Consistency-based motion classification for laser sensors dealing with cross traffic in urban environments

In this paper an approach for a consistency-based motion classification for laser sensors is presented which concentrates on urban environments. In these complex environments the algorithm has to match both cross traffic and structures in parallel to the road, as well as objects starting and stopping moving. This leads to a conflict to be solved. For a better understanding we introduce some basic definitions at the beginning. As there are limits due to the sensor´s properties, the proposed algorithm can be configured. The parameters depend on the special dynamic characteristics of the scenario to be detected on the one hand and on the other hand on the sensor´s properties. In combination with the resulting speed limit of the ego vehicle, these parameters describe the theoretical limits of this approach in a comprehensible way. This approach runs online and has been validated in crowded urban environment.