  Trajectory and intention prediction of traffic participants is an important
task in automated driving and crucial for safe interaction with the
environment. In this paper, we present a new approach to vehicle trajectory
prediction based on automatically generated maps containing statistical
information about the behavior of traffic participants in a given area. These
maps are generated based on trajectory observations using image processing and
map matching techniques and contain all typical vehicle movements and
probabilities in the considered area. Our prediction approach matches an
observed trajectory to a behavior contained in the map and uses this
information to generate a prediction. We evaluated our approach on a dataset
containing over 14000 trajectories and found that it produces significantly
more precise mid-term predictions compared to motion model-based prediction
approaches.
