CN113848898A - Path planning method, device, automatic driving vehicle and storage medium - Google Patents
Path planning method, device, automatic driving vehicle and storage medium Download PDFInfo
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Abstract
The method comprises the steps of obtaining running information of a vehicle, determining a first constraint condition and a second constraint condition of the vehicle according to the running information, wherein the first constraint condition is a constraint item of a position relation between an outline and an obstacle when the vehicle runs, the second constraint condition is a constraint item of a relative angle between a front vehicle body and a rear vehicle body, then determining a target constraint condition of the vehicle aiming at a planned path according to the first constraint condition and the second constraint condition, and finally determining a target path of the vehicle according to the target constraint condition, environment information and a mixed A-star algorithm. According to the technical scheme, the target constraint condition of the more accurate planned path is obtained from the angle relation between the front vehicle body and the rear vehicle body of the vehicle and the position relation between the barrier and the vehicle driving area, so that the path which meets the actual operation requirement of the vehicle is planned.
Description
Technical Field
The present application relates to the field of automatic driving technologies, and in particular, to a path planning method and apparatus, an automatic driving vehicle, and a storage medium.
Background
With the continuous development of the unmanned technology, many companies have been developing unmanned trucks with great efforts due to their good application scenarios. The unmanned driving technology is wide in range and comprises positioning, sensing, decision planning, motion control and the like, wherein the path planning is one of core technologies for realizing the unmanned driving of the truck.
In the prior art, in the path planning of an unmanned truck, a passenger vehicle is mainly referred to, and a planned path is corrected by using a hybrid a-star algorithm with a constraint condition as a reference, wherein the constraint condition is determined based on a steering radius.
In the process of implementing the invention, the inventor finds that at least the following problems exist in the prior art: the trailer truck is composed of a trailer and a trailer, and the constraint condition design based on the passenger car does not meet the actual operation requirement of the trailer truck, so that the path planning is inaccurate.
Disclosure of Invention
The embodiment of the application provides a path planning method and device, an automatic driving vehicle and a storage medium, which are used for solving the problem that the path planning of a trailer truck in the prior art is inaccurate.
In a first aspect, an embodiment of the present application provides a path planning method, which is applied to an autonomous vehicle, where the autonomous vehicle includes: a front vehicle body and a rear vehicle body, the method comprising:
acquiring operation information of a vehicle, wherein the operation information comprises: a steering angle of the front wheels of the vehicle, a hinge angle of the front body and the rear body, a length of the front body, a length of a hinge point to the rear axle of the vehicle, and a width of the vehicle;
determining a first constraint condition and a second constraint condition of the vehicle according to the running information, wherein the first constraint condition is a constraint item of a position relation between an outline and an obstacle when the vehicle runs, and the second constraint condition is a constraint item of a relative angle of the front vehicle body and the rear vehicle body;
determining a target constraint condition of the vehicle for a planned path according to the first constraint condition and the second constraint condition;
and determining the target path of the vehicle according to the target constraint condition, the environmental information and the mixed A star algorithm.
In a possible design of the first aspect, the operation information further includes: the number of commutations of the vehicle in the planned path, the heading angles of two waypoints of the vehicle in the planned path and the distance between the two waypoints, the method further comprising:
determining a third constraint condition of the vehicle according to the reversing times, wherein the third constraint condition is a constraint item of a reversing action of the vehicle in a planned path;
determining a fourth constraint condition of the vehicle according to the course angles of the two path points and the distance between the two path points, wherein the fourth constraint condition is a constraint item of the course angle change rate in the planned path of the vehicle;
and determining a target constraint condition of the vehicle for a planned path according to the first constraint condition, the second constraint condition, the third constraint condition and the fourth constraint condition.
In another possible design of the first aspect, the determining a first constraint condition of the vehicle according to the operation information includes:
determining a first distance from the outer edge of the vehicle to a center of rotation of the vehicle based on the length of the front body and the articulation angle;
determining a second distance of the inner edge of the vehicle to a center of rotation of the vehicle based on a length of a hinge point to the rear axle of the vehicle, the vehicle width, and the hinge angle;
determining the width of the vehicle driving area according to the first distance and the second distance;
and determining a first constraint condition of the vehicle according to the position of the obstacle and the width of the vehicle in a planned path.
In still another possible design of the first aspect, the determining a second constraint condition of the vehicle based on the operation information includes:
and determining the second constraint condition according to the articulation angle, a first preset articulation threshold, a second preset articulation threshold, a third preset articulation threshold and the correlation coefficient of the articulation angle, wherein the second preset articulation threshold is greater than the first preset articulation threshold and smaller than the third preset articulation threshold, and the first preset articulation threshold is greater than 0.
Optionally, before the obtaining of the operation information of the vehicle, the method further includes:
establishing a coordinate system by taking the vertex of the hinged angle as an origin and taking a line of the rotating center passing through the origin as a vertical coordinate axis;
acquiring a first course angle of the front vehicle body and a second course angle of the rear vehicle body, and determining a quadrant pointed by the first course angle and a quadrant pointed by the second course angle, wherein the quadrants comprise: a first quadrant, a second quadrant, a third quadrant, or a fourth quadrant;
and determining the articulation angle according to the relation between the quadrant pointed by the first course angle and the quadrant pointed by the second course angle.
