Modeling Intelligent Traffic Control System for Urban Agglomeration

This paper presents the modeling of an intelligent system for traffic control in urban agglomerations. The modeling process is complex and consists of several stages. The first step consists of modeling the capacity of urban transportation network using neural networks. The second step is to evaluate the level of traffic controllability using hierarchical sensitivity analysis. The third step involves classification of the transportation network using neuro- fuzzy classifier. All these stages precede managerial decisions on creation and regulation of traffic flows within the urban network.