Mikroskopische Verkehrssimulationen auf Basis der 3-Phasen-Theorie zur Stauerkennung und zum Automatisierten Fahren

Autoren

J. Paczia, H. Rehborn, O. Stein - Mercedes Benz AG, S. Klenov - Moskow Institute of Physics and Technology, B. Kerner, M. Schreckenberg - Universität Duisburg-Essen

Zusammenfassung

Modern navigation systems use probe vehicle data in order to avoid increased travel times due to traffic congestions. To ensure a high reliability of such traffic information it is crucial to receive data from a certain percentage of probe vehicles in the total traffic flow. Microscopic traffic simulations allow to examine the number of vehicles sending data to achieve a desirable data quality for congestion recognition. These simulations based on the three-phase traffic theory by Kerner allow the investigation of arbitrary congested traffic scenarios, we focus on a synchronized flow pattern and a general congested traffic pattern. In this paper, we review some last results of microscopic traffic simulations of the effect of automated driving on traffic breakdown in mixed traffic as well as make an analysis of some simulations of the application of probe vehicle data to gain traffic information and to improve traffic navigation systems. The simulations reveal that the detection of a travel time increase of 2 min with up to 2 min latency much less than 5 % probe vehicles are required in order to achieve a 90 % detection probability at the data center. The traffic simulations also reveal some features of mixed traffic with automated and non-automated vehicles. Suboptimal driving automated vehicles can produce traffic congestions instead of improving traffic. Automated vehicles driving similar to human drivers are able to improve the traffic flow. One general conclusion is that only a small number of suboptimal driving automated vehicles can lead to a traffic breakdown while a much larger percentage of well-driving automated vehicles would be necessary to suppress such traffic breakdowns in mixed traffic.