Recognition of situation classes at road intersections

— The recognition and prediction of situations is an indispensable skill of future driver assistance systems. This study focuses on the recognition of situations involving two vehicles at intersections. For each vehicle, a set of possible future motion trajectories is estimated and rated based on a motion database for a time interval of 2–4 seconds ahead. Realistic situations are generated by a pairwise combination of these individual motion trajectories and classified according to nine categories with a polynomial classifier. In the proposed framework, situations are penalised for which the time to collision significantly exceeds the typical human reaction time. The correspondingly favoured situations are combined by a probabilistic framework, resulting in a more reliable situation recognition and collision detection than obtained based on independent motion hypotheses. The proposed method is evaluated on a real-world differential GPS data set acquired during a test drive of 10...

• Type: Journal
• Year: 2010
• Where: ICRA
• Authors: Eugen Kafer, Christoph Hermes, Christian Wöhler, Helge Ritter, Franz Kummert
• Keywords: Future Motion Trajectories, ICRA 2010, Individual Motion Trajectories, Motion Trajectories, Robotics