CN109987092B - Method for determining vehicle obstacle avoidance and lane change time and method for controlling obstacle avoidance and lane change - Google Patents

Method for determining vehicle obstacle avoidance and lane change time and method for controlling obstacle avoidance and lane change Download PDF

Info

Publication number
CN109987092B
CN109987092B CN201711460191.XA CN201711460191A CN109987092B CN 109987092 B CN109987092 B CN 109987092B CN 201711460191 A CN201711460191 A CN 201711460191A CN 109987092 B CN109987092 B CN 109987092B
Authority
CN
China
Prior art keywords
vehicle
obstacle
distance
speed
lane change
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CN201711460191.XA
Other languages
Chinese (zh)
Other versions
CN109987092A (en
Inventor
吴光耀
苏常军
杨学青
刘振楠
王辉
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Yutong Bus Co Ltd
Original Assignee
Zhengzhou Yutong Bus Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Zhengzhou Yutong Bus Co Ltd filed Critical Zhengzhou Yutong Bus Co Ltd
Priority to CN201711460191.XA priority Critical patent/CN109987092B/en
Publication of CN109987092A publication Critical patent/CN109987092A/en
Application granted granted Critical
Publication of CN109987092B publication Critical patent/CN109987092B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • 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
    • B60W30/18—Propelling the vehicle
    • B60W30/18009—Propelling the vehicle related to particular drive situations
    • B60W30/18163—Lane change; Overtaking manoeuvres
    • 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
    • B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
    • B60W40/02—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to ambient conditions
    • B60W40/04—Traffic conditions
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • 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

Landscapes

  • Engineering & Computer Science (AREA)
  • Automation & Control Theory (AREA)
  • Physics & Mathematics (AREA)
  • Transportation (AREA)
  • Mechanical Engineering (AREA)
  • Mathematical Physics (AREA)
  • Aviation & Aerospace Engineering (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • General Physics & Mathematics (AREA)
  • Traffic Control Systems (AREA)
  • Control Of Driving Devices And Active Controlling Of Vehicle (AREA)

Abstract

The invention relates to the field of automatic control of intelligent automobiles, in particular to a method for determining obstacle avoidance and lane change time of a vehicle and a method for controlling obstacle avoidance and lane change, wherein the method for determining the lane change time comprises the steps of judging whether conditions are set between obstacles around the vehicle and the vehicle by acquiring information of obstacles around the vehicle and road condition information, judging that the vehicle can avoid obstacles and change lanes when the set conditions are met, and simultaneously carrying out curve fitting according to coordinates of a starting point, coordinates of a target point and a 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 a lane change path; by means of the intelligent environment sensing capability of the vehicle, the safe driving of the vehicle is guaranteed, meanwhile, the road diameter is changed in an intelligent planning mode, and the problem that automatic obstacle avoidance or road changing control strategies are unreasonable in the automatic driving of the intelligent vehicle is solved.

