in a planned path according to some embodiments of the present disclosure.
Fig. 4 is a schematic diagram of a planned path curvature relationship according to some embodiments of the present disclosure.
Fig. 5 is a schematic illustration of an incremental relationship of heuristic path lengths to planned path lengths according to some embodiments of the present disclosure.
Fig. 6 is a schematic illustration of a current driving lane of a vehicle and its center line according to some embodiments of the present disclosure.
Fig. 7 is a schematic diagram of a planned path visualization in a lane keeping scenario in a high-speed driving state when the heuristic path length threshold H is taken 80m, according to some embodiments of the present disclosure.
Fig. 8 is a schematic diagram of a planned path visualization in a lane keeping scenario in a high-speed driving state when the heuristic path length threshold H is taken 50m, according to some embodiments of the present disclosure.
Fig. 9 is a schematic illustration of a planned path visualization in a lane keeping scenario in a high-speed driving state when the heuristic path length threshold H is taken 120m, according to some embodiments of the present disclosure.
Fig. 10 is a schematic diagram of a planned path visualization in a lane-change scenario in a high-speed driving state when the heuristic path length threshold H is taken 80m, according to some embodiments of the present disclosure.
Fig. 11 is a schematic illustration of a planned path visualization in a lane-change scenario in a high-speed driving state when the heuristic path length threshold H is taken at 50m, according to some embodiments of the present disclosure.
Fig. 12 is a schematic diagram of a planned path visualization in a lane-change scenario in a high-speed driving state when the heuristic path length threshold H is taken at 120m, according to some embodiments of the present disclosure.
Fig. 13 is a block schematic diagram of a vehicle path planning apparatus employing a hardware implementation of a processing system according to one embodiment of the present disclosure.
Detailed Description
The present disclosure is described in further detail below with reference to the drawings and the embodiments. It is to be understood that the specific embodiments described herein are merely illustrative of the relevant content and not limiting of the present disclosure. It should be further noted that, for convenience of description, only a portion relevant to the present disclosure is shown in the drawings.
In addition, embodiments of the present disclosure and features of the embodiments may be combined with each other without conflict. The technical aspects of the present disclosure will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.
Unless otherwise indicated, the exemplary implementations/embodiments shown are to be understood as providing exemplary features of various details of some ways in which the technical concepts of the present disclosure may be practiced. Thus, unless otherwise indicated, features of the various implementations/embodiments may be additionally combined, separated, interchanged, and/or rearranged without departing from the technical concepts of the present disclosure.
The use of cross-hatching and/or shading in the drawings is typically used to clarify the boundaries between adjacent components. As such, the presence or absence of cross-hatching or shading does not convey or represent any preference or requirement for a particular material, material property, dimension, proportion, commonality between illustrated components, and/or any other characteristic, attribute, property, etc. of a component, unless indicated. In addition, in the drawings, the size and relative sizes of elements may be exaggerated for clarity and/or descriptive purposes. While the exemplary embodiments may be variously implemented, the specific process sequences may be performed in a different order than that described. For example, two consecutively described processes may be performed substantially simultaneously or in reverse order from that described. Moreover, like reference numerals designate like parts.
When an element is referred to as being "on" or "over", "connected to" or "coupled to" another element, it can be directly on, connected or coupled to the other element or intervening elements may be present. However, when an element is referred to as being "directly on," "directly connected to," or "directly coupled to" another element, there are no intervening elements present. For this reason, the term "connected" may refer to physical connections, electrical connections, and the like, with or without intermediate components.
The terminology used herein is for the purpose of describing particular embodiments and is not intended to be limiting. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. Furthermore, when the terms "comprises" and/or "comprising," and variations thereof, are used in the present specification, the presence of stated features, integers, steps, operations, elements, components, and/or groups thereof is described, but the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof is not precluded. It is also noted that, as used herein, the terms "substantially," "about," and other similar terms are used as approximation terms and not as degree terms, and as such, are used to explain the inherent deviations of measured, calculated, and/or provided values that would be recognized by one of ordinary skill in the art.
The path planning referred to in this disclosure is referred to as local path planning.
Fig. 1 illustrates a flow diagram of a vehicle path planning method of some embodiments of the present disclosure. As shown in fig. 1, a vehicle path planning method according to an embodiment of the present disclosure may include the steps of:
step S102, acquiring wheelbase, current state information and target state information of a vehicle;
the current state information may include, but is not limited to, cartesian coordinates of the current location, the current heading angle, the current travel speed, the current steering wheel angle, the current steering wheel speed.