Optionally, the determining, according to the number of times of the reversing, a third constraint condition of the vehicle, where the third constraint condition is a constraint term of a reversing action of the vehicle in a planned path, includes:
and determining the third constraint condition according to the reversing times and a preset reversing basic value.
Optionally, the determining a fourth constraint condition of the vehicle according to the heading angles of the two waypoints and the distance between the two waypoints includes:
determining a correlation coefficient of the course angles of the two waypoints and the distance between the two waypoints according to the course angles of the two waypoints and the distance between the two waypoints;
and determining the fourth constraint condition according to the correlation coefficient.
In a second aspect, an embodiment of the present application provides a path planning apparatus, which is applied to an autonomous vehicle, where the autonomous vehicle includes: a front vehicle body and a rear vehicle body, the apparatus comprising: the device comprises an acquisition module, a determination module and a processing module;
the acquisition module is used for acquiring the running information of the vehicle, and the running information comprises: a steering angle of the front wheels of the vehicle, a hinge angle of the front body and the rear body, a length of the front body, a length of a hinge point to the rear axle of the vehicle, and a width of the vehicle;
the determining module is used for determining a first constraint condition and a second constraint condition of the vehicle according to the running information, wherein the first constraint condition is a constraint item of a position relation between an outline and an obstacle when the vehicle runs, the second constraint condition is a constraint item of a relative angle between the front vehicle body and the rear vehicle body, and a target constraint condition of the vehicle for a planned path is determined according to the first constraint condition and the second constraint condition;
and the processing module is used for determining the target path of the vehicle according to the target constraint condition, the environmental information and the mixed A star algorithm.
In one possible design of the second aspect, the operation information further includes: the number of commutations of the vehicle in the planned path, the heading angles of two waypoints of the vehicle in the planned path, and the distance between the two waypoints, and the determining module is further configured to:
determining a third constraint condition of the vehicle according to the reversing times, wherein the third constraint condition is a constraint item of a reversing action of the vehicle in a planned path;
determining a fourth constraint condition of the vehicle according to the course angles of the two path points and the distance between the two path points, wherein the fourth constraint condition is a constraint item of the course angle change rate in the planned path of the vehicle;
and determining a target constraint condition of the vehicle for a planned path according to the first constraint condition, the second constraint condition, the third constraint condition and the fourth constraint condition.
In another possible design of the second aspect, the determining module determines, according to the operation information, a first constraint condition of the vehicle, specifically to:
determining a first distance from the outer edge of the vehicle to a center of rotation of the vehicle based on the length of the front body and the articulation angle;
determining a second distance of the inner edge of the vehicle to a center of rotation of the vehicle based on a length of a hinge point to the rear axle of the vehicle, the vehicle width, and the hinge angle;
determining the width of the vehicle driving area according to the first distance and the second distance;
and determining a first constraint condition of the vehicle according to the position of the obstacle and the width of the vehicle in a planned path.
In yet another possible design of the second aspect, the determining module determines, according to the operation information, a second constraint condition of the vehicle, specifically to:
and determining the second constraint condition according to the articulation angle, a first preset articulation threshold, a second preset articulation threshold, a third preset articulation threshold and the correlation coefficient of the articulation angle, wherein the second preset articulation threshold is greater than the first preset articulation threshold and smaller than the third preset articulation threshold, and the first preset articulation threshold is greater than 0.
Optionally, the determining module is further configured to establish a coordinate system with a vertex of the articulation angle as an origin and a line of the rotation center passing through the origin as a ordinate axis;
the acquisition module is further configured to acquire a first course angle of the front vehicle body and a second course angle of the rear vehicle body, and determine a quadrant to which the first course angle points and a quadrant to which the second course angle points, where the quadrants include: a first quadrant, a second quadrant, a third quadrant, or a fourth quadrant;
the determining module is further configured to determine the articulation angle according to a relationship between a quadrant pointed by the first course angle and a quadrant pointed by the second course angle.
Optionally, the determining module determines a third constraint condition of the vehicle according to the number of times of the reversing, where the third constraint condition is a constraint item of a reversing action of the vehicle in a planned path, and is specifically configured to:
and determining the third constraint condition according to the reversing times and a preset reversing basic value.
Optionally, the determining module is configured to determine a fourth constraint condition of the vehicle according to the heading angles of the two waypoints and the distance between the two waypoints, and specifically configured to:
determining a correlation coefficient of the course angles of the two waypoints and the distance between the two waypoints according to the course angles of the two waypoints and the distance between the two waypoints;
and determining the fourth constraint condition according to the correlation coefficient.
In a third aspect, an embodiment of the present application provides an autonomous vehicle, including: a processor, a memory;
the memory stores computer-executable instructions;
the processor executes the computer executable instructions to cause the computer apparatus to perform a path planning method as described above in the first aspect and in various possible designs.
In a fourth aspect, embodiments of the present application provide a computer-readable storage medium, in which computer-executable instructions are stored, and when the computer-executable instructions are executed by a processor, the computer-readable storage medium is configured to implement the path planning method as described in the first aspect and various possible designs.
