Local Path Planning for Autonomous Vehicles: Crash Mitigation

被引：0
|
作者：
Wang, Hong [1 ]
Huang, Yanjun [1 ]
Khajepour, Amir [1 ]
Liu, Teng [1 ]
Qin, Yechen [2 ]
Zhang, Yubiao [1 ]
机构：
[1] Univ Waterloo, Mech & Mechatron Engn Dept, Waterloo, ON N2L 3G1, Canada
[2] Beijing Inst Technol, Dept Mech & Vehicle Engn, Beijing, Peoples R China
来源：
2018 IEEE INTELLIGENT VEHICLES SYMPOSIUM (IV) | 2018年
基金：
加拿大自然科学与工程研究理事会;
关键词：
Crash Mitigation; Potential Crash Severity; Autonomous Vehicles; Path Planning; MPC; Safety; INJURY; RISK;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
A path planning approach to generate a path which mitigates the effects of an inevitable crash for autonomous vehicles is presented in this brief. The model predictive control algorithm is adopted here for path planning The artificial potential field, which describes the obstacles and the potential crash severity, are added to the control objectives to avoid the obstacle, and also to mitigate the inevitable crash. The vehicle dynamic is also considered as an optimal control objective. Based on the analysis above, the model predictive controller can guarantee the command following, obstacle avoidance, vehicle dynamics, and mitigate the inevitable crash. Simulation results verified that the proposed 'C has the abilities of obstacles avoidance and mitigation of the inevitable crash.
引用
收藏
页码：1602 / 1607
页数：6
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