CN112874536B - Intelligent vehicle deflector rod track changing method - Google Patents

Intelligent vehicle deflector rod track changing method Download PDF

Info

Publication number
CN112874536B
CN112874536B CN202110067915.4A CN202110067915A CN112874536B CN 112874536 B CN112874536 B CN 112874536B CN 202110067915 A CN202110067915 A CN 202110067915A CN 112874536 B CN112874536 B CN 112874536B
Authority
CN
China
Prior art keywords
lane
steering wheel
angle
intelligent vehicle
calculating
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
CN202110067915.4A
Other languages
Chinese (zh)
Other versions
CN112874536A (en
Inventor
枚元元
王继贞
田锋
秦伦
吕敏
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.)
Inbo Supercomputing Nanjing Technology Co Ltd
Original Assignee
Inbo Supercomputing Nanjing Technology 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 Inbo Supercomputing Nanjing Technology Co Ltd filed Critical Inbo Supercomputing Nanjing Technology Co Ltd
Priority to CN202110067915.4A priority Critical patent/CN112874536B/en
Publication of CN112874536A publication Critical patent/CN112874536A/en
Application granted granted Critical
Publication of CN112874536B publication Critical patent/CN112874536B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

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
    • B60W60/00—Drive control systems specially adapted for autonomous road vehicles
    • B60W60/001—Planning or execution of driving tasks
    • 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
    • B60W10/00—Conjoint control of vehicle sub-units of different type or different function
    • B60W10/20—Conjoint control of vehicle sub-units of different type or different function including control of steering systems
    • 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
    • B60W40/06—Road conditions
    • 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
    • B60W40/06—Road conditions
    • B60W40/072—Curvature of the road
    • 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
    • B60W60/00—Drive control systems specially adapted for autonomous road vehicles
    • B60W60/001—Planning or execution of driving tasks
    • B60W60/0015—Planning or execution of driving tasks specially adapted for safety

Landscapes

  • Engineering & Computer Science (AREA)
  • Transportation (AREA)
  • Mechanical Engineering (AREA)
  • Automation & Control Theory (AREA)
  • Human Computer Interaction (AREA)
  • Physics & Mathematics (AREA)
  • Mathematical Physics (AREA)
  • Chemical & Material Sciences (AREA)
  • Combustion & Propulsion (AREA)
  • Steering Control In Accordance With Driving Conditions (AREA)

Abstract

The invention innovatively provides an intelligent vehicle shift lever track changing method, which comprises a shift lever track changing function starting judging step, a first lane track changing determining step, a first feedforward steering angle and rotation angle determining step, a first feedback steering wheel rotation angle driving step, a first theoretical steering wheel rotation angle determining step, a first shift lever track changing operation step, a second lane track changing determining step, a second feedforward steering angle and rotation angle determining step, a second feedback steering wheel rotation angle driving step, a second theoretical steering wheel rotation angle determining step and a second shift lever track changing operation step, wherein the first lane track changing operation step comprises the following steps of: the intelligent vehicle translates 1/4 lane width to the target lane to obtain a first lane change track planning discrete point, and the second lane change track determining step: and the intelligent vehicle translates 1/2 lane width to the target lane to obtain a second lane change track planning discrete point.