In a fifth aspect, embodiments of the present application provide a computer program product, which includes a computer program, and when the computer program is executed by a processor, the computer program is configured to implement the path planning method as described in the first aspect and various possible designs.
According to the path planning method and device, the automatic driving vehicle and the storage medium, the method obtains the running information of the vehicle, and the running information comprises the following steps: the method comprises the steps of determining a steering angle of a front wheel of a vehicle, an articulation angle of a front vehicle body and a rear vehicle body, a length of the front vehicle body, a length from an articulation point to a rear shaft of the vehicle and a width of the vehicle, determining a first constraint condition and a second constraint condition of the vehicle according to running information, wherein the first constraint condition is a constraint item of a position relation between a contour and an obstacle when the vehicle runs, the second constraint condition is a constraint item of a relative angle between the front vehicle body and the rear vehicle body, determining a target constraint condition of the vehicle for a planned path according to the first constraint condition and the second constraint condition, and finally determining a target path of the vehicle according to the target constraint condition, environment information and a mixed A-star algorithm. According to the technical scheme, the target constraint condition of the more accurate planned path is obtained from the angle relation between the front vehicle body and the rear vehicle body of the vehicle and the position relation between the barrier and the vehicle driving area, so that the path which meets the actual operation requirement of the vehicle is planned.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and together with the description, serve to explain the principles of the disclosure.
Fig. 1 is a schematic view of an application scenario of a path planning method according to an embodiment of the present application;
fig. 2 is a schematic flowchart of a first embodiment of a path planning method according to an embodiment of the present application;
FIG. 3 is a schematic illustration of a representation of vehicle operation information provided by an embodiment of the present application;
fig. 4 is a schematic flow chart of a second embodiment of a path planning method provided in the embodiment of the present application;
fig. 5 is a schematic structural diagram of a path planning apparatus according to an embodiment of the present application;
fig. 6 is a schematic structural diagram of an autonomous vehicle according to an embodiment of the present application.
With the foregoing drawings in mind, certain embodiments of the disclosure have been shown and described in more detail below. These drawings and written description are not intended to limit the scope of the disclosed concepts in any way, but rather to illustrate the concepts of the disclosure to those skilled in the art by reference to specific embodiments.
Detailed Description
Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the exemplary embodiments below are not intended to represent all implementations consistent with the present disclosure. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present disclosure, as detailed in the appended claims.
Before introducing the embodiments of the present application, the background of the present application is explained first:
with the continuous development of the unmanned technology, more and more scenes are applied to the unmanned technology, for example, the path planning of the vehicle, and the traditional free space path planning basically adopts a hybrid a-star algorithm and considers a kinematic model of the vehicle, so that the searched path better conforms to the kinematic constraint of the vehicle. Since the hybrid a star is more compliant with the kinematic constraints of the vehicle, it is widely used in path planning for autonomous vehicles.
In the prior art, a target path of a passenger car is obtained by designing a constraint condition and adopting a hybrid A-star algorithm from the steering radius of the passenger car.
However, in a vehicle with two bodies (a front body and a rear body) such as a trailer, there are relatively many factors to be considered, and for example, an angular relationship between the front body and the rear body, a vehicle body length relationship, and the like are also considered.
Based on the problems in the prior art, fig. 1 is a schematic view of an application scenario of a path planning method provided in an embodiment of the present application, so as to solve the technical problems. As shown in fig. 1, the application scenario diagram includes: an obstacle 11, a vehicle 12, a start point S, an end point E, and a target route 13.
Alternatively, from the starting point S to the end point E, there may be a lane 1, a lane 2 and a lane 3 in parallel, just by way of example. The obstacle 11 may be another vehicle, an object related at the time of road maintenance, a pedestrian, or the like. The vehicle 12 may be a trailer (including a front body 121 and a rear body 122).
In one possible implementation, when the vehicle 12 is located at the starting point S and needs to reach the end point E, and a route of the vehicle 12 is planned, an Electronic Control Unit (ECU) in the vehicle 12 acquires operation information (detailed operation information content given below) of the vehicle, obtains constraint conditions for planning the route of the vehicle 12 according to the operation information, inputs environment information (including the obstacle 11 and other information) of the road to the hybrid a-star algorithm, performs parameter correction on the hybrid a-star algorithm by using the constraint conditions, and obtains the target route 13 in fig. 1 after processing.
It should be understood that the target path 13, and even the application scenario, is merely an example and is not limiting.
In order to solve the technical problems, the technical conception process of the inventor is as follows: in the prior art, the constraint condition of the trailer is considered from the perspective of a passenger vehicle, the actual condition that the trailer is formed by two carriage structures is ignored, the relative angle between the two carriages changes along with the running of the vehicle, the running profile of the vehicle is greatly different from that of the passenger vehicle, and the influence between the two carriages is not negligible during steering.
The technical solution of the present application is described in detail below by specific embodiments with a schematic frame structure shown in fig. 1. It should be noted that the following specific embodiments may be combined with each other, and the same or similar concepts or processes may not be described in detail in some embodiments. Embodiments of the present application will be described below with reference to the accompanying drawings.
