CN111301409A - Parking path planning method and device, vehicle and storage medium - Google Patents

Parking path planning method and device, vehicle and storage medium Download PDF

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Publication number
CN111301409A
CN111301409A CN202010166385.4A CN202010166385A CN111301409A CN 111301409 A CN111301409 A CN 111301409A CN 202010166385 A CN202010166385 A CN 202010166385A CN 111301409 A CN111301409 A CN 111301409A
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point
parking
target
path
vehicle
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李超
杜建宇
刘斌
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FAW Group Corp
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FAW Group Corp
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Priority to CN202010166385.4A priority Critical patent/CN111301409A/en
Publication of CN111301409A publication Critical patent/CN111301409A/en
Priority to PCT/CN2021/079540 priority patent/WO2021180035A1/en
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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units
    • B60W30/08—Active safety systems predicting or avoiding probable or impending collision or attempting to minimise its consequences
    • B60W30/095—Predicting travel path or likelihood of collision
    • B60W30/0956—Predicting travel path or likelihood of collision the prediction being responsive to traffic or environmental parameters
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units
    • B60W30/06—Automatic manoeuvring for parking
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S15/00—Systems using the reflection or reradiation of acoustic waves, e.g. sonar systems
    • G01S15/88—Sonar systems specially adapted for specific applications
    • G01S15/93—Sonar systems specially adapted for specific applications for anti-collision purposes
    • G01S15/931—Sonar systems specially adapted for specific applications for anti-collision purposes of land vehicles
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2520/00—Input parameters relating to overall vehicle dynamics
    • B60W2520/06—Direction of travel
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2530/00—Input parameters relating to vehicle conditions or values, not covered by groups B60W2510/00 or B60W2520/00
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2540/00—Input parameters relating to occupants
    • B60W2540/18—Steering angle
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S15/00—Systems using the reflection or reradiation of acoustic waves, e.g. sonar systems
    • G01S15/88—Sonar systems specially adapted for specific applications
    • G01S15/93—Sonar systems specially adapted for specific applications for anti-collision purposes
    • G01S15/931—Sonar systems specially adapted for specific applications for anti-collision purposes of land vehicles
    • G01S2015/932—Sonar systems specially adapted for specific applications for anti-collision purposes of land vehicles for parking operations

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  • Engineering & Computer Science (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Automation & Control Theory (AREA)
  • Transportation (AREA)
  • Mechanical Engineering (AREA)
  • Physics & Mathematics (AREA)
  • Acoustics & Sound (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • General Physics & Mathematics (AREA)
  • Control Of Driving Devices And Active Controlling Of Vehicle (AREA)
  • Traffic Control Systems (AREA)

Abstract

The invention discloses a parking path planning method, a parking path planning device, a vehicle and a storage medium. The method comprises the following steps: determining a starting point and a target point of a parking path on a pre-established parking scene coordinate system; under the condition that the target point is effective, determining whether a path from the starting point to the target point exists at the current state point of the target vehicle by utilizing an RS geometric algorithm; when a path from a starting point to a target point exists, performing collision detection and cost calculation on each planned parking path; when no collision-free parking path exists, determining an alternative state point set of the target vehicle by using a hybrid A star algorithm; and performing collision detection and cost calculation on each candidate state point in the candidate state point set until the output cost is lowest, no collision occurs, and the state point reaches the target point. According to the embodiment of the invention, the RS geometric algorithm is spliced in the parking path searching process by using the hybrid A star algorithm, so that the path searching calculation speed is increased, and the parking path searching real-time performance is ensured.

Description

Parking path planning method and device, vehicle and storage medium
Technical Field
The embodiment of the invention relates to parking technologies, in particular to a parking path planning method, a parking path planning device, a vehicle and a storage medium.
Background
With the increasing number of vehicles, automatic parking can effectively solve the problem of difficult parking, and path planning is an important step of automatic parking.
At present, path planning methods are various, a part of the methods are based on a geometric mode, an RS (Reed-Shepp) algorithm is taken as an example, the mode is mostly a parking path designed for a specific parking scene, scene limitation exists, the method cannot be applied to all parking types, and a part of scenes may not plan the parking path, so that the parking failure is caused; the other method is based on a search mode, for example, a hybrid star A is taken as an example, the method can search required parking paths for various parking scenes, but is limited by the limitation of calculation time and resources, so that the real-time performance is poor, and the method cannot be transplanted to a product controller.
Disclosure of Invention
In view of this, the invention provides a parking path planning method, a parking path planning device, a vehicle and a storage medium, which improve the calculation speed of path search and ensure the real-time performance of path planning.
