Traffic mapping for autonomous cars
Nicolai Steinke, Daniel Göhring, Raúl Rojas – 2018
Today's car traffic is dominated by human drivers. Autonomous cars must comprehend the behavior of human drivers in order to fit in current daily traffic scenarios. To achieve this goal, analysis of the behavior of other traffic participants is necessary. In this paper we present a system to record, store, and analyze the movements of other traffic participants with an autonomous car and evaluate traffic maps, which are obtained from real world experiments. The evaluation shows that the maps cover more than 80% of the driveable area with a precision of 80 to 90%. Additionally, we present the results of a traffic behavior change detection heuristic, which can detect anomalous traffic conditions.