Author(s)

M. JUNGHANS, A. LEICH, K. KOZEMPEL, H. SAUL & S. KNAKE-LANGHORST

Abstract

The automated detection of atypical and critical traffic situations is essentially important to help to understand driver behaviour, to find functional correlations between traffic conflicts and real accidents, and eventually, to prevent, particularly severe accidents. In this paper, a tool chain is introduced that enables fully automated traffic situation detection in wide-area traffic on the basis of a single camera. The tool chain takes into account novel powerful methods for object detection, classification and track- ing on the basis of robust regression with preconditioning. Moreover, the tool chain considers methods for traffic situation detection and classification on the basis of probabilistic approaches and eventually, traffic event recording. The approach was tested at an ungated level crossing in the small town Bien-rode, which is a district of Brunswick, Germany. It is shown that atypical situations, e.g. overtaking, braking, stopping, inadequate speeds, and accelerations, as well as critical situations, e.g. tailgating, can be detected within a range of up to 120 m distance of the camera automatically. The approach enables new ways of analysing traffic areas with regard to traffic safety and performance. The results shown in this paper were obtained in the project OptiSiLK, whose abbreviation means “Optimisation of the safety and the performance at intersections of different traffic modes”. OptiSiLK was funded by the Ministry for Science and Culture of the State of Lower Saxony (MWK).

Keywords

atypical and critical traffic situations, surrogate safety measures, wide-area traffic detection