Description

Intelligent vehicle deflector rod track changing method
Technical Field
The invention relates to the technical field of automatic driving technology, in particular to a track changing method for an intelligent vehicle deflector rod.
Background
The intelligent vehicle is characterized in that advanced devices such as a sensor (radar, camera), a controller and an actuator are added on the basis of a common vehicle, intelligent information exchange with people, vehicles, roads and the like is realized through a vehicle-mounted sensing system and an information terminal, so that the vehicle has intelligent environment sensing capability, the running safety and dangerous state of the vehicle can be automatically analyzed, the vehicle reaches a destination according to the wish of the people, and finally the purpose of replacing the people to operate is realized. In recent years, intelligent vehicles have become a hot spot of research in the world vehicle engineering field and a new power for the growth of the automobile industry.
The study on the intelligent vehicle leaves no automatic driving technology, and the intelligent vehicle combines the automatic driving technology, so that the travel convenience and travel experience of people can be improved, and the travel efficiency of people can be greatly improved.
When people drive the vehicle, the automatic driving function is started, and then the steering and lane changing processes are all required to be automatically completed by the intelligent vehicle. In the automatic driving process, in order to improve the safety of automatic driving, the intelligent vehicle should also enable the intelligent vehicle to automatically identify the safety risk of the borderline and automatically steer to the central lane line of the borderline. How to automatically change the lane of the intelligent vehicle to the lane center line of the adjacent lane on the premise of ensuring safety in the automatic driving process is a key problem to be solved in the automatic driving field.
Disclosure of Invention
Aiming at the defects existing in the prior art, the invention aims to provide the intelligent vehicle driving lever lane changing method, which can enable an intelligent vehicle to automatically change lanes to lane center lines of adjacent lanes on the premise of ensuring safety in the automatic driving process and is used for overcoming the defects in the prior art.
In order to achieve the above purpose, the present invention provides the following technical solutions:
an intelligent vehicle shift lever lane changing method is characterized in that: the method comprises the following steps:
the starting and judging step of the track changing function of the deflector rod: when the intelligent vehicle receives a driving lever lane changing function starting command, lane information is acquired, the lane line information comprises whether the intelligent vehicle acquires lane lines of lanes at the two sides of a current lane, if not, the driving lever lane changing function is exited, and if so, a first lane changing track determining step is entered;
a first lane change track determining step, namely acquiring the lane line information in the driving lever lane change function starting judging step, calculating the width information of the current lane according to the lane line information, translating the current lane width information and the lane line into a target lane by 1/4 lane width to obtain a first lane change track planning discrete point, and obtaining a first lane change track line fitting coefficient according to the first lane change track planning discrete point, wherein the first lane change track line fitting coefficient represents the position data of each point on the lane change track planning line of the target lane;
a first feed-forward direction angle rotation angle determination step: acquiring data information of an intelligent vehicle, wherein the data information comprises the longitudinal speed of the intelligent vehicle, calculating the curvature radius of a lane change track rule according to the first lane change track first fitting coefficient, and calculating a first feedforward steering wheel corner according to the curvature radius of the lane change track rule and the data information through a preset feedforward steering wheel corner algorithm;
a first feedback steering wheel angle driving step: calculating a transverse offset and a relative course angle of each point of the lane change track rule according to the first lane change track fitting coefficient, wherein the transverse offset represents the distance between the preset distance of the course direction of the intelligent vehicle and the corresponding point on the lane change track planning line, the relative course angle represents the angle deviation between the course direction of the intelligent vehicle and the lane change track rule, and the first feedback steering wheel angle is calculated through a preset feedback steering wheel angle algorithm according to the transverse offset and the relative course angle;
a first theoretical steering wheel angle determination step: calculating a first theoretical steering wheel angle according to the first feedforward steering wheel angle and the first feedback steering wheel angle, and entering a first shifting lever channel changing operation step;
the first shift lever channel changing operation steps are as follows: the intelligent vehicle controls the steering wheel on the intelligent vehicle to rotate according to the first theoretical steering wheel angle so as to enable the vehicle to travel to a lane change track planning line;
the second lane change track determining step comprises the steps of obtaining width information of a current lane, translating a lane line of the current lane by 1/2 lane width according to the width information of the current lane and the lane line of the current lane to obtain a second lane change track planning discrete point, and obtaining a second lane change track line fitting coefficient according to the second lane change track planning discrete point, wherein the second lane change track first fitting coefficient represents position data of each point on a central line of the target lane;
a second feed-forward direction angle rotation angle determination step: acquiring data information of an intelligent vehicle, wherein the data information comprises the longitudinal speed of the intelligent vehicle, calculating the curvature radius of a center line of a target lane according to the first fitting coefficient of the second lane change track, and calculating a second feedforward steering wheel corner according to the curvature radius of the center line of the target lane and the data information through a preset feedforward steering wheel corner algorithm;
a second feedback steering wheel angle driving step: calculating the lateral offset and the relative course angle of each point of the central line of the target lane according to the first fitting coefficient of the second lane change track, wherein the lateral offset represents the distance between the preset distance of the course direction of the intelligent vehicle and the corresponding point on the central line of the target lane and the relative course angle represents the angle deviation between the course direction of the intelligent vehicle and the central line of the target lane, and calculating the second feedback steering wheel corner through a preset feedback steering wheel corner algorithm according to the lateral offset and the relative course angle;
