CN110920616A - Intelligent vehicle lane changing track and lane changing track following control method - Google Patents

Intelligent vehicle lane changing track and lane changing track following control method Download PDF

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CN110920616A
CN110920616A CN201911343960.7A CN201911343960A CN110920616A CN 110920616 A CN110920616 A CN 110920616A CN 201911343960 A CN201911343960 A CN 201911343960A CN 110920616 A CN110920616 A CN 110920616A
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vehicle
track
lateral position
deviation
fuzzy
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何飞
管欣
贾鑫
卢萍萍
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Jilin University
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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units
    • B60W30/18—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
    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
    • 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
    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
    • B60W2050/0001—Details of the control system
    • B60W2050/0002—Automatic control, details of type of controller or control system architecture
    • 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
    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
    • B60W2050/0001—Details of the control system
    • B60W2050/0002—Automatic control, details of type of controller or control system architecture
    • B60W2050/0008—Feedback, closed loop systems or details of feedback error signal
    • B60W2050/0011—Proportional Integral Differential [PID] controller

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  • Engineering & Computer Science (AREA)
  • Automation & Control Theory (AREA)
  • Transportation (AREA)
  • Mechanical Engineering (AREA)
  • Human Computer Interaction (AREA)
  • Steering Control In Accordance With Driving Conditions (AREA)

Abstract

The invention discloses an intelligent vehicle lane change track following control method, which comprises the steps of firstly generating an expected lane change track; then calculating the deviation e and the deviation change rate error-rate according to the current lateral position and direction angle information of the vehicle and the expected lateral position and expected direction angle information; then, the dynamic delta k is obtained according to the membership function and the fuzzy rulep、Δki、ΔkdAnd finally, the PID outputs the steering wheel turning angle to control the vehicle to follow the track, so that the vehicle can safely, stably, comfortably and quickly realize lane change, reduce traffic accidents and improve the road passing efficiency. The invention also discloses an intelligent vehicle lane change track.