In one embodiment, an embodiment of the present invention provides a parking path planning method, including:
determining a starting point and a target point of a parking path on a pre-established parking scene coordinate system;
under the condition that the target point is effective, determining whether a path from the starting point to the target point exists at the current state point of the target vehicle by utilizing an RS geometric algorithm;
under the condition that the path from the starting point to the target point exists, performing collision detection and cost calculation on each planned parking path;
under the condition that no parking path without collision exists, determining a set of alternative state points of the target vehicle by using a hybrid A star algorithm;
and performing collision detection and cost calculation on each candidate state point in the candidate state point set until the output cost is lowest, no collision occurs, and the state point of the target point is reached.
In an embodiment, an embodiment of the present invention further provides a parking path planning apparatus, including:
the parking system comprises a first determining module, a second determining module and a control module, wherein the first determining module is used for determining a starting point and a target point of a parking path on a pre-established parking scene coordinate system;
the second determination module is used for determining whether a path from the starting point to the target point exists at the current state point of the target vehicle by utilizing an RS geometric algorithm under the condition that the target point is effective;
the first detection calculation module is used for performing collision detection and cost calculation on each planned parking path under the condition that a path from the starting point to the target point exists;
the third determination module is used for determining the candidate state point set of the target vehicle by using a hybrid A star algorithm under the condition that no collision-free parking path exists;
and the second detection calculation module is used for performing collision detection and cost calculation on each candidate state point in the candidate state point set until the output cost is lowest, no collision occurs, and the state point of the target point is reached.
In one embodiment, an embodiment of the present invention further provides a vehicle, including: a memory, and one or more processors;
a memory for storing one or more programs;
when the one or more programs are executed by the one or more processors, the one or more processors implement the parking path planning method according to the first aspect.
In one embodiment, a computer-readable storage medium has stored thereon a computer program which, when executed by a processor, implements a parking path planning method according to the first aspect.
The method comprises the steps of determining a starting point and a target point of a parking path on a pre-established parking scene coordinate system; under the condition that the target point is effective, determining whether a path from the starting point to the target point exists at the current state point of the target vehicle by utilizing an RS geometric algorithm; under the condition that a path from a starting point to a target point exists, performing collision detection and cost calculation on each planned parking path; under the condition that no collision-free parking path exists, determining an alternative state point set of the target vehicle by using a hybrid A star algorithm; and performing collision detection and cost calculation on each candidate state point in the candidate state point set until the output cost is lowest, no collision occurs, and the state point of the target point is reached. According to the embodiment of the invention, the RS geometric algorithm is spliced in the parking path searching process by using the hybrid A star algorithm, so that the path searching calculation speed is increased, and the parking path searching real-time performance is ensured.
Drawings
Fig. 1 is a flowchart of a parking path planning method according to an embodiment of the present invention;
fig. 2 is a schematic diagram illustrating that a target point corresponds to a target parking space;
fig. 3 is a schematic diagram of displaying obstacle map information according to an embodiment of the present invention;
FIG. 4 is a schematic diagram illustrating establishment of a parking scene coordinate system according to an embodiment of the present invention;
FIG. 5 is a schematic diagram of a collision detection provided by an embodiment of the present invention;
FIG. 6 is a diagram illustrating a hybrid A star state update according to an embodiment of the present invention;
FIG. 7 is a schematic illustration showing a parking path planning result according to an embodiment of the present invention;
FIG. 8 is a flowchart of another parking path planning method provided by an embodiment of the present invention;
FIG. 9 is a schematic illustration of a parking path planning process provided by an embodiment of the present invention;
fig. 10 is a block diagram illustrating a parking path planning apparatus according to an embodiment of the present invention;
fig. 11 is a schematic hardware structure diagram of a vehicle according to an embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention. It should be further noted that, for the convenience of description, only some of the structures related to the present invention are shown in the drawings, not all of the structures.
Fig. 1 is a flowchart of a parking path planning method according to an embodiment of the present invention, which may be implemented by a parking path planning apparatus and is applicable to automatically planning a parking path for a vehicle, where the method may be implemented by hardware and/or software and may be generally integrated in a vehicle.
As shown in fig. 1, the method specifically includes the following steps:
and S110, determining a starting point and a target point of the parking path on a pre-established parking scene coordinate system.
In the embodiment, the parking scene coordinate system is used for determining the starting point and the target point of the parking path. The starting point of the parking path can be determined according to the current position automatically positioned by the GPS positioning module in the target vehicle, namely the starting point of the parking path is the current position point of the target vehicle; the target point of the parking path can be determined according to the target position to which the target vehicle is to arrive, namely the target point of the parking path is the position point of the target parking space of the target vehicle. Of course, in order to more accurately determine the starting point and the target point of the parking path, in an embodiment, the center point of the rear axle corresponding to the current position point of the target vehicle may be used as the starting point, and the geometric center point of the position point of the target parking space to which the target vehicle will arrive may be used as the target point.
In the actual operation process, the target point can also be determined in other manners. For example, the user may manually click on the determined coordinate point directly on the parking scene coordinate system, and use the coordinate point as the coordinates of the target point.
And S120, under the condition that the target point is effective, determining whether the current state point of the target vehicle has a path from the starting point to the target point by utilizing an RS geometric algorithm.
