CN109976329B - Planning method for vehicle obstacle avoidance and lane change path - Google Patents
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0212—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory
- G05D1/0214—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory in accordance with safety or protection criteria, e.g. avoiding hazardous areas
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0231—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means
- G05D1/0238—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using obstacle or wall sensors
- G05D1/024—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using obstacle or wall sensors in combination with a laser
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0231—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means
- G05D1/0246—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using a video camera in combination with image processing means
- G05D1/0253—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using a video camera in combination with image processing means extracting relative motion information from a plurality of images taken successively, e.g. visual odometry, optical flow
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0255—Control of position or course in two dimensions specially adapted to land vehicles using acoustic signals, e.g. ultra-sonic singals
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0257—Control of position or course in two dimensions specially adapted to land vehicles using a radar
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0276—Control of position or course in two dimensions specially adapted to land vehicles using signals provided by a source external to the vehicle
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0276—Control of position or course in two dimensions specially adapted to land vehicles using signals provided by a source external to the vehicle
- G05D1/0278—Control of position or course in two dimensions specially adapted to land vehicles using signals provided by a source external to the vehicle using satellite positioning signals, e.g. GPS
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0276—Control of position or course in two dimensions specially adapted to land vehicles using signals provided by a source external to the vehicle
- G05D1/028—Control of position or course in two dimensions specially adapted to land vehicles using signals provided by a source external to the vehicle using a RF signal
Abstract
The invention relates to the field of automatic control of intelligent automobiles, in particular to a planning method for an obstacle avoidance and lane change path of a vehicle, which obtains a starting point coordinate, a target point coordinate and a road course angle through corresponding equipment, wherein the starting point coordinate is a geodetic coordinate of a set distance of the current vehicle position along the driving direction, the target point coordinate is a geodetic coordinate of a position where a front obstacle endpoint deviates the sum of the width of the vehicle body and a set safe lateral distance in the lane change direction, the road course angle is a vehicle course angle after the vehicle reaches the target point coordinate, curve fitting is carried out according to the starting point coordinate, the target point coordinate and the road course angle to obtain the road change path from the starting point coordinate to the target point coordinate, the road change path of the vehicle is reasonably planned, and the problem that the automatic obstacle avoidance or the road change path is unreasonable in the automatic driving of the intelligent vehicle is solved.
Description
Technical Field
The invention relates to the field of automatic control of intelligent automobiles, in particular to a method for planning an obstacle avoidance and lane change path of a vehicle.
Background
The general situation of an intelligent vehicle is that advanced sensors, controllers, execution devices and the like are added on the basic structure of a common vehicle, and intelligent information exchange of the vehicle, the road, a driver and the like is realized through a vehicle-mounted sensing system and an information system, so that the vehicle has certain intelligent environment sensing capability, the path is identified, the current road condition is analyzed, the obstacle is detected by combining the position of the vehicle, real-time early warning is realized, or the vehicle is stopped and avoided in time according to the actual situation, the driving safety is improved, and a reasonable driving strategy is configured according to the path and the intention of the driver.
A patent document with a Chinese patent publication number of CN104407613B discloses a method for smoothly optimizing an obstacle avoidance path, which first obtains the range of an obstacle area; then, acquiring an initial node and a target node of the obstacle avoidance search path, and initially defining the initial node as a mark starting point and the target node as a mark end point; then obtaining coordinates of each point of a connecting line between the mark starting point and the mark end point; then, judging whether the redefined mark starting point is equal to the mark end point or not by judging whether the obtained point coordinate is located in the range of the obstacle area or not, and carrying out corresponding operation to obtain a smooth path; and finally, defining the obtained path starting node as a mark end point and the target node as a mark starting point, and performing judgment operation again to finally obtain the smoothly optimized obstacle avoidance path. The method can reduce the accumulated turning times in the obstacle avoidance search path, reduce the accumulated turning angle in the obstacle avoidance search path, and effectively reduce the length of the obstacle avoidance search path. However, the position coordinates of the target point of the vehicle cannot be determined according to the real-time road condition information, and meanwhile, although the obstacle avoidance path obtained through the smooth optimization by the method has less length of the obstacle avoidance search path, the reasonableness is poor for the vehicle driving, and certain influence is brought to the driving safety.