Description

Intelligent vehicle lane changing track and lane changing track following control method
Technical Field
The invention belongs to the field of unmanned collision safety, and particularly relates to an intelligent vehicle lane change track and a lane change track following control method.
Background
With the improvement of national economic level, automobiles become popular, and due to the development of intelligent automobiles, the automation degree of automobiles is higher and higher, and from the aspects of the life and property of consumers, the stable development of social economy and the like, the improvement of the traffic efficiency and riding comfort of roads and the reduction of traffic accidents become more important.
Lane changing is a common operation in the driving process of an automobile, and has important influence on driving safety, comfort and traffic efficiency. The curvature of the track changing track is discontinuous, so that the rider is uncomfortable in the track changing process; the track curvature non-convergence approaches zero at the end of lane changing, so that the automobile cannot run smoothly according to an expected path, and the danger is increased; in addition, when the lateral acceleration exceeds a safety threshold value in the lane changing process, potential safety hazards can be caused, even traffic accidents are caused, road congestion is caused, and the road passing efficiency is reduced.
Common track changing tracks comprise circular arc track changing tracks, constant-speed offset track changing tracks and sine function track changing tracks, and the constant-speed offset track changing tracks have abrupt points, so that the automobile cannot realize good following performance; the circular arc track changing track can meet the requirement of a lateral acceleration peak value, but the lateral acceleration has a sudden change phenomenon at the end point of the track; the sinusoidal function lane changing track has larger lateral acceleration at the end of lane changing; najib and the like design trapezoidal lane changing tracks, but the application of the paths is lack of flexibility, and the applicable road conditions are simpler. The existing control algorithm comprises sliding mode control, PID control, optimal control, neural network control and the like, and the requirements of simplicity, convenience, high speed, instantaneity and the like of calculation are hardly considered while the requirement of accurate track following is met.
Therefore, a reasonable lane change track and a good track following method need to be designed, so that the safety, the comfort and the road passing efficiency of the automobile are ensured in the lane change process.
Disclosure of Invention
The invention aims to provide an intelligent vehicle lane change track and a lane change track following control method, and aims to enable a vehicle to safely, stably and quickly realize lane change, avoid traffic accidents and improve road passing efficiency.
The invention provides an intelligent vehicle lane change track, which adopts a lane change track function of constant speed deviation and sine synthesis, wherein the lane change track function is as follows:
Figure BDA0002332846670000011
wherein u is the longitudinal speed of the vehicle in m/s; l is the longitudinal distance of lane change, unit m; d is the lane width in m.
The invention also provides an intelligent vehicle track change track following control method, which comprises the following steps:
generating a track changing track function, and outputting vehicle lateral position information and direction angle information;
the track-changing trajectory function is as follows:
Figure BDA0002332846670000021
wherein u is the longitudinal speed of the vehicle in m/s; l is the longitudinal distance of lane change, unit m; d is the lane width in m;
step two, pose error calculation: calculating the lateral position deviation y according to the position relation of the vehicle and the road in the geodetic coordinate systemcurAnd deviation of direction angle
Figure BDA0002332846670000022
Calculating the total deviation e and the deviation change rate error-rate of the lateral position information and the direction angle information;
step three, solving a dynamic proportion parameter delta k according to a membership function and a fuzzy rulepDynamic integral parameter Δ kiDynamic differential parameter Δ kd；
Step four, closing the fuzzy controller to set PID initial parameters; PID control: according to dynamic input Δ kpΔkiΔkdDetermining PID proportion, integral and differential parameters by the PID initial parameters;
and step five, establishing a vehicle model, and controlling the vehicle following track according to the PID control output steering wheel turning angle. The coordinates of the vehicle body are converted into a geodetic coordinate system, and the vehicle state information is input to the attitude error calculation section.
The invention has the following beneficial effects:
1. the intelligent vehicle lane change track provided by the invention adopts a lane change track function integrating constant speed deviation and sine, the change of the curvature of the lane change track is continuous and smooth, the riding comfort is improved, and the curvature of the initial end and the terminal end of the track is zero, so that the intelligent vehicle lane change track is beneficial to starting or finishing the lane change of the vehicle stably and driving along the set direction.
2. The invention provides an intelligent vehicle track-changing track following control method, which comprises the steps of firstly generating an expected track-changing track; then calculating the deviation e and the deviation change rate error-rate according to the current lateral position and direction angle information of the vehicle and the expected lateral position and expected direction angle information; then, the dynamic delta k is obtained according to the membership function and the fuzzy rulep、Δki、ΔkdAnd finally, the PID outputs the steering wheel turning angle to control the vehicle to follow the track, so that the vehicle can safely, stably, comfortably and quickly realize lane change, reduce traffic accidents and improve the road passing efficiency.
Drawings
FIG. 1 is a schematic view of a lane-changing process of a vehicle
FIG. 2 is a diagram of a track-changing track following method
FIG. 3 is a graph showing the change of curvature of the track-changing track
FIG. 4 is a trace simulation diagram of track change following when u is 20m/s
FIG. 5 is a lateral acceleration curve diagram in the process of following track-changing track simulation when u is 20m/s
FIG. 6 is a simulation diagram of track change following when u is 25m/s
FIG. 7 is a lateral acceleration curve diagram in the track-changing track following simulation process when u is 25m/s
FIG. 8 is a trace-change-following simulation diagram when u is 30m/s
FIG. 9 is a lateral acceleration curve diagram in the track-changing track following simulation process when u is 30m/s
FIG. 10 is a simulation diagram of the track following track change when u is 35m/s
FIG. 11 is a lateral acceleration curve diagram in the following track-changing track simulation process when u is 35m/s
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail with reference to the following embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and do not limit the invention.
As shown in fig. 1, an intelligent vehicle lane change track adopts a lane change track function of constant speed deviation and sine synthesis, and the lane change track function is as follows:
Figure BDA0002332846670000031