In an embodiment, the target point is valid, meaning that the target vehicle can be parked normally. The method for determining whether the target point is valid includes: and determining whether the target parking space corresponding to the target point can park the target vehicle. For example, assuming that the length and width of the target vehicle are 5m and 2m, respectively, and the standard length and standard width of the target parking space corresponding to the target point are 6m and 2.5m, respectively, but since there are vehicles parked in the parking spaces on both sides of the target parking space, and the parking spaces are inclined to some extent, the current length and width of the target parking space are 4.5m and 1.9m, respectively, it is determined that the target parking space cannot be normally parked in the target vehicle, i.e., the target point is invalid.
Fig. 2 is a schematic diagram illustrating that a target point corresponds to a target parking space. In the embodiment, the parking spaces can be respectively vertical parking spaces, horizontal parking spaces and inclined parking spaces. As shown in fig. 2, the standard lengths and widths of the parking spaces in different directions are both 6m and 2.5 m. It can be understood that, in the case where the length and width of the target slot satisfy 6m and 2.5m, the target slot is determined to be valid, i.e., the target point is valid. Of course, in the actual operation process, whether the target parking space is effective or not can be determined according to the actual length and width of the target vehicle. For example, the target vehicle is a mini-type QQ vehicle, and even when the length and width of the target slot do not satisfy 6m and 2.5m, the target vehicle can park in the target slot, that is, it can be determined that the target point is valid.
In the embodiment, the current state point of the target vehicle refers to a state in which the target vehicle is at the current time. For example, the current state points may include: the current position point, the current steering wheel angle, the current vehicle speed, etc. In an embodiment, an RS geometric algorithm is used to determine whether a path can be planned between a starting point and a target point of a target vehicle. The RS geometric algorithm is a route planning method based on the geometric algorithm, and can rapidly plan a path from a start point to an end point (i.e., a target point).
And S130, under the condition that the path from the starting point to the target point exists, performing collision detection and cost calculation on each planned parking path.
In the actual operation process, the path planned by the RS geometric algorithm does not take the obstacle information into account. Therefore, collision detection and cost calculation are required for the path planned by the RS. It can be understood that, in the case where a route from a start point to a target point can be planned using the RS geometric algorithm, collision detection and cost calculation are required for each planned parking route. And if at least two collision-free paths exist, outputting the path with the minimum cost as a parking path.
And S140, under the condition that no collision-free parking path exists, determining the candidate state point set of the target vehicle by using the hybrid A star algorithm.
In the embodiment, when there is no non-collision parking path among all paths drawn by the RS geometric algorithm, the parking path update is performed by using the hybrid a-star algorithm. Specifically, the set of candidate state points of the target vehicle may be determined according to the ackermann steering equation. The set of candidate state points refers to a combination of a plurality of candidate state points determined according to the ackermann steering direction. At least two candidate state points are included in the set of candidate state points.
S150, performing collision detection and cost calculation on each candidate state point in the candidate state point set until the output cost is lowest, no collision occurs, and the state point of the target point is reached.
In the embodiment, after a plurality of candidate state points are obtained, collision detection and cost calculation are required to be sequentially carried out on each candidate state point, and if the candidate state points have collision, the candidate state points are skipped; if all the alternative state points collide, stopping calculation and directly outputting no solution; and if the alternative state points are not collided, sequentially carrying out cost calculation on the alternative state points without collision, calculating and selecting the cost for jumping from the current state point to the alternative state point, updating the current state point of the target vehicle after the detection of all the alternative state points is finished, and selecting the state point with the lowest cost as the next state to carry out state updating.
Then, judging whether the updated current state point of the target vehicle can reach the target point, if so, terminating the calculation, and directly outputting the result of the hybrid A star search; if the target point cannot be reached, repeatedly executing S120, namely determining whether a collision-free parking path exists at the current state point after the target vehicle is updated by utilizing an RS algorithm, if so, terminating the hybrid A star algorithm, and splicing the path with the lowest cost calculated by the RS algorithm and the result of hybrid A star search together for output; if there is no collision-free parking path, S120 is continuously executed until a state point that is collision-free and can reach the target point is obtained.
According to the technical scheme, a starting point and a target point of a parking path are determined on a pre-established parking scene coordinate system; and then, based on the starting point and the target point of the target vehicle, a parking path is searched by using a hybrid A star algorithm, and the parking path is subjected to collision detection, so that collision avoidance of the planned parking path can be realized under the condition that the parking path meets vehicle constraints. Meanwhile, in the process of searching the path by using the hybrid A star algorithm, the RS geometric algorithm is spliced, the calculation speed of path search is improved, and the real-time property of parking path search is ensured.
In one embodiment, before the pre-established parking scene coordinate system, the method further includes: and determining the parking type and the target parking space position of the target vehicle under the condition that the parking function of the target vehicle is started.