Disclosure of Invention
The invention aims to provide a method for planning an obstacle avoiding and road changing path of a vehicle, which is used for solving the problem that automatic obstacle avoiding or road changing path planning is unreasonable in automatic driving of an intelligent automobile.
In order to achieve the purpose, the invention provides a method for planning a vehicle obstacle avoidance and lane change path, which comprises the following technical scheme:
the first method scheme is as follows: a method for planning a vehicle obstacle avoidance and lane change path comprises the following steps:
1) when a vehicle changes lanes, determining a starting point coordinate, a target point coordinate and a road course angle of the lane change, wherein the starting point coordinate is a geodetic coordinate of a set distance of the current vehicle position along the driving direction, the target point coordinate is a geodetic coordinate of a position where a front obstacle endpoint deviates the sum of the vehicle body width and a set safe lateral distance towards the lane change direction, and the road course angle is a vehicle course angle after the vehicle reaches the target point coordinate;
2) and performing B-spline curve fitting according to the coordinates of the starting point, the coordinates of the target point and the road course angle to obtain a path from the coordinates of the starting point to the coordinates of the target point, wherein the path is the road-changing path.
The method has the beneficial effects that in the first scheme of the method, when the vehicle changes the road, curve fitting is carried out according to the coordinates of the starting point, the coordinates of the target point and the road course angle to obtain the road changing path from the coordinates of the starting point to the coordinates of the target point, so that the road changing path of the vehicle is reasonably planned, and the problem that automatic obstacle avoidance or unreasonable road changing path planning is carried out in the automatic driving of the intelligent automobile is solved.
The second method comprises the following steps: on the basis of method option one, the set distance is 0.2 m.
The third method scheme is as follows: on the basis of the first method scheme or the second method scheme, the B spline method is a cubic B spline curve method.
The method scheme four comprises the following steps: on the basis of the third method scheme, the maximum bounded curvature in the B-spline curve planning process is calculated as follows: the shape of the B-spline curve is completely determined by the control points, for a section of cubic B-spline curve determined by the three control points, the middle points of two line segments are added as new control points, the shape of the B-spline depends on the length L of the smaller line segment of the two line segments and the included angle alpha of the two line segments, and the curvature change of the B-spline curve is obtained as follows:
order to
When u is 0.5, κ has a maximum value; the maximum curvature is substituted into the above equation, thereby obtaining the relationship between L and α:
wherein, any two adjacent control line segments satisfy the relationship, and the curvature of the B spline curve can be ensured.
The method scheme five: on the basis of the fourth method scheme, before the vehicle reaches the target point, whether the vehicle meets a return condition is judged, and if the vehicle meets the return condition, the vehicle is controlled to return according to a set return path; if not, controlling the vehicle to move straight;
the return conditions are specifically as follows: 1. one side of the vehicle returning direction is set to be free of obstacles within a safe distance range; 2. the rear part of one side of the vehicle returning direction is free from obstacles, or the distance between the vehicle and the tail part of the vehicle is larger than the set safe time distance due to the existence of the obstacles; 3. the front of the vehicle on the side of the returning direction has no obstacle, or has an obstacle but the vehicle speed is greater than the vehicle speed.
Drawings
FIG. 1 is a schematic diagram of an obstacle avoidance and lane change system of an intelligent vehicle;
FIG. 2 is a flow chart of a method for planning a vehicle obstacle avoidance lane change path;
FIG. 3 is a convex hull schematic of a B-spline curve;
FIG. 4 is two variables that affect the shape of a cubic B-spline curve;
fig. 5 is a B-spline curve planning diagram of a vehicle obstacle avoidance and lane change path planning method.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings.