in the formula, u is the longitudinal speed of the vehicle, and the value of the longitudinal speed u of the vehicle is respectively 20m/s, 25m/s, 30m/s and 35 m/s; l is the longitudinal distance of lane change, the unit m, and the limit value of the longitudinal distance L of lane change according to the highway construction standard is 150 m; d is the lane width, the unit m, the lane width d is 3.8m, and the lane changing process respectively passes through 7.5s, 6s, 5s and 4.3 s.
As shown in fig. 2 to 11, an intelligent vehicle lane change track following control method includes the following steps:
step one, generating a track changing track function integrating constant speed deviation and sine, and outputting vehicle lateral position information and direction angle information.
The track-changing trajectory function is as follows:
Figure BDA0002332846670000032
in the formula, the longitudinal speed u is 20m/s, 25m/s, 30m/s and 35m/s respectively, the limit value of the lane change longitudinal distance L according to the highway construction standard is 150m, the lane width d is 3.8m, and the lane change process is respectively carried out for 7.5s, 6s, 5s and 4.3 s.
Step two, pose error calculation: and calculating the lateral position deviation and the direction angle deviation according to the position relation of the vehicle and the road under the geodetic coordinate system.
(1) Calculating the lateral position deviation according to the current lateral position information and the expected lateral position information of the vehicle, and calculating the azimuth deviation according to the current direction angle information and the expected direction angle information of the vehicle, wherein the calculation formula is as follows:
Δy＝yexp-ycur
Figure BDA0002332846670000033
in the formula, yexpTo a desired lateral position, ycurFor the current lateral position of the car,
Figure BDA0002332846670000034
is the current direction angle of the automobile, deltay is the lateral position deviation,
Figure BDA0002332846670000041
is the angular deviation of the direction.
(2) And calculating the total deviation e and the deviation change rate error-rate, wherein e is the sum of the deviation of the lateral position information and the direction angle information:
Figure BDA0002332846670000042
in the formula, the lambda is the direction action coefficient value of 1; the differentiated rate of change of deviation error-rate.
Step three, fuzzy control:
the total deviation e is covered by 7 fuzzy subsets, and a trimf type function is selected as a membership function. The function names are ZD (positive big), ZZ (positive middle), ZX (positive small), Z (zero), FX (negative small), FZ (negative middle) and FD (negative big) in sequence from positive to negative according to a threshold interval, and the threshold interval is [ -0.4,0.6 ]. In the function name, the maximum positive interval is positive, the middle positive interval is positive, the minimum positive interval is positive, and so on.
The deviation change rate error-rate is covered by 7 fuzzy subsets, a trimf type function is selected as a membership function, function names are sequentially ZD, ZZ, ZX, Z, FX, FZ and FD according to a positive-to-negative sequence of a threshold interval, and the threshold interval is [ -0.6 and 0.6 ].
The output quantities of the fuzzy controller are dynamic proportional parameters delta k respectivelypDynamic integral parameter Δ kiDynamic differential parameter Δ kdThe threshold value interval is [ -0.8,0.8]、[-0.2,1]And [0,0.1]Selecting a trimf type function as an output membership function; with 7 ambiguitiesThe subset covers output quantity, and function names are FD, FZ, FX, Z, ZX, ZZ and ZD in sequence from negative to positive according to a threshold value interval.
Fuzzy control rule: selecting if and then rules in the fuzzy controller, wherein the specific rules are shown in tables 1 to 3:
If e and error-rate then Δkp；
If e and error-rate then Δki；
If e and error-rate then Δkd；
TABLE 1 is Δ kpFuzzy rule
Figure BDA0002332846670000043
TABLE 2 as Δ kiFuzzy rule
Figure BDA0002332846670000051
TABLE 3 is Δ kdFuzzy rule
Figure BDA0002332846670000052
Step four, PID control: according to dynamic input Δ kpΔkiΔkdAnd determining PID proportion, integral and differential parameters by the initial parameters, wherein the formula is as follows:
kp＝kp0+Δkpki＝ki0+Δkikd＝kd0+Δkd
in the formula, kp0As a proportional initial parameter, ki0To integrate the initial parameters, kd0Is a differential initial parameter.
Turning off the fuzzy controller, and debugging and determining an initial parameter k for the vehicle model by using PIDp0、ki0And kd0。
Step five: and establishing a vehicle model, controlling the vehicle following track according to the PID control output steering wheel turning angle, converting the vehicle body coordinate into a geodetic coordinate system, and inputting the vehicle state information to a position and attitude error calculation part.
The vehicle model adopts a two-degree-of-freedom motion differential equation:
Figure BDA0002332846670000053
Figure BDA0002332846670000054
Figure BDA0002332846670000061
Figure BDA0002332846670000062
in the formula, ωrThe yaw angular velocity is in unit rad/s, β is the mass center and the slip angle is in unit degree, delta is the front wheel corner is in unit degree, u is the longitudinal vehicle speed is in unit m/s, and other physical quantities and values are shown in Table 4
TABLE 4
Physical quantity Value of Unit of
Mass m of the whole vehicle 2065 kg
Vehicle center of mass to front axle distance a 1.489 m
Vehicle center of mass to rear axle distance b 1.722 m
Front wheel side cornering stiffness k1 -77800 N/rad
Rear wheel side cornering stiffness k2 -76500 N/rad
Moment of inertia Iz around Z axis of finished vehicle 3400 kg/m2
And integrating the yaw velocity to obtain a yaw angle, and calculating the velocity formula of the automobile in a geodetic coordinate system as follows:
Figure BDA0002332846670000063
Figure BDA0002332846670000064
in the formula, the values of the longitudinal speed u under the vehicle body coordinate system are respectively 20m/s, 25m/s, 30m/s and 35m/s during simulation,
Figure BDA0002332846670000065
is the angle of the direction, and the direction angle,
Figure BDA0002332846670000066
is the longitudinal speed under the geodetic coordinate system,
Figure BDA0002332846670000067
is the lateral velocity in the geodetic coordinate system.
Lateral velocity in geodetic coordinate system
Figure BDA0002332846670000068
And performing integration to obtain lateral position information, and using the lateral position information and the direction angle as the input of a pose error calculation part for calculating the error and the error-rate of change of the error.
The invention provides an intelligent vehicle track-changing track following method, which comprises the steps of firstly generating an expected track-changing track; then calculating deviation e and a deviation change rate error-rate according to the current lateral position and direction angle of the vehicle and the expected lateral position and the expected direction angle; then, the dynamic delta k is obtained according to the membership function and the fuzzy rulep、Δki、ΔkdAnd the fuzzy controller is closed to determine initial parameters by using PID debugging, and finally the PID module outputs a steering wheel corner to control the vehicle to follow the track, so that the vehicle is safer, more comfortable and more stable in the lane change process, the traffic accidents are reduced, the road passing efficiency is improved, and the method has high popularization and application values.