The target state information may include, but is not limited to, cartesian coordinate system coordinates of the target end point position, heading angle of the target end point, road curvature of the target end point.
In the embodiment of the present disclosure, the position of the vehicle is based on the center of the rear axle of the vehicle, that is, the position of the center of the rear axle of the vehicle is taken as the position of the vehicle.
Step S104, a planned path of the vehicle is generated according to a preset heuristic path length threshold value, current state information of the vehicle and target state information.
The positions of all track points on the planned path of the vehicle are represented by coordinates in a Cartesian coordinate system.
The vehicle path planning method can be directly completed under a Cartesian coordinate system, coordinate conversion is not needed, calculation force consumption is low, and the vehicle path planning efficiency can be improved while hardware cost is reduced so as to meet real-time requirements of high-speed scenes. Meanwhile, the factors such as the current steering wheel angle and the steering wheel rotating speed of the vehicle are added in the vehicle path planning, so that the safety, the comfort and the stability of the vehicle planned path can be improved. In addition, the starting point of the path planning in the embodiment of the disclosure is consistent with the current state of the vehicle, the end point of the path planning accords with the actual condition of high-speed running of the vehicle, and the method has high-order continuity, little dependence on a reference path, low requirement on the continuity of the reference path and no need of smooth curvature of the reference path.
In some embodiments, before step S104 or step S102, the method may further include: seven-degree polynomials are respectively constructed for all coordinate axes of a Cartesian coordinate system, wherein the seven-degree polynomials take heuristic path length as independent variables and the coordinates of the corresponding coordinate axes as function values. In step S104, coefficients of each of the seven polynomials may be determined based on the heuristic path length threshold, the vehicle current state information, and the target state information, and polynomial fitting may be performed to determine coordinates of the track points on the planned path on corresponding coordinate axes in the cartesian coordinate system.
For example, the cartesian coordinate system may be a two-dimensional rectangular coordinate system parallel to the ground, the coordinate axes of the cartesian coordinate system including an x-axis and a y-axis. At this time, seven-degree polynomials are respectively constructed for each coordinate axis of the cartesian coordinate system, which may include: a first polynomial for calculating the X-axis coordinates of a Cartesian coordinate system of each track point in the planning path and a second polynomial for calculating the Y-axis coordinates of a Cartesian coordinate system of each track point in the planning path are constructed, wherein the first polynomial and the second polynomial are seven-degree polynomials and take heuristic path length as independent variables.
The embodiment of the disclosure adopts a seven-degree polynomial, can effectively reduce the influence of polynomial distortion on a planned path, and improves the safety and the comfort of the planned path while ensuring the precision and the accuracy of the planned path. It should be noted that, the polynomial in the specific application may be freely selected in combination with various factors such as scene, precision requirement, etc. For example, a polynomial or the like higher than seven degrees may be selected to be adopted as needed to improve the accuracy of planning the path.
Taking the foregoing cartesian coordinate system including the x-axis and the y-axis as an example, the expression of the first polynomial x (h) and the second polynomial y (h) using the seven degree polynomials is shown in the following formula (1):
Wherein x (H) represents a Cartesian coordinate system x-axis coordinate of a track point with a heuristic path length H on a planned path, y (H) represents a Cartesian coordinate system y-axis coordinate of a track point with a heuristic path length H on the planned path, a track point with H equal to 0 is a path starting point, a track point with H equal to H is a path ending point, H represents a preset heuristic path length threshold value, and a 0 、a 1 、a 2 、a 3 、a 4 、a 5、 a 6、 a 7 Coefficients representing a first polynomial, b 0 、b 1 、b 2 、b 3 、b 4 、b 5 、b 6 、b 7 Coefficients representing the second polynomial.
In a specific application, the heuristic path-length threshold H may take a calibrated value. The heuristic path length threshold H may be calibrated according to the vehicle speed, or may be calibrated to be a fixed value. For example, different values can be sampled for H, and after the planned paths obtained by the values are compared, a planned path with smaller cost is selected as a path planning result, and meanwhile, a sampling value corresponding to the planned path can be used as a set value of the heuristic path length threshold H. For example, H may be sampled to 50 meters, 80 meters, and 120 meters, to obtain three planned paths corresponding to the three sampled values, compare cost functions of the three planned paths, and select a planned path with a smaller cost function value as a result of path planning and output.
