The development of Advanced Transport Telematics (ATT) systems has highlighted the need for a significantly improved treatment of the impact of information on travel behaviour. The aim of this paper is to describe a new microsimulation model (DynaMIT) which has been specially developed for analysing the behavioural impacts of ATT systems, especially dynamic traveller information systems. The model uses satisfying search techniques, developed in the field of Artificial Intelligence, to model the planning and execution of route choice. These techniques represent a powerful new theoretical foundation not only to model the travel planning process, but also to model en-route modification of plans in plans in response to information messages. The first section of the paper introduces some of the key issues involved in modelling the effects of information on travel behaviour and briefly reviews existing modelling approaches. The second section outlines the overall structure of the DynaMIT model and the third section describes the basis of the search heuristic, which is the behavioural core of the model. The fourth section discusses the implementation of the model, including the role of object-oriented programming technologies. The fifth section presents the results of an application of the model to the analysis of a parking guidance system. The final section presents overall conclusions and discusses direction for future work. An abstract only is published in this seminar.
Abstract