Description

Method for determining vehicle obstacle avoidance and lane change time and method for controlling obstacle avoidance and lane change
Technical Field
The invention relates to the field of automatic control of intelligent automobiles, in particular to a method for determining obstacle avoidance and lane change time of a vehicle and a method for controlling obstacle avoidance and lane change.
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 performing 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 determining vehicle obstacle avoidance and lane change time and a method for controlling obstacle avoidance and lane change, which are used for solving the problem that an automatic obstacle avoidance or lane change control strategy is unreasonable in automatic driving of an intelligent automobile.
In order to achieve the purpose, the invention provides a method for determining the obstacle avoidance and lane change time of a vehicle, which comprises the following technical scheme:
determining a first scheme of the method: a method for determining the time for vehicle obstacle avoidance and lane change comprises the following steps:
1) detecting whether an obstacle exists in front of the vehicle, if so, judging whether the distance and the speed of the obstacle in front of the vehicle meet first set conditions, and if so, detecting obstacle information of a lane on the right side or the left side of the vehicle;
2) judging whether the transverse distance between the obstacle in front of the vehicle and the obstacle on the right side or the left side of the vehicle is greater than a set distance;
3) if so, judging whether an obstacle exists in at least one lane width range on the right side or the left side of the vehicle;
4) and if no obstacle exists, judging whether the distance and the speed of the obstacle behind the right side or the left side of the vehicle meet second set conditions, and if so, changing the lane to the right side or the left side.
The method has the advantages that whether the vehicle is subjected to lane changing control or not is judged by acquiring the information of obstacles and road conditions around the vehicle, the vehicle is guaranteed to run safely and intelligently planned to avoid obstacles and change lanes at the same time through the intelligent environment sensing capacity of the vehicle, and the problem that automatic obstacle avoidance or lane changing control strategies are unreasonable in the automatic driving of the intelligent automobile is solved.
And determining a second scheme: on the basis of determining the first method scheme, the first setting condition is as follows: the speed of the obstacle in front of the vehicle is less than 1/2 of the speed of the vehicle, and the distance between the obstacle in front and the vehicle is more than or equal to two vehicle bodies of the vehicle.
And a third determination method scheme: on the basis of determining the first method scheme or determining the second method scheme, the second setting condition is as follows: the distance between the obstacle behind the right side or the left side of the vehicle and the rear end of the vehicle is not less than 1 vehicle body of the vehicle, and the speed is less than the vehicle speed of the vehicle; or the speed of the obstacle behind the right side or the left side of the vehicle is greater than the speed of the vehicle, and the distance between the obstacle and the rear end of the vehicle is greater than 2 vehicle bodies of the vehicle.
And determining a scheme IV: on the basis of the third determination method, the set distance is 1 lane width.
The invention provides a control method for vehicle obstacle avoidance and lane change, which comprises the following technical scheme:
the first control method scheme comprises the following steps: a control method for vehicle obstacle avoidance and lane change comprises the following steps:
1) detecting whether an obstacle exists in front of the vehicle, if so, judging whether the distance and the speed of the obstacle in front of the vehicle meet first set conditions, and if so, detecting obstacle information of a lane on the right side or the left side of the vehicle;
2) judging whether the transverse distance between the obstacle in front of the vehicle and the right or left obstacle is greater than a set distance;
3) if so, judging whether an obstacle exists in at least one lane width range on the right side or the left side of the vehicle;
4) if no obstacle exists, judging whether the distance and the speed of the obstacle behind the right side or the left side of the vehicle meet second set conditions, and if so, changing the lane to the right side or the left side;
5) when the vehicle changes lanes to the left side or the right side, determining the coordinates of a starting point, the coordinates of a target point and a road course angle of the lane change;
6) 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 path from the coordinates of the starting point to the coordinates of the target point, wherein the path is the road-changing path.
And the control method scheme II comprises the following steps: on the basis of the first control method scheme, the first setting condition is as follows: the speed of the obstacle in front of the vehicle is less than 1/2 of the speed of the vehicle, and the distance between the obstacle in front and the vehicle is more than or equal to two vehicle bodies of the vehicle.
And the third control method comprises the following scheme: on the basis of the first control method scheme or the second control method scheme, the second setting condition is as follows: the distance between the obstacle behind the right side or the left side of the vehicle and the rear end of the vehicle is not less than 1 vehicle body of the vehicle, and the speed is less than the vehicle speed of the vehicle; or the speed of the obstacle behind the right side or the left side of the vehicle is greater than the speed of the vehicle, and the distance between the obstacle and the rear end of the vehicle is greater than 2 vehicle bodies of the vehicle.
The control method scheme four: on the basis of the third control method scheme, the set distance is 1 lane width.
And the control method scheme five: on the basis of the first control method scheme, the second control method scheme or the fourth control method scheme, the curve fitting method is a B-spline method.
And a sixth control method scheme: on the basis of the fifth control method scheme, the B spline method is a cubic B spline curve method.
The control method comprises a seventh scheme: on the basis of the sixth control 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:
Figure BDA0001530109480000041
order to
Figure BDA0001530109480000042
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:
Figure BDA0001530109480000043
wherein, any two adjacent control line segments satisfy the relationship, and the curvature of the B spline curve can be ensured.
And the control method comprises the following scheme eight: on the basis of the first control method scheme, the second control method scheme, the fourth control method scheme, the sixth control method scheme or the seventh control method scheme, before the vehicle reaches a 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 control method for vehicle obstacle avoidance and lane change;
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 schematic diagram of a control method for vehicle obstacle avoidance and lane changing.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings.
