基于动态距离窗的交叉口CAV轨迹规划算法

doi:10.19562/j.chinasae.qcgc.2021.04.011

Abstract

Abstract:

Considering the problem that the existing trajectory planning algorithms for connected and autonomous vehicle （CAV） passing through intersections cannot achieve optimal coordination of traffic efficiency and safety， the concept of dynamic distance windows （DDW） is introduced according to different initial driving states when CAV drives into the communication range of the intersection， and a trajectory planning algorithm which is suitable for the optimal traffic efficiency under the controllable and safe driving condition is proposed. The DDW corresponding to the initial driving state of CAV can be obtained according to the information of initial driving state parameters of CAV and the signal lights， and the constraints of the maximum comfortable acceleration/deceleration and the speed limit of road. For the two types of situation that the distance between the initial position of CAV and a certain position in front of the stop line is within or outside of the DDW， the corresponding trajectory planning algorithm is designed respectively to achieve the minimum delay of CAV passing through the intersection. The simulation results show that the proposed algorithm can improve the efficiency of CAV passing through the intersection， with smaller speed fluctuations and smoother spatiotemporal trajectory of CAV.

Key words: cooperative vehicle?infrastructure systems, connected and autonomous vehicle, trajectory planning, dynamic distance windows

Zhijun Gao,Jiangfeng Wang,Lei Chen,Jiakuan Dong,Dongyu Luo,Xuedong Yan. Trajectory Planning Algorithm for CAV at Intersections Based on Dynamic Distance Windows[J].Automotive Engineering, 2021, 43(4): 537-545.

Figures/Tables 16

速度变化模式	不同速度轨迹阶段间的过渡时刻		需要满足的约束条件	各阶段加速度
速度变化模式	t₁	t₂	需要满足的约束条件	a₁	a₂	a₃
减速-匀速-加速	$v 0 - v u n i a B$	$t G - v * - v u n i a A$	$x ˉ$ > $x * - x 0$ ；式(8)； $v u n i ≤ v *$ ； $0 ≤ v u n i ≤ v 0$ ； $0 ≤ t 1 ≤ t 2 ≤ t G$	a_B	0	a_A
减速-匀速-减速	$v 0 - v u n i a B$	$t G - v u n i - v * a B$	$x ˉ$ > $x * - x 0$ ；式(9)； $v u n i ≥ v *$ ； $0 ≤ v u n i ≤ v 0$ ； $0 ≤ t 1 ≤ t 2 ≤ t G$	a_B	0	a_B
加速-匀速-减速	$v u n i - v 0 a A$	$t G - v u n i - v * a B$	$x ˉ$ < $x * - x 0$ ；式(10)； $v * ≤ v u n i$ ； $v 0 ≤ v u n i ≤ v m a x$ ； $0 ≤ t 1 ≤ t 2 ≤ t G$	a_A	0	a_B
加速-匀速-加速	$v u n i - v 0 a A$	$t G - v * - v u n i a A$	$x ˉ$ < $x * - x 0$ ；式(11)； $v * ≥ v u n i$ ； $v 0 ≤ v u n i ≤ v m a x$ ； $0 ≤ t 1 ≤ t 2 ≤ t G$	a_A	0	a_A

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场景	统计指标	平均延误/s	平均速度/(m·s^-1)	通过车辆数	停车数量	总停车时间/s	仿真结束时头车位置/m	仿真结束时同号尾车位置/m	速度方差/（m²·s^-2）
场景1	无规划	23.6	8.4	9	5	38.6	524.4	218.3	19.6
	有规划	19.6	9.4	11	0	0	590.1	261.1	5.7
	变化	-16.9%	+11.9%	+22.2%	-100%	-100%	+65.7	+42.8	-70.9%
场景2	无规划	29.4	7.1	9	5	36.0	524.2	218.0	15.5
	有规划	25.5	8.0	11	0	0	589.0	260.0	5.9
	变化	-13.3%	+12.7%	+22.2%	-100%	-100%	+64.8	+42.0	-61.9%
场景3	无规划	31.4	6.6	9	4	26.3	524.1	218.1	15.9
	有规划	27.5	7.5	11	0	0	588.6	259.8	9.1
	变化	-12.4%	+13.6%	+22.2%	-100%	-100%	+64.5	+41.7	-42.8%

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Trajectory Planning Algorithm for CAV at Intersections Based on Dynamic Distance Windows

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