Fig. 2 shows a selected example diagram of a heuristic path length h on a planned path. In fig. 2, the planned starting point refers to the path starting point of the planned path, and the planned ending point refers to the path ending point of the planned path. As shown in fig. 2, the heuristic path length h may take discrete values in the interval [0, h ], where the discrete values correspond to a plurality of track points that are discretely distributed on the planned path, and the interval lengths of adjacent track points on the planned path on the reference path are equal. In general, the finer the granularity of choice of h, the higher the accuracy of path planning. For example, when H is set to 120 meters, the interval length of the adjacent track points on the planned path on the reference path is set to 20 meters, and at this time, H may take the following values in the interval [0, 120 ]: 0. 20, 40, … …, 120. For another example, when H is set to 80 meters, the interval length of the adjacent track points on the planned path on the reference path is set to 10 meters, and at this time, H may take the following values in the interval [0, 80 ]: 0. 10, 20, 30, 40, 50, 60, 70, 80.
In step S104, the coefficients of the seven-degree polynomial are determined according to the coordinates of the coordinate axes corresponding to the cartesian coordinate system of the path start point and the derivative thereof with respect to the heuristic path length, the coordinates of the coordinate axes corresponding to the cartesian coordinate system of the path end point and the derivative thereof with respect to the heuristic path length, and the heuristic path length threshold; the Cartesian coordinate system of the path starting point corresponds to the coordinate axis coordinate, and the derivative of the path starting point relative to the heuristic path length is determined according to the wheelbase of the vehicle, the Cartesian coordinate system of the current position of the vehicle corresponds to the coordinate axis coordinate, the current course angle of the vehicle, the current running speed of the vehicle, the current steering wheel angle of the vehicle and the current steering wheel rotating speed of the vehicle; the Cartesian coordinate system of the path end point corresponds to the coordinate axis coordinate, and the derivative of the path end point with respect to the heuristic path length is determined according to the Cartesian coordinate system of the target end point corresponds to the coordinate axis coordinate, the heading angle and the road curvature.
In some embodiments, in step S104, the current curvature and the curvature change rate of the vehicle may be determined in advance according to the wheelbase of the vehicle, the current steering wheel angle, and the current steering wheel speed. Then, the Cartesian coordinate system of the path start point corresponds to the coordinate axis coordinate and the derivative thereof about the inspired path length are determined according to the wheelbase of the vehicle, the Cartesian coordinate system of the current position of the vehicle corresponds to the coordinate axis coordinate, the current course angle of the vehicle, the current running speed of the vehicle, the current curvature of the vehicle and the curvature change rate.
Taking the foregoing cartesian coordinate system including the x-axis and the y-axis as an example, in step S104, the coefficients of the first polynomial may be determined according to the cartesian coordinate system of the start point of the path and its derivative with respect to the heuristic path length, the cartesian coordinate system of the end point of the path and its derivative with respect to the heuristic path length, and the heuristic path length threshold. The Cartesian coordinate system x-axis coordinate of the path starting point and the derivative thereof about the heuristic path length can be determined according to the wheelbase of the vehicle, the Cartesian coordinate system x-axis coordinate of the current position of the vehicle, the current course angle of the vehicle, the current running speed of the vehicle, the current steering wheel angle of the vehicle and the current steering wheel rotating speed of the vehicle; the Cartesian coordinate system x-axis coordinates of the path end point and its derivatives with respect to the heuristic path length may be determined from the Cartesian coordinate system x-axis coordinates of the target end point, the heading angle of the target end point, and the road curvature of the target end point. The coefficients of the second polynomial may be determined from the cartesian coordinate system y-axis coordinates of the path start point and its derivative with respect to the heuristic path length, the cartesian coordinate system y-axis coordinates of the path end point and its derivative with respect to the heuristic path length, and the heuristic path length threshold. The cartesian coordinate system y-axis coordinate of the path starting point and the derivative thereof about the heuristic path length can be determined according to the cartesian coordinate system y-axis coordinate of the current position of the vehicle, the wheelbase of the vehicle, the current course angle of the vehicle, the current running speed of the vehicle, the current steering wheel angle of the vehicle and the current steering wheel rotating speed of the vehicle; the derivative of the cartesian y-axis coordinate of the path end point with respect to the heuristic path length may be determined from the cartesian y-axis coordinate of the target end point, the heading angle of the target end point, and the road curvature of the target end point.