Fig. 2 is a schematic flow chart of a first embodiment of a path planning method provided in the embodiment of the present application. As shown in fig. 2, the path planning method may include the following steps:
and step 21, acquiring the running information of the vehicle.
Wherein the operation information includes: the steering angle of the front wheels of the vehicle, the articulation angle of the front body and the rear body, the length of the front body, the length of the articulation point to the rear axle of the vehicle, the width of the vehicle.
It should be understood that the vehicle in the embodiment of the present application refers to an autonomous vehicle.
In this solution, fig. 3 is a schematic illustration of a mark of the vehicle operation information provided in the embodiment of the present application. In one possible implementation, the embodiments of the present application are described in conjunction with fig. 3.
In this step, when planning a route of a vehicle, the operation information of the vehicle needs to be acquired in real time, which includes: information that the vehicle itself does not change (e.g., characteristics of the vehicle itself), information that changes as the vehicle operates.
Alternatively, taking as an example a vehicle in a turn (the vehicle of the embodiment of the present application may be a trailer, which includes a front body and a rear body), the characteristics of the vehicle itself may include: length l of front body1Length l of hinge point A to rear axle of vehicle2A vehicle width w; the information that changes as the vehicle operates may include: steering angle d of the front wheels of the vehicle, articulation angle h of the front body and the rear body.
The hinge angle h is an included angle formed by the relative positions of the front vehicle body and the rear vehicle body; the hinge point a is the point of connection of the front and rear bodies, i.e. the vertex of the hinge angle h in fig. 1, the direction of travel of the vehicle is denoted v and the centre of rotation is denoted O.
And step 22, determining a first constraint condition and a second constraint condition of the vehicle according to the operation information.
The first constraint condition is a constraint item of the position relation between the outline and the obstacle when the vehicle runs, and the second constraint condition is a constraint item of the relative angle of the front vehicle body and the rear vehicle body.
In the scheme, on the basis of the hybrid A-star algorithm, a kinematic model of the vehicle is considered, so that the searched path is more consistent with kinematic constraint of the vehicle. Although the hybrid a-star is more compliant with the kinematic constraints of the vehicle, corresponding constraints need to be added for the trailer.
In this step, since the trailer is formed of two vehicle bodies, when the trailer is running on a road, for example, when the trailer makes a turn, the path that the front and rear wheels of the trailer pass through is wider than that of a general vehicle, that is, the profile of the trailer when the vehicle is running needs to be determined. Further, the positional relationship between the contour of the vehicle during running and the obstacle on the road also needs to be considered.
The obstacle may refer to not only other vehicles, pedestrians, buildings, etc., but also road environments, such as lane lines, lane fences, etc.
Furthermore, the relative angle of the front and rear bodies also needs to be considered when steering the vehicle. Namely, the phenomenon that the front vehicle body and the rear vehicle body are folded in the driving process is avoided, namely, the relative angle between the front vehicle body and the rear vehicle body is less than or equal to 90 degrees. Once the folding phenomenon occurs, the damage of the vehicle body can be caused, and the vehicle can be out of control seriously. But the relative angle is acceptable to change within a certain range, and the larger the relative angle is, the greater the potential safety hazard is caused.
In one possible implementation, the first constraint realization of the vehicle may comprise the steps of:
step 1, determining a first distance from the outer edge of the vehicle to the rotation center of the vehicle according to the length of the front vehicle body and the hinge angle.
The outer edge of the vehicle refers to the position of the point farthest from the rotation center on the vehicle body when the vehicle turns.
Optionally, the first distance r1The calculation formula of (c) may be:
and 2, determining a second distance from the inner edge of the vehicle to the rotation center of the vehicle according to the length from the hinge point to the rear axle of the vehicle, the width of the vehicle and the hinge angle.
The inner edge of the vehicle refers to the position of the point, which is closest to the rotation center, on the vehicle body when the vehicle turns.
Optionally, the second distance r2The calculation formula of (c) may be:
r2＝l2 cot(h)-0.5w
and step 3, determining the width of the vehicle driving area according to the first distance and the second distance.
The width of the vehicle driving area is the width of the vehicle profile when the vehicle turns.
Optionally, the width d of the vehicle driving areawThe calculation formula of (c) may be:
and 4, determining a first constraint condition of the vehicle according to the position of the obstacle and the width of the vehicle in the planned path.
Wherein, whether the obstacle collides with the vehicle running track or not can be judged by judging whether the obstacle coordinates (x, y) are in the vehicle running track or not. First constraint costcCan be expressed as follows:
that is, when the obstacle is located in the vehicle traveling region dwCost of internal time, collisioncA value of a, no obstacle in the vehicle driving area dwWhen the vehicle is inside, the vehicle collides with the costcIs 0. Wherein a is the value of the preset constraint term.
In one possible implementation, the implementation of the second constraint of the vehicle may comprise the following operations:
optionally, according to the articulation angle h and the first preset articulation threshold haA second preset articulation threshold hbDetermining a second constraint condition cost by using a third preset hinging threshold h and a correlation coefficient epsilon of a hinging angleaThe second constraint stripThe part is a constraint term of relative angles of the front vehicle body and the rear vehicle body.