a second theoretical steering wheel angle determining step: calculating a second theoretical steering wheel angle according to the second feedforward steering wheel angle and the second feedback steering wheel angle, and entering a second shifting lever channel changing operation step;
the second driving lever channel changing operation steps are as follows: and the intelligent vehicle controls the steering wheel on the intelligent vehicle to rotate according to the second theoretical steering wheel angle so as to drive the vehicle to the center line of the target lane.
Further, the first lane change track determining step includes a lane width calculating sub-step, and the lane width calculating sub-step: initializing a lane width preset value, and determining the lane width according to the lane line information and the lane width preset value.
Further, the lane width calculation substep specifically includes: initializing a lane width preset value, judging whether a left lane line and a right lane line of a current lane are acquired at the same time according to the lane line information, and if the left lane line and the right lane line of the current lane are not acquired at the same time, determining the lane width preset value as a lane width; otherwise, calculating the sum of distance values of the transverse geometric center of the intelligent vehicle and the left lane line and the right lane line, and filtering the sum of the distance values through a Gaussian filtering algorithm to obtain the lane width.
Further, the data information further includes relevant parameters of the intelligent vehicle, and the step of determining the first feed-forward steering wheel angle specifically includes: acquiring data information of an intelligent vehicle, determining a pre-aiming point according to the longitudinal speed of the intelligent vehicle, calculating the curvature radius of the pre-aiming point according to the first lane change track first fitting coefficient, and calculating the first feed-forward steering wheel corner according to the data information and the curvature radius of the pre-aiming point through the feed-forward steering wheel corner algorithm.
Further, the step of determining the second feed-forward steering wheel angle specifically includes: acquiring data information of the intelligent vehicle, determining a pre-aiming point according to the longitudinal speed of the intelligent vehicle, calculating the curvature radius of the pre-aiming point according to the first fitting coefficient of the second lane change track, and calculating the second feedforward steering wheel corner according to the data information and the curvature radius of the pre-aiming point through the feedforward steering wheel corner algorithm.
Further, the intelligent vehicle related parameters include a distance between a front wheel axle and a rear wheel axle, a rear axle to intelligent vehicle center of gravity distance, a total vehicle mass, a front wheel cornering coefficient, and a rear wheel cornering coefficient, and the feed-forward steering wheel angle algorithm is configured to:
wherein:
F steer -feed-forward steering wheel angle;
W b -the distance of the front wheel axis from the rear wheel axis;
L f -the rear axle to intelligent vehicle center of gravity distance;
C f -a front wheel yaw coefficient;
m- -the total mass of the vehicle;
v—longitudinal speed of the intelligent vehicle;
C r -a rear wheel yaw coefficient;
α f -feed-forward rotation angle;
r-radius of curvature.
Further, the first feedback steering wheel angle determining step includes a relative course angle determining sub-step and a feedback steering wheel angle calculating sub-step;
the relative heading angle determination sub-step: according to the first lane change trajectory fitting coefficient, the intelligent vehicle is pre-aimed along the heading direction for a distance X 0 Calculating the transverse offset as D 0 Pretarget a distance X 1 Calculating the transverse offset as D 1 Pretarget a distance X 2 Calculating the transverse offset as D 2 According to the pretightening distance X 1 And X 2 Lateral offset D 1 And D 2 Calculating a course angle through a preset relative course angle algorithm, carrying out mean value filtering on the course angle to obtain the relative course angle, and entering a feedback steering wheel angle calculation sub-step;
the feedback steering wheel angle calculation sub-step: according to the relative course angle and the transverse offset D 0 And calculating the first feedback steering wheel angle through the feedback steering wheel angle algorithm.
Further, the relative heading angle algorithm is configured to:
wherein:
epsilon- -relative heading angle.
The feedback steering wheel angle algorithm is configured to:
C steer ＝C 1 D 0 +C 2 ε
wherein:
C steer -feedback steering wheel angle;
C 1 -a distance weight value, said distance weight value being determined from a longitudinal speed of said intelligent vehicle;
C 2 -an angle weight value, said angle weight value being determined from said relative heading angle.
Further, the first theoretical steering wheel angle determining step specifically includes: and taking the sum of the first feedforward steering wheel angle, the first feedback steering wheel angle, the steering angle deviation and the steering wheel angle compensation as a first theoretical steering wheel angle, and entering a first driving lever lane change operation step, wherein the steering angle deviation represents a deviation value between the theoretical steering wheel angle and an actual vehicle angle, the steering wheel angle compensation represents a variation value of the steering angle deviation under different vehicle speeds, and the steering angle deviation and the steering wheel angle compensation are obtained by directly acquiring vehicle conditions through an intelligent vehicle.
Further, the step of judging the starting of the track changing function of the shift lever comprises a collision detection step, wherein the collision detection step comprises the following steps: and acquiring any lane line of lanes at the two sides of the current lane, acquiring target lane image information by the intelligent vehicle as risk assessment information, judging whether the target lane has collision risk according to the risk assessment information, if so, exiting the driving lever lane change function, and if not, entering a first lane change track determination step.
