协同换道避障模型和轨迹数据驱动的车辆协同避障策略

doi:10.13229/j.cnki.jdxbgxb.20220754

Abstract

Abstract:

Considering the vehicle type， driving style， and the most important objects （MIO） affecting the vehicle lane change at different stages， cooperative lane-change obstacle avoidance model （CLAM） was constructed by describing the "vehicle-vehicle interaction" mechanism in the vehicle obstacle avoidance process as a force relationship； the vehicle lane change avoidance execution events under emergencies were extracted according to the lane change execution segment extraction criterion to establish a vehicle obstacle avoidance micro-trajectory dataset to unexpected events. The cooperative vehicle lane change obstacle avoidance was transformed into a multi-constraint optimal control problem. The cooperative lane-change obstacle avoidance model-optimistic algorithm strategy （CLAM-OA strategy） was designed with the optimization algorithm as a bridge. The results show that compared with the data-driven LSTM model， the outputs of the CLAM-OA strategy have significantly lower errors and more stable results in different time domains of vehicle speed and displacement.

Key words: engineering of communication and transportation system, collision avoidance control strategy, hybrid drive, vehicle control, lane changing behavior, micro-trajectory data

CLC Number:

U491

Ya-qin QIN,Zheng-fu QIAN,Ji-ming XIE. Vehicle cooperative obstacle avoidance strategy driven by CLAM model and trajectory data[J].Journal of Jilin University(Engineering and Technology Edition), 2024, 54(5): 1311-1322.

Figures/Tables 15

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Table 1

Parameter distribution of lane changing cut-out model"

参数	参数描述	参数范围	平均值	标准差	5%分位数	50%分位数	95%分位数
$α$	期望速度修正系数	［-9.454， 3.222］	0.075	1.492	-1.423	0.058	1.740
$β$	从众系数	［-5.360， 11.659］	0.304	2.027	-2.160	0.094	2.557
$χ$	对后车的排斥强度	［0.003， 20.488］	2.217	3.721	0.017	0.779	9.008
$δ$	对后车排斥力的作用范围	［0.172， 45.075］	10.172	11.040	0.443	6.388	34.053
$ε$	对目标车道前后车辆的排斥强度	［0， 11.963］	0.630	2.065	0.001	0.013	3.416
$?$	受目标车道车辆排斥力的作用范围	［0.046， 49.396］	6.213	9.588	0.156	2.019	22.486
$φ$	对突发障碍的排斥强度	［0.183， 42.610］	11.970	11.994	0.716	6.343	40.965
$γ$	受突发障碍排斥力的作用范围	［0.218， 53.127］	9.120	9.934	0.446	6.578	24.613

Table 1

Table 2

Parameter distribution of lane changing cut-in model"

参数	参数描述	参数范围	平均值	标准差	5%分位数	50%分位数	95%分位数
$α$	期望速度修正系数	［-1.962， 6.380］	0.088	1.181	-1.563	0.010	1.517
$β$	从众系数	［-8.203， 10.036］	-0.250	2.004	-5.681	0.049	1.487
$ε$	对目标车道前后车辆的排斥强度	［-15.487， 162.008］	2.814	10.754	-10.801	1.747	22.364
$?$	受目标车道车辆排斥力的作用范围	［0， 65.982］	19.429	9.904	1.382	19.023	32.346
$C L$	规则力修正系数	［0， 14.940］	1.928	2.847	0.092	1.076	9.232
$f$	车道线的规则力	［0， 8.832］	0.921	1.510	0.016	0.350	3.562

Table 2

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Table 4

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指标	CLAM-OA				LSTM
指标	纵向位移x	横向位移y	纵向速度v_x	横向速度v_y	纵向位移x	横向位移y	纵向速度v_x	横向速度v_y
MSE	0.187	0.051	0.020	0.005	24.102	0.029	9.149	0.480
RMSE	0.432	0.226	0.140	0.074	4.909	0.170	3.025	0.693
MAE	0.309	0.058	0.071	0.032	3.327	0.110	1.971	0.346
RMSPE	0.007	0.004	0.041	0.135	0.083	0.003	0.879	1.275

时域/s	CLAM-OA		LSTM
时域/s	ADE/m	FDE/m	ADE/m	FDE/m
1	0.232	0.714	0.216	2.145
2	0.353	1.053	1.444	8.173
3	0.510	1.212	3.799	18.286

Vehicle cooperative obstacle avoidance strategy driven by CLAM model and trajectory data

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