Simulating Transport and Land Use Interdependencies for Strategic Urban Planning—An Agent Based Modelling Approach

Abstract

Agent based modelling has been widely accepted as a promising tool for urban planning purposes thanks to its capability to provide sophisticated insights into the social behaviours and the interdependencies that characterise urban systems. In this paper, we report on an agent based model, called TransMob, which explicitly simulates the mutual dynamics between demographic evolution, transport demands, housing needs and the eventual change in the average satisfaction of the residents of an urban area. The ability to reproduce such dynamics is a unique feature that has not been found in many of the like agent based models in the literature. TransMob, is constituted by six major modules: synthetic population, perceived liveability, travel diary assignment, traffic micro-simulator, residential location choice, and travel mode choice. TransMob is used to simulate the dynamics of a metropolitan area in South East of Sydney, Australia, in 2006 and 2011, with demographic evolution. The results are favourably compared against survey data for the area in 2011, therefore validating the capability of TransMob to reproduce the observed complexity of an urban area. We also report on the application of TransMob to simulate various hypothetical scenarios of urban planning policies. We conclude with discussions on current limitations of TransMob, which serve as suggestions for future developments.

A dynamic behavioural traffic assignment model with strategic agents

“…The strategic agents have been used in Transmob, an agent-based model which simulates the dynamics between demographic evolution, transport demands, housing needs and the eventual change in the average satisfaction of the residents of Randwick, a suburb of Sydney (Australia). The different modules of Transmob, including the traffic demand generation and assignment as well as their validations are detailed in (Huynh et al, 2015). The simulation involves 100,000 agents (of which 25% are strategic) performing 360,000 trips during a typical weekday in a network made of 7,000 nodes and 17,000 links.…”

A Fine Grained Hybrid Spatial Microsimulation Technique for Generating Detailed Synthetic Individuals from Multiple Data Sources: An Application to Walking and Cycling

“…Transport microsimulation is widely used to generate a population of individuals for use in activity based models. Such models take behavioural data to forecast travel patterns and demand over a city or region (Barthelemy & Toint, 2015;Barton, Thompson, Burgess, & Grant, 2015;Beckman, Baggerly, & McKay, 1996;Guo & Bhat, 2007;Huynh, Perez, Berryman, & Barthélemy, 2015;Ma, Heppenstall, Harland, & Mitchell, 2014;Müller, Axhausen, Axhausen, & Axhausen, 2010). As a typical example, the ILUTE model integrates the simulation of the land-use and transport environment and their development over time (Salvini & Miller, 2005), given input data (census data, activity survey data, travel survey data and land-use data).…”

Modelling future impacts of urban development in Kuwait with the use of ABM and GIS

“…ABM is such a tool, and has been integrated with GIS for modeling predictions and assessing plans (Brueckner, ; Clark, ; Liu, , Jokar Arsanjani, Helbich, & De Noronha Vaz, ; Waddell, ). The combination is regarded as a powerful way to model spatiotemporal dynamics of urban development (Zhang, Jin, Wang, Zhou, & Shu, ) or the dynamics between demographics, transportation, housing and the average satisfaction of the residents (Huynh, Perez, Berryman, & Barthelemy, ).…”