Particle filter map matching and trajectory prediction using a spline based intersection model

For Advanced Driver Assistance Systems and Autonomous Driving it is of major advantage to know future trajectories of traffic participants. These are influenced by many factors in the environment. One important factor is the geometry of the intersection a vehicle is approaching. In this paper we describe how we can extract a spline based intersection model from low detail map data like Open-StreetMap that can be adjusted over time. A particle filter based map matching algorithm is used to localize the ego vehicle relative to the intersection model. Additionally, objects detected from the ego vehicle´s sensors are matched onto the intersection model in order to predict the future trajectories of the ego vehicle and other traffic participants using the intersection model.