转向避撞工况下装载激光雷达车辆的障碍物跟踪

doi:10.19562/j.chinasae.qcgc.2021.11.006

Abstract

Abstract:

At present， the perception and positioning of surrounding obstacles by onboard lidarare mostly based on vehicle coordinate system. When the vehicle turns to avoid collision， due to the change of heading angle and the rotation of vehicle coordinate system， the difficulties of the obstacle data correlation， the analysis of surrounding vehicle motion state and the path planning for collision avoidance will increase. In order to eliminate the adverse effects of vehicle steering， atarget obstacle tracking methodis proposed based on the transformation of onboardlidar coordinate system. Firstly， the improved K-means clustering algorithm is used to cluster the road boundary points extracted to fit the road boundary line.Then， sparrow search algorithmisadopted to solve out the heading angle of vehicle accordingtoroad boundary， with the lidar coordinate system transformed. Finally， the association algorithm and particle filter are used to track the target obstacles. The results of real vehicle test show that the algorithm proposed can accurately extract the road boundary and track obstacles in vehicle turning for collision avoidance.

Key words: lidar, road boundary extraction, K-means clustering, sparrow search algorithm, target tracking

Zhiguo Zhao,Peng Wang,Xiaorong Chen,Kaichong Liang. Obstacle Tracking of a Lidar-equipped Vehicle in Turning for Collision Avoidance[J].Automotive Engineering, 2021, 43(11): 1611-1619.

Figures/Tables 14

算法：粒子滤波器

1.初始化。从先验概率中随机采样N个粒子，粒子状态为 $X 0 i i = 1,2, ?, N$ ，所有粒子的权值为1/N。

2.更新。在k时刻，根据系统的状态转移方程可获得目标预测值，通过对比获得的实际量测值，更新粒子的权重。系统的状态转移方程为

$x v x y v y k = 1 T 00 0100 001 T 0001 x v x y v y k - 1 + ε x ε v x ε y ε v y k - 1$

式中： $ε$ 为状态方程的过程噪声；T为激光雷达数据测量的时间间隔。

3.归一化权重。 $W k i = w k i / ∑ i = 1 N w k i$

4.重要性重采样。当有效样本数N_eff小于设定阈值，即 $N e f f = 1 / ∑ i = 1 N w k i 2 < N t h$ 时进行重采样，得到新的粒子集合 $X k i * | i = 1,2, ?, N$ 。

5.状态估计。 $X ? k = ∑ i = 1 N W k i X k i$

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Obstacle Tracking of a Lidar-equipped Vehicle in Turning for Collision Avoidance

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