Taking the aforementioned cartesian coordinate system including the x-axis and the y-axis as an example, it is assumed that the polynomial shown in the formula (1) is employed, at this time, 8 coefficients of the first polynomial x (h) may be determined by the following formula (2), and 8 coefficients of the first polynomial y (h) may be determined by the following formula (3).
Wherein H represents a preset heuristic path length threshold value, x 0 Cartesian coordinate system x-axis coordinates, x, representing the start of a planned path ′ 0 Represents x 0 Regarding the first derivative of the heuristic path length h, x ′ 0 ′ Represents x 0 Regarding the second derivative of the heuristic path length h, x ′ 0 "means x 0 Regarding the third derivative of the heuristic path length h, x 1 Cartesian coordinate system x-axis coordinates, x, representing the planned path end position ′ 1 Represents x 1 Regarding the first derivative of the heuristic path length h, x ′ 1 ′ Represents x 1 Regarding the second derivative of the heuristic path length h, x ′ 1 "means x 1 With respect to the third derivative of the heuristic path length h, y 0 Cartesian coordinate system Y-axis coordinate representing planned path end position, Y ′ 0 Representing y 0 Regarding the first derivative of the heuristic path length h, y ′ 0 ′ Representing y 0 Regarding the second derivative of the heuristic path length h, y ′ 0 "means y 0 With respect to the third derivative of the heuristic path length h, y 1 Cartesian coordinate system Y-axis coordinate representing planned path end position, Y ′ 1 Representing y 1 Regarding the first derivative of the heuristic path length h, y ′ 1 ′ Representing y 1 Regarding the second derivative of the heuristic path length h, y ′ 1 "means y 1 Third derivative with respect to heuristic path length h.
The current curvature of the vehicle may be determined by the following equation (4), and the rate of change of the current curvature of the vehicle may be determined by the following equation (5):
wherein k is v Indicating the current curvature of the vehicle,indicating the rate of change of the current curvature of the vehicle, L indicating the wheelbase of the vehicle, ω indicating the current steering wheel angle of the vehicle, the position ω of steering wheel return positive being equal to 0, ω being positive when the steering wheel is hit left, ω being negative when the steering wheel is hit right,>the current steering wheel rotational speed of the vehicle, i.e., the current steering angle change rate of the vehicle, r represents the proportionality coefficient of the steering wheel angle to the front wheel angle of the vehicle.
Wherein x is 0 And its derivative with respect to the heuristic path length h can be determined by the following equation (6), y 0 And its derivative with respect to the heuristic path length h can be determined by the following equation (7), x 1 And its derivative with respect to the heuristic path length h can be determined by the following equation (8), y 1 And its derivative with respect to the heuristic path length h can be determined by the following equation (9).
Wherein x is v Cartesian coordinate system x-axis coordinates, y representing the current position of the vehicle (i.e., the center position of the rear axle of the vehicle) v Cartesian coordinate system y-axis coordinate, θ, representing the current position of the vehicle v Representing the current heading angle of the vehicle, V v Indicating the current speed, k of the vehicle v Indicating the current curvature of the vehicle,representing the rate of change, x, of the current curvature of the vehicle t Cartesian x-axis coordinates, y, of a target end position t Cartesian coordinate system y-axis coordinate, θ, representing target end position t Heading angle, k, representing target endpoint t Road curvature representing the target destination.
The principles of equations (6) to (9) and their reasoning process are described in detail below.
The planned path in the embodiment of the disclosure is a path obtained by polynomial fitting with heuristic path length as a parameter, and the planned path is continuous with the position of a planned starting point, continuous in course angle, continuous in curvature and continuous in curvature transformation rate, so that the smoothness of path planning is improved, and the comfort and safety of high-speed running of a vehicle can be improved.
For simplicity and clarity of the proving process, x 'is the first derivative of x with respect to h, x "is the second derivative of x with respect to h, x'" is the third derivative of x with respect to h, and other variables are similar, such as y 'is the first derivative of y with respect to h, y "is the second derivative of y with respect to h, and y'" is the third derivative of y with respect to h.
