Exploring real-time traffic simulation with massively parallel computing architecture

Abstract

The advent of parallel computing architectures presents an attainable opportunity for transportation professionals to simulate a large-scale traffic network with sufficiently fast response time for real-time operation. However, it necessitates a fundamental change in the modelling algorithm to take full advantage of parallel computing. Currently there are two general types of parallel processing architectures: (a) single instruction multiple data (SIMD) streams, and (b) multiple instruction multiple data streams (MIMD). This paper describes a model to simulate network traffic with the Connection Machine, a massively parallel SIMD computer. First we introduce the basic parallel computing architectures along with a list of commercially available parallel computers. It is followed by an in-depth presentation of the proposed simulation methodology with a massively parallel computer. The proposed traffic simulation model has an inherent path-processing capability to represent drivers' route choice behavior at the individual/vehicle level. Such a feature is critical to its integration with a real-time dynamic assignment model in IVHS applications. The proposed model has been implemented on the Connection Machine. Several simulation experiments were carried out which show that massively parallel computers provide a viable alternative for use in the real-time application. The results show that the CM-2 with 16,384 processors can simulate 32,000 vehicles for 30 minutes at a one-second interval within 3 1 2 minutes.