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

Conference Paper


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.

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). In Simulation Series Vol. 45 (pp. 9-14).

Scopus Eid


  • 2-s2.0-84876854923

Start Page


  • 9

End Page


  • 14

Volume


  • 45

Issue


  • 4

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.

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). In Simulation Series Vol. 45 (pp. 9-14).

Scopus Eid


  • 2-s2.0-84876854923

Start Page


  • 9

End Page


  • 14

Volume


  • 45

Issue


  • 4