First, the positions are continuous, i.e. the coordinates of the x-axis and the y-axis in a cartesian coordinate system are continuous. To ensure that the planned path positions are continuous, the following conditions (10) to (11) are satisfied:
x 0 ＝x v (10)
y 0 ＝y v (11)
and secondly, the course angle is continuous, namely the initial tangential direction of the planned path is equal to the direction of the planned starting point. As shown in FIG. 3, the angle between the direction of the planned starting point and the x-axis is equal to θ v Assuming that the heuristic path experiences a rate of change of Δh, the change in the x-direction is caused to be equal to Δx and the change in the y-direction is caused to be equal to Δy. The direction of the constraint route start point is required to be equal to the direction of the planning start point, that is, the conditions shown in the following formulas (12) to (13) are satisfied.
Δx＝Δh·cos(θ v ) (12)
Δy＝Δh·sin(θ v ) (13)
Record x' 0 To plan the first derivative of the path start point with respect to the heuristic path length h, record y' 0 For planning the first derivative of the path start point with respect to the heuristic path length h, there is a relationship as shown in the following formulas (14) to (15):
again, the curvature is continuous, i.e. the curvature of the starting point of the planned path is equal to the curvature of the planned starting point. From the curvature relationship "arc length variation equals radius times angle variation" of FIG. 4, R v ·Δθ v =Δh, therefore, the following formula (16) holds:
thus, the planned route start points have the relationships shown in the following formulas (17) to (18):
Finally, the curvature change rate is continuous, that is, the following formula (19) holds:
as shown in fig. 5, it is assumed that the path length increment Δh corresponds to an increment of the planned path existence Δs, and if Δh=Δs, s represents the planned path length, there is a relationship shown in the following formula (20)
In the formula (20), t represents time,representing the derivative of curvature with respect to time, the following formula (21) can be derived from the above:
similarly, the following formula (22) holds.
Equations (6) to (7) regarding the start point of the planned route are obtained by equations (10) to (22). Similarly, the planned route end point needs to satisfy the positional continuity, the heading angle continuity, the curvature continuity, and the curvature change rate continuity as in the planned route start point, and the relational expressions (8) to (9) of the planned route end point can be obtained in the same manner as in the expressions (10) to (22).
In the embodiments of the present disclosure, the target state information may be obtained in various manners. In view of the high-speed scene, the vehicle generally travels along the lane line, and thus, the target state information may be acquired by referring to the path information. Specifically, the target state information may be acquired by: acquiring reference path information of a vehicle, wherein the reference path information can comprise Cartesian coordinate system coordinates, course angles and road curvatures of all track points on a reference path; and searching a track point with the path length between track points closest to the current position of the vehicle as a heuristic path length threshold on the reference path as a target destination of the vehicle, and extracting information of the target destination from the reference path information as target state information of the vehicle.
The reference path information may be information of a reference path (e.g., a lane line in which the vehicle is currently traveling). The reference path information may be from a high-definition map or may be provided by a lane line perceived by a visual sensor of the vehicle.
In other embodiments, the target state information may also be obtained by extracting, from the reference path information, etc. after the user selects the target destination point on the reference path, and the method for obtaining the target state information is not limited in this disclosure.
Two embodiments of the algorithm of the present invention are presented below, lane keeping and lane changing planning, respectively, for high speed scenarios.
In the following two embodiments, the wheelbase l=2.4m of the vehicle, the steering wheel angle and front wheel angle scaling factor r=15. The current state information of the vehicle is as follows: x is x v ＝1.0m，y v ＝-499.0m，θ v ＝0，V v ＝80km/h，ω＝-5°，Fig. 6 shows a schematic view of the current driving lane of the vehicle and its center line in the following two embodiments.
Example 1
In a lane keeping scenario, the vehicle's goal is to travel along the centerline of the current lane. The heuristic path length threshold h=80m may be taken, and the corresponding target state information should be: x is x t ＝79.66m，y t ＝-493.61m，θ t ＝9.17°，k t The planned path visualization obtained by the vehicle path planning method according to the embodiment of the present disclosure is shown in fig. 7.
In addition, multiple path planning may be performed using multiple different heuristic path length thresholds, from which a less costly planned path is selected as the final path planning result.
Fig. 8 shows a schematic diagram of a planned path in a lane keeping scene in a high-speed driving state when the heuristic path length threshold H is taken at 50m, and fig. 9 shows a schematic diagram of a planned path in a lane keeping scene in a high-speed driving state when the heuristic path length threshold H is taken at 120 m.
Since the vehicle mainly runs along the lane center line in the high-speed scene, a planned path with a start point or an end point on the lane center line or closer to the lane center line can be selected as a final planned result.
