This paper presents a trajectory planner for autonomous driving based on a Nonlinear Model Predictive Control (NMPC) algorithm that accounts for Pacejka's nonlinear lateral tyre dynamics as well as for zero speed conditions through a novel slip angles calculation. In the NMPC framework, road boundaries and obstacles (both static and moving) are taken into account thanks to soft and hard constraints implementation. The numerical solution of the NMPC problem is carried out using ACADO toolkit coupled with the quadratic programming solver qpOASES. The effectiveness of the proposed NMPC trajectory planner has been tested using CarMaker multibody models. Time analysis results provided by the simulations shown, state that the proposed algorithm can be implemented on the real-time control framework of an autonomous vehicle under the assumption of data coming from an upstream estimation block.
翻译:本文介绍了基于非线性模型预测控制算法的自主驾驶轨迹规划仪,该算法计算了Pacejka的非线性横向轮胎动态,并通过新式滑角计算得出了零速度条件。在NMPC框架内,由于软和硬性限制措施的实施,道路界限和障碍(静态和移动)都得到了考虑。NMPC问题的数字解决方案使用ACADO工具包和四面式编程求解器qpOASES进行。拟议的NMPC轨迹规划仪的有效性已经用Carmaker多体模型进行了测试。模拟提供的时间分析结果表明,假设上游估计区的数据,可以在自主飞行器实时控制框架上实施拟议的算法。