The invention has the beneficial effects that: judging whether lane lines of a bilateral lane can be obtained or not in advance through a driving lever lane change function starting judging step, if the lane lines can not be obtained, the driving lever lane change function can not be started, if the lane lines can not be obtained, the safety of a borderline lane is required to be judged, if the safety risk is judged, the driving lever lane change function can not be started, and if the safety risk is judged, a first lane change track fitting coefficient and a second lane change track fitting coefficient are respectively determined through a first lane change track determining step and a second lane change track determining step; when a vehicle is driven on a curve, a driver usually presupposes a distance in front of the curve, adjusts a certain angle of a steering wheel after judging the bending condition of a road in front of the curve, and adjusts the angle of the steering wheel according to the angle difference between the direction of the head of the vehicle and the bending direction of the road when the vehicle passes through the road section; the first feedforward steering wheel turning angle determining step is to calculate a first feedforward steering wheel turning angle according to the radius of curvature of a lane changing track rule, wherein the first feedforward steering wheel turning angle is equivalent to an adjusting angle of a steering wheel after a certain distance is pretightened before a person drives a vehicle, the second feedforward steering wheel turning angle determining step is to calculate a second feedforward steering wheel turning angle according to the radius of curvature of a center line of a target lane, and the second feedforward steering wheel turning angle is equivalent to an adjusting angle of the steering wheel after the person drives the vehicle to a lane changing track rule and pretightens a certain distance before the lane changing track rule in the lane changing process. The first feedback steering wheel angle driving step is to calculate the first feedback steering wheel angle according to the transverse offset and the relative course angle, wherein the first feedback steering wheel angle is equal to an adjustment angle for adjusting the steering wheel angle according to the angle difference between the vehicle head direction and the road bending direction when people drive the vehicle.
According to the invention, the first theoretical steering wheel angle and the second theoretical steering wheel angle are respectively calculated through the first theoretical steering wheel angle determining step and the second theoretical steering wheel angle determining step, and finally the track changing purpose is realized through the track changing operation step of the deflector rod. Therefore, the method can enable the intelligent vehicle to automatically change lanes in the automatic driving process, effectively avoid collision with the vehicle in the current lane and the vehicle in the adjacent lane, and improve the safety of automatic driving.
Drawings
FIG. 1 is a schematic flow chart of the present invention;
FIG. 2 is a flow chart of the lane width calculation sub-step of the present invention;
FIG. 3 is a flow chart of a lane change trajectory determination step in the present invention;
FIG. 4 is a flow chart of the feed-forward steering wheel angle determination step of the present invention;
FIG. 5 is a flow chart of the feedback steering wheel angle determination step of the present invention;
FIG. 6 is a model diagram of a first feedback steering wheel angle determination step in accordance with the present invention;
fig. 7 is a model diagram of a second feedback steering wheel angle determination step in the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
It will be understood that when an element is referred to as being "fixed to" another element, it can be directly on the other element or intervening elements may also be present. When a component is considered to be "connected" to another component, it can be directly connected to the other component or intervening components may also be present. When an element is referred to as being "disposed on" another element, it can be directly on the other element or intervening elements may also be present. The terms "vertical," "horizontal," "left," "right," and the like are used herein for illustrative purposes only.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terminology used herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The term "and/or" as used herein includes any and all combinations of one or more of the associated listed items.
Embodiments of the invention are described in further detail below with reference to the attached drawing figures:
because people need to be automatically completed by the intelligent vehicle in the steering and lane changing process after starting the automatic driving function when driving the vehicle. In the automatic driving process, in order to improve the safety of automatic driving, the intelligent vehicle should also enable the intelligent vehicle to automatically identify the safety risk of the borderline and automatically steer to the central lane line of the borderline. How to automatically change the lane of the intelligent vehicle to the lane center line of the adjacent lane on the premise of ensuring safety in the automatic driving process is a key problem to be solved in the automatic driving field; therefore, the invention designs a track changing method for various intelligent vehicle deflector rods, which is characterized in that: the method comprises the following steps:
as shown in fig. 1, the step of judging the starting of the track changing function of the shift lever comprises the following steps: when the intelligent vehicle receives a driving lever lane changing function starting command, lane information is acquired, the lane line information comprises whether the intelligent vehicle acquires lane lines of lanes on two sides of a current lane, if no lane line of the lanes on two sides of the current lane is acquired, the driving lever lane changing function is exited, if any lane line of the lanes on two sides of the current lane is acquired, the intelligent vehicle acquires target lane image information as risk assessment information, whether collision risk exists in the target lane is judged according to the risk assessment information, if collision risk exists is judged, the driving lever lane changing function is exited, and if no collision risk exists is judged, the first lane changing track determining step is entered.
The first lane change track determining step, as shown in fig. 3, comprises the steps of obtaining lane line information in the starting and judging step of a shift lever lane change function, calculating width information of a current lane according to the lane line information, translating the current lane width information and the lane line by 1/4 lane width to a target lane to obtain a first lane change track planning discrete point, obtaining a first lane change track fitting coefficient according to the first lane change track planning discrete point, and representing position data of each point on the lane change track planning line of the target lane by the first lane change track fitting coefficient; as shown in fig. 2, the first lane change track determining step includes a lane width calculating sub-step of: initializing a lane width preset value, and determining the lane width according to lane line information and the lane width preset value; the lane width calculation substeps specifically include: initializing a lane width preset value, judging whether a left lane line and a right lane line of a current lane are acquired at the same time according to lane line information, and if the left lane line and the right lane line of the current lane are not acquired at the same time, determining the lane width preset value as a lane width; otherwise, calculating the sum of distance values of the transverse geometric center of the intelligent vehicle and the left lane line and the right lane line, and filtering the sum of the distance values through a Gaussian filtering algorithm to obtain the lane width; the lane width preset value in this embodiment is set to 3.7 meters. The Gaussian filter algorithm is used for smoothing abrupt changes of the lane width, so that the lane width change is smoother.
