针对CACC(cooperative adaptive cruise control)车队在弯道行驶的安全性和稳定性问题,提出一种V2X(vehicle to everything)环境下基于MPC(model predictive control)算法的弯道区域CACC车队行驶轨迹跟踪策略.首先,分析CACC车队在弯道区域的行驶工况以及纵向平衡问题,并基于牛顿第二定律构建车辆在弯道行驶的车辆动力学模型;其次,CACC车队基于V2X技术实现车车之间状态信息的实时交互,并以基于车辆运动学的MPC算法为基础,引入可变间距的车队安全距离控制模型,提出一种适用于弯道区域的轨迹跟踪模型;最后,通过二次规划进行模型求解.实验分析结果表明:V2X环境下的CACC车队在弯道行驶过程中面对不同的行驶工况能够不同程度地保证车车之间的安全性、稳定性以及驾乘人员的舒适性,有效验证了所提V2X环境下基于MPC算法的弯道区域CACC车队轨迹跟踪策略的可行性.
Abstract
An model predictive control(MPC)algorithm based cooperative adaptive cruise control(CACC)fleet driving trajectory tracking approach is proposed under the V2X environment to address the issue of safety and stability of CACC fleet driving trajectory in the curved area.First,the driving conditions and longitudinal balance of the CACC fleet in the bend region are analyzed,and a model of vehicle dynamics based on the Newton's second law is established.Second,the CACC fleet realizes real-time interaction of state information between vehicles using V2X technology,and introduces a fleet safety distance control model with variable spacing based on the MPC algorithm of vehicle kinematics,then a trajectory tracking model for curved areas is proposed.Finally,the model is solved using quadratic programming.Analysis of the experimental results shows that the CACC fleet in a V2X environment can ensure the safety,stability,and comfort of the drivers and passengers to varying degrees while driving in the bend.It effectively verifies the feasibility of the MPC algorithm-based trajectory tracking control strategy for the CACC fleet driving in curved areas under the V2X environment.
维普
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