Journal of Jilin University(Engineering and Technology Edition) ›› 2022, Vol. 52 ›› Issue (7): 1515-1523.doi: 10.13229/j.cnki.jdxbgxb20210118

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Collision avoidance trajectory planning for intelligent vehicles in emergency conditions

Wei ZHANG(),Shu-pei ZHANG(),Chong-en LUO,Sheng ZHANG,Guo-lin WANG   

  1. School of Automotive and Traffic Engineering，Jiangsu University，Zhenjiang 212013，China
  • Received:2021-02-05 Online:2022-07-01 Published:2022-08-08
  • Contact: Shu-pei ZHANG E-mail:zhangwei@ujs.edu.cn;zhangsp@ujs.edu.cn

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Abstract:

The mandatory stability constraints of the existing trajectory planning methods lead to insufficient utilization of the vehicle's collision avoidance potential. This makes it impossible to plan an effective collision avoidance trajectory for intelligent vehicles under certain critical conditions. Aiming at this practical problem， this paper proposes the concept and definition method of emergency conditions， and based on the optimal control theory， integrates nonlinear vehicle dynamics model， stability domain information and environmental information， and considers the saturation constraints of the vehicle steering actuator to develop a method for planning the collision avoidance trajectory of intelligent vehicles under emergency conditions. The simulation results show that this method can accurately plan the safe collision avoidance trajectory when the vehicle is in a critical steady state under emergency conditions， and it has good applicability on different roads， which provides strong theoretical support for the development of collision avoidance control systems for intelligent vehicles.

Key words: transportation system engineering, intelligent vehicle, emergency conditions, trajectory planning

CLC Number: 

  • U491

Fig.1

Schematic diagram of division of feasible collision avoidance areas"

Fig.2

Two-degree-of-freedom vehicle model"

Fig.3

β-dβ phase plane diagram for different roadadhesion coefficients"

Fig.4

Size of stability region changes with road adhesion coefficient"

Fig.5

β-dβ phase plane diagram at different longitudinal vehicle speeds"

Fig.6

Size of stability region changes with longitudinal speed"

Fig.7

β-dβ phase plan view at different front wheel angles"

Fig.8

Size of stability field varies with front wheel angle"

Table 1

Simulation conditions"

工况

道路附着

系数

车速/

（km·h-1）

方向盘输入

幅值/（°）

I0.812020
II0.8120120
III0.38020
IV0.380120

Fig.9

Simulation curve of working condition I"

Fig.10

Simulation curve of working condition II"

Fig.11

Collision avoidance scene"

Table 2

Values of simulation parameters"

参数单位值
mkg1723
lfm1.232
lrm1.468
Izkg·m24175
bm1.988
dfm1.8
drm2.2
τ-1.02
Dsm0.1

Fig.12

Time domain response of collision avoidance trajectory and dynamic index under dry concrete pavement"

Fig.13

Stability comparison at different vehicle speeds （dry concrete pavement）"

1 周兵,万希,吴晓建,等. 紧急避撞工况下的路径规划与跟踪[J]. 湖南大学学报:自然科学版, 2020, 47 (10): 11-18.
Zhou Bing, Wan Xi, Wu Xiao-jian, et al. Path planning and tracking in scenario of emergency collision avoidance[J]. Journal of Hunan University(Natural Sciences), 2020, 47 (10): 11-18.
2 Ji J, Khajepour A, Melek W W, et al. Path planning and tracking for vehicle collision avoidance based on model predictive control with multiconstraints[J]. IEEE Transactions on Vehicular Technology, 2017, 66(2): 952-964.
3 Li B, Zhang Y, Feng Y, et al. Balancing computation speed and quality: a decentralized motion planning method for cooperative lane changes of connected and automated vehicles[J]. IEEE Transactions on Intelligent Vehicles, 2018(3): 340-350.
4 张友安,王丽英,张刚,等. 轨迹优化的直接数值解法综述[J].海军航空工程学院学报, 2012, 27(5): 481-486, 498.
Zhang You-an, Wang Li-ying, Zhang Gang, et al. A survey of numerical methods for trajectory optimization[J]. Journal of Naval Aeronautical Engineering Institute,2012,27(5):481-486, 498.
5 余卓平, 李奕姗, 熊璐. 无人车运动规划算法综述[J]. 同济大学学报:自然科学版, 2017, 45(8): 1150-1159.
Yu Zhuo-ping, Li Yi-shan, Xiong Lu. A review of the motion planning problem of autonomous vehicle[J]. Journal of Tongji University(Natural Science), 2017, 45(8):1150-1159.
6 Inagaki S, Kushiro I, Yamamoto M. Analysis on vehicle stability in critical cornering using phase-plane method[J]. JSAE Review, 1994, 16(2): 211-216.
7 熊璐, 曲彤, 冯源,等. 极限工况下车辆行驶的稳定性判据[J]. 机械工程学报, 2015, 51(10): 103-111.
Xiong Lu, Qu Tong, Feng Yuan, et al. Stability criterion for the vehicle under critical driving situation[J]. Journal of Mechanical Engineering, 2015, 51(10): 103-111.
8 Liu W, Xiong L, Leng B, et al. Vehicle stability criterion research based on phase plane method[C]∥ WCX™ SAE World Congress Experience,Detroit, USA,2017.
9 孟少华,向锦武,罗漳平,等. 微小型无人直升机避障最优轨迹规划[J]. 北京航空航天大学学报, 2014, 40(2): 246-251.
Meng Shao-hua, Xiang Jin-wu, Luo Zhang-ping, et al. Optimal trajectory planning for small-scale unmanned helicopter obstacle avoidance[J]. Journal of Beijing University of Aeronautics and Astronautics, 2014, 40(2): 246-251.
10 Li B, Shao Z. A unified motion planning method for parking an autonomous vehicle in the presence of irregularly placed obstacles[J]. Knowledge Based Systems, 2015, 86: 11-20.
11 Patterson M A, Rao A V. GPOPS-II: a Matlab software for solving multiple-phase optimal control problems using hp-adaptive gaussian quadrature collocation methods and sparse nonlinear programming[J]. ACM Transactions on Mathematical Software, 2010, 41(1): 1-37.
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