Simulating the Actions of Commuters Using a Multi-Agent System
Journal of Artificial Societies and Social Simulation
The activity of commuting to and from a place of work a ects 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 e ects of changes to working patterns and locations and inform decision making. In this paper we outline an agent-based so ware framework that combines realworld data from multiple sources to simulate the actions of commuters. We
... emonstrate 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 sta within the organisation to a new work site. Introduction and Motivation . Over million people commute daily within the United Kingdom (DFT ), accounting for % of all journeys made (ONS ). Employing organisations are faced with the need to take into account the impact of commuting activities of their sta and ultimately reduce their impact. There is a range of actions that employers can take, but determining the most e ective action, especially if budgets and time are constrained, is a major di iculty. In this paper we propose a means of modelling and simulating commuter activities that will highlight the e ects of actions, guiding an employer towards adopting those measures that are most likely to result in a meaningful improvement. . Employers can play an important role in decreasing the costs of commuting by adopting commuting trip reduction programmes (Litmann ), e.g. measures could include subsidising public transport, providing facilities for cyclists or promoting car-pooling. The interest of employers in improving commuting conditions may stem from the need to improve productivity (e.g. ensuring that employees reach work punctually and safely) or to make the work environment more attractive (promoting healthy lifestyles). Many organizations regard reducing environmental impact as part of their corporate and social responsibilities and so support sustainable mobility choices. Employers face a major challenge, in that o en limited resources are available to pay for changes thus constraining the options available. . It is desirable for organisations to be able to predict the likely modes of travel used by commuters, this allows an organisation to quantify the e ect that the commuting activities of its workforce has on the environment and community. The ability to predict is useful when an organisation is considering changes in working practices, such as opening new places of work or moving substantial numbers of workers between sites and needs to predict the e ects of such moves.