A Model Based Motion Planning Framework for Automated Vehicles in Structured Environments

Abstract

A main difficulty in autonomous driving is the assurance of maneuver acceptability by other traffic participants. Thus, knowledge about social interaction needs to be incorporated into the motion planning process. In this paper we present a model based framework to verify the acceptance of considered maneuvers and to plan social compliant motions. Therefore, we fuse two powerful approaches, one for decision-making and one for planning and show how the methods benefit from each other. Our method adheres to the classical structure of decision-making with subsequent trajectory planning and is consistent in the sense that both components are subject on the same, identical parametrized driver model. The overall method is real-time capable and the resulting trajectories adhere to kinematic constraints. Thus, the approach is applicable in real-world systems.