An agent-based model for modal shift in public transport

Authors:
  • TBThibaut Barbet
    Thibaut Barbet
  • ANAmine Nacer-Weill
    Amine Nacer-Weill
  • CYChangtao Yang
    Changtao Yang
  • JRJuste Raimbault
    Juste Raimbault
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Abstract
Modal shift in public transport as a consequence of a disruption on a line has in some cases unforeseen consequences such as an increase in congestion in the rest of the network. How information is provided to users and their behavior plays a central role in such configurations. We introduce here a simple and stylised agent-based model aimed at understanding the impact of behavioural parameters on modal shift. The model is applied on a case study based on a stated preference survey for a segment of Paris suburban train network. We systematically explore the parameter space and show non-trivial patterns of congestion for some values of discrete choice parameters linked to perceived wait time and congestion. We also apply a genetic optimisation algorithm to the model to search for optimal compromises between congestion in different modes.
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