An agent based model for the simulation of transport demand and land use. Application to a Sydney metropolitan area
RIS ID
97842
Abstract
Agent based modelling has emerged as a promising tool to provide planners with sophisticated insights on social behaviour and the interdependencies characterising urban system, particularly with respect to traffic and transport planning. This paper presents an agent based model for the simulation of road traffic and transport demand of an urban area in south east Sydney, Australia. In this model, each agent represents an individual in the population of the study area. Each individual in the model has a travel diary which comprises a sequence of trips the person makes in a representative day as well as trip attributes such as travel mode, trip purpose, and departure time. Individuals in the model are associated with each other by their household relationship, which helps define the interdependencies of their travel diary and constrains their mode choice. This feature allows the model to not only realistically reproduce how the current population uses existing transport infrastructure but more importantly provide comprehensive insight into future transport demands of an urban area. The router of the traffic micro-simulation package TRANSIMS is incorporated in the agent based model to inform the actual travel time of each trip (which agents use in considering new travel modes) and changes of traffic density on the road network. Simulation results show very good agreement with survey data in terms of the distribution of trips done by the population by transport modes and by trip purposes, as well as the traffic density along the main road in the study area.
Publication Details
Huynh, N., Cao, V. Lam., Wickramasuriya, R., Berryman, M., Perez, P. & Barthemlemy, J. (2015). An agent based model for the simulation of transport demand and land use. Application to a Sydney metropolitan area. In T. Dolan & B. Collins (Eds.), International Symposium for Next Generation Infrastructure (ISNGI 2014) (pp. 69-74). United Kingdom: University College London.