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无人驾驶汽车路面自适应MPC轨迹跟踪控制

Trajectory tracking control of driverless vehicle based on road adaptive model predictive control

  • 摘要: 针对无人驾驶汽车轨迹跟踪工况范围狭窄、评价方法片面和路面自适应控制不足等问题,研究全车速和全道路附着系数工况轨迹跟踪精度和行驶安全性.提出路面自适应的多约束模型预测控制,由车辆3自由度非线性动力学模型得到离散化线性时变预测模型,根据传感器检测的道路附着系数实现路面自适应的车速范围匹配,制定车速增量约束条件.融合CarSim和Matlab软件进行研究,得到路径跟踪误差、侧向加速度、质心侧偏角、前轮侧偏角最大值和标准差随车速和道路附着系数变化的规律;结合轮胎侧偏机理评价行驶安全性,划分全工况轨迹跟踪稳定区和失稳区.结果表明:根据道路附着系数自适应调节车速大小,汽车在全工况下,轨迹跟踪精度较高,行驶安全性较好.

     

    Abstract: To solve the problems of narrow driving condition range, partial evaluation method and insufficient road adaptive control of trajectory tracking, the trajectory tracking accuracy and driving safety under full speed and full road adhesion coefficient were investigated. In the road adaptive model predictive control(MPC), the discrete linear time-varying predictive model was obtained by the three-degree-of-freedom nonlinear dynamic model of the vehicle. The road adaptive speed range matching was realized according to the road adhesion coefficient detected by sensors, and the constraint condition of the speed increment was formulated. The maximum and standard deviation of path tracking error, lateral acceleration, centroid sideslip angle and front wheel sideslip angle with the change of velocity and road adhesion coefficient were obtained by integrating CarSim and Matlab softwares. Combined with the mechanism of tire sideslip, the driving safety was evaluated, and the trajectory tracking stability/instability area of vehicle under all working conditions was divided. The results show that the vehicle speed can be adaptively adjusted according to the road information to achieve excellent trajectory tracking accuracy and driving safety under all working conditions.

     

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