In an embodiment, the parking type refers to a type of a target parking space corresponding to a target point to be reached by a target vehicle. Exemplary parking types may include: vertical parking spaces, horizontal parking spaces and inclined parking spaces. The target parking space position refers to a position of a target parking space corresponding to a target point to which the target vehicle arrives. In an embodiment, the target parking space position includes a target point, that is, the target point may be a geometric center point of the target parking space position.
Of course, in order to achieve automatic parking of the target vehicle, a parking function needs to be installed and activated in the target vehicle.
In one embodiment, after determining the starting point and the target point of the parking path, determining whether the current state point of the target vehicle has a path from the starting point to the target point by using an RS geometric algorithm, further includes: establishing barrier map information according to the ultrasonic radar information in the parking space searching process; determining a berthable area and an obstacle coordinate point of the target vehicle according to the obstacle map information.
In the embodiment, the obstacle map information refers to information including positions of all obstacles from the start point to the target point. In the embodiment, the position information of all obstacles may be determined by using the ultrasonic radar information in the parking space searching process, and of course, in the actual operation process, the position information of the obstacles may also be determined by using other positioning methods, which is not limited. In an embodiment, after the obstacle map information is established, the user may see the position information of the obstacle on the obstacle map, and the processor of the vehicle may automatically detect and determine the parkable area of the target vehicle and the obstacle coordinate point according to the obstacle map information. Herein, the berthable region refers to a region where the target vehicle can travel but cannot park. Fig. 3 is a schematic diagram illustrating display of obstacle map information according to an embodiment of the present invention. As shown in fig. 3, in the parking space searching process, an obstacle map may be established according to the ultrasonic radar information, and a parking available area and a position of the obstacle may be displayed on the obstacle map, so as to facilitate subsequent determination of a target point of the target vehicle and collision detection.
In one embodiment, the process of establishing the parking scene coordinate system includes: obtaining current parking parameters of a target vehicle, wherein the current parking parameters comprise the following parameters: the minimum turning radius of the vehicle, the distance from the midpoint of the rear axle to the front suspension, the distance from the midpoint of the rear axle to the rear suspension, the width of the vehicle and the wheelbase; and establishing a corresponding parking scene coordinate system according to the current parking parameters, the geometric central point of the target vehicle and the direction pointed by the vehicle head.
In an embodiment, the current parking parameters of the target vehicle may include the following: minimum turning radius R of vehicle and distance L from midpoint of rear axle to front suspensionfDistance L from the midpoint of the rear axle to the rear overhangrVehicle width LwAnd a wheel base L. Illustratively, fig. 4 is a schematic diagram of establishing a parking scene coordinate system according to an embodiment of the present invention. As shown in fig. 4, the target vehicle is operated with the parking function onThe geometric center point is used as a coordinate origin, the direction of a longitudinal axis pointed by the vehicle head is an x axis, and the left direction perpendicular to the x axis is a y axis, so that a right-hand coordinate system is established. Then, the geometric center point of the target parking space is used as an end point, and the coordinates of the target point (namely the coordinates of the end point) are determined.
In the embodiment, in the process of planning the parking path, the parking path is planned by using the coordinates of the center point of the rear axle of the target vehicle, that is, at the time when the parking function of the target vehicle is turned on, the center point of the rear axle of the target vehicle may be used as a starting position (i.e., a starting point) and a position designated by the driver may be used as an ending position (i.e., a target point).
In one embodiment, the process of collision detection for each planned parking path includes: determining four boundary points of a target vehicle; and determining whether a path point colliding with the obstacle exists in each parking path according to the distances between the four boundary points and the obstacle coordinate point.
In the embodiment, the collision detection refers to performing collision detection on the planned path points in sequence, and checking whether each path point collides with an obstacle. In actual operation, collision detection can be performed in various ways. Illustratively, fig. 5 is a schematic diagram of collision detection provided by an embodiment of the present invention. As shown in fig. 5, the target vehicle is simplified into a rectangle, a, B, C, and D are the coordinates of four vertices (i.e. four boundary points) of the target vehicle, Ob is the obstacle point in the obstacle map, and its coordinate is (Ob)i，Obj)，i，j∈[1,2，......n]If the Ob point satisfies
Figure BDA0002407609910000091
It indicates that the Ob point has a collision with the target vehicle, i.e., the target vehicle has a collision with an obstacle.
In one embodiment, the process of performing a cost calculation for each planned parking path or alternative status point includes: acquiring a steering wheel angle of a target vehicle, a steering wheel angle variable quantity and a current distance between an obstacle and the target vehicle; and determining the cost of the parking path or the alternative state point according to the steering wheel angle of the target vehicle, the steering wheel angle variable quantity, the current distance between the obstacle and the target vehicle, and a preset steering wheel weight coefficient, a steering wheel change weight system and a weight coefficient far away from the obstacle.