The invention provides a control method for vehicle obstacle avoidance and lane change, 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 module is connected with the information fusion module and is used for collecting the output signal of the information fusion module and simultaneously carrying a 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.
The invention provides a control method for vehicle obstacle avoidance and lane change, which comprises a method for determining the time for vehicle obstacle avoidance and lane change, as shown in fig. 2, and comprises the following steps:
1. and obtaining the information of obstacles and road conditions around the vehicle.
The information of the front obstacle, the rear obstacle, the left and right front obstacles, the left and right rear obstacles and the road condition information, such as the distance to the obstacle, the speed of the obstacle, the lane width and the like, of the vehicle are collected through a radar or a camera.
2. And judging whether the lane change condition is met or not by a method for determining the time for changing the lane by avoiding the obstacle of the vehicle.
The lane change condition needs to ensure the safety of vehicles and the comfort of passengers, the generation of the lane change intention needs to repeatedly compare, judge and detect a plurality of groups of data, namely, the steering operation is carried out when the lane change condition is considered to be met, meanwhile, the intelligent vehicle presets a steering lamp to provide a guarantee in time before the steering like a human driver when the lane change intention is generated, so that the intelligent vehicle smoothly blends into a normal traffic flow. However, the width of the turning intention time cannot be too large, and the time for changing the track is missed; too small, which reduces the driving safety of the vehicle. The method for determining the obstacle avoidance and lane change time of the vehicle comprises the following specific steps:
1) detecting whether an obstacle exists in front of the vehicle, if so, judging whether the distance and the speed of the obstacle in front of the vehicle meet first set conditions, and if so, detecting obstacle information of a lane on the right side or the left side of the vehicle;
2) judging whether the transverse distance between the obstacle in front of the vehicle and the right or left obstacle is greater than a set distance;
3) if so, judging whether an obstacle exists in at least one lane width range on the right side or the left side of the vehicle;
4) and if no obstacle exists, judging whether the distance and the speed of the obstacle behind the right side or the left side of the vehicle meet second set conditions, and if so, changing the lane to the right side or the left side.
Wherein the first setting condition is: the speed of the obstacle in front of the vehicle is less than 1/2 of the speed of the vehicle, and the distance between the obstacle in front and the vehicle is more than or equal to two vehicle bodies of the vehicle; the second setting condition is: the distance between the obstacle behind the right side or the left side of the vehicle and the rear end of the vehicle is not less than 1 vehicle body of the vehicle, and the speed is less than the vehicle speed of the vehicle; or the speed of the obstacle behind the right side or the left side of the vehicle is greater than the speed of the vehicle, and the distance between the obstacle and the rear end of the vehicle is greater than 2 vehicle bodies of the vehicle; the distance is set to 1 lane width.
The judgment conditions can be optimized and configured according to experimental data:
for example, when the speed of the obstacle in front of the vehicle is lower than 1/2 of the vehicle speed and the distance between the obstacle and the obstacle in front is more than two vehicle bodies, the driving habit of human beings is simulated; if lane changing is carried out to the right, the width of the front obstacle from the other obstacle to the right side is larger than 1 lane width, and the speed of the front obstacle is larger than the speed of the vehicle;
meanwhile, when the vehicle determines to change lanes to the right, the information that any obstacle is not allowed in a lane width range on the right side of the vehicle is obtained; when the vehicle determines to change lanes to the left, the information that any obstacle is not allowed in the width range of one lane on the left side of the vehicle;
like a human driving a vehicle, after the intention to change lanes is generated, a human also needs to check the situation of a rear obstacle through a rearview mirror to judge whether to change lanes, and the requirement that the distance from the rear obstacle to the rear end of the vehicle is more than 2 vehicle bodies or the distance from the rear obstacle to the rear end of the vehicle is more than 1 vehicle body is also met, and the speed of the rear obstacle is less than the vehicle speed of the vehicle.
3. And if the conditions are met, controlling the vehicle to change the lane according to the set obstacle avoidance path.
When the lane changing condition is met, the vehicle can be controlled to change lanes, and the intelligent automobile needs to change lanes according to the set path, so that the path for avoiding obstacles and changing lanes of the vehicle needs to be planned.
When the vehicle changes lanes, determining the coordinates of a starting point, the coordinates of a target point and a road course angle of the lane change; 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 path from the coordinates of the starting point to the coordinates of the target point, wherein the path is the road-changing path.
The starting point coordinate is a geodetic coordinate of the current vehicle position or a geodetic coordinate after the vehicle driving direction is 0.2 m; 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 course angle is obtained by a high-definition map.
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
Figure BDA0001530109480000071
And n + k +1 parametric node vectors
Figure BDA0001530109480000072
Determining a k-order, i.e. k-1 degree B-spline curve, which is expressed as:
Figure BDA0001530109480000073
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:
Figure BDA0001530109480000081
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 Ck-1-rThe 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
Figure BDA0001530109480000082
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 solve the analytic solution by using a numerical method, and the solving process is complexLocking; 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:
Figure BDA0001530109480000091
order to
Figure BDA0001530109480000092
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:
Figure BDA0001530109480000093
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 path 2 and a set return path 4, wherein when a vehicle is to avoid an obstacle and change lanes, 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 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.
4. And 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 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.
In summary, as shown in fig. 5, after the intelligent vehicle lane change intention is generated, path planning is performed 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 (5)

