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Simulating the Actions of Commuters Using a Multi-Agent System

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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.

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  • Neil Urquhart & Simon Powers & Zoe Wall & Achille Fonzone & Jiaqi Ge & J. Gareth Polhill, 2019. "Simulating the Actions of Commuters Using a Multi-Agent System," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 22(2), pages 1-10.
    • Handle: RePEc:jas:jasssj:2018-86-2
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    1. Sundo, Marloe B. & Fujii, Satoshi, 2005. "The effects of a compressed working week on commuters' daily activity patterns," Transportation Research Part A: Policy and Practice, Elsevier, vol. 39(10), pages 835-848, December.
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