In this paper, we perform safety and performance analysis of an autonomous vehicle that implements reactive planner and controller for navigating a race lap. Unlike traditional planning algorithms that have access to a map of the environment, reactive planner generates the plan purely based on the current input from sensors. Our reactive planner selects a waypoint on the local Voronoi diagram and we use a pure-pursuit controller to navigate towards the waypoint. Our safety and performance analysis has two parts. The first part demonstrates that the reactive planner computes a plan that is locally consistent with the Voronoi plan computed with full map. The second part involves modeling of the evolution of vehicle navigating along the Voronoi diagram as a hybrid automata. For proving the safety and performance specification, we compute the reachable set of this hybrid automata and employ some enhancements that make this computation easier. We demonstrate that an autonomous vehicle implementing our reactive planner and controller is safe and successfully completes a lap for five different circuits. In addition, we have implemented our planner and controller in a simulation environment as well as a scaled down autonomous vehicle and demonstrate that our planner works well for a wide variety of circuits.
翻译:在本文中,我们对使用反应式规划师和调度员的自动飞行器进行安全性和性能分析。 与能够访问环境地图的传统规划算法不同, 反应式规划师纯粹根据传感器的当前输入量来生成计划。 我们的被动规划师在当地的Voronoi图表上选择了一条路标, 我们用纯纯净的搜索控制器向路标方向行驶。 我们的安全和性能分析有两个部分。 第一部分显示反应规划师根据用完整地图计算出的沃罗诺伊计划, 计算出一个符合当地情况的计划。 第二部分涉及根据Voronoi图表进行车辆导航的演进模型, 作为一种混合自动图。 为了证明安全和性能规格, 我们计算出该混合自动图的可达性, 并使用一些使计算更容易的增强功能。 我们证明执行反应式规划师和调度员的安全性能和成功完成五种不同电路的一圈。 此外, 我们已在模拟环境中执行我们的规划师和调度员, 以及一个缩放的自动飞行器。