As shown in fig. 4, the first feed-forward direction angle-of-rotation determination step: acquiring data information of the intelligent vehicle, wherein the data information comprises the longitudinal speed of the intelligent vehicle, calculating the curvature radius of a lane change track rule according to a first lane change track first fitting coefficient, and calculating a first feedforward steering wheel corner through a preset feedforward steering wheel corner algorithm according to the curvature radius of the lane change track rule and the data information;
the specific calculation process of the curvature radius is to solve a first-order derivative and a second-order derivative for a first lane-changing track first fitting coefficient, wherein the calculation formula is as follows:
wherein R- -radius of curvature, kappa- -curvature.
The data information also comprises relevant parameters of the intelligent vehicle, and the first feedforward steering wheel rotation angle determining step specifically comprises the following steps: acquiring data information of an intelligent vehicle, determining a pre-aiming point according to the longitudinal speed of the intelligent vehicle, calculating the curvature radius of the pre-aiming point according to a first lane change track first fitting coefficient, and calculating a first feed-forward steering wheel corner according to the data information and the curvature radius of the pre-aiming point by a feed-forward steering wheel corner algorithm; the intelligent vehicle related parameters include a distance between the front wheel axle and the rear wheel axle, a distance between the rear axle and the center of gravity of the intelligent vehicle, a total mass of the vehicle, a front wheel cornering coefficient, and a rear wheel cornering coefficient, and the feed-forward steering wheel angle algorithm is configured to:
wherein:
F steer -feed-forward steering wheel angle;
W b -the distance of the front wheel axis from the rear wheel axis;
L f -the rear axle to intelligent vehicle center of gravity distance;
C f -a front wheel yaw coefficient;
m- -the total mass of the vehicle;
v—longitudinal speed of the intelligent vehicle;
C r -a rear wheel yaw coefficient;
α f -a feedforward steering angle, wherein a calculation formula of the feedforward steering angle is derived according to a vehicle dynamics understeer principle;
r-radius of curvature.
As shown in fig. 5, the first feedback steering wheel angle driving step: calculating a transverse offset and a relative course angle of each point of the lane change track rule according to a first lane change track fitting coefficient, wherein the transverse offset represents the distance between the course direction of the intelligent vehicle and a corresponding point on the lane change track planning line at a preset distance of the vehicle, the relative course angle represents the angle deviation between the course direction of the intelligent vehicle and the lane change track rule, and a first feedback steering wheel corner is calculated through a preset feedback steering wheel corner algorithm according to the transverse offset and the relative course angle;
the first feedback steering wheel angle determining step includes a relative course angle determining sub-step and a feedback steering wheel angle calculating sub-step;
as shown in fig. 6, the relative heading angle determination sub-step: according to the fitting coefficient of the first lane change trajectory, the intelligent vehicle is pre-aimed along the heading direction for a distance X 0 Calculating the transverse offset as D 0 Pretarget a distance X 1 Calculating the transverse offset as D 1 Pretarget a distance X 2 Calculating the transverse offset as D 2 According to the pretightening distance X 1 And X 2 Lateral offset D 1 And D 2 Calculating a course angle through a preset relative course angle algorithm, carrying out mean value filtering on the course angle to obtain a relative course angle, and entering a feedback steering wheel angle calculation sub-step; the mean value filtering is used for smoothing abrupt changes of the course angle, so that the changes of the course angle are smoother. The transverse offset represents the distance between the heading direction of the intelligent vehicle and the corresponding point on the first lane change track line at the preset distance from the vehicle. The relative heading angle characterizes an angular deviation of a heading direction of the intelligent vehicle from a first lane change trajectory.
A feedback steering wheel angle calculation sub-step: according to relative course angle and lateral offset D 0 And calculating to obtain a first feedback steering wheel angle through a feedback steering wheel angle algorithm.
The relative heading angle algorithm is configured to:
wherein:
epsilon- -relative heading angle.
The feedback steering wheel angle algorithm is configured to:
C steer ＝C 1 D 0 +C 2 ε
wherein:
C steer -feedback steering wheel angle;
C 1 -a distance weight value, the distance weight value being determined from the longitudinal speed of the intelligent vehicle;
C 2 -an angle weight value, the angle weight value being determined from the relative heading angle.
The intelligent vehicle can be provided with a distance weight algorithm and an angle weight algorithm, when the longitudinal speeds of the intelligent vehicle are different, different distance weight values are obtained, and when the relative course angles are different, different angle weight values are obtained.
A first theoretical steering wheel angle determination step: calculating a first theoretical steering wheel angle according to the first feedforward steering wheel angle and the first feedback steering wheel angle, and entering a first shifting lever channel changing operation step; as shown in fig. 1, the first theoretical steering wheel angle determining step specifically includes: and taking the sum of the first feedforward steering wheel angle, the first feedback steering wheel angle, the angle deviation and the steering wheel angle compensation as a first theoretical steering wheel angle, entering a first driving lever lane change operation step, wherein the angle deviation represents a deviation value between the theoretical steering wheel angle and an actual vehicle angle, the steering wheel angle compensation represents a variation value of the angle deviation under different vehicle speeds, and the angle deviation and the steering wheel angle compensation are obtained by directly acquiring the vehicle condition by an intelligent vehicle.
The first shift lever channel changing operation steps are as follows: the intelligent vehicle controls a steering wheel on the intelligent vehicle to rotate according to the first theoretical steering wheel angle so that the vehicle can travel to a lane change track planning line;
the second lane change track determining step comprises the steps of obtaining width information of a current lane, translating a lane line of the current lane by 1/2 lane width according to the width information of the current lane and the lane line of the current lane to obtain a second lane change track planning discrete point, obtaining a second lane change track line fitting coefficient according to the second lane change track planning discrete point, and representing position data of each point on a central line of the target lane by the second lane change track first fitting coefficient;
a second feed-forward direction angle rotation angle determination step: acquiring data information of the intelligent vehicle, wherein the data information comprises the longitudinal speed of the intelligent vehicle, calculating the curvature radius of the center line of the target lane according to the first fitting coefficient of the second lane change track, and calculating a second feedforward steering wheel corner through a preset feedforward steering wheel corner algorithm according to the curvature radius of the center line of the target lane and the data information;
