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Route Choice Through Regions by Pedestrian Agents (Short Paper)

Authors Gabriele Filomena , Ed Manley , Judith A. Verstegen

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Author Details

Gabriele Filomena
  • Institute for Geoinformatics, University of Münster, Germany
Ed Manley
  • The Bartlett Centre for Advanced Spatial Analysis, University College London, London, UK
  • The Alan Turing Institute, London, UK
Judith A. Verstegen
  • Institute for Geoinformatics, University of Münster, Germany

Cite AsGet BibTex

Gabriele Filomena, Ed Manley, and Judith A. Verstegen. Route Choice Through Regions by Pedestrian Agents (Short Paper). In 14th International Conference on Spatial Information Theory (COSIT 2019). Leibniz International Proceedings in Informatics (LIPIcs), Volume 142, pp. 5:1-5:8, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)
https://doi.org/10.4230/LIPIcs.COSIT.2019.5

Abstract

Simulation models for pedestrian movement are valuable tools to support decision-making processes in urban design. However, existing models of pedestrian behaviour are built on simplistic assumptions regarding people’s representation of the urban space and spatial behaviour. In this work, a route-choice algorithm that takes into account regionalisation processes and the hierarchical organisation of geographical elements is adapted for pedestrian movement and incorporated into an agent-based model. The macro-level patterns emerging from two scenarios, one employing an angular-change minimisation algorithm and the other employing the regional algorithm here proposed, are compared for a case study in London, UK. Our routing algorithm led agents to recur to a higher number of street segments, i.e. routes were more diverse among agents. Though validation has not yet been performed, we deem the patterns resulting from the regional algorithm more plausible.

Subject Classification

ACM Subject Classification
  • Computing methodologies → Multi-agent systems
Keywords
  • pedestrians
  • agent-based modelling
  • street network
  • cognitive regions
  • cognitive maps
  • Lynch

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