Claims (7)

1. The utility model provides an intelligence car track change orbit which characterized in that adopts the track change orbit function of constant velocity skew and sinusoidal synthesis, and the track change orbit function is:
Figure FDA0002332846660000011
wherein u is the longitudinal speed of the vehicle in m/s; l is the longitudinal distance of lane change, unit m; d is the lane width in m.
2. An intelligent vehicle track change track following control method is characterized by comprising the following steps:
generating a track changing track function, and outputting vehicle lateral position information and direction angle information;
the track-changing trajectory function is as follows:
Figure FDA0002332846660000012
wherein u is the longitudinal speed of the vehicle in m/s; l is the longitudinal distance of lane change, unit m; d is the lane width in m;
step two, pose error calculation: calculating the lateral position deviation y according to the position relation of the vehicle and the road in the geodetic coordinate systemcurAnd deviation of direction angle
Figure FDA0002332846660000016
Calculating the total deviation e and the deviation change rate error-rate of the lateral position information and the direction angle information;
step three, solving a dynamic proportion parameter delta k according to a membership function and a fuzzy rulepDynamic integral parameter Δ kiDynamic differential parameter Δ kd；
Step four, closing the fuzzy controller to set PID initial parameters; PID control: according to dynamic input Δ kp、Δki、ΔkdDetermining PID proportion, integral and differential parameters by the PID initial parameters;
and step five, establishing a vehicle model, controlling the vehicle following track according to the PID control output steering wheel turning angle, converting the vehicle body coordinate into a geodetic coordinate system, and inputting the vehicle state information to a position and attitude error calculation part.
3. The intelligent vehicle lane change track following control method according to claim 2, wherein the specific calculation process of the step of calculating the two-position attitude error is as follows:
1) calculating the lateral position deviation according to the current lateral position information and the expected lateral position information of the vehicle, and calculating the azimuth deviation according to the current direction angle information and the expected direction angle information of the vehicle, wherein the calculation formula is as follows:
Δy＝yexp-ycur
Figure FDA0002332846660000013
in the formula (I), the compound is shown in the specification,yexpto a desired lateral position, ycurFor the current lateral position of the car,
Figure FDA0002332846660000014
is the current direction angle of the automobile, deltay is the lateral position deviation,
Figure FDA0002332846660000015
is the deviation of the direction angle;
2) calculating the total deviation e:
Figure FDA0002332846660000021
in the formula, the lambda is the direction action coefficient value of 1;
and differentiating to obtain the error rate.
4. The intelligent vehicle lane change track following control method according to claim 2, wherein the step three fuzzy control process comprises:
covering the total deviation e by using 7 fuzzy subsets, and selecting a trimf type function as a membership function; the function names are ZD, ZZ, ZX, Z, FX, FZ and FD in sequence from positive to negative according to a threshold interval, and the threshold interval is [ -0.4,0.6 ];
covering the error-rate by 7 fuzzy subsets, selecting a trimf type function as a membership function, sequentially arranging ZD, ZZ, ZX, Z, FX, FZ and FD according to a positive-to-negative sequence of a threshold interval, wherein the threshold interval is [ -0.60.6 ];
the output quantities of the fuzzy controllers are respectively delta kp、Δki、ΔkdThe threshold value interval is [ -0.8,0.8]、[-0.2，1]And [0,0.1]Selecting a trimf type function as an output membership function;
covering output quantities by 7 fuzzy subsets, wherein function names are ZD, ZZ, ZX, Z, FX, FZ and FD in sequence from positive to negative according to a threshold value interval;
if and then rules in the fuzzy controller are selected as fuzzy control rules.
5. The intelligent vehicle lane-change track following control method according to claim 4, wherein the specific fuzzy control rule comprises:
Δkpthe fuzzy rule is as follows:
Figure FDA0002332846660000022
Δkithe fuzzy rule is as follows:
Figure FDA0002332846660000031
Δkdthe fuzzy rule is as follows:
Figure FDA0002332846660000032
6. the intelligent vehicle lane change track following control method according to claim 2, wherein the step four PID control processes are as follows:
turning off the fuzzy controller, debugging the vehicle model by using PID, and determining PID proportion initial parameter kp0Integral initial parameter ki0And a differential initial parameter kd0；
Obtaining dynamic input delta k according to the step threep、Δki、ΔkdAnd PID initial parameters, determining PID proportional parameters, integral parameters and differential parameters:
kp＝kp0+Δkp
ki＝ki0+Δki
kd＝kd0+Δkd。
7. the intelligent vehicle lane change track following control method according to claim 2, wherein the step five comprises the following processes:
the vehicle model adopts a two-degree-of-freedom motion differential equation:
Figure FDA0002332846660000041
Figure FDA0002332846660000042
Figure FDA0002332846660000043
Figure FDA0002332846660000044
in the formula, ωrThe yaw angular velocity is unit rad/s, β is a mass center sidesway angle and unit degree, delta is a front wheel corner and unit degree, m is the whole vehicle mass and unit kg, a is the distance between the vehicle mass center and the front axle and unit m, b is the distance between the vehicle mass center and the rear axle and unit m, k1 is the front wheel sidesway stiffness and unit N/rad, k2 is the rear wheel sidesway stiffness and unit N/rad, IZ is the Z-axis inertia moment of the whole vehicle around the Z axis and unit kg/m2(ii) a u is the longitudinal speed in m/s;
and integrating the yaw velocity to obtain a yaw angle, and calculating the velocity formula of the automobile in a geodetic coordinate system as follows:
Figure FDA0002332846660000045
Figure FDA0002332846660000046
in the formula, u is the longitudinal speed u under the vehicle body coordinate system and the unit m/s;
Figure FDA0002332846660000047
is a direction angle;
Figure FDA00023328466600000410
the longitudinal speed under the geodetic coordinate system;
Figure FDA0002332846660000048
is the lateral velocity under the geodetic coordinate system;
lateral velocity in geodetic coordinate system
Figure FDA0002332846660000049
And performing integration to obtain lateral position information, and using the lateral position information and the direction angle as the input of a pose error calculation part for calculating the error and the error-rate of change of the error.
CN201911343960.7A 2019-12-24 2019-12-24 Intelligent vehicle lane changing track and lane changing track following control method Pending CN110920616A (en)