the specific calculation process of the curvature radius is to solve a first derivative and a second derivative of the first fitting coefficient of the second lane change track, and the calculation formula is as follows:
wherein R- -radius of curvature, kappa- -curvature.
The second feedforward steering wheel rotation angle determining step specifically comprises the following steps: acquiring data information of an intelligent vehicle, determining a pre-aiming point according to the longitudinal speed of the intelligent vehicle, calculating the curvature radius of the pre-aiming point according to a first fitting coefficient of a second lane change track, and calculating a second feedforward steering wheel corner through a feedforward steering wheel corner algorithm according to the data information and the curvature radius of the pre-aiming point; the intelligent vehicle related parameters include a distance between the front wheel axle and the rear wheel axle, a distance between the rear axle and the center of gravity of the intelligent vehicle, a total mass of the vehicle, a front wheel cornering coefficient, and a rear wheel cornering coefficient, and the feed-forward steering wheel angle algorithm is configured to:
wherein:
F steer -feed-forward steering wheel angle;
W b -the distance of the front wheel axis from the rear wheel axis;
L f -the rear axle to intelligent vehicle center of gravity distance;
C f -a front wheel yaw coefficient;
m- -the total mass of the vehicle;
v—longitudinal speed of the intelligent vehicle;
C r -a rear wheel yaw coefficient;
α f -feedforward rotation angle, the calculation formula of the feedforward rotation angle is thatDerived according to the principle of vehicle dynamics understeer;
r-radius of curvature.
A second feedback steering wheel angle driving step: calculating the lateral offset and the relative course angle of each point of the central line of the target lane according to the first fitting coefficient of the second lane change track, wherein the lateral offset represents the distance between the preset distance of the course direction of the intelligent vehicle and the corresponding point on the central line of the target lane and the relative course angle represents the angle deviation between the course direction of the intelligent vehicle and the central line of the target lane, and calculating the second feedback steering wheel corner through a preset feedback steering wheel corner algorithm according to the lateral offset and the relative course angle;
the second feedback steering wheel angle determining step also includes a relative heading angle determining sub-step and a feedback steering wheel angle calculating sub-step; as shown in fig. 7, the relative heading angle determination sub-step: according to the fitting coefficient of the second lane change trajectory, the intelligent vehicle is pre-aimed along the heading direction for a distance X 0 Calculating the transverse offset as D 0 Pretarget a distance X 1 Calculating the transverse offset as D 1 Pretarget a distance X 2 Calculating the transverse offset as D 2 According to the pretightening distance X 1 And X 2 Lateral offset D 1 And D 2 Calculating a course angle through a preset relative course angle algorithm, carrying out mean value filtering on the course angle to obtain a relative course angle, and entering a feedback steering wheel angle calculation sub-step; the mean value filtering is used for smoothing abrupt changes of the course angle, so that the changes of the course angle are smoother. The transverse offset represents the distance between the heading direction of the intelligent vehicle and the corresponding point on the second lane change track line at the preset distance from the vehicle. The relative course angle represents the angle deviation between the course direction of the intelligent vehicle and the second lane change track line; the relative course angle in the second feedback steering wheel angle in the invention takes the lane change track rule line in fig. 7 as a reference, at the moment, the intelligent vehicle runs onto the lane change track planning line in the course of lane change, and prepares to run to the lane center line of the target lane, wherein the calculation formula is the same as the relative course angle algorithm in the first feedback steering wheel angle, and only the variable value therein changes。
A feedback steering wheel angle calculation sub-step: according to relative course angle and lateral offset D 0 And calculating to obtain a first feedback steering wheel angle through a feedback steering wheel angle algorithm.
The relative heading angle algorithm is configured to:
wherein:
epsilon- -relative heading angle.
The feedback steering wheel angle algorithm is configured to:
C steer ＝C 1 D 0 +C 2 ε
wherein:
C steer -feedback steering wheel angle;
C 1 -a distance weight value, the distance weight value being determined from the longitudinal speed of the intelligent vehicle;
C 2 -an angle weight value, the angle weight value being determined from the relative heading angle.
The intelligent vehicle can be provided with a distance weight algorithm and an angle weight algorithm, when the longitudinal speeds of the intelligent vehicle are different, different distance weight values are obtained, and when the relative course angles are different, different angle weight values are obtained.
A second theoretical steering wheel angle determining step: calculating a second theoretical steering wheel angle according to the second feedforward steering wheel angle and the second feedback steering wheel angle, and entering a second shifting lever channel changing operation step; the second theoretical steering wheel angle determining step specifically comprises: and taking the sum of the second feedforward steering wheel angle, the second feedback steering wheel angle, the steering angle deviation and the steering wheel angle compensation as a second theoretical steering wheel angle, entering a second deflector rod lane change operation step, wherein the steering angle deviation represents a deviation value between the theoretical steering wheel angle and an actual vehicle angle, the steering wheel angle compensation represents a variation value of the steering angle deviation under different vehicle speeds, and the steering angle deviation and the steering wheel angle compensation are obtained by directly acquiring the vehicle condition by an intelligent vehicle.
The second driving lever channel changing operation steps are as follows: the intelligent vehicle controls the steering wheel on the intelligent vehicle to rotate according to the second theoretical steering wheel angle so that the vehicle can travel to the center line of the target lane.
The above is only a preferred embodiment of the present invention, and the protection scope of the present invention is not limited to the above examples, and all technical solutions belonging to the concept of the present invention belong to the protection scope of the present invention. It should be noted that modifications and adaptations to the present invention may occur to one skilled in the art without departing from the principles of the present invention and are intended to be within the scope of the present invention.

