无人车辆轨迹规划与跟踪控制的统一建模方法  

Unified Modeling of Trajectory Planning and Tracking for Unmanned Vehicle

作　　者：徐杨 陆丽萍[1] 褚端峰[2] 黄子超[2] XU Yang;LU Li-Ping;CHU Duan-Feng;HUANG Zi-Chao(College of Computer Science and Technology, Wuhan Uni- versity of Technology, Wuhan 430070;Intelligent Trans- portation Systems Research Center, Wuhan University of Tech- nology, Wuhan 430063)

机构地区：[1]武汉理工大学计算机科学与技术学院,武汉430070 [2]武汉理工大学智能交通系统研究中心,武汉430063

出　　处：《自动化学报》2019年第4期799-807,共9页Acta Automatica Sinica

基　　金：国家重点研究发计划(2018YFB0105004);国家自然科学基金(51675390;U1764262);湖北省技术创新专项重大项目(2016AAA007);清华大学汽车安全与节能国家重点实验室开发基金(KF1807)资助~~

摘　　要：无人车辆的轨迹规划与跟踪控制是实现自动驾驶的关键.轨迹规划与跟踪控制一般分为两个部分,即先根据车辆周边环境信息以及自车运动状态信息规划出参考轨迹,再依此轨迹来调节车辆纵横向输出以实现跟随控制.本文通过对无人车辆的轨迹规划与跟踪进行统一建模,基于行车环境势场建模与车辆动力学建模,利用模型预测控制中的优化算法来选择人工势场定义下的局部轨迹,生成最优的参考轨迹,并在实现轨迹规划的同时进行跟踪控制.通过Car Sim与MATLAB/Simulink的联合仿真实验表明,该方法可在多种场景下实现无人车辆的动态避障.Trajectory planning and tracking control of unmanned vehicles are the keys to autonomy. Generally, trajectory planning and tracking control are two functions in charge of generating reference trajectory according to the vehicle surrounding information and vehicle state information, and controlling vehicle motions according to the reference trajectory, respectively. In this paper, a unified modeling method to integrate trajectory planning and tracking control is presented. Based on the artificial potential field approach and vehicle dynamics modeling, the optimization algorithm of model predictive control is used to select the optimal local trajectory defined by the artificial potential field as the reference trajectory, which can be then tracked through vehicle motion control. A joint simulation of Car Sim and MATLAB/Simulink shows that this method can effectively accomplish obstacle avoidance for the unmanned vehicle in several traffic scenarios.

关 键 词：人工势场 模型预测控制 轨迹规划 跟踪控制 无人车辆 

分 类 号：U463.6[机械工程—车辆工程]