Enabling Crowd Simulations To Handle Ripple Effects Across Transport Networks

EasyChair Preprint 2065

Abstract

Pedestrian modelling and simulation has been vastly researched over the last decades, resulting in the emergence of a wide range of software packages that are sophisticated and yet computationally efficient enough for reliable reproducing and investigations of pedestrian movements through complex environments. Many studies can be found successfully using these powerful tools for crowd management and/or facility management at public transport stations. However, there are gaps in understanding the ripple effect of crowding and passenger demands at a station to the crowdedness at stations further down a transit line. This paper reports a computational framework that links crowd simulations at a number of transit stations of an urban network. Inherently the framework allows for the simulation of the transferring of mobility characteristics of passengers along a transit line as they travel from one station to another and its impacts on crowdedness at these stations. The framework should be adaptable to any crowd simulation package. The open source Python implementation of the framework and of the proof of concept would help enhance their reproducibility and be useful to both researchers and practitioners.

Keyphrases: MassMotion, Pedestrian, Transportation, crowd simulation

@booklet{EasyChair:2065,
  author    = {Nam Huynh and Johan Barthelemy and Pascal Perez},
  title     = {Enabling Crowd Simulations To Handle Ripple Effects Across Transport Networks},
  howpublished = {EasyChair Preprint 2065},
  year      = {EasyChair, 2019}}