An agent-based framework for the assessment of drivers´ decision-making

This paper addresses the complexity of modelling drivers behaviour by the adoption of agent-based techniques. As human factors are central to intelligent transportation systems (ITS), it has became imperative to consider the uncertainty and variability inherent in drivers´ behaviour for simulation frameworks aimed at assessing ITS technologies. An agent-based extension to an existing microscopic simulation model, DRACULA, is suggested which aims at benefiting from characteristics such as reasoning capabilities and autonomy, offered by agent-based approaches. The scope of this work is particularly concerned with the departure time and route choice processes in a commuter scenario