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作 者:高洪波 李升波[1] 谢国涛[3] 成波 GAO Hong-Bo;LI Sheng-Bo;XIE Guo-Tao;CHENG Bo(State Key Laboratory of Automotive Safety and Energy,Tsinghua University,Beijing 100084,China;Center for Intelligent Connected Vehicles and Transportation,Tsinghua University,Beijing 100084,China;Department of Automotive Engineering,Hunan University,Changsha Hunan 410082,China)
机构地区:[1]清华大学汽车安全与节能国家重点实验室,北京100084 [2]清华大学智能网联汽车与交通研究中心,北京100084 [3]湖南大学车辆工程系,湖南长沙410082
出 处:《指挥与控制学报》2018年第4期297-305,共9页Journal of Command and Control
基 金:中国博士后科学基金特别资助项目(2018T110095);中国博士后科学基金(2017M620765);国家重点研发计划(2017YFB0102603);国家自然科学基金联合基金(U1804161)资助~~
摘 要:智能化是汽车的三大变革技术之一,正逐步改变人类社会的出行方式和交通模式.良好的控制性和智能性是自动驾驶汽车上路的前提.提出了智能汽车横向轨迹跟踪的离散模型预测控制方法,将车辆轨迹跟踪转化为开环最优控制问题,对预测控制目标函数与约束进行设计,进行预测型转化,并开发横向跟踪预测控制器.给定参考轨迹下,针对不同速度进行仿真实验,仿真结果显示横向误差的平均值为25cm;跟踪稳定的情况下,前轮转角误差快速收敛为零,具有良好的全局稳定性,验证了该方法对轨迹跟踪控制具有较高的准确性、较强的鲁棒性和良好的自适应性,达到了横向运动控制的目标要求.Intellectualization is one of the three transformation technologies of automobile,which is gradually changing the mode of travel and traffic in human society.Desirable controllability and intelligence is the premise of self-driving cars on the road.This paper presents a discrete-time model predictive control method for lateral trajectory tracking of intelligent vehicles.The lateral trajectory tracking is first transformed into an open-loop optimal control problem.The objective function and input-output constraints are then designed.The lateral tracking predictive controller is developed finally by using the receding horizon optimization..The simulation results show that the average lateral error is 25cm under the given reference trajectory conditions.Under the condition of tracking stability,the front wheel angle error converges to zero,which has good global stability.The results show that this method has high accuracy,strong robustness and adaptability to real traffic scenarios,which meets the requirements of lateral motion control in autonomous driving.
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