The second preset hinge threshold is greater than the first preset hinge threshold and smaller than the third preset hinge threshold, and the first preset hinge threshold is greater than 0.
Prior to this implementation, the articulation angle of the vehicle needs to be determined, and in one possible implementation, the determination of the articulation angle may include the steps of:
step 1, establishing a coordinate system by taking the vertex of the hinge angle as an origin and taking a line of a rotation center passing through the origin as a vertical coordinate axis;
the line of the rotation center passing through the origin points to the ordinate axis direction, and the axis direction is the positive semi-axis direction, at the moment, the abscissa axis is also determined, so that a coordinate system taking the vertex of the hinge angle as the origin is established, and the coordinate system is divided into a first quadrant, a second quadrant, a third quadrant and a fourth quadrant.
And 2, acquiring a first course angle of the front vehicle body and a second course angle of the rear vehicle body, and determining a quadrant pointed by the first course angle and a quadrant pointed by the second course angle.
Wherein, the quadrant includes: a first quadrant, a second quadrant, a third quadrant, or a fourth quadrant;
wherein the first course angle theta of the front vehicle bodyfThe original point is taken as a ray starting point, the direction of the front vehicle body is taken as a vector line of the ray, and the advancing direction of the front vehicle body is marked; second heading angle theta of rear vehicle bodyrThe direction of the rear vehicle body is marked by using the origin as the starting point of the ray and the direction of the rear vehicle body as the vector line of the ray.
And 3, determining the articulation angle according to the relation between the quadrant pointed by the first course angle and the quadrant pointed by the second course angle.
Wherein, for a quadrant pointed by the heading angle, the articulation angle h may be expressed as follows:
optionally, a second constraint costaCan be represented asThe following:
and step 23, determining a target constraint condition of the vehicle for the planned path according to the first constraint condition and the second constraint condition.
In this step, the first constraint costcAnd a second constraint costaThe sum together determines the target constraints for the planned path.
In one possible implementation, the expression formula of the target constraint cost may be:
cost＝costc+costa
and 24, determining a target path of the vehicle according to the target constraint condition, the environmental information and the hybrid A-star algorithm.
In this step, the model constructed by the hybrid a-star algorithm is subjected to parameter constraint using the target constraint condition, and environment information, for example, obstacle information, road condition information, and the like, is input to the model constructed by the hybrid a-star algorithm, so that a target path of the vehicle can be obtained, in which the influence of the obstacle on the vehicle travel area and the angle between the front vehicle body and the rear vehicle body of the vehicle during travel is taken into consideration.
According to the path planning method provided by the embodiment of the application, the running information of the vehicle is obtained, the first constraint condition and the second constraint condition of the vehicle are determined according to the running information, the first constraint condition is a constraint item of the position relation between the outline and the obstacle when the vehicle runs, the second constraint condition is a constraint item of the relative angle between the front vehicle body and the rear vehicle body, then the target constraint condition of the vehicle for the planned path is determined according to the first constraint condition and the second constraint condition, and finally the target path of the vehicle is determined according to the target constraint condition, the environment information and the mixed A-star algorithm. According to the method, a more accurate target constraint condition for planning the path is obtained from the angle relation between the front vehicle body and the rear vehicle body of the vehicle, the position of the obstacle and the driving area of the vehicle, so that the path which meets the actual operation requirement of the vehicle is planned.
On the basis of the foregoing embodiments, fig. 4 is a schematic flow chart of a second embodiment of the path planning method provided in the embodiment of the present application. As shown in fig. 4, before the step 24, the path planning method may further include the following steps:
and step 41, determining a third constraint condition of the vehicle according to the reversing times.
And the third constraint condition is a constraint item of the reversing action of the vehicle in the planned path.
In the scheme, in order to obtain the target path more accurately, factors of turning times and course angle change of the vehicle during traveling can be taken into consideration as constraint items of the target constraint condition.
In this step, in the free space path planning, the planned target path allows the vehicle to complete parking or turning around, which requires the vehicle to perform reversing driving. However, for the towed vehicle, the risk of vehicle driving is greatly increased by each change of driving direction, so that the reversing action of the path needs to be strictly restricted, and the vehicle can reach an ideal position by the least reversing paths.
In one possible implementation, a third constraint condition may be determined according to the number of commutations and a preset commutation basic value, and the third constraint condition cost _ n may be expressed as follows:
cost_n＝bn_d
and n _ d is the reversing times of the path in the path planning, and b is a reversing basic value which is a preset value.
And step 42, determining a fourth constraint condition of the vehicle according to the course angles of the two path points and the distance between the two path points.
And the fourth constraint condition is a constraint item of the change rate of the heading angle in the planned path of the vehicle.
Optionally, for a large vehicle such as a trailer, the planned path is to ensure the smoothness of the vehicle, which is a guarantee of driving safety. In order to obtain a smoother path, a constraint term of the change rate of the heading angle is specially added.
In one possible implementation, this step may include the following implementation:
step 1, determining a correlation coefficient of the course angles of the two waypoints and the distance between the two waypoints according to the course angles of the two waypoints and the distance between the two waypoints.
