Combining Static and Dynamic Models for Traffic Signal Optimization Inherent Load-dependent Travel Times in a Cyclically Time-expanded Network Model
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, a cyclically time-expanded network is presented 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 of modelling 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. The authors study the inherent properties of travel times in this model and demonstrate its capabilities by simulation results obtained with state-of-the-art simulation tools.
In this paper we treat multistate systems under the same setting as the one of F. Ohi and T. Nishida [14], i.e., all the state spaces of components and the system are not necessarily the same. Definitions of series and parallel systems are introduced and existence theorems for such systems are given. Furthermore, it is shown that the preservation of IFR-stochastic property determines a multistate system as a series system. This fact is proved by using the concept of hazard transform of which definition has been presented by F. Ohi and T. Nishida [14].