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.

中文翻译：

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使用多智能体系统模拟通勤者的行为

上下班的通勤活动不仅影响出行者，还通过其对交通拥堵和污染的影响而影响整个社会。希望有一种模拟通勤的方法，以使组织能够预测工作模式和位置​​变化的影响并告知决策。在本文中，我们概述了一个基于代理的软件框架，该框架结合了来自多个来源的真实数据来模拟通勤者的行为。我们使用英国爱丁堡市一家雇主提供的数据来演示该框架。我们证明，采用BDI启发的决策框架能够预测要使用的运输方式。最后，我们提出一个案例研究，