Applicability and Application of Microscopic Traffic Simulations ; Anwendbarkeit und Anwendung mikroskopischer Verkehrssimulationen

Traffic flow is a very prominent example of a driven non-equilibrium system, which shows a very complex spatiotemporal dynamics. A characteristic phenomenon of traffic dynamics is the spontaneous and abrupt drop of the average velocity on a stretch of road leading to congestion. To assess the quality of three selected microscopic traffic models (the Nagel-Schreckenberg model (NSM), the intelligent driver model (IDM), and the comfortable driving model (CDM)), we study their ability to reproduce such a traffic breakdown, whose spatiotemporal dynamics we investigate as well. Our analysis is based on empirical traffic data from stationary loop detectors showing a spontaneous breakdown on a German Autobahn. We then present several methods to assess the results and to compare the models with each other. In addition, we will also discuss some important modeling aspects and their impact on the resulting spatiotemporal pattern. For the CDM, which gave good results in this assessment, we analyze the spatiotemporal patterns resulting from different inflow and outflow rates with open boundary conditions. Based on time series of local measurements, the local traffic states are assigned to different traffic phases according to Kerner's three-phase traffic theory. For this classification we use the rule-based FOTO-method, which was developed by Kerner et al. in 2002. Our analysis shows that the model is indeed able to reproduce three qualitatively different traffic phases: free flow, synchronized traffic, and wide moving jams. This is surprising because traffic models with a fundamental diagram, such as the CDM, are not expected to reproduce the synchronized phase. By virtue of this overall good agreement with empirical findings, we chose the CDM to investigate via computer simulations how traffic congestion can be reduced with the help of vehicle-to-vehicle communication. As the reasons for a traffic breakdown are perturbations caused by human drivers in dense traffic, we propose using periodically emitted status messages to ...