In an embodiment, the cost calculation is used for selecting and evaluating multiple alternative collision-free paths, i.e. the lower the cost, the more reasonable the path is. Illustratively, different weight coefficients are set for the planned route points, such as a shift coefficient weight, a left-right conversion coefficient weight, and a weight close to an obstacle, the cost of each route point is calculated, and the route point with the lowest cost is selected as the optimal route. Illustratively, the cost calculation formula for each waypoint is as follows:
cstt＝cstt-1+κ1*δ+κ2*Δδ+κ3/Dis
where cst represents the cost of a waypoint, κ1Indicates the weight coefficient, k, of the steering wheel2Weight coefficient, k, representing steering wheel variation3The weight coefficient indicates the distance to an obstacle, δ indicates the steering angle of the steering wheel, Δ δ indicates the amount of change in the steering angle of the steering wheel, and Dis indicates the distance between the obstacle and the target vehicle. And calculating the cost of the path points by using the formula, and selecting the path with the optimal cost from the alternative paths.
In one embodiment, determining the set of candidate state points for the target vehicle using a hybrid a-star algorithm comprises: acquiring the control quantity and the state quantity of a target vehicle in the searching and updating process by using the hybrid A star algorithm; the control amount includes: direction of travel and steering wheel angle; the state quantities include: coordinates and course angles of the middle point of the rear axle; determining at least two corresponding alternative state points according to the control quantity, the speed of the center of the rear axle of the vehicle and the wheel base of the vehicle; combining at least two candidate state points into a corresponding set of candidate state points.
In the embodiment, if the current position has no non-collision path, the path point is searched and updated by using the hybrid A star algorithm, and the selected control quantity is the advancing direction and the steering wheel rotation angle in the searching and updating process by using the hybrid A star algorithm; the state quantity selects the coordinate and the course angle of the midpoint of the rear axle of the target vehicle, the vehicle state is updated according to different control quantity inputs and by combining an Ackerman steering equation, the next state of the vehicle is calculated, and the next state of the target vehicle is limited by the steering angle (namely the steering wheel angle) of the vehicle in the updating process by using the hybrid A star. Exemplarily, fig. 6 is a schematic diagram of a hybrid a star state update provided by an embodiment of the present invention. As shown in fig. 6, the state of the target vehicle is updated by using ackermann steering principle, so as to ensure that the next updated state of the target vehicle meets the constraint of the target vehicle. It is understood that the subject vehicle may be traveling straight (i.e., a'), turning left (a), or turning right (i.e., a ").
Figure BDA0002407609910000111
Figure BDA0002407609910000112
Figure BDA0002407609910000113
In the formula, L represents a vehicle wheel base, v represents a speed of a center of a rear axle of the vehicle, x, y represent coordinates of a rear axle end point of the vehicle, θ represents a heading angle of the vehicle, and δ represents a front wheel turning angle of the vehicle, respectively. And repeating S120 all the time in the searching process, detecting whether the updated position has a collision-free path, if so, terminating the mixed A star algorithm, and splicing the searching result of the mixed A star and the RS curve together for outputting. Fig. 7 is a schematic diagram illustrating a parking path planning result according to an embodiment of the present invention. As shown in fig. 7, the line is the result of the hybrid a-star algorithm search, and the dotted line is the path calculated by the RS geometric algorithm; otherwise, searching until the ending point by using the hybrid A star algorithm. In the hybrid A star algorithm searching process, collision detection needs to be carried out on the states and the cost of the selectable state needs to be calculated every time the states are updated, and the states which are free of collision and have the minimum cost are selected as the next states of the hybrid A star.
Fig. 8 is a flowchart of another parking path planning method according to an embodiment of the present invention. As shown in fig. 8, the present embodiment includes the following steps:
and S210, starting a parking function.
And S220, determining the parking type and searching the parking space.
And S230, determining the position of the target parking space.
And S240, establishing a parking scene coordinate system, and determining coordinates of a target point and obstacle map information.
S250, judging whether the target point is valid or not, if so, executing S260; if not, S2120 is executed.
S260, whether the target point is reached or not is judged, if yes, S2110 is executed; if not, go to S270.
S270, judging whether the RS geometric algorithm has a solution or not, if so, executing S280; if not, S2130 is executed.
S280, detecting whether collision occurs to the obstacle or not, and if so, executing S2130; if not, then proceed to step S290.
S290, judging whether a plurality of collision-free paths exist or not, if so, executing S2100; if not, S2130 is executed.
And S2100, outputting the path with the lowest cost.
And S2110, path splicing optimization.
And S2120, outputting a parking path.
And S2130, updating the state by using a hybrid A star algorithm.
