Real-time dynamic environment perception in driving scenarios using difference fronts

Abstract

The environment representation is one of the main challenges of autonomous navigation. In the case of complex driving environments such as crowded city traffic scenarios, achieving satisfactory results becomes even more difficult. In this paper we propose a real-time solution for two main issues of advanced driver assistance systems: unstructured environment representation and extraction of dynamic properties of traffic participants. For the real-time environment representation we propose a solution to extract object delimiters from the traffic scenes and represent them as polygonal models. In order to track dynamic entities, an intermediate evidence map named “Stereo Temporal Difference Map” is proposed. This difference map is computed by comparing the occupancy of a cell between two consecutive frames. Based on the Stereo Temporal Difference Map information, difference fronts are extracted and are subjected to a particle based filtering mechanism. Finally, the provided dynamic features are associated to the extracted polygonal models. The result is a more compact representation of the dynamic environment.