1. A control method for vehicle obstacle avoidance and lane change is characterized by comprising the following steps:
1) detecting whether an obstacle exists in front of the vehicle, if so, judging whether the distance and the speed of the obstacle in front of the vehicle meet first set conditions, and if so, detecting obstacle information of a lane on the right side or the left side of the vehicle;
2) judging whether the transverse distance between the obstacle in front of the vehicle and the right or left obstacle is greater than a set distance;
3) if so, judging whether an obstacle exists in at least one lane width range on the right side or the left side of the vehicle;
4) if no obstacle exists, judging whether the distance and the speed of the obstacle behind the right side or the left side of the vehicle meet second set conditions, and if so, changing the lane to the right side or the left side;
5) when the vehicle changes lanes to the left side or the right side, determining the coordinates of a starting point, the coordinates of a target point and a road course angle of the lane change;
6) 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 path from the coordinates of the starting point to the coordinates of the target point, wherein the path is a road-changing path;
the curve fitting method is a B spline method;
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:
Figure FDA0002577050440000011
order to
Figure FDA0002577050440000012
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:
Figure FDA0002577050440000021
wherein, any two adjacent control line segments satisfy the relationship, and the curvature of the B spline curve can be ensured.
2. The vehicle obstacle avoidance and lane change control method according to claim 1, wherein the first setting condition is that: the speed of the obstacle in front of the vehicle is less than 1/2 of the speed of the vehicle, and the distance between the obstacle in front and the vehicle is more than or equal to two vehicle bodies of the vehicle.
3. The vehicle obstacle avoidance and lane change control method according to claim 1 or 2, wherein the second setting condition is that: the distance between the obstacle behind the right side or the left side of the vehicle and the rear end of the vehicle is not less than 1 vehicle body of the vehicle, and the speed is less than the vehicle speed of the vehicle; or the speed of the obstacle behind the right side or the left side of the vehicle is greater than the speed of the vehicle, and the distance between the obstacle and the rear end of the vehicle is greater than 2 vehicle bodies of the vehicle.
4. The vehicle obstacle avoidance and lane changing control method according to claim 3, wherein the set distance is 1 lane width.
5. The vehicle obstacle avoidance and lane change control method according to claim 1, 2 or 4, wherein before the vehicle reaches a 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 returning direction and the rear end of the vehicle is larger than the set safe time distance; 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.
CN201711460191.XA 2017-12-28 2017-12-28 Method for determining vehicle obstacle avoidance and lane change time and method for controlling obstacle avoidance and lane change Active CN109987092B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201711460191.XA CN109987092B (en) 2017-12-28 2017-12-28 Method for determining vehicle obstacle avoidance and lane change time and method for controlling obstacle avoidance and lane change

