论文标题
在静态和动态障碍限制下的实时统一轨迹计划和城市自动驾驶的最佳控制
Real-Time Unified Trajectory Planning and Optimal Control for Urban Autonomous Driving Under Static and Dynamic Obstacle Constraints
论文作者
论文摘要
历史上，轨迹计划和控制已分为自动驾驶堆栈中的两个模块。轨迹计划着重于更高级别的任务，例如避免障碍物并保持在路面上，而控制器则尽力遵循有史以来不断变化的参考轨迹。我们认为，由于计划的轨迹与控制器可以执行什么之间的不匹配，因此这种分离是有缺陷的，并且（2）由于模型预测性控制（MPC）范式的灵活性而不必要。取而代之的是，在本文中，我们提出了一个基于统一的MPC的轨迹计划和控制计划，该计划可以保证在道路边界，静态和动态环境方面的可行性，并实施乘客舒适性限制。该方案在各种方案中进行了严格的评估，该方案旨在证明最佳控制问题（OCP）设计和实时解决方案方法的有效性。原型代码将在https://github.com/watonomous/control上发布。
Trajectory planning and control have historically been separated into two modules in automated driving stacks. Trajectory planning focuses on higher-level tasks like avoiding obstacles and staying on the road surface, whereas the controller tries its best to follow an ever changing reference trajectory. We argue that this separation is (1) flawed due to the mismatch between planned trajectories and what the controller can feasibly execute, and (2) unnecessary due to the flexibility of the model predictive control (MPC) paradigm. Instead, in this paper, we present a unified MPC-based trajectory planning and control scheme that guarantees feasibility with respect to road boundaries, the static and dynamic environment, and enforces passenger comfort constraints. The scheme is evaluated rigorously in a variety of scenarios focused on proving the effectiveness of the optimal control problem (OCP) design and real-time solution methods. The prototype code will be released at https://github.com/WATonomous/control.
