Agent-Based Simulation of Traffic Jams, Crowds, and Supply Networks
Thursday, November 6, 2003 - 8:45am - 9:20am
Dirk Helbing (TU Dresden)
Why are vehicles sometimes stopped by so-called phantom traffic jams, although they all like to drive fast? What are the mechanisms behind stop-and-go traffic? Why are there several different kinds of congestion, and how are they related? Why do most traffic jams occur considerably before the road capacity is reached? Can a temporary reduction of the traffic volume cause a lasting traffic jam? All of this is important to understand from the perspective of intelligent transportation systems. Surprisingly, speed limits can speed up traffic under certain conditions, and traffic lights at on-ramps can reduce the overall travel times. Driver assistance systems have a particularly high potential. And decision experiments are carried out in order to learn re-routing strategies which do not invalidate traffic forecasts. A lot has also been learned about pedestrian streams. In particular, we understand why pedestrians moving in opposite directions normally organize in lanes, while similar systems are freezing by heating. In other cases, one observes fluctuation-induced ordering, oscillations of the flow direction at bottlenecks, rotary traffic, or herding effects. We also understand why panicking pedestrians produce dangerous deadlocks and how these can be avoided by a skillful design of buildings. These insights can be applied to optimize production processes.