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CN112026759A (en) * 2020-09-12 2020-12-04 哈尔滨理工大学 Electric intelligent automobile collision avoidance device with multi-mode switching and method
CN113561969A (en) * 2021-08-31 2021-10-29 岚图汽车科技有限公司 Backing-up assisting method and device
CN114220262A (en) * 2021-11-19 2022-03-22 东南大学 Vehicle track change deviation calculation method based on traffic simulation
CN114220262B (en) * 2021-11-19 2023-06-23 东南大学 Vehicle lane change track deviation calculation method based on traffic simulation
CN114906142A (en) * 2022-04-29 2022-08-16 中汽创智科技有限公司 Vehicle cooperative lane changing method and device, electronic equipment and storage medium
CN114906168A (en) * 2022-05-24 2022-08-16 合众新能源汽车有限公司 Control method, system and equipment for automatic driving of vehicle and computer readable storage medium
CN114906168B (en) * 2022-05-24 2024-06-21 合众新能源汽车股份有限公司 Control method, system, equipment and computer readable storage medium for automatic driving of vehicle
CN115482687A (en) * 2022-09-15 2022-12-16 吉咖智能机器人有限公司 Method, apparatus, device and medium for vehicle lane change risk assessment
CN115482687B (en) * 2022-09-15 2024-05-07 吉咖智能机器人有限公司 Method, device, equipment and medium for vehicle lane change risk assessment
CN116311863A (en) * 2022-11-29 2023-06-23 北京航空航天大学 Intersection connection road section vehicle formation control method under automatic driving environment
CN116311863B (en) * 2022-11-29 2024-05-10 北京航空航天大学 Intersection connection road section vehicle formation control method under automatic driving environment

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