What lies in the shadows? Safe and computation-aware motion planning for autonomous vehicles using intent-aware dynamic shadow regions

摘要

One of the challenges of developing autonomous vehicles is planning in an inhabited environment under sensing uncertainty as well as limited perception and computational resources. Besides reasoning about the behaviour of traffic participants that are within the vehicles' field of view, safe autonomous driving also requires the vehicle to reason about possible traffic participants that might exist beyond its sensing horizon, and to adapt its driving behaviour accordingly. This paper describes an inference and motion planning pipeline that is able to guarantee passive safety (collisions are possible, but the autonomous vehicle will be at rest) with respect to hypothetical hidden agents that have not been observed yet. We also incorporate the vehicle's reaction time due to sensing and computational delays into the planning process; for example, we show how having a fast reaction time due to the availability of more computational resources leads to more aggressive trajectories, while a car with a larger reaction time will choose more relaxed trajectories that require less attention.