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

Abstract

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.