The invention provides a planning method for vehicle obstacle avoidance and road path replacement, which can be applied to an unmanned vehicle, as shown in figure 1, the unmanned vehicle comprises a transverse control module, a longitudinal control module, an information fusion module and a decision module, wherein the information fusion module is used for sampling and connecting ZigBee, a first-line laser radar, an ultrasonic radar, a red road lamp signal radio frequency receiver, an inertial navigation GPS, a lane line identification camera and a millimeter wave radar, and processing or analyzing a sampling signal; the input end of the decision-making module is connected with the information fusion module and is used for collecting the output signal of the information fusion module and simultaneously carrying logic judgment and outputting a control signal to the transverse control module and the longitudinal control module; the transverse control module controls the acceleration and deceleration of the vehicle, and the longitudinal control module controls the steering wheel to turn, so that the vehicle is controlled to avoid obstacles and change lanes.
As shown in fig. 2, the method for planning the obstacle avoidance and lane change path of the vehicle provided by the invention specifically comprises the following steps:
1. and acquiring the coordinates of the starting point, the coordinates of the target point and the road course angle.
When the change condition is met, acquiring a starting point coordinate, a target point coordinate and a road course angle according to information around the current vehicle, wherein the starting point coordinate is a geodetic coordinate of the current vehicle position or a geodetic coordinate after a distance is set arbitrarily in the vehicle running direction, for example, the geodetic coordinate of the current vehicle position after 0.2m towards the running direction; the coordinate of the target point is the geodetic coordinate of the front obstacle endpoint at the position where the front obstacle endpoint deviates from the sum of the width of the vehicle half body and the set safe lateral distance in the lane changing direction, and the information of the front obstacle endpoint is obtained by a laser radar; the road heading angle is the vehicle heading angle after the vehicle reaches the target point coordinate, and the vehicle heading angle is a set included angle.
2. And performing curve fitting according to the coordinates of the starting point, the coordinates of the target point and the road course angle to obtain a fitting curve, namely the planned path.
The curve fitting method is as follows:
the essence of path planning is to compute a curve connecting the starting and ending positions, and the requirements and key points of path computation are that the curve is continuously smooth and bounded in curvature. At present, various curves can be selected: polynomial curves, bezier curves, B-spline curves, etc., where the control and calculation of curvature by B-splines is relatively simple, the method is as follows:
through n +1 control points
And n + k +1 parametric node vectors
Determining a k-order, i.e. k-1 degree B-spline curve, which is expressed as:
wherein B isi,k(U) is referred to as Un,kA B-spline basis function of the upper k order, the basis function being determined by a deBoox-Cox recurrence relation, the relation being as follows:
the properties of the B-spline curve according to the present invention are:
1) continuity: at r heavy nodes ui(k-1. ltoreq. i. ltoreq.n) is at least C -k-1rThe continuity of the whole curve is not lower than k-1-rmaxWherein r ismaxRepresenting a node uiMaximum value of multiplicity.
2) The locality is as follows: b isi,k(u) only in the interval [ u ]i,ui+1) Takes positive value and is 0 in other intervals, so that the B spline curve is in the parameter interval [ ui,ui+1) (k-1. ltoreq. i. ltoreq.n) is only the sum of partial line segments
A total of k control vertices.
3) Convex hull property: b spline curve in parameter interval ui,ui+1) The portion (k-1. ltoreq. i.ltoreq.n) lies within the convex hull of the k control vertices, as shown in FIG. 3.
