Active Collision Avoidance System Design Based on Model Predictive Control with Varying Sampling Time

作     者：Wanying Xue Ling Zheng Wanying Xue;Ling Zheng

作者机构：Automobile Engineering DepartmentChongqing UniversityChongqing 400044China The State Key Laboratory of Mechanical TransmissionChongqing 400044China 

出 版 物：《Automotive Innovation》 (汽车创新工程（英文）)

年 卷 期：2020年第3卷第1期

页      面：62-72页

核心收录：

学科分类：08[工学] 080204[工学-车辆工程] 0802[工学-机械工程] 0823[工学-交通运输工程] 

基　　金：supported by the National Natural Science Foundation of China(Grant No.51875061) the National Key Research and Development Program of China under Grants(2016YFB0100904). 

主　　题：Active collision avoidance Improved MPC controller Varying sampling time Tracking control 

摘      要：In active collision avoidance,the trajectory tracking controller determines the deviation from the reference path and the vehicle stability.The main objective of this study was to reduce the tracking error and improve the tracking performance in collision avoidance.Unlike the previously proposed model predictive control(MPC)strategies with constant sampling time,an improved MPC controller with varying sampling time based on the hierarchical control framework was proposed in this paper.Compared with the original MPC tracking controller,the improved MPC controller demonstrated better adaptive capability for the varying road adhesion coefficients and vehicle speed on a curved road.The simulation results revealed that the hierarchical control framework generated an optimal trajectory for collision avoidance in real-time by minimizing the potential field energy.