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201711460191.XA CN109987092B (en) 2017-12-28 2017-12-28 Method for determining vehicle obstacle avoidance and lane change time and method for controlling obstacle avoidance and lane change

Publications (2)

Publication Number Publication Date
CN109987092A CN109987092A (en) 2019-07-09
CN109987092B true CN109987092B (en) 2020-10-30

Family

ID=67108272

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201711460191.XA Active CN109987092B (en) 2017-12-28 2017-12-28 Method for determining vehicle obstacle avoidance and lane change time and method for controlling obstacle avoidance and lane change

Country Status (1)

Country Link
CN (1) CN109987092B (en)

Families Citing this family (22)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110389589A (en) * 2019-07-26 2019-10-29 阿尔法巴人工智能(深圳)有限公司 Intelligent driving vehicle obstacle-avoidance system and method
CN112572424B (en) * 2019-09-11 2022-05-17 北京百度网讯科技有限公司 Vehicle control method, device, equipment and medium based on obstacle recognition
CN110614999B (en) * 2019-09-25 2020-10-27 浙江吉利汽车研究院有限公司 Automatic lane-changing overtaking control method and system for vehicle
CN112896152B (en) * 2019-12-02 2022-06-14 上海汽车集团股份有限公司 Obstacle avoidance method and device for unmanned vehicle
CN111256719B (en) * 2020-02-18 2022-02-22 北京九曜智能科技有限公司 Obstacle detouring method and device
CN111653113B (en) * 2020-04-20 2022-09-27 浙江吉利汽车研究院有限公司 Method, device, terminal and storage medium for determining local path of vehicle
CN111897328B (en) * 2020-07-17 2022-02-15 武汉理工大学 Path planning method, device and equipment based on improved artificial potential field method
CN114115209B (en) * 2020-08-11 2023-08-18 宇通客车股份有限公司 Vehicle, obstacle avoidance method and device for vehicle
CN114120685B (en) * 2020-08-27 2023-04-07 宇通客车股份有限公司 Channel changing control method and device
CN112477864B (en) * 2020-11-10 2022-07-08 合肥工业大学 Control method and system for safe lane change of automatic driving vehicle
CN112498370A (en) * 2021-02-08 2021-03-16 中智行科技有限公司 Vehicle control method and device and electronic equipment
CN113138598A (en) * 2021-03-31 2021-07-20 深圳市优必选科技股份有限公司 Control method of intelligent trolley and intelligent trolley
CN115158308A (en) * 2021-04-02 2022-10-11 清华大学 Intelligent vehicle active obstacle avoidance control method and device, storage medium and terminal
CN113916246B (en) * 2021-09-26 2023-09-01 江苏徐工工程机械研究院有限公司 Unmanned obstacle avoidance path planning method and system
CN114379576B (en) * 2021-12-15 2022-11-11 禾多科技（北京）有限公司 Lane change information prompting method and device, electronic equipment and computer readable medium
CN114655206A (en) * 2022-04-29 2022-06-24 重庆长安汽车股份有限公司 Following target decision method, vehicle and storage medium
CN115179970B (en) * 2022-09-14 2022-11-29 毫末智行科技有限公司 Path planning method and device, electronic equipment and storage medium
CN115489548B (en) * 2022-09-20 2024-06-04 重庆大学 Intelligent automobile park road path planning method
CN115657684B (en) * 2022-12-08 2023-03-28 禾多科技（北京）有限公司 Vehicle path information generation method, device, equipment and computer readable medium
CN116048087B (en) * 2023-02-10 2024-04-09 吉咖智能机器人有限公司 Local path planning method and device, electronic equipment and readable storage medium
CN116476840B (en) * 2023-06-21 2023-09-01 北京斯年智驾科技有限公司 Variable-lane driving method, device, equipment and storage medium
CN117270548B (en) * 2023-11-23 2024-02-09 安徽领云物联科技有限公司 Intelligent inspection robot with route correction function

Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103386975A (en) * 2013-08-02 2013-11-13 重庆市科学技术研究院 Vehicle obstacle avoidance method and system based on machine vision
JP2015066956A (en) * 2013-09-26 2015-04-13 株式会社デンソー Vehicle control system and image sensor
CN106427998A (en) * 2016-09-30 2017-02-22 江苏大学 Control method for avoiding collision during emergent lane changing of vehicle in high-speed state
CN106527452A (en) * 2016-12-30 2017-03-22 广州汽车集团股份有限公司 Motion path planning method of pilotless automobile when encountering obstacle and system thereof
CN106681319A (en) * 2016-12-09 2017-05-17 重庆长安汽车股份有限公司 Automatic lane-changing system and method
CN107215339A (en) * 2017-06-26 2017-09-29 地壳机器人科技有限公司 The lane-change control method and device of automatic driving vehicle
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

Patent Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103386975A (en) * 2013-08-02 2013-11-13 重庆市科学技术研究院 Vehicle obstacle avoidance method and system based on machine vision
JP2015066956A (en) * 2013-09-26 2015-04-13 株式会社デンソー Vehicle control system and image sensor
CN106427998A (en) * 2016-09-30 2017-02-22 江苏大学 Control method for avoiding collision during emergent lane changing of vehicle in high-speed state
CN106681319A (en) * 2016-12-09 2017-05-17 重庆长安汽车股份有限公司 Automatic lane-changing system and method
CN106527452A (en) * 2016-12-30 2017-03-22 广州汽车集团股份有限公司 Motion path planning method of pilotless automobile when encountering obstacle and system thereof
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
CN107215339A (en) * 2017-06-26 2017-09-29 地壳机器人科技有限公司 The lane-change control method and device of automatic driving vehicle

Also Published As

Publication number Publication date
CN109987092A (en) 2019-07-09

Similar Documents

Publication Publication Date Title
CN109987092B (en) Method for determining vehicle obstacle avoidance and lane change time and method for controlling obstacle avoidance and lane change
CN109976329B (en) Planning method for vehicle obstacle avoidance and lane change path
US11532167B2 (en) State machine for obstacle avoidance
US11427191B2 (en) Obstacle avoidance action
US11181920B2 (en) Travel assistance method and travel assistance apparatus
US10663973B2 (en) Autonomous driving system
WO2020135742A1 (en) Autonomous driving vehicle horizontal decision system and horizontal decision-making method
JP6308233B2 (en) Vehicle control apparatus and vehicle control method
EP3715204A1 (en) Vehicle control device
US20200238980A1 (en) Vehicle control device
US10343686B2 (en) Autonomous driving system
CN113916246A (en) Unmanned obstacle avoidance path planning method and system
JP6641583B2 (en) Vehicle control device, vehicle control method, and program
Zheng et al. RRT based path planning for autonomous parking of vehicle
US20200353918A1 (en) Vehicle control device
CN111361564A (en) Lane change system considering benefit maximization and comprehensive decision method
KR20150061781A (en) Method for controlling cornering of vehicle and apparatus thereof
EP3738849A1 (en) Vehicle control device
CN102673560A (en) Method for recognizing turn-off maneuver and driver assistance system
CN110758381B (en) Method and device for generating steering track, storage medium and electronic equipment
US11480962B1 (en) Dynamic lane expansion
WO2021086781A1 (en) Obstacle avoidance action
CN113581181B (en) Intelligent vehicle overtaking track planning method
Jo et al. Overall reviews of autonomous vehicle a1-system architecture and algorithms
CN115056783A (en) Vehicle lane changing method, device and equipment

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant
CP03 Change of name, title or address
CP03 Change of name, title or address

Address after: 450061 Yudao Road, Guancheng District, Zhengzhou City, Henan Province

Patentee after: Yutong Bus Co., Ltd

Address before: 450016 Yutong Industrial Zone, eighteen Li River, Henan, Zhengzhou

Patentee before: Zhengzhou Yutong Bus Co., Ltd