A Multi-agent Demand Model

The rapid growth of urban areas has deserved special attention from the technical and scientific community over the last decades. Traffic and transportation systems have been a subject of special concern as they play an important and indispensable role in today’s society. Heterogeneity and uncertainty have become even more evident, and researchers have been challenged by how to cope with modelling and simulating new measures brought about by the adoption of new information technologies. According to Schleiffer (2000), modelling heterogeneity in a microscopic level is a key step toward the understanding of a macroscopic behaviour, and the use of artificial agents to represent individual mechanisms is the tool to better comprehend highly complex and dynamic collective behaviour of traffic. In this work, we use agent-based techniques to represent traffic demand as a community of autonomous driver agents. Our approach relies on an extension to the DRACULA microsimulation suite, as proposed in (Rossetti et al., 2000). Drivers are modelled by way of the BDI architecture (Belief, Desire, and Intention) and our focus is given to route and departure time choices.