Curve continuity and maximum curvature bounding are requirements that a path curve must meet, subject to constraints of the vehicle model. Compared with other types of curves, the solution of the boundary condition of the polynomial curve usually needs to use a numerical method to solve an analytic solution, and the solving process is complicated; the control points of the Bezier curve correspond to the orders of the curve one by one, and if the required path is longer, the control capability of the control points on the curve shape is weakened under the condition of not increasing the orders of the curve; the B-spline is a generalized Bessel curve, the number of control points is not necessarily related to the curve order, boundary conditions and curvature constraints can be met by selecting appropriate control points without solving complex numerical calculation, and cubic B-splines are enough to meet the requirement of C2Continuity, so as to meet the vehicle motion requirements, a cubic B-spline curve is selected as the path curve. The maximum bounded curvature of the B-spline is calculated as follows:
as shown in fig. 4, the shape of the B-spline curve is completely determined by the control points, and for a cubic B-spline curve determined by three control points, the midpoint of two line segments is added as a new control point, the B-spline shape depends on the length L of the smaller line segment of the two line segments and the included angle α of the two line segments, wherein, assuming that the lengths of the two line segments are equal, the length is smaller in practical calculation, if the calculation of the smaller length line segment can meet the curvature requirement, then the curvature requirement is certainly met when the length of one of the line segments is increased, and the curvature change of the B-spline curve is obtained as:
order to
When u is 0.5, κ has a maximum value; the curvature maximum is substituted into the above equation, thereby obtaining the relationship between L and α:
wherein, any two adjacent control line segments satisfy the relationship, and the curvature of the B spline curve can be ensured.
The path planned by the B-spline curve is a global path, and as shown in fig. 5, the path includes a set obstacle avoidance and change road path 2 and a set return path 4, wherein when a vehicle avoids and changes an obstacle, the vehicle travels from an obstacle avoidance starting coordinate point 1 to an obstacle avoidance target coordinate point 3 according to the set obstacle avoidance and change road path 2; when the vehicle returns, the vehicle travels from the obstacle avoidance target coordinate point 3 to the end position coordinate point 6 according to the set return path 4.
3. When the lane changing condition is met, the vehicle can be controlled to change lanes according to the planned path.
4. And after the lane change is finished, judging whether a return condition is met.
If yes, controlling the vehicle to return according to a set return path; if not, controlling the vehicle to move straight.
The return conditions are specifically as follows: 1. one side of the vehicle returning direction is set to be free of obstacles within a safe distance range; 2. the rear part of one side of the vehicle returning direction is free from obstacles, or the distance between the vehicle and the tail part of the vehicle is larger than the set safe time distance due to the existence of the obstacles; 3. the front of one side of the vehicle returning direction has no obstacle or has an obstacle but the vehicle speed is larger than the vehicle speed.
In summary, as shown in fig. 5, after the intelligent vehicle lane change intention is generated, the path is planned according to a B-spline curve, including an obstacle avoidance start coordinate point 1, an obstacle avoidance target coordinate point 3, an end position coordinate point 6, and a road course angle; the method comprises the steps that when a vehicle reaches an obstacle avoidance starting coordinate point, the vehicle starts to form along a set obstacle avoidance path 2, when the vehicle reaches an obstacle avoidance target coordinate point 3, whether a return condition is met or not is judged according to an instruction of a decision module, if the return condition is met, the vehicle is controlled to return from the obstacle avoidance target coordinate point 3 to an end position coordinate point 6 according to a set return path 4 obtained by a B spline curve, and if the return condition is not met, the vehicle is controlled to run along an obstacle avoidance straight path 5 from the obstacle avoidance target coordinate point 3.
The present invention has been described in relation to particular embodiments thereof, but the invention is not limited to the described embodiments. In the thought given by the present invention, the technical means in the above embodiments are changed, replaced, modified in a manner that is easily imaginable to those skilled in the art, and the functions are basically the same as the corresponding technical means in the present invention, and the purpose of the invention is basically the same, so that the technical scheme formed by fine tuning the above embodiments still falls into the protection scope of the present invention.
