Impact of driver information system on traffic dynamics on a german autobahn: Lessons for U.S. applications

This paper presents results of an empirical study focusing on the fusion of traffic data from multiple sources-including fixed freeway sensors, floating probe vehicles, dynamic navigation system, and variable speed limit/dynamic message sign data-from a freeway corridor in Munich, Germany. The analysis includes identification of recurrent freeway bottlenecks using archived sensor data, has used these diagnoses to measure the capacity at these cross-sections, and has identified driver behavior (including truck passing activity) that led to the formation of the upstream queues. These results were validated using high-resolution spatio-temporal location data from probe vehicles. The analysis has also compared the magnitude and extent of congestion identified from the archived sensor data with the dynamically reported extent of congestion from the traffic management center. Finally, the study has analyzed the variable speed limit and dynamic message sign data in order to develop an improved understanding of the impacts of these messages on driver behavior and bottleneck formation/location. The results of this project should contribute toward improved travel time estimation and forecasting for traffic management, traveler information and for driver assistance systems. The project benefits from increasing data availability and from the development of a reliable methodology.