Hybrid agent based simulation with adaptive learning of travel mode choices for university commuters (WIP)

Authors:
Nagesh Shukla;Albert Munoz;Jun Ma;Nam Huynh
Affiliations:
University of Wollongong, Wollongong, Australia;University of Wollongong, Wollongong, Australia;University of Wollongong, Wollongong, Australia;University of Wollongong, Wollongong, Australia
Venue:
Proceedings of the Symposium on Theory of Modeling & Simulation - DEVS Integrative M&S Symposium
Year:
2013

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Abstract

This paper presents a methodology for developing a hybrid agent-based micro-simulation model to capture the impacts of commuter travel mode choices on a University campus transport network. The proposed methodology involves: (i) developing realistic population of commuter agents (students and staff); (ii) assigning activity lists and travel mode choices to agents using machine learning method; and, (iii) traffic micro-simulation of the study area transport network. This furthers the understanding of current transport modal distributions, factors affecting the travel mode choice decisions, and, network performance through a number of hypothetical travel scenarios.