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Cyclists are more likely to be injured in fatal crashes than motorised vehicles. To gain detailed and precise behavioural data of road users, i.e. trajectories, a measuring campaign was conducted. Therefore, a black-spot for accidents with cyclists in Berlin, Germany was selected. The traffic has been detected by a fully automated traffic video analysis system continuously for twelve hours. The video surveillance system is capable of automatically extracting trajectories, classifying road user types and precise determining and positioning of conflicts and accidents. Additionally, pre-conflict and pre-accident situations could be analysed to provide further in-depth understanding of accident causation. The evaluation of the measuring campaign comprised the investigation of traffic parameters, e.g. traffic flow, as well as traffic-safety related parameters based on Surrogate Safety Measures (SSM). Furthermore, the spatial and temporal distributions of conflicts involving cyclists were determined. As a result, three possible conflict clusters could be identified, of which one cluster could be confirmed by detailed video analysis, showing conflicts caused by right turning vehicles.
Millions of kilometers are driven and recorded by car manufacturers and researchers every year to gather information about realistic traffic situations. The focus of these studies is often the recording of critical situations to create test scenarios for the development of new systems before introducing them into the market. This paper shows a novel Analysis and Investigation Method for All Traffic Scenarios (AIMATS) based on real traffic scenes. It also shows how to get detailed information about speeds, trajectories and behavior of all participants without driving thousands of kilometers at the example of conflict situations with animals. Basis of the AIMATS is the identification of the most relevant locations as "Points of Interest" (POI), the recording of the critical situations and their "base lines" at these POI. This paper presents a new method to identify critical scenarios involving both vehicles and animals as well as preliminary results of a study done in Saxony using this new method.