A DSS approach to urban traffic management

Urban traffic management is a continuous decision process of coordination of all the individual elements (traffic signals, arterial roads, traffic, parking) and the interrelated components of urban transport (private cars, transit, pedestrians, etc.). Its aim is the achievement of maximum efficiency and productivity for the whole system through the application of operating, pricing, regulatory and service policies. For this purpose, many different specific problems have been addressed and several models developed according to the classical system engineering approach. However, the complexity or urban traffic systems and the presence of a large number of conflicting goals and objectives postulated by various groups emphasizes the need for a DSS approach in this field. Thanks to this approach, the integration of different methods and techniques (e.g. Operations Research and Artificial Intelligence) and the effective support of public decision making could be obtained. Moreover, the approach and the scenario considered must also take into account the needs arising from the introduction of new information technologies and strategies in urban transport systems, such as route guidance, integrated traffic control and demand management. In this paper, a general DSS architecture is presented and its main components are analyzed and discussed. In particular, attention is focused on the model base, composed of the following relevant tools: resource optimization models, traffic simulation and evaluation models. The latter are based on cost-benefit effectiveness, multicriteria analysis and goal achievement analysis. Finally, some of the ideas and results attained by the research we are currently carrying our within Drive/EEC and Prometheus/Eureka projects are illustrated.