论文标题
在动态场景中，基于赛车的多层轨迹计划
Multilayer Graph-Based Trajectory Planning for Race Vehicles in Dynamic Scenarios
论文作者
论文摘要
在高速和处理范围下的轨迹规划是一项艰巨的任务。为了应付赛车场景的要求，我们提出了一个远视的两个步骤，基于图形的轨迹计划者，能够以高达212〜 km/h的速度运行。该计划者旨在生成一组多个可驱动轨迹的动作集，从而使相邻的行为计划者能够为场景中的全球状态选择最合适的动作。此方法有其目标，例如赛车线跟踪，以下，停止，超车和速度轮廓，该速度可以在摩擦极限下处理车辆。因此，它提供了很高的更新速率，较远的计划范围和针对非凸情景的解决方案。所提出方法的功能在模拟和真实的赛车中得到了证明。
Trajectory planning at high velocities and at the handling limits is a challenging task. In order to cope with the requirements of a race scenario, we propose a far-sighted two step, multi-layered graph-based trajectory planner, capable to run with speeds up to 212~km/h. The planner is designed to generate an action set of multiple drivable trajectories, allowing an adjacent behavior planner to pick the most appropriate action for the global state in the scene. This method serves objectives such as race line tracking, following, stopping, overtaking and a velocity profile which enables a handling of the vehicle at the limit of friction. Thereby, it provides a high update rate, a far planning horizon and solutions to non-convex scenarios. The capabilities of the proposed method are demonstrated in simulation and on a real race vehicle.