Example two
In the lane change scenario, the vehicle is aimed to travel along the center line of the target lane, which is to the left of the current travel lane in this embodiment. Taking a heuristic path length threshold h=80m, and the corresponding target state information is: x is x t ＝79.65m,y t ＝-489.76m,θ t ＝9.24°,k t ＝2.02×10 -3 m-1, a planned path visualization diagram obtained by adopting the vehicle path planning method according to the embodiment of the present disclosure is shown in fig. 10.
Of course, in this embodiment, the vehicle path planning method according to the embodiment of the present disclosure may also be used to calculate the planned paths under different heuristic path length thresholds, and select a planned path with smaller cost from the calculated planned paths as the final path planning result. Fig. 11 shows a schematic view of a planned path in a lane change scene in a high-speed driving state when the heuristic path length threshold H is taken by 50m, and fig. 12 shows a schematic view of the planned path in the lane change scene in the high-speed driving state when the heuristic path length threshold H is taken by 120 m.
Fig. 13 is a block schematic diagram of a vehicle path planning apparatus employing a hardware implementation of a processing system according to one embodiment of the present disclosure.
The apparatus may include corresponding modules that perform the steps of the flowcharts described above. Thus, each step or several steps in the flowcharts described above may be performed by respective modules, and the apparatus may include one or more of these modules. A module may be one or more hardware modules specifically configured to perform the respective steps, or be implemented by a processor configured to perform the respective steps, or be stored within a computer-readable medium for implementation by a processor, or be implemented by some combination.
The hardware architecture may be implemented using a bus architecture. The bus architecture may include any number of interconnecting buses and bridges depending on the specific application of the hardware and the overall design constraints. Bus 1400 connects together various circuits including one or more processors 1500, memory 1600, and/or hardware modules. Bus 1400 may also connect various other circuits 1700 such as peripherals, voltage regulators, power management circuits, external antennas, and the like.
Bus 1400 may be an industry standard architecture (ISA, industry Standard Architecture) bus, a peripheral component interconnect (PCI, peripheral Component) bus, or an extended industry standard architecture (EISA, extended Industry Standard Component) bus, among others. The buses may be divided into address buses, data buses, control buses, etc. For ease of illustration, only one connection line is shown in the figure, but not only one bus or one type of bus.
Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing specific logical functions or steps of the process, and further implementations are included within the scope of the preferred embodiment of the present disclosure in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the embodiments of the present disclosure. The processor performs the various methods and processes described above. For example, method embodiments in the present disclosure may be implemented as a software program tangibly embodied on a machine-readable medium, such as a memory. In some embodiments, part or all of the software program may be loaded and/or installed via memory and/or a communication interface. One or more of the steps of the methods described above may be performed when a software program is loaded into memory and executed by a processor. Alternatively, in other embodiments, the processor may be configured to perform one of the methods described above in any other suitable manner (e.g., by means of firmware).
Logic and/or steps represented in the flowcharts or otherwise described herein may be embodied in any readable storage medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions.
For the purposes of this description, a "readable storage medium" can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of the readable storage medium would include the following: an electrical connection (electronic device) having one or more wires, a portable computer diskette (magnetic device), a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable read-only memory (CDROM). In addition, the readable storage medium may even be paper or other suitable medium on which the program can be printed, as the program can be electronically captured, via, for instance, optical scanning of the paper or other medium, then compiled, interpreted, or otherwise processed in a suitable manner if necessary, and then stored in a memory.
It should be understood that portions of the present disclosure may be implemented in hardware, software, or a combination thereof. In the above-described embodiments, the various steps or methods may be implemented in software stored in a memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, may be implemented using any one or combination of the following techniques, as is well known in the art: discrete logic circuits having logic gates for implementing logic functions on data signals, application specific integrated circuits having suitable combinational logic gates, programmable Gate Arrays (PGAs), field Programmable Gate Arrays (FPGAs), and the like.
Those of ordinary skill in the art will appreciate that all or part of the steps implementing the method of the above embodiments may be implemented by a program to instruct related hardware, and the program may be stored in a readable storage medium, where the program when executed includes one or a combination of the steps of the method embodiments.
Furthermore, each functional unit in each embodiment of the present disclosure may be integrated into one processing module, or each unit may exist alone physically, or two or more units may be integrated into one module. The integrated modules may be implemented in hardware or in software functional modules. The integrated modules may also be stored in a readable storage medium if implemented in the form of software functional modules and sold or used as a stand-alone product. The storage medium may be a read-only memory, a magnetic disk or optical disk, etc.