Optionally, in the path planning, because the path lengths of adjacent points are not fixed, the course angles of two path points with fixed length interval of l are respectively βiAnd betai+1Then a relationship between the change in heading angle and the distance is established, i.e., the correlation coefficient τ of the heading angles of the two waypoints and the distance between the two waypointsiIs expressed as follows:
and step 2, determining a fourth constraint condition according to the correlation coefficient.
The course angle change condition is judged according to the correlation coefficient of the course angles of the two path points and the distance between the two path points, namely, the expression formula of a fourth constraint condition cost _ s related to the course angle change rate is as follows:
and 43, determining a target constraint condition of the vehicle for the planned path according to the first constraint condition, the second constraint condition, the third constraint condition and the fourth constraint condition.
Optionally, the first constraint condition, the second constraint condition, the third constraint condition, and the fourth constraint condition are all for making the planned path better meet the special requirement of the trailer on the path, and the final constraint term constraint condition cost thereof may be expressed as:
cost＝cost_c+cost_n+cost_a+cost_s
according to the path planning method provided by the embodiment of the application, the third constraint condition of the vehicle is determined according to the reversing times, the fourth constraint condition of the vehicle is determined according to the course angles of the two path points and the distance between the two path points, and then the target constraint condition of the vehicle for the planned path is determined according to the first constraint condition, the second constraint condition, the third constraint condition and the fourth constraint condition.
On the basis of the above method embodiment, fig. 5 is a schematic structural diagram of a path planning apparatus provided in the embodiment of the present application. As shown in fig. 5, the path planning apparatus includes: an acquisition module 51, a determination module 52 and a processing module 53;
an obtaining module 51, configured to obtain operation information of the vehicle, where the operation information includes: the steering angle of the front wheels of the vehicle, the hinge angle of the front vehicle body and the rear vehicle body, the length of the front vehicle body, the length from a hinge point to a rear shaft of the vehicle and the width of the vehicle;
the determining module 52 is configured to determine a first constraint condition and a second constraint condition of the vehicle according to the operation information, where the first constraint condition is a constraint item of a position relationship between an outline and an obstacle when the vehicle is running, the second constraint condition is a constraint item of a relative angle between a front vehicle body and a rear vehicle body, and a target constraint condition of the vehicle for a planned path is determined according to the first constraint condition and the second constraint condition;
and the processing module 53 is configured to determine a target path of the vehicle according to the target constraint condition, the environmental information, and the hybrid a-star algorithm.
In one possible design of the embodiment of the present application, the operation information further includes: the number of commutations of the vehicle in the planned path, the heading angles of the vehicle at two waypoints in the planned path, and the distance between the two waypoints, the determination module 52, further configured to:
determining a third constraint condition of the vehicle according to the reversing times, wherein the third constraint condition is a constraint item of a reversing action of the vehicle in a planned path;
determining a fourth constraint condition of the vehicle according to the course angles of the two path points and the distance between the two path points, wherein the fourth constraint condition is a constraint item of the course angle change rate in the planned path of the vehicle;
and determining a target constraint condition of the vehicle for the planned path according to the first constraint condition, the second constraint condition, the third constraint condition and the fourth constraint condition.
In another possible design of the embodiment of the present application, the determining module 52 determines, according to the operation information, a first constraint condition of the vehicle, specifically to:
determining a first distance from an outer edge of the vehicle to a center of rotation of the vehicle based on the length of the front body and the articulation angle;
determining a second distance from the inner edge of the vehicle to the center of rotation of the vehicle based on the length of the hinge point to the rear axle of the vehicle, the width of the vehicle, and the hinge angle;
determining the width of a vehicle driving area according to the first distance and the second distance;
a first constraint of the vehicle is determined based on the position of the obstacle and the width of the vehicle in the planned path.
In yet another possible design of the embodiment of the present application, the determining module 52 determines, according to the operation information, a second constraint condition of the vehicle, specifically to:
and determining a second constraint condition according to the articulation angle, the first preset articulation threshold, the second preset articulation threshold, the third preset articulation threshold and the correlation coefficient of the articulation angle, wherein the second preset articulation threshold is greater than the first preset articulation threshold and smaller than the third preset articulation threshold, and the first preset articulation threshold is greater than 0.
Optionally, the determining module 52 is further configured to establish a coordinate system with a vertex of the hinge angle as an origin and a line of the rotation center passing through the origin as an ordinate axis;
the obtaining module 51 is further configured to obtain a first heading angle of the front vehicle body and a second heading angle of the rear vehicle body, and determine a quadrant pointed by the first heading angle and a quadrant pointed by the second heading angle, where the quadrants include: a first quadrant, a second quadrant, a third quadrant, or a fourth quadrant;
the determining module 52 is further configured to determine the articulation angle according to a relationship between the quadrant pointed to by the first heading angle and the quadrant pointed to by the second heading angle.
Optionally, the determining module 52 determines a third constraint condition of the vehicle according to the number of times of the reversing, where the third constraint condition is a constraint item of a reversing action of the vehicle in the planned path, and is specifically configured to:
and determining a third constraint condition according to the reversing times and a preset reversing basic value.
