Combining Static and Dynamic Models for Traffic Signal Optimization Inherent Load-dependent Travel Times in a Cyclically Time-expanded Network Model

Abstract

Travel times in traffic models are of great interest for developing realistic solutions for traffic assignment and traffic signal coordination in urban traffic networks. In this paper, we present a cyclically time-expanded network for this purpose, which is a static and linear model from its structure. However, it provides enough dynamics to reproduce load-dependent travel times and it is capable to model traffic signals. Thus, this traffic flow model is at the cutting-edge of static and dynamic models, and furthermore, it allows the simultaneous optimization of traffic assignment and signal coordination with exact mathematical programming techniques. We study the inherent properties of the travel times in this model and demonstrate its capabilities by simulation results obtained with state-of-the-art simulation tools.