Multilayer graph-based trajectory planning for race vehicles in dynamic scenarios

T Stahl, A Wischnewski, J Betz… - 2019 IEEE intelligent …, 2019 - ieeexplore.ieee.org
2019 IEEE intelligent transportation systems conference (ITSC), 2019ieeexplore.ieee.org
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 …
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.
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