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Investigating the Minimum Size of Study Area for an Activity-Based Travel Demand Forecasting Model

机译:研究基于活动的旅行需求预测模型的最小研究区域大小

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Nowadays, considerable attention has been paid to the activity-based approach for transportation planning and forecasting by both researchers and practitioners. However, one of the practical limitations of applying most of the currently available activity-based models is their computation time, especially when large amount of population and detailed geographical unit level are taken into account. In this research, we investigated the possibility of restraining the size of the study area in order to reduce the computation time when applying an activity-based model, as it is often the case that only a small territory rather than the whole region is the focus of a specific study. By introducing an accuracy level of the model, we proposed in this research an iteration approach to determine the minimum size of the study area required for a target territory. In the application, we investigated the required minimum size of the study area surrounding each of the 327 municipalities in Flanders, Belgium, with regard to two different transport modes, that is, car as driver and public transport. Afterwards, a validation analysis and a case study were conducted. All the experiments were carried out by using the FEATHERS, an activity-based microsimulation modeling framework currently implemented for the Flanders region of Belgium.
机译:如今,研究人员和从业人员都对基于活动的运输计划和预测方法给予了极大的关注。但是,应用大多数当前可用的基于活动的模型的实际限制之一是它们的计算时间,尤其是在考虑到大量人口和详细地理单位级别的情况下。在这项研究中,我们研究了限制研究区域的大小以减少应用基于活动的模型时的计算时间的可能性,因为通常只关注一小块区域而不是整个区域具体研究。通过引入模型的准确性级别,我们在本研究中提出了一种迭代方法,以确定目标区域所需的最小研究区域大小。在应用程序中,我们针对两种不同的运输方式,即汽车作为驾驶员和公共交通,调查了比利时佛兰德327个城市中每个研究区域的所需最小面积。之后,进行了验证分析和案例研究。所有实验都是通过使用FEATHERS进行的,FEATHERS是目前在比利时佛兰德地区实施的基于活动的微观模拟建模框架。

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