Formation control of vehicle clusters in multi-lane scenarios based on Multi-Agent System consensus

doi:10.3969/j.issn.1674-8484.2024.05.012

Abstract

Abstract:

A control strategy with multi-lane vehicle platoon formation was investigated for Connected-Automated-Vehicles (CAV) based on Multi-Agent System (MAS) consensus to solve the problem of safe and efficient formation control of multi-lane, randomly distributed vehicle clusters. A platoon's desired geometric topology was established based on an interleaved structure for the vehicle cluster with multiple lanes and scattered random distribution. A three-stage formation control process was proposed, including the spacing adjustment stage, lane change control stage, and formation convergence stage. A platoon formation controller was designed based on consensus theory, and the stability of the controller is demonstrated. Formation experiment of vehicle clusters was conducted in extreme initial distribution scenarios within a three-lane environment, with two typical scenarios being selected to perform numerical simulations and vehicle dynamics simulations of the formation process. The results show that for highly uneven and irregularly distributed vehicle clusters on multiple lanes, all vehicles are effectively controlled to achieve the desired formation in a safe and efficient manner. Throughout the control process, the longitudinal distance error between vehicles and the desired spacing is within 0.5 m, and the lateral position error relative to the desired position is within 5 cm, and the velocity quickly converges to the desired value after changes. Therefore, the strategy can effectively control the vehicles of the cluster to safely and efficiently achieve the desired formation.

Key words: connected-automated-vehicles (CAV), vehicle clusters formation control, consensus control, multi-agent system (MAS), restricted road scenario

CLC Number:

U461.99

JI Pengxiao, KONG Weiwei, LUO Yugong, YU Jie, LIU Yanbin, WANG Junjie, ZHU Weizhen, LIANG Weiming. Formation control of vehicle clusters in multi-lane scenarios based on Multi-Agent System consensus[J]. Journal of Automotive Safety and Energy, 2024, 15(5): 742-752.

Figures/Tables 15

References 17

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车道内车辆数目(场景a)	N₁= 4、N₂= 3、N₃= 1
车道内车辆数目(场景b)	N₁= 4、N₂= 0、N₃= 4
车群期望车速	v_x_,exp= 20 m / s
初始纵向位置*	x_lane,_m(i) / m = 150 - (i - 1)rand([30,50])
初始横向位置*	y_lane,_m(i) / m = 4(m - 1).
初始纵向速度*	v_x_,lane,_m(i) / (m·s) = 20 + 5rand([-1,1])
初始横向速度*	v_y_,lane,_m(i) / (m·s) = 0.
车道宽度	W_lane= 4 m
间距调整、变道控制阶段期望车间距	D₁/ m = 3.2[v_x_,lane,_m / (m·s)]
收敛阶段期望车间距	D₂/ m = 1.7[v_x_,lane,_m / (m·s)]

车道内车辆数目(场景a)	N₁= 4、N₂= 3、N₃= 1
车道内车辆数目(场景b)	N₁= 4、N₂= 0、N₃= 4
车群期望车速	v_x_,exp= 20 m / s
初始纵向位置*	x_lane,_m(i) / m = 150 - (i - 1)rand([30,50])
初始横向位置*	y_lane,_m(i) / m = 4(m - 1).
初始纵向速度*	v_x_,lane,_m(i) / (m·s) = 20 + 5rand([-1,1])
初始横向速度*	v_y_,lane,_m(i) / (m·s) = 0.
车道宽度	W_lane= 4 m
间距调整、变道控制阶段期望车间距	D₁/ m = 3.2[v_x_,lane,_m / (m·s)]
收敛阶段期望车间距	D₂/ m = 1.7[v_x_,lane,_m / (m·s)]

仿真步长	h = 10 ms
初始纵向位置*	x_lane,_m(i) / m = 210 - 70(i - 1)
初始横向位置*	y_lane,_m(i) / m = 4(m - 1)
初始纵向速度*	v_x_,lane,_m(i) / (m·s) = 20 + rand([-1,1])
初始横向速度*	v_y_,lane,_m(i) / (m·s) = 0
控制器参数	k₀_x = 0.8，k₁_x = 0.8，k₀_y = 0.561，k₁_y = 1.4
车辆参数	C_f = C_r = 52 480，i_sw = 16.34，m_car = 1.575 t I_Z = 1.992 t m/s^-2，a = 1.2 m，b = 1.6 m

仿真步长	h = 10 ms
初始纵向位置*	x_lane,_m(i) / m = 210 - 70(i - 1)
初始横向位置*	y_lane,_m(i) / m = 4(m - 1)
初始纵向速度*	v_x_,lane,_m(i) / (m·s) = 20 + rand([-1,1])
初始横向速度*	v_y_,lane,_m(i) / (m·s) = 0
控制器参数	k₀_x = 0.8，k₁_x = 0.8，k₀_y = 0.561，k₁_y = 1.4
车辆参数	C_f = C_r = 52 480，i_sw = 16.34，m_car = 1.575 t I_Z = 1.992 t m/s^-2，a = 1.2 m，b = 1.6 m