Dealing with mixed and non-normative traffic. An agent-based simulation with the GAMA platform

PLoS One. 2023 Mar 6;18(3):e0281658. doi: 10.1371/journal.pone.0281658. eCollection 2023.

Abstract

Continuous improvement in computing power allowed for an increase of the scales micro-traffic models can be used at. Among them, agent-based frameworks are now appropriate for studying ordinary traffic conditions at city-scale, but remain difficult to adapt, especially for non-computer scientists, to more specific application contexts (e.g., car accidents, evacuation following a natural disaster), that require integrating particular behaviors for the agents. In this paper, we present a built-in model integrated into the GAMA open-source modeling and simulation platform, allowing the modeler to easily define traffic simulations with a detailed representation of the driver's operational behaviors. In particular, it allows modelling road infrastructures and traffic signals, change of lanes by driver agents and less normative traffic mixing car and motorbike as in some South East Asian countries. Moreover, the model allows to carry out city-level simulations with tens of thousands of driver agents. An experiment carried out shows that the model can accurately reproduce the traffic in Hanoi, Vietnam.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Computer Simulation
  • Humans
  • Motorcycles
  • Natural Disasters*
  • Pentaerythritol Tetranitrate*
  • Physicians*

Substances

  • Pentaerythritol Tetranitrate

Associated data

  • figshare/10.6084/m9.figshare.21369090.v1

Grants and funding

This work is funded by the ANR ESCAPE project, grant ANR-16-CE39-0011-01 of the French National Research Agency (https://anr.fr/) The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.