Christopher Barrett, Kai Nagel, Marcus Rickert
Paper #: 96-10-080
Large-scale microscopic (i.e., vehicle-based) traffic simulations pose high demands on computational speed in at least two application areas: (i) real-time traffic forecasting, and (ii) long-term planning applications (where repeated “looping” between the microsimulation and the simulated planning of individual person’s behavior is necessary). As a rough number, a real-time simulation of an area such as Los Angeles (ca. 1 million travelers) will need a computational speed of much higher than 1 million “particle” (=vehicle) updates per second. This paper reviews how this problem is approached in different projects and how these approaches are dependent both on the specific questions and on the prospective user community. The approaches reach from highly parallel and vectorizable, single-bit implementations on parallel supercomputers for Statistical Physics questions, via more realistic implementations on coupled workstations, to more complicated driving dynamics implemented again on parallel supercomputers.