A cognitive model for routing in agent-based modelling

Jascha Grübel*, Sarah Wise, Tyler Thrash, Christoph Hölscher

*Corresponding author for this work

Research output: Contribution to Book/Report typesConference contributionpeer-review

Abstract (may include machine translation)

Agent-based modelling (ABM) can be used as a computational tool to model human routing behaviour, and offers particular promise when combined with insights from cognitive science. In this paper, we introduce typical errors into the encoding of the agents mental representation of the environment. This method deviates from the classical computer science paradigm of optimality to capture human behaviour more accurately. By incorporating common distance and direction estimation errors, our model produces routes with fewer computational artefacts such as zigzagging (i.e., turning more often than the typical human) and bottlenecks (i.e., routing through one particular node that maximises efficiency). We demonstrate our results in regular and irregular environments and validate our model using a set of real-world footfall data from Westminster, London.

Original languageEnglish
Title of host publicationInternational Conference on Numerical Analysis and Applied Mathematics, ICNAAM 2018
EditorsTheodore Simos, Charalambos Tsitouras
PublisherAmerican Institute of Physics Inc.
ISBN (Electronic)9780735418547
DOIs
StatePublished - 2019
Externally publishedYes
EventInternational Conference on Numerical Analysis and Applied Mathematics 2018, ICNAAM 2018 - Rhodes, Greece
Duration: 13 Sep 201818 Sep 2018

Publication series

NameAIP Conference Proceedings
Volume2116
ISSN (Print)0094-243X
ISSN (Electronic)1551-7616

Conference

ConferenceInternational Conference on Numerical Analysis and Applied Mathematics 2018, ICNAAM 2018
Country/TerritoryGreece
CityRhodes
Period13/09/1818/09/18

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