Claims (10)

1. An intelligent vehicle shift lever lane changing method is characterized in that: the method comprises the following steps:
the starting and judging step of the track changing function of the deflector rod: when the intelligent vehicle receives a driving lever lane change function starting command, lane line information is acquired, wherein the lane line information comprises whether the intelligent vehicle acquires lane lines of lanes at the two sides of a current lane, if not, the intelligent vehicle exits the driving lever lane change function, and if so, the intelligent vehicle enters a first lane change track determining step;
a first lane change track determining step, namely acquiring the lane line information in the driving lever lane change function starting judging step, calculating the width information of the current lane according to the lane line information, translating the current lane width information and the lane line into a target lane by 1/4 lane width to obtain a first lane change track planning discrete point, and obtaining a first lane change track line fitting coefficient according to the first lane change track planning discrete point, wherein the first lane change track line fitting coefficient represents the position data of each point on the lane change track planning line of the target lane;
a first feed-forward direction angle rotation angle determination step: acquiring data information of an intelligent vehicle, wherein the data information comprises the longitudinal speed of the intelligent vehicle, calculating the curvature radius of a lane change track rule according to the first lane change track first fitting coefficient, and calculating a first feedforward steering wheel corner according to the curvature radius of the lane change track rule and the data information through a preset feedforward steering wheel corner algorithm;
a first feedback steering wheel angle driving step: calculating a transverse offset and a relative course angle of each point of the lane change track rule according to the first lane change track fitting coefficient, wherein the transverse offset represents the distance between the preset distance of the course direction of the intelligent vehicle and the corresponding point on the lane change track planning line, the relative course angle represents the angle deviation between the course direction of the intelligent vehicle and the lane change track rule, and the first feedback steering wheel angle is calculated through a preset feedback steering wheel angle algorithm according to the transverse offset and the relative course angle;
a first theoretical steering wheel angle determination step: calculating a first theoretical steering wheel angle according to the first feedforward steering wheel angle and the first feedback steering wheel angle, and entering a first shifting lever channel changing operation step;
the first shift lever channel changing operation steps are as follows: the intelligent vehicle controls the steering wheel on the intelligent vehicle to rotate according to the first theoretical steering wheel angle so as to enable the vehicle to travel to a lane change track planning line;
the second lane change track determining step comprises the steps of obtaining width information of a current lane, translating a lane line of the current lane by 1/2 lane width according to the width information of the current lane and the lane line of the current lane to obtain a second lane change track planning discrete point, and obtaining a second lane change track line fitting coefficient according to the second lane change track planning discrete point, wherein the second lane change track first fitting coefficient represents position data of each point on a central line of the target lane;
a second feed-forward direction angle rotation angle determination step: acquiring data information of an intelligent vehicle, wherein the data information comprises the longitudinal speed of the intelligent vehicle, calculating the curvature radius of a center line of a target lane according to the first fitting coefficient of the second lane change track, and calculating a second feedforward steering wheel corner according to the curvature radius of the center line of the target lane and the data information through a preset feedforward steering wheel corner algorithm;
a second feedback steering wheel angle driving step: calculating the lateral offset and the relative course angle of each point of the central line of the target lane according to the first fitting coefficient of the second lane change track, wherein the lateral offset represents the distance between the preset distance of the course direction of the intelligent vehicle and the corresponding point on the central line of the target lane and the relative course angle represents the angle deviation between the course direction of the intelligent vehicle and the central line of the target lane, and calculating the second feedback steering wheel corner through a preset feedback steering wheel corner algorithm according to the lateral offset and the relative course angle;
a second theoretical steering wheel angle determining step: calculating a second theoretical steering wheel angle according to the second feedforward steering wheel angle and the second feedback steering wheel angle, and entering a second shifting lever channel changing operation step;
the second driving lever channel changing operation steps are as follows: and the intelligent vehicle controls the steering wheel on the intelligent vehicle to rotate according to the second theoretical steering wheel angle so as to drive the vehicle to the center line of the target lane.
2. The intelligent vehicle shift lever lane changing method according to claim 1, wherein: the first lane change track determining step comprises a lane width calculating sub-step, wherein the lane width calculating sub-step is as follows: initializing a lane width preset value, and determining the lane width according to the lane line information and the lane width preset value.
3. The intelligent vehicle shift lever lane changing method according to claim 2, wherein: the lane width calculation substeps specifically include: initializing a lane width preset value, judging whether a left lane line and a right lane line of a current lane are acquired at the same time according to the lane line information, and if the left lane line and the right lane line of the current lane are not acquired at the same time, determining the lane width preset value as a lane width; otherwise, calculating the sum of distance values of the transverse geometric center of the intelligent vehicle and the left lane line and the right lane line, and filtering the sum of the distance values through a Gaussian filtering algorithm to obtain the lane width.
4. The intelligent vehicle shift lever lane changing method according to claim 1, wherein: the data information further comprises relevant parameters of the intelligent vehicle, and the first feed-forward steering wheel rotation angle determining step specifically comprises the following steps: acquiring data information of an intelligent vehicle, determining a pre-aiming point according to the longitudinal speed of the intelligent vehicle, calculating the curvature radius of the pre-aiming point according to the first lane change track first fitting coefficient, and calculating the first feed-forward steering wheel corner according to the data information and the curvature radius of the pre-aiming point through the feed-forward steering wheel corner algorithm.
5. The intelligent vehicle shift lever lane changing method according to claim 4, wherein: the second feed-forward steering wheel angle determining step specifically comprises the following steps: acquiring data information of the intelligent vehicle, determining a pre-aiming point according to the longitudinal speed of the intelligent vehicle, calculating the curvature radius of the pre-aiming point according to the first fitting coefficient of the second lane change track, and calculating the second feedforward steering wheel corner according to the data information and the curvature radius of the pre-aiming point through the feedforward steering wheel corner algorithm.
6. The intelligent vehicle shift lever lane changing method according to claim 1, wherein: the intelligent vehicle related parameters include a distance between a front wheel axle and a rear wheel axle, a distance between the rear axle and an intelligent vehicle center of gravity, a total vehicle mass, a front wheel cornering coefficient, and a rear wheel cornering coefficient, and the feed-forward steering wheel angle algorithm is configured to:
wherein:
F steer -feed-forward steering wheel angle;
W b -the distance of the front wheel axis from the rear wheel axis;
L f rear axle to intelligent vehicle center of gravity distance；
C f -a front wheel yaw coefficient;
m- -the total mass of the vehicle;
v—longitudinal speed of the intelligent vehicle;
C r -a rear wheel yaw coefficient;
α f -feed-forward rotation angle;
r-radius of curvature.
7. The intelligent vehicle shift lever lane changing method according to claim 1, wherein: the first feedback steering wheel angle determining step comprises a relative course angle determining sub-step and a feedback steering wheel angle calculating sub-step;
the relative heading angle determination sub-step: according to the first lane change trajectory fitting coefficient, the intelligent vehicle is pre-aimed along the heading direction for a distance X 0 Calculating the transverse offset as D 0 Pretarget a distance X 1 Calculating the transverse offset as D 1 Pretarget a distance X 2 Calculating the transverse offset as D 2 According to the pretightening distance X 1 And X 2 Lateral offset D 1 And D 2 Calculating a course angle through a preset relative course angle algorithm, carrying out mean value filtering on the course angle to obtain the relative course angle, and entering a feedback steering wheel angle calculation sub-step;
the feedback steering wheel angle calculation sub-step: according to the relative course angle and the transverse offset D 0 And calculating the first feedback steering wheel angle through the feedback steering wheel angle algorithm.
8. The intelligent vehicle shift lever lane changing method according to claim 1, wherein: the relative heading angle algorithm is configured to:
wherein:
epsilon- -relative heading angle;
the feedback steering wheel angle algorithm is configured to:
C steer ＝C 1 D 0 +C 2 ε
wherein:
C steer -feedback steering wheel angle;
C 1 -a distance weight value, said distance weight value being determined from a longitudinal speed of said intelligent vehicle; c (C) 2 -an angle weight value, said angle weight value being determined from said relative heading angle.
9. The intelligent vehicle shift lever lane changing method according to claim 1, wherein: the first theoretical steering wheel rotation angle determining step specifically comprises the following steps: and taking the sum of the first feedforward steering wheel angle, the first feedback steering wheel angle, the steering angle deviation and the steering wheel angle compensation as a first theoretical steering wheel angle, and entering a first driving lever lane change operation step, wherein the steering angle deviation represents a deviation value between the theoretical steering wheel angle and an actual vehicle angle, the steering wheel angle compensation represents a variation value of the steering angle deviation under different vehicle speeds, and the steering angle deviation and the steering wheel angle compensation are obtained by directly acquiring vehicle conditions through an intelligent vehicle.
10. The intelligent vehicle shift lever lane changing method according to claim 1, wherein: the step of judging the starting of the track changing function of the deflector rod comprises a collision detection step, wherein the collision detection step comprises the following steps: and acquiring any lane line of lanes at the two sides of the current lane, acquiring target lane image information by the intelligent vehicle as risk assessment information, judging whether the target lane has collision risk according to the risk assessment information, if so, exiting the driving lever lane change function, and if not, entering a first lane change track determination step.
CN202110067915.4A 2021-01-19 2021-01-19 Intelligent vehicle deflector rod track changing method Active CN112874536B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202110067915.4A CN112874536B (en) 2021-01-19 2021-01-19 Intelligent vehicle deflector rod track changing method