Optionally, the determining module 52 determines a fourth constraint condition of the vehicle according to the heading angles of the two waypoints and the distance between the two waypoints, where the fourth constraint condition is specifically used for:
determining a correlation coefficient of the course angles of the two waypoints and the distance between the two waypoints according to the course angles of the two waypoints and the distance between the two waypoints;
and determining a fourth constraint condition according to the correlation coefficient.
The path planning apparatus provided in the embodiment of the present application may be used to execute the technical solutions corresponding to the path planning methods in the embodiments, and the implementation principles and technical effects thereof are similar and will not be described herein again.
It should be noted that the division of the modules of the above apparatus is only a logical division, and the actual implementation may be wholly or partially integrated into one physical entity, or may be physically separated. And these modules can be realized in the form of software called by processing element; or may be implemented entirely in hardware; and part of the modules can be realized in the form of calling software by the processing element, and part of the modules can be realized in the form of hardware. In addition, all or part of the modules can be integrated together or can be independently realized. The processing element described herein may be an integrated circuit having signal processing capabilities. In implementation, each step of the above method or each module above may be implemented by an integrated logic circuit of hardware in a processor element or an instruction in the form of software.
Fig. 6 is a schematic structural diagram of an autonomous vehicle according to an embodiment of the present application. As shown in fig. 6, the vehicle may include: a processor 60, a memory 61, and computer program instructions stored on the memory 61 and executable on the processor 60.
Wherein the autonomous vehicle may be a trailer or the like.
The processor 60 executes computer-executable instructions stored by the memory 61, causing the processor 60 to perform the aspects of the embodiments described above. The processor 60 may be a general-purpose processor including a central processing unit CPU, a Network Processor (NP), and the like; but also a digital signal processor DSP, an application specific integrated circuit ASIC, a field programmable gate array FPGA or other programmable logic device, discrete gate or transistor logic, discrete hardware components.
Optionally, the autonomous vehicle may further include: a transceiver 62.
The memory 61 and the transceiver 62 are connected to the processor 60 via a system bus and communicate with each other, and the memory 61 is used for storing computer program instructions.
The transceiver 62 is used for communication with other devices, the transceiver 62 constituting a communication interface.
Optionally, in terms of hardware implementation, the obtaining module 51 in the embodiment shown in fig. 5 corresponds to the transceiver 62 in this embodiment.
The system bus may be a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, or the like. The system bus may be divided into an address bus, a data bus, a control bus, and the like. For ease of illustration, only one thick line is shown, but this does not mean that there is only one bus or one type of bus.
Optionally, the autonomous vehicle may further include: and the display is used for displaying the related information such as the target path.
It should be understood that the processor 60, memory 61 and transceiver 62 described above may all be integrated in the ECU of the vehicle or may be separate devices mounted in the vehicle.
The automatic driving vehicle provided by the embodiment of the application can be used for executing the technical scheme corresponding to the path planning method in the embodiment, the implementation principle and the technical effect are similar, and the detailed description is omitted.
The embodiment of the application also provides a chip for running the instructions, and the chip is used for executing the technical scheme of the path planning method in the embodiment.
An embodiment of the present application further provides a computer-readable storage medium, where a computer instruction is stored in the computer-readable storage medium, and when the computer instruction runs on a computer device, the computer device is enabled to execute the technical solution of the path planning method in the foregoing embodiment.
The embodiment of the present application further provides a computer program product, which includes a computer program, and the computer program is used for executing the technical solution of the path planning method in the foregoing embodiment when being executed by a processor.
The computer-readable storage medium described above may be implemented by any type of volatile or non-volatile memory device or combination thereof, such as Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic or optical disk. Readable storage media can be any available media that can be accessed by a general purpose or special purpose computer device.
It will be understood that the present disclosure is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.
Claims (11)
1. A path planning method for use with an autonomous vehicle, the autonomous vehicle comprising: a front vehicle body and a rear vehicle body, the method comprising:
acquiring operation information of a vehicle, wherein the operation information comprises: a steering angle of the front wheels of the vehicle, a hinge angle of the front body and the rear body, a length of the front body, a length of a hinge point to the rear axle of the vehicle, and a width of the vehicle;
determining a first constraint condition and a second constraint condition of the vehicle according to the running information, wherein the first constraint condition is a constraint item of a position relation between an outline and an obstacle when the vehicle runs, and the second constraint condition is a constraint item of a relative angle of the front vehicle body and the rear vehicle body;
determining a target constraint condition of the vehicle for a planned path according to the first constraint condition and the second constraint condition;
and determining the target path of the vehicle according to the target constraint condition, the environmental information and the mixed A star algorithm.
2. The method of claim 1, wherein the operational information further comprises: the number of commutations of the vehicle in the planned path, the heading angles of two waypoints of the vehicle in the planned path and the distance between the two waypoints, the method further comprising:
determining a third constraint condition of the vehicle according to the reversing times, wherein the third constraint condition is a constraint item of a reversing action of the vehicle in a planned path;
determining a fourth constraint condition of the vehicle according to the course angles of the two path points and the distance between the two path points, wherein the fourth constraint condition is a constraint item of the course angle change rate in the planned path of the vehicle;
and determining a target constraint condition of the vehicle for a planned path according to the first constraint condition, the second constraint condition, the third constraint condition and the fourth constraint condition.