In the embodiment, a parking function of a target vehicle is started, and a parking type and a target parking space position are determined; establishing a parking scene coordinate system according to the current parking parameters of the target vehicle, determining a starting point and a target point of a parking path plan, and determining a parking available area and obstacle information of the vehicle according to the obstacle map information; judging whether the target point is valid, if not, terminating the parking path planning, and if so, continuing; judging whether a path from a starting point to a target point exists at a current state point of the target vehicle by utilizing an RS geometric algorithm; if the path point exists, collision detection and cost calculation are required to be carried out on the planned path point, if the path point does not collide, the calculation is stopped, the path with the lowest cost is directly output, and if the path point does not collide, the calculation is continued; and updating the path state points by using the mixed A star, determining the alternative state points of the vehicle according to the Aceman steering equation, and then sequentially performing collision detection and cost calculation on the alternative state point set in the searching process. If the alternative state points have collision, skipping the state points, and if all the alternative state points have collision, terminating the calculation and directly outputting the solution-free state points; and if the alternative state points are not collided, sequentially carrying out cost calculation on the alternative state points without collision, calculating and selecting the cost for jumping from the current state to the alternative state points, updating the current state after the detection of all the alternative state points is finished, selecting the state point with the lowest cost as the next state, and updating the state. And judging whether the current state point reaches the target point. If the target point is reached, stopping calculation, directly outputting the result of the mixed A star search, if the target point is not reached, then based on the current state, repeatedly using the RS geometric algorithm to perform the judgment process, namely judging whether the current position can plan the collision-free path from the current position to the target point by using the RS geometric algorithm once, if the collision-free path exists, stopping the mixed A star algorithm, and splicing the path with the lowest cost calculated by the RS geometric algorithm and the result of the mixed A star search together for output; otherwise, the process of judging by utilizing the RS geometric algorithm is continued. The embodiment can ensure that the paths for realizing collision avoidance under the condition of meeting vehicle constraints can be planned under various working conditions, and in addition, the RS geometric algorithm is spliced, so that the calculation speed of path search is improved, and the real-time performance of path planning is ensured.
Fig. 9 is a schematic illustration showing a parking path planning process according to an embodiment of the present invention. As shown in fig. 9, it is assumed that a starting point of a parking path is determined as a and a target point is determined as B on a parking scene coordinate system established in advance. Under the condition that the target point B is valid, determining that a path from a starting point to the target point exists at the current state point of the target vehicle by using an RS geometric algorithm, namely a dotted line shown in FIG. 9, performing collision detection on the planned path, if the path has a collision condition with an obstacle, determining a candidate state point set of the target vehicle by using a hybrid A-star algorithm, namely candidate state points C, C ', C and C' shown in FIG. 9, judging whether a path can be planned between each candidate state point and the target point B by using the RS geometric algorithm, and if the path cannot be planned between each candidate state point and the target point B, selecting an optimal state point (for example, C) from the four candidate state points; then based on the point C, determining whether a path to a target point can be planned or not by using an RS geometric algorithm, and if the path cannot be planned; the hybrid a-star algorithm is again used for state updating, e.g. to obtain the alternative state points D, D ', D "', then, whether a path can be planned between each candidate state point (D, D ', D') and the target point B by using the RS geometric algorithm is judged, if not, then the optimal state point (for example, D ') is selected from the four candidate state points, and so on until the point E' is updated, the RS geometric algorithm can plan the path to the target point B, a, C, D 'and E' are spliced to the path output by the RS algorithm to obtain a final parking path, thereby ensuring that the collision-avoidance path can be planned under various working conditions under the condition of meeting the vehicle constraint, and the path points obtained by the RS geometric algorithm are spliced, so that the calculation speed of path search is improved, and the real-time performance of path planning is ensured.
Fig. 10 is a block diagram of a parking path planning apparatus according to an embodiment of the present invention, which is suitable for automatically planning a parking path for a vehicle, and which may be implemented by hardware/software and may be generally integrated in a vehicle. As shown in fig. 10, the apparatus includes: a first determination module 310, a second determination module 320, a first detection calculation module 330, a third determination module 340, and a second detection calculation module 350.
The first determining module 310 is configured to determine a starting point and a target point of a parking path on a pre-established parking scene coordinate system;
a second determining module 320, configured to determine whether a path from the starting point to the target point exists at the current state point of the target vehicle by using an RS geometric algorithm if the target point is valid;
the first detection calculation module 330 is configured to perform collision detection and cost calculation on each planned parking path in the presence of a path from a starting point to a target point;
a third determining module 340, configured to determine, by using a hybrid a-star algorithm, a set of candidate state points of the target vehicle when there is no parking path without collision;
and a second detection calculation module 350, configured to perform collision detection and cost calculation on each candidate state point in the candidate state point set until the output cost is lowest, no collision occurs, and a state point of the target point is reached.
According to the technical scheme of the embodiment, a starting point and a target point of a parking path are determined on a pre-established parking scene coordinate system; and then, based on the starting point and the target point of the target vehicle, a parking path is searched by using a hybrid A star algorithm, and the parking path is subjected to collision detection, so that collision avoidance of the planned parking path can be realized under the condition that the parking path meets vehicle constraints. Meanwhile, in the process of searching the path by using the hybrid A star algorithm, the RS geometric algorithm is spliced, the calculation speed of path search is improved, and the real-time property of parking path search is ensured.