Claims (3)
1. A method for planning a vehicle obstacle avoidance and lane change path is characterized by comprising the following steps:
1) when a vehicle changes lanes, determining a starting point coordinate, a target point coordinate and a road course angle of the lane change, wherein the starting point coordinate is a geodetic coordinate of a set distance of the current vehicle position along the driving direction, the target point coordinate is a geodetic coordinate of a position where a front obstacle endpoint deviates from the lane change direction by the sum of the vehicle body width and a set safe lateral distance, and the road course angle is a vehicle course angle after the vehicle reaches the target point coordinate;
2) b-spline curve fitting is carried out according to the coordinates of the starting point, the coordinates of the target point and the road course angle, and a path from the coordinates of the starting point to the coordinates of the target point is obtained, wherein the path is a road changing path;
the B spline method is a cubic B spline curve method;
the maximum bounded curvature in the B-spline curve planning process is calculated as follows: the shape of the B-spline curve is completely determined by the control points, for a section of cubic B-spline curve determined by the three control points, the middle points of two line segments are added as new control points, the shape of the B-spline depends on the length L of the smaller line segment of the two line segments and the included angle alpha of the two line segments, and the curvature change of the B-spline curve is obtained as follows:
order to
When u is 0.5, κ has a maximum value; the curvature maximum is substituted into the above equation, thereby obtaining the relationship between L and α:
wherein, any two adjacent control line segments satisfy the relationship, and the curvature of the B spline curve can be ensured.
2. The method for planning an obstacle avoidance and lane change path of a vehicle according to claim 1, wherein the set distance is 0.2 m.
3. The method for planning the obstacle avoidance and lane change path of the vehicle according to claim 1, wherein before the vehicle reaches the target point, it is further determined whether the vehicle meets a return condition, and if so, the vehicle is controlled to return according to a set return path; if not, controlling the vehicle to move straight;
the return conditions are specifically as follows: 1. one side of the vehicle returning direction is set to be free of obstacles within a safe distance range; 2. the rear part of one side of the vehicle returning direction is free from obstacles, or the distance between the vehicle and the tail part of the vehicle is larger than the set safe time distance due to the existence of the obstacles; 3. the front of the vehicle on the side of the returning direction has no obstacle, or has an obstacle but the vehicle speed is greater than the vehicle speed.
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Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP1777143A1 (en) * | 2005-10-20 | 2007-04-25 | Volkswagen Aktiengesellschaft | Lane-change assistant |
| CN102609765A (en) * | 2012-03-22 | 2012-07-25 | 北京工业大学 | Intelligent vehicle lane change path planning method based on polynomial and radial basis function (RBF) neural network |
| CN105929848A (en) * | 2016-06-28 | 2016-09-07 | 南京邮电大学 | Track planning method for multi-unmanned plane system in three-dimensional environment |
| CN106114507A (en) * | 2016-06-21 | 2016-11-16 | 百度在线网络技术（北京）有限公司 | Local path planning method and device for intelligent vehicle |
| CN106926844A (en) * | 2017-03-27 | 2017-07-07 | 西南交通大学 | A kind of dynamic auto driving lane-change method for planning track based on real time environment information |
| CN107264531A (en) * | 2017-06-08 | 2017-10-20 | 中南大学 | The autonomous lane-change of intelligent vehicle is overtaken other vehicles motion planning method in a kind of semi-structure environment |
-
2017
- 2017-12-28 CN CN201711458491.4A patent/CN109976329B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP1777143A1 (en) * | 2005-10-20 | 2007-04-25 | Volkswagen Aktiengesellschaft | Lane-change assistant |
| CN102609765A (en) * | 2012-03-22 | 2012-07-25 | 北京工业大学 | Intelligent vehicle lane change path planning method based on polynomial and radial basis function (RBF) neural network |
| CN106114507A (en) * | 2016-06-21 | 2016-11-16 | 百度在线网络技术（北京）有限公司 | Local path planning method and device for intelligent vehicle |
| CN105929848A (en) * | 2016-06-28 | 2016-09-07 | 南京邮电大学 | Track planning method for multi-unmanned plane system in three-dimensional environment |
| CN106926844A (en) * | 2017-03-27 | 2017-07-07 | 西南交通大学 | A kind of dynamic auto driving lane-change method for planning track based on real time environment information |
| CN107264531A (en) * | 2017-06-08 | 2017-10-20 | 中南大学 | The autonomous lane-change of intelligent vehicle is overtaken other vehicles motion planning method in a kind of semi-structure environment |
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