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202110067915.4A CN112874536B (en) 2021-01-19 2021-01-19 Intelligent vehicle deflector rod track changing method

Publications (2)

Publication Number Publication Date
CN112874536A CN112874536A (en) 2021-06-01
CN112874536B true CN112874536B (en) 2023-09-12

Family

ID=76049674

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202110067915.4A Active CN112874536B (en) 2021-01-19 2021-01-19 Intelligent vehicle deflector rod track changing method

Country Status (1)

Country Link
CN (1) CN112874536B (en)

Families Citing this family (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113799776A (en) * 2021-10-14 2021-12-17 苏州挚途科技有限公司 Vehicle lane changing method and device and electronic equipment
CN117429436B (en) * 2023-12-21 2024-03-26 广汽埃安新能源汽车股份有限公司 Method and device for controlling track switching of deflector rod of intelligent vehicle

Citations (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
DE102015107987A1 (en) * 2014-05-21 2015-11-26 Toyota Jidosha Kabushiki Kaisha Power transmission system for a vehicle
CN106080595A (en) * 2015-05-01 2016-11-09 丰田自动车株式会社 Controlling device for vehicle running
CN108622093A (en) * 2018-05-04 2018-10-09 奇瑞汽车股份有限公司 The track of intelligent vehicle keeps control method and device
CN109664888A (en) * 2019-01-31 2019-04-23 上海蔚来汽车有限公司 High-speed functions automatic switchover system, advanced driving assistance system and high-speed functions automatic switching method
CN110481551A (en) * 2019-08-16 2019-11-22 中国第一汽车股份有限公司 A kind of control method, device and the vehicle of automatic lane-change
WO2019242718A1 (en) * 2018-06-22 2019-12-26 长城汽车股份有限公司 Vehicle lane change control method and device
WO2020011025A1 (en) * 2018-07-12 2020-01-16 广州小鹏汽车科技有限公司 Automated vehicular lane changing method and apparatus
CN110979305A (en) * 2019-03-18 2020-04-10 长城汽车股份有限公司 Vehicle abnormal lane change control method, device and system
CN111016902A (en) * 2019-12-30 2020-04-17 重庆长安汽车股份有限公司 Vehicle speed auxiliary control method and system during lane changing of vehicle and vehicle
CN111717189A (en) * 2019-03-18 2020-09-29 长城汽车股份有限公司 Lane keeping control method, device and system

Family Cites Families (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US10647322B2 (en) * 2017-07-25 2020-05-12 Hyundai Mobis Co., Ltd. Backward driving assist apparatus for vehicle and control method thereof

Patent Citations (11)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
DE102015107987A1 (en) * 2014-05-21 2015-11-26 Toyota Jidosha Kabushiki Kaisha Power transmission system for a vehicle
CN106080595A (en) * 2015-05-01 2016-11-09 丰田自动车株式会社 Controlling device for vehicle running
CN108622093A (en) * 2018-05-04 2018-10-09 奇瑞汽车股份有限公司 The track of intelligent vehicle keeps control method and device
WO2019242718A1 (en) * 2018-06-22 2019-12-26 长城汽车股份有限公司 Vehicle lane change control method and device
WO2020011025A1 (en) * 2018-07-12 2020-01-16 广州小鹏汽车科技有限公司 Automated vehicular lane changing method and apparatus
CN109664888A (en) * 2019-01-31 2019-04-23 上海蔚来汽车有限公司 High-speed functions automatic switchover system, advanced driving assistance system and high-speed functions automatic switching method
CN110979305A (en) * 2019-03-18 2020-04-10 长城汽车股份有限公司 Vehicle abnormal lane change control method, device and system
WO2020187257A1 (en) * 2019-03-18 2020-09-24 长城汽车股份有限公司 Vehicle abnormal lane change control method, device and system
CN111717189A (en) * 2019-03-18 2020-09-29 长城汽车股份有限公司 Lane keeping control method, device and system
CN110481551A (en) * 2019-08-16 2019-11-22 中国第一汽车股份有限公司 A kind of control method, device and the vehicle of automatic lane-change
CN111016902A (en) * 2019-12-30 2020-04-17 重庆长安汽车股份有限公司 Vehicle speed auxiliary control method and system during lane changing of vehicle and vehicle

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
工程机械的随动转向装置;宗存元, 王军;机械研究与应用(第04期);全文 *

Also Published As

Publication number Publication date
CN112874536A (en) 2021-06-01

Similar Documents

Publication Publication Date Title
CN112537303B (en) Intelligent vehicle lane centering keeping method
EP3932761A1 (en) Vehicle abnormal lane change control method, device and system
CN106114511B (en) A kind of automobile cruise system core target identification method
CN110329255B (en) Lane departure auxiliary control method based on man-machine cooperation strategy
CN111610780B (en) Automatic driving vehicle path tracking control method and device
US7860653B2 (en) Obstacle avoidance control apparatus
US8805604B2 (en) Method for adjusting a steering system in a vehicle
CN109976159A (en) Intelligent vehicle crosswise joint method based on safely controllable domain
CN112874536B (en) Intelligent vehicle deflector rod track changing method
CN109131325B (en) Lane keeping control method for three-dimensional extension preview switching of intelligent driving automobile
CN111891125B (en) Lane departure active deviation correction method based on torque control
CN105329238A (en) Self-driving car lane changing control method based on monocular vision
CN111086510B (en) Front wheel steering vehicle lane keeping control method based on prediction function control
CN110293970A (en) A kind of travel control method of autonomous driving vehicle, device and automobile
CN109080627B (en) Method for controlling lateral force during turning driving of unmanned vehicle
WO2023138258A1 (en) Self-learning cooperative control method of active steering and yaw moment
CN115551756A (en) Path control module, associated path control device and associated method
JP2022547414A (en) Devices for predictive control of movement of motor vehicles
CN113460088A (en) Unmanned vehicle path tracking control method based on nonlinear tire and driver model
CN110703775B (en) Commercial vehicle lane keeping path planning method based on improved artificial potential field
CN112644488A (en) Adaptive cruise system
US20080275607A1 (en) Method for Operating an Active Chassis System
CN116639114A (en) Transverse control method for vehicle overbending
CN114371691B (en) Tracking control method for auxiliary driving curve track
CN112706770B (en) Vehicle entry control system and method considering steer-by-wire delay

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