In this paper, we address the problem of motion planning and control at the limits of handling, under locally varying traction conditions. We propose a novel solution method where traction variations over the prediction horizon are represented by time-varying tire force constraints, derived from a predictive friction estimate. A constrained finite time optimal control problem is solved in a receding horizon fashion, imposing these time-varying constraints. Furthermore, our method features an integrated sampling augmentation procedure that addresses the problems of infeasibility and sensitivity to local minima that arise at abrupt constraint alterations, e.g., due to sudden friction changes. We validate the proposed algorithm on a Volvo FH16 heavy-duty vehicle, in a range of critical scenarios. Experimental results indicate that traction adaptive motion planning and control improves the vehicle's capacity to avoid accidents, both when adapting to low local traction, by ensuring dynamic feasibility of the planned motion, and when adapting to high local traction, by realizing high traction utilization.

翻译：在本文中,我们根据不同的牵引条件,在操作限度内处理运动规划和控制问题;我们提出一种新的解决办法,根据预测摩擦估计,预测地平线上的牵力变化由时间变化的轮胎受限所代表;有限时间的最佳控制问题以递减地平线的方式解决,强加这些时间变化的限制;此外,我们的方法采用综合抽样增强程序,解决在突然限制改变时产生的对当地小型车辆不可行和敏感问题,例如突然摩擦变化造成的问题;我们验证了在一系列关键情况下沃尔沃FH16重型车辆上的拟议算法;实验结果显示,在适应低地方牵引时,通过确保计划运动的动态可行性,在适应高牵引时,通过实现高牵引利用提高车辆避免事故的能力。