Fig. 13 is a schematic structural view of a vehicle path planning apparatus 1300 according to an embodiment of the present disclosure. As shown in fig. 13, a vehicle path planning apparatus 1300 according to the present disclosure may include:
an information obtaining unit 1302, configured to obtain a wheelbase, current state information, and target state information of a vehicle, where the current state information includes a cartesian coordinate system coordinate of a current position, a current heading angle, a current running speed, a current steering wheel angle, and a current steering wheel rotation speed; the target state information comprises Cartesian coordinate system coordinates of a target end point position, a course angle of the target end point and road curvature of the target end point;
the path generating unit 1304 is configured to generate a planned path of the vehicle according to a preset heuristic path length threshold, current state information of the vehicle, and target state information, where positions of each track point on the planned path are represented by coordinates in a cartesian coordinate system.
In some embodiments, the vehicle path planning apparatus 1300 may further include: a construction unit 1306, configured to construct a seven-degree polynomial for each coordinate axis of the cartesian coordinate system, where the seven-degree polynomial uses the heuristic path length as an argument and uses the coordinates of the corresponding coordinate axis as a function value. The path generation unit 1304 may be configured to determine coefficients of each of the seven-degree polynomials based on the heuristic path length threshold, the vehicle current state information, and the target state information, and perform polynomial fitting to determine coordinates of the trajectory point on the planned path on corresponding coordinate axes in a cartesian coordinate system.
For other technical details of the vehicle path planning apparatus 1300 according to the embodiment of the disclosure, reference may be made to the foregoing method section, and details are not repeated.
The present disclosure also provides an electronic device, including: a memory storing execution instructions; and a processor or other hardware module that executes the memory-stored execution instructions to cause the processor or other hardware module to perform the vehicle path planning method described above.
The present disclosure also provides a readable storage medium having stored therein execution instructions that when executed by a processor are configured to implement the vehicle path planning method described above.
In the description of the present specification, reference to the terms "one embodiment/mode," "some embodiments/modes," "examples," "specific examples," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment/mode or example is included in at least one embodiment/mode or example of the present application. In this specification, the schematic representations of the above terms are not necessarily the same embodiments/modes or examples. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments/modes or examples. Furthermore, the various embodiments/implementations or examples described in this specification and the features of the various embodiments/implementations or examples may be combined and combined by persons skilled in the art without contradiction.
Furthermore, the terms "first," "second," and the like, are used for descriptive purposes only and are not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include at least one such feature. In the description of the present application, the meaning of "plurality" means at least two, for example, two, three, etc., unless specifically defined otherwise.
It will be appreciated by those skilled in the art that the above-described embodiments are merely for clarity of illustration of the disclosure, and are not intended to limit the scope of the disclosure. Other variations or modifications will be apparent to persons skilled in the art from the foregoing disclosure, and such variations or modifications are intended to be within the scope of the present disclosure.
Claims (10)
1. A vehicle path planning method, comprising:
acquiring wheelbase, current state information and target state information of a vehicle, wherein the current state information comprises Cartesian coordinate system coordinates of a current position, a current course angle, a current running speed, a current steering wheel angle and a current steering wheel rotating speed; the target state information comprises Cartesian coordinate system coordinates of a target end point position, a course angle of the target end point and road curvature of the target end point;
And generating a planned path of the vehicle according to a preset heuristic path length threshold value, current state information and target state information of the vehicle, wherein the positions of all track points on the planned path are represented by coordinates in a Cartesian coordinate system.
2. The vehicle path planning method according to claim 1, characterized in that,
the vehicle path planning method further includes: respectively constructing seven-degree polynomials aiming at all coordinate axes of a Cartesian coordinate system, wherein the seven-degree polynomials take heuristic path length as independent variables and coordinate of the corresponding coordinate axes as function values;
the generating a planned path of the vehicle according to the preset heuristic path length threshold value, the current state information and the target state information of the vehicle comprises the following steps: and determining coefficients of seven-degree polynomials based on the heuristic path length threshold value, the current state information of the vehicle and the target state information, and performing polynomial fitting to determine coordinates of corresponding coordinate axes of the track points on the planned path in a Cartesian coordinate system.
