On-Line Simulation and . . .

We study an approach to forecast vehicular traffic using a micro-simulator. In order to provide network-wide information about the current traffic state a cellular automaton traffic flow model is combined with measured data. The framework is applied to the freeway network of North Rhine-Westphalia, where data from about 3,500 loop detectors are available and provided on-line minute by minute. Further, heuristics based on the statistical analysis of historical data are developed. Combining these methods and the results obtained we present an Internet application. This can provide the traffic information given by the on-line simulation such as travel times and the current traffic state for a broad public

Cellular Automaton Modeling of the Autobahn Traffic in North Rhine-Westphalia

In 1992 Nagel and Schreckenberg proposed a stochastic cellular automaton model of vehicular traffic [13], which was able to reproduce some empirically observed non-trivial traffic phenomena like spontaneous traffic jam formation. This publication captured the interest of the physicists community and ever since there has been a continuous progress in the development of cellular automata models of vehicular traffic. The most recent models are able to reproduce free flow, spontaneous jam formation, synchronized traffic, as well as meta-stability. However, these models have one major drawback. They were developed and tested on topologically simple road networks and the translation to large and topologically complex real road networks is non-trivial. In this paper we describe the cellular automaton model we use to simulate the traffic on the autobahn network in North Rhine-Westphalia. Further, we consider some algorithmic implementation details and discuss some of the challenges that arise when using this model on such a huge and topologically complex network