Abstract:

To help the autonomous vehicle plan a safe， comfortable and efficient driving trajectory， a trajectory planning approach based on model predictive control was proposed. First， to simplify the planning environment， a safe and feasible “three-circle” expansion of the safety zone was introduced， which also eliminates the collision issues caused by the idealized model of the vehicle. Then， the trajectory planning was decoupled in lateral and longitudinal space. A model prediction method was applied for lateral planning to generate a series of candidate trajectories that met the driving requirements， and a dynamic planning approach was utilized for longitudinal planning， which improved the efficiency of the planning process. Eventually， the factors affecting the selection of optimal trajectories were considered comprehensively， and an optimal trajectory evaluation function was proposed for path planning and speed planning more compatible with the driving requirements. The effectiveness of the proposed algorithm was verified by joint simulation with Matlab/Simulink， Prescan and Carsim software. Experimental results indicate that the vehicle achieves the expected effects in terms of comfort metrics， steering wheel angle variation and localization accuracy， and the planning curve also perfectly matches the tracking curve， which validates the advantage of the proposed algorithm.

Key words: autonomous driving, trajectory planning, model prediction, spatial decoupling, optimal trajectory selection

摘要：

为帮助自动驾驶车辆规划一条安全、舒适和高效的行驶轨迹，提出一种基于模型预测控制的轨迹规划方法。首先，为简化规划的环境，提出一种安全、可行的“三圆”膨胀化的安全区，避免车辆理想化模型引发的碰撞问题；其次，将轨迹规划进行横、纵向空间解耦，横向规划使用模型预测的方法生成一系列满足行驶要求的候选轨迹，纵向规划使用动态规划方法，提高规划的效率；最后，综合考虑影响最优轨迹挑选的因素，提出更符合行驶要求的路径规划和速度规划的最优轨迹评价函数，并通过Matlab/Simulink、Prescan和Carsim软件的联合仿真验证所提算法的有效性。实验结果表明，车辆的舒适度指标、方向盘转角变化和定位精度等均达到预期效果，规划曲线与跟踪曲线完美贴合，验证了所提算法的优越性。

关键词: 自动驾驶, 轨迹规划, 模型预测, 空间解耦, 最优轨迹选择