3. The vehicle path planning method according to claim 2, wherein the cartesian coordinate system is a two-dimensional rectangular coordinate system parallel to the ground, and coordinate axes of the cartesian coordinate system include an x-axis and a y-axis;
Seven-degree polynomials are respectively constructed for each coordinate axis of a Cartesian coordinate system, and the seven-degree polynomials comprise: a first polynomial for calculating the X-axis coordinates of a Cartesian coordinate system of each track point in a planning path and a second polynomial for calculating the Y-axis coordinates of a Cartesian coordinate system of each track point in the planning path are constructed, wherein the first polynomial and the second polynomial are seven-degree polynomials and take heuristic path length as independent variables.
4. The vehicle path planning method according to claim 2, characterized in that,
the coefficients of the seven-degree polynomial are determined according to the coordinate of the coordinate axis corresponding to the Cartesian coordinate system of the path starting point and the derivative thereof relative to the heuristic path length, the coordinate of the coordinate axis corresponding to the Cartesian coordinate system of the path ending point and the derivative thereof relative to the heuristic path length, and the heuristic path length threshold;
the Cartesian coordinate system of the path starting point corresponds to the coordinate axis coordinate and the derivative thereof about the inspired path length are determined according to the wheelbase of the vehicle, the Cartesian coordinate system of the current position of the vehicle corresponds to the coordinate axis coordinate, the current course angle of the vehicle, the current running speed of the vehicle, the current steering wheel angle of the vehicle and the current steering wheel rotating speed of the vehicle;
And the Cartesian coordinate system of the path end point corresponds to the coordinate axis coordinate and the derivative of the Cartesian coordinate system of the path end point relative to the heuristic path length is determined according to the Cartesian coordinate system of the target end point corresponds to the coordinate axis coordinate, the course angle and the road curvature.
5. The vehicle path planning method according to claim 4, characterized in that,
further comprises: determining the current curvature and the curvature change rate of the vehicle according to the wheelbase of the vehicle, the current steering wheel angle and the current steering wheel rotating speed;
the Cartesian coordinate system of the path starting point corresponds to coordinate axis coordinates and derivatives thereof related to the heuristic path length are determined according to the wheelbase of the vehicle, the Cartesian coordinate system of the current position of the vehicle corresponds to coordinate axis coordinates, the current course angle of the vehicle, the current running speed of the vehicle, the current curvature of the vehicle and the curvature change rate.
6. The vehicle path planning method according to claim 1, characterized in that the target state information is obtained by:
acquiring reference path information of a vehicle, wherein the reference path information comprises Cartesian coordinate system coordinates, course angles and road curvatures of all track points on a reference path;
and searching a track point with the path length between track points closest to the current position of the vehicle as the heuristic path length threshold on the reference path as a target destination of the vehicle, and extracting information of the target destination from the reference path information as target state information of the vehicle.
7. A vehicle path planning apparatus, characterized by comprising:
the information acquisition unit is used for acquiring the wheelbase, the current state information and the target state information of the vehicle, wherein the current state information comprises Cartesian coordinate system coordinates of a current position, a current course angle, a current running speed, a current steering wheel rotation angle and a current steering wheel rotation speed; the target state information comprises Cartesian coordinate system coordinates of a target end point position, a course angle of the target end point and road curvature of the target end point;
the path generation unit is used for generating a planning path of the vehicle according to a preset heuristic path length threshold value, current state information of the vehicle and target state information, and the positions of all track points on the planning path are represented by coordinates in a Cartesian coordinate system.
8. The vehicle path planning apparatus according to claim 7, characterized in that,
further comprises: the construction unit is used for respectively constructing seven-degree polynomials aiming at all coordinate axes of the Cartesian coordinate system, wherein the seven-degree polynomials take heuristic path length as independent variables and the coordinates of the corresponding coordinate axes as function values;
the path generating unit is used for determining coefficients of seven-degree polynomials based on the heuristic path length threshold value, the current state information of the vehicle and the target state information and performing polynomial fitting to determine coordinates of corresponding coordinate axes of the track points on the planned path in a Cartesian coordinate system.
9. An electronic device, comprising:
a memory storing execution instructions; and
a processor executing the execution instructions stored in the memory, causing the processor to execute the vehicle path planning method according to any one of claims 1 to 6.
10. A readable storage medium having stored therein execution instructions which, when executed by a processor, are adapted to carry out the vehicle path planning method according to any one of claims 1 to 6.
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