Simulating the Actions of Commuters Using a Multi-Agent System

Neil Urquhart (), Simon Powers (), Zoe Wall (), Achille Fonzone (), Jiaqi Ge () and J. Gareth Polhill ()
Additional contact information
Neil Urquhart: https://www.napier.ac.uk/people/neil-urquhart
Simon Powers: https://www.napier.ac.uk/people/simon-powers
Jiaqi Ge: https://environment.leeds.ac.uk/geography/staff/2702/jiaqi-ge
J. Gareth Polhill: https://www.hutton.ac.uk/people/gary-polhill/

Journal of Artificial Societies and Social Simulation, 2019, vol. 22, issue 2, 10

Abstract: The activity of commuting to and from a place of work affects not only those travelling but also wider society through their contribution to congestion and pollution. It is desirable to have a means of simulating commuting in order to allow organisations to predict the effects of changes to working patterns and locations and inform decision making. In this paper, we outline an agent-based software framework that combines real-world data from multiple sources to simulate the actions of commuters. We demonstrate the framework using data supplied by an employer based in the City of Edinburgh UK. We demonstrate that the BDI-inspired decision-making framework used is capable of forecasting the transportation modes to be used. Finally, we present a case study, demonstrating the use of the framework to predict the impact of moving staff within the organisation to a new work site.

Keywords: Transport Mode Choice; Transport Network; BDI Agent (search for similar items in EconPapers)
Date: 2019-03-31
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Persistent link: https://EconPapers.repec.org/RePEc:jas:jasssj:2018-86-2

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