3. The method according to claim 1 or 2, wherein said determining a first constraint of the vehicle based on said operation information comprises:
determining a first distance from the outer edge of the vehicle to a center of rotation of the vehicle based on the length of the front body and the articulation angle;
determining a second distance of the inner edge of the vehicle to a center of rotation of the vehicle based on a length of a hinge point to the rear axle of the vehicle, the vehicle width, and the hinge angle;
determining the width of the vehicle driving area according to the first distance and the second distance;
and determining a first constraint condition of the vehicle according to the position of the obstacle and the width of the vehicle in a planned path.
4. The method according to claim 1 or 2, wherein said determining a second constraint of the vehicle from the operation information comprises:
and determining the second constraint condition according to the articulation angle, a first preset articulation threshold, a second preset articulation threshold, a third preset articulation threshold and the correlation coefficient of the articulation angle, wherein the second preset articulation threshold is greater than the first preset articulation threshold and smaller than the third preset articulation threshold, and the first preset articulation threshold is greater than 0.
5. The method of claim 3, wherein prior to said obtaining operational information of the vehicle, the method further comprises:
establishing a coordinate system by taking the vertex of the hinged angle as an origin and taking a line of the rotating center passing through the origin as a vertical coordinate axis;
acquiring a first course angle of the front vehicle body and a second course angle of the rear vehicle body, and determining a quadrant pointed by the first course angle and a quadrant pointed by the second course angle, wherein the quadrants comprise: a first quadrant, a second quadrant, a third quadrant, or a fourth quadrant;
and determining the articulation angle according to the relation between the quadrant pointed by the first course angle and the quadrant pointed by the second course angle.
6. The method according to claim 2, wherein the determining a third constraint condition of the vehicle according to the reversing times, the third constraint condition being a constraint term of a reversing action of the vehicle in a planned path, comprises:
and determining the third constraint condition according to the reversing times and a preset reversing basic value.
7. The method of claim 2, wherein determining a fourth constraint for the vehicle based on the heading angles of the two waypoints and the distance between the two waypoints comprises:
determining a correlation coefficient of the course angles of the two waypoints and the distance between the two waypoints according to the course angles of the two waypoints and the distance between the two waypoints;
and determining the fourth constraint condition according to the correlation coefficient.
8. A path planning apparatus for use with an autonomous vehicle, the autonomous vehicle comprising: a front vehicle body and a rear vehicle body, the apparatus comprising: the device comprises an acquisition module, a determination module and a processing module;
the acquisition module is used for acquiring the running information of the vehicle, and the running information comprises: a steering angle of the front wheels of the vehicle, a hinge angle of the front body and the rear body, a length of the front body, a length of a hinge point to the rear axle of the vehicle, and a width of the vehicle;
the determining module is used for determining a first constraint condition and a second constraint condition of the vehicle according to the running information, wherein the first constraint condition is a constraint item of a position relation between an outline and an obstacle when the vehicle runs, the second constraint condition is a constraint item of a relative angle between the front vehicle body and the rear vehicle body, and a target constraint condition of the vehicle for a planned path is determined according to the first constraint condition and the second constraint condition;
and the processing module is used for determining the target path of the vehicle according to the target constraint condition, the environmental information and the mixed A star algorithm.
9. An autonomous vehicle comprising: a processor, a memory and computer program instructions stored on the memory and executable on the processor, wherein the processor implements the path planning method according to any of claims 1 to 7 when executing the computer program instructions.
10. A computer-readable storage medium having computer-executable instructions stored thereon, which when executed by a processor, are configured to implement a path planning method according to any one of claims 1 to 7.
11. A computer program product comprising a computer program for implementing a path planning method according to any one of claims 1 to 7 when the computer program is executed by a processor.
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| CN202111095214.8A CN113848898A (en) | 2021-09-17 | 2021-09-17 | Path planning method, device, automatic driving vehicle and storage medium |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114719875A (en) * | 2022-03-10 | 2022-07-08 | 阿波罗智能技术(北京)有限公司 | Automatic driving path planning method and device, electronic equipment, medium and vehicle |
| CN117533317A (en) * | 2023-12-12 | 2024-02-09 | 北京斯年智驾科技有限公司 | Tractor reversing path smoothing method, system, device and storage medium |
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2021
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114719875A (en) * | 2022-03-10 | 2022-07-08 | 阿波罗智能技术(北京)有限公司 | Automatic driving path planning method and device, electronic equipment, medium and vehicle |
| CN114719875B (en) * | 2022-03-10 | 2023-05-05 | 阿波罗智能技术(北京)有限公司 | Automatic driving path planning method and device, electronic equipment, medium and vehicle |
| CN117533317A (en) * | 2023-12-12 | 2024-02-09 | 北京斯年智驾科技有限公司 | Tractor reversing path smoothing method, system, device and storage medium |
| CN117533317B (en) * | 2023-12-12 | 2024-05-17 | 北京斯年智驾科技有限公司 | Tractor reversing path smoothing method, system, device and storage medium |
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