A Potential Field-Based Model Predictive Path-Planning Controller for Autonomous Road Vehicles
A Potential Field-Based Model Predictive Path-Planning Controller for Autonomous Road Vehicles
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DOI：
10.1109/tits.2016.2604240
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发表时间：
2017-05-01
影响因子：
8.5
通讯作者：
Litkouhi, Bakhtiar
中科院分区：
文献类型：
--
作者：
Rasekhipour, Yadollah;Khajepour, Amir;Litkouhi, Bakhtiar
人工势场和最优控制器是自主车辆路径规划的两种常用方法。人工势场法能够为不同类型的障碍物和道路结构分配不同的势函数，并基于这些势函数规划路径。然而，它不包括路径规划过程中的车辆动力学。另一方面，结合车辆动力学的最优路径规划控制器规划出一条最优可行路径，保证了车辆在跟踪该路径时的稳定性。在这种方法中，障碍物和道路边界通常作为约束条件包含在最优控制问题中，而不是任何任意函数。本文介绍了一种模型预测路径规划控制器，它的目标包括势函数和车辆动力学项。因此，该路径规划系统能够在利用车辆动力学规划最优路径的同时，区分不同的障碍物和道路结构。针对一些复杂的测试场景，在CarSim模型上对路径规划控制器进行了建模和仿真。结果表明，在该路径规划控制器的作用下，车辆能够避开障碍物，遵守道路规则，并具有适当的车辆动力学特性。此外，由于障碍物和道路规则可以被定义为具有不同的功能，因此路径规划系统根据它们的重要性和优先级来规划路径。
Artificial potential fields and optimal controllers are two common methods for path planning of autonomous vehicles. An artificial potential field method is capable of assigning different potential functions to different types of obstacles and road structures and plans the path based on these potential functions. It does not, however, include the vehicle dynamics in the path-planning process. On the other hand, an optimal path-planning controller integrated with vehicle dynamics plans an optimal feasible path that guarantees vehicle stability in following the path. In this method, the obstacles and road boundaries are usually included in the optimal control problem as constraints and not with any arbitrary function. A model predictive path-planning controller is introduced in this paper such that its objective includes potential functions along with the vehicle dynamics terms. Therefore, the path-planning system is capable of treating different obstacles and road structures distinctly while planning the optimal path utilizing vehicle dynamics. The path-planning controller is modeled and simulated on a CarSim vehicle model for some complicated test scenarios. The results show that, with this path-planning controller, the vehicle avoids the obstacles and observes road regulations with appropriate vehicle dynamics. Moreover, since the obstacles and road regulations can be defined with different functions, the path-planning system plans paths corresponding to their importance and priorities.