In one embodiment, the parking path planning apparatus further includes:
and the fourth determining module is used for determining the parking type and the position of the target parking space of the target vehicle under the condition that the parking function of the target vehicle is started before the pre-established parking scene coordinate system.
In one embodiment, the parking path planning apparatus further includes:
the system comprises an establishing module, a parking position searching module and a parking position searching module, wherein the establishing module is used for establishing barrier map information according to ultrasonic radar information in the parking position searching process after determining a starting point and a target point of a parking path and before determining whether a path from the starting point to the target point exists at a current state point of a target vehicle by utilizing an RS geometric algorithm;
and the fifth determination module is used for determining the berthable area of the target vehicle and the obstacle coordinate point according to the obstacle map information.
In one embodiment, the process of establishing the parking scene coordinate system includes: obtaining current parking parameters of a target vehicle, wherein the current parking parameters comprise the following parameters: the minimum turning radius of the vehicle, the distance from the midpoint of the rear axle to the front suspension, the distance from the midpoint of the rear axle to the rear suspension, the width of the vehicle and the wheelbase; and establishing a corresponding parking scene coordinate system according to the current parking parameters, the geometric central point of the target vehicle and the direction pointed by the vehicle head.
In one embodiment, the process of collision detection for each planned parking path includes: determining four boundary points of a target vehicle; and determining whether a path point colliding with the obstacle exists in each parking path according to the distances between the four boundary points and the obstacle coordinate point.
In one embodiment, the process of performing a cost calculation for each planned parking path or alternative status point includes: acquiring a steering wheel angle of a target vehicle, a steering wheel angle variable quantity and a current distance between an obstacle and the target vehicle; and determining the cost of the parking path or the alternative state point according to the steering wheel angle of the target vehicle, the steering wheel angle variable quantity, the current distance between the obstacle and the target vehicle, and a preset steering wheel weight coefficient, a steering wheel change weight system and a weight coefficient far away from the obstacle.
In one embodiment, determining the set of candidate state points for the target vehicle using a hybrid a-star algorithm comprises: acquiring the control quantity and the state quantity of a target vehicle in the searching and updating process by using the hybrid A star algorithm; the control amount includes: direction of travel and steering wheel angle; the state quantities include: coordinates and course angles of the middle point of the rear axle; determining at least two corresponding alternative state points according to the control quantity, the speed of the center of the rear axle of the vehicle and the wheel base of the vehicle; combining at least two candidate state points into a corresponding set of candidate state points.
The parking path planning device can execute the parking path planning method provided by any embodiment of the invention, and has corresponding functional modules and beneficial effects of the execution method.
Fig. 11 is a schematic hardware structure diagram of a vehicle according to an embodiment of the present invention. As shown in fig. 11, a vehicle according to an embodiment of the present invention includes: a memory 410, and one or more processors 420. The number of the processors 420 in the vehicle may be one or more, one processor 420 is taken as an example in fig. 11, the processor 420 and the memory 410 in the vehicle may be connected through a bus or in other manners, and the connection through the bus is taken as an example in fig. 11.
The memory 410 in the vehicle, as a computer-readable storage medium, may be used to store one or more programs, which may be software programs, computer-executable programs, and modules, corresponding to program instructions/modules of the parking path planning method provided in the embodiment of the present invention (for example, the modules in the parking path planning apparatus shown in fig. 10 include the first determining module 310, the second determining module 320, the first detecting calculating module 330, the third determining module 340, and the second detecting calculating module 350). The processor 410 executes various functional applications and data processing of the device by running software programs, instructions and modules stored in the memory 410, so as to implement the parking path planning method in the above-described method embodiment.
The memory 410 may include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data created according to use of a device configured in the device, and the like. Further, the memory 410 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid state storage device. In some examples, memory 410 may further include memory located remotely from processor 420, which may be connected to configured ones of the devices over a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
In one embodiment, a vehicle is provided comprising a memory 410 and a processor 420, the memory 410 storing a computer program, the processor 420 implementing the following steps when executing the computer program:
determining a starting point and a target point of a parking path on a pre-established parking scene coordinate system; under the condition that the target point is effective, determining whether a path from the starting point to the target point exists at the current state point of the target vehicle by utilizing an RS geometric algorithm; under the condition that a path from a starting point to a target point exists, performing collision detection and cost calculation on each planned parking path; under the condition that no collision-free parking path exists, determining an alternative state point set of the target vehicle by using a hybrid A star algorithm; and performing collision detection and cost calculation on each candidate state point in the candidate state point set until the output cost is lowest, no collision occurs, and the state point of the target point is reached.
The vehicle can execute the picture processing method provided by any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the execution method.
An embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements a parking path planning method provided by an embodiment of the present invention, where the method includes: determining a starting point and a target point of a parking path on a pre-established parking scene coordinate system; under the condition that the target point is effective, determining whether a path from the starting point to the target point exists at the current state point of the target vehicle by utilizing an RS geometric algorithm; under the condition that a path from a starting point to a target point exists, performing collision detection and cost calculation on each planned parking path; under the condition that no collision-free parking path exists, determining an alternative state point set of the target vehicle by using a hybrid A star algorithm; and performing collision detection and cost calculation on each candidate state point in the candidate state point set until the output cost is lowest, no collision occurs, and the state point of the target point is reached.
Computer storage media for embodiments of the invention may employ any combination of one or more computer-readable media. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Computer program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + +, or the like, as well as conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments illustrated herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in greater detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention, and the scope of the present invention is determined by the scope of the appended claims.

Claims (10)

1. A parking path planning method, comprising:
determining a starting point and a target point of a parking path on a pre-established parking scene coordinate system;
under the condition that the target point is effective, determining whether a path from the starting point to the target point exists at the current state point of the target vehicle by utilizing an RS geometric algorithm;
under the condition that the path from the starting point to the target point exists, performing collision detection and cost calculation on each planned parking path;
under the condition that no parking path without collision exists, determining a set of alternative state points of the target vehicle by using a hybrid A star algorithm;
and performing collision detection and cost calculation on each candidate state point in the candidate state point set until the output cost is lowest, no collision occurs, and the state point of the target point is reached.
2. The method of claim 1, further comprising, prior to the pre-established parking scene coordinate system: and determining the parking type and the target parking space position of the target vehicle under the condition that the parking function of the target vehicle is started.
3. The method of claim 1, wherein after said determining a starting point and a target point of the parking path, said determining whether the current state point of the target vehicle has a path from the starting point to the target point using the RS geometry algorithm further comprises:
establishing barrier map information according to the ultrasonic radar information in the parking space searching process;
determining a berthable area and an obstacle coordinate point of the target vehicle according to the obstacle map information.
4. The method of claim 1, wherein the establishing of the parking scene coordinate system comprises:
obtaining current parking parameters of the target vehicle, wherein the current parking parameters comprise the following parameters: the minimum turning radius of the vehicle, the distance from the midpoint of the rear axle to the front suspension, the distance from the midpoint of the rear axle to the rear suspension, the width of the vehicle and the wheelbase;
and establishing a corresponding parking scene coordinate system according to the current parking parameters, the geometric central point of the target vehicle and the direction pointed by the vehicle head.
5. A method according to claim 1 or 3, wherein the process of collision detection for each planned parking path comprises:
determining four boundary points of the target vehicle;
and determining whether a path point colliding with the obstacle exists in each parking path according to the distances between the four boundary points and the obstacle coordinate point.
6. The method of claim 1, wherein the process of performing a cost calculation for each planned parking path or alternative state point comprises:
acquiring a steering wheel angle, a steering wheel angle variable quantity and a current distance between an obstacle and the target vehicle of the target vehicle;
and determining the cost of the parking path or the alternative state point according to the steering wheel angle of the target vehicle, the steering wheel angle variable quantity, the current distance between the obstacle and the target vehicle, a preset steering wheel weight coefficient, a steering wheel change weight system and a weight coefficient far away from the obstacle.
7. The method of claim 1, wherein determining the set of candidate state points for the target vehicle using a hybrid a-star algorithm comprises:
acquiring the control quantity and the state quantity of the target vehicle in the searching and updating process by using the hybrid A star algorithm; the control amount includes: direction of travel and steering wheel angle; the state quantities include: coordinates and course angles of the middle point of the rear axle;
determining at least two corresponding alternative state points according to the control quantity, the speed of the center of the rear axle of the vehicle and the wheel base of the vehicle;
and combining the at least two alternative state points into a corresponding alternative state point set.
8. A parking path planning apparatus, comprising:
the parking system comprises a first determining module, a second determining module and a control module, wherein the first determining module is used for determining a starting point and a target point of a parking path on a pre-established parking scene coordinate system;
the second determination module is used for determining whether a path from the starting point to the target point exists at the current state point of the target vehicle by utilizing an RS geometric algorithm under the condition that the target point is effective;
the first detection calculation module is used for performing collision detection and cost calculation on each planned parking path under the condition that a path from the starting point to the target point exists;
the third determination module is used for determining the candidate state point set of the target vehicle by using a hybrid A star algorithm under the condition that no collision-free parking path exists;
and the second detection calculation module is used for performing collision detection and cost calculation on each candidate state point in the candidate state point set until the output cost is lowest, no collision occurs, and the state point of the target point is reached.
9. A vehicle, characterized by comprising: a memory, and one or more processors;
a memory for storing one or more programs;
when executed by the one or more processors, cause the one or more processors to implement the method for parking path planning according to any of claims 1-7.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out a parking path planning method according to any one of claims 1 to 7.
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