An agent-based approach to modelling driver route choice behaviour under the influence of real-time information

An agent-based approach to modelling individual driver behaviour under the influence of real-time traffic information is presented and the potential to develop more complex driver behavioural dynamics based on the belief-desire-intention agent architecture is demonstrated.

Abstract

This paper presents an agent-based approach to modelling individual driver behaviour under the in-fluence of real-time traffic information. The driver behaviour models developed in this study are based on a behavioural survey of drivers which was conducted on a congested commuting corridor in Brisbane, Australia, Commuters responses to travel information were analysed and a number of discrete choice models were developed to determine the factors influencing behaviour and their propensity to change route and adjust travel patterns. Based on the results obtained from the behavioural survey, the agent behaviour parameters which define driver characteristics, knowledge and preferences were identified and their values determined. A case study implementing a simple agent-based route choice decision model within a microscopic traffic simulation tool is also presented. Driver-vehicle units (DVUs) were modelled as autonomous software components that can each be assigned a set of goals to achieve and a database of knowledge comprising certain beliefs, intentions and preferences concerning the driving task. Each DVU provided route choice decision-making capabilities, based on perception of its environment, that were similar to the described intentions of the driver it represented. The case study clearly demonstrated the feasibility of the approach and the potential to develop more complex driver behavioural dynamics based on the belief- desire-intention agent architecture.