Skip to main content
placeholder image

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

Conference Paper


Download full-text (Open Access)

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.

Authors


  •   Shukla, Nagesh (external author)
  •   Munoz, Albert
  •   Ma, Jun
  •   Huynh, Nam N. (external author)

Publication Date


  • 2013

Citation


  • Shukla, N., Munoz, A., Ma, J. & Huynh, N. (2013). Hybrid agent based simulation with adaptive learning of travel mode choices for University commuters (WIP). Proceedings of the Symposium on Theory of Modeling & Simulation - DEVS Integrative M&S Symposium (pp. 1-6). United States: Society for Computer Simulation International.

Scopus Eid


  • 2-s2.0-84876854923

Ro Full-text Url


  • http://ro.uow.edu.au/cgi/viewcontent.cgi?article=1126&context=smartpapers

Ro Metadata Url


  • http://ro.uow.edu.au/smartpapers/99

Start Page


  • 1

End Page


  • 6

Place Of Publication


  • http://dl.acm.org/citation.cfm?id=2499636

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.

Authors


  •   Shukla, Nagesh (external author)
  •   Munoz, Albert
  •   Ma, Jun
  •   Huynh, Nam N. (external author)

Publication Date


  • 2013

Citation


  • Shukla, N., Munoz, A., Ma, J. & Huynh, N. (2013). Hybrid agent based simulation with adaptive learning of travel mode choices for University commuters (WIP). Proceedings of the Symposium on Theory of Modeling & Simulation - DEVS Integrative M&S Symposium (pp. 1-6). United States: Society for Computer Simulation International.

Scopus Eid


  • 2-s2.0-84876854923

Ro Full-text Url


  • http://ro.uow.edu.au/cgi/viewcontent.cgi?article=1126&context=smartpapers

Ro Metadata Url


  • http://ro.uow.edu.au/smartpapers/99

Start Page


  • 1

End Page


  • 6

Place Of Publication


  • http://dl.acm.org/citation.cfm?id=2499636