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Activity-based model for medium-sized cities considering external activity-travel: Enhancing FEATHERS framework

机译:考虑外部活动旅行的中型城市基于活动的模型:增强FEATHERS框架

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Travel demand modeling has evolved from the traditional four-step models to tour-based models which eventually became the basis of the advanced Activity-Based Models (ABM). The added value of the ABM over others is its ability to test various policy scenarios by considering the complete activity-travel pattern of individuals living in the region. However, the majority of the ABM restricts residents' activities within the study area which results in distorted travel patterns. The external travel is modeled separately via external models which are insensitive to policy tests that an ABM is capable of analyzing. Consequently, to minimize external travel, transport planners tend to define a larger study area. This approach, however, requires huge resources which significantly deterred the worldwide penetration of ABM. To overcome these limitations, this study presents a framework to model residents' travel and activities outside the study area as part of the complete activity-travel schedule. This is realized by including the Catchment Area (CA), a region outside the study area, in the destination choice models. Within the destination choice models, a top-level model is introduced that specifies for each activity its destination inside or outside the study area. For activities to be performed inside the study area, the detailed land use information is utilized to determine the exact location. However, for activities in the CA, another series of models are presented that use land use information obtained from open-source platforms in order to minimize the data collection efforts. These modifications are implemented in FEATHERS, an ABM operational for Flanders, Belgium and the methodology is tested on three medium-sized regions within Flanders. The results indicate improvements in the model outputs by defining medium-sized regions as study areas as compared to defining a large study area. Furthermore, the Points of Interests (POI) density is also found to be significant in many cases. Lastly, a comprehensive validation framework is presented to compare the results of the ABM for the medium-sized regions against the ABM for Flanders. The validation includes the (dis)aggregate distribution of activities, trips, and tours in time, space and structure (e.g. transport modes used and types of activities performed) through eleven measures. The results demonstrate similar distributions between the two ABM (i.e. ABM for medium-sized regions and for Flanders) and thus confirms the validity of the proposed methodology. This study, therefore, shall lead to the development of ABM for medium-sized regions. (C) 2019 Elsevier B.V. All rights reserved.
机译:出行需求建模已从传统的四步模型演变为基于旅行的模型,最终成为高级基于活动的模型(ABM)的基础。反弹道导弹相对于其他导弹的附加价值在于,它能够通过考虑居住​​在该地区的个人的完整活动旅行模式来测试各种政策方案。但是,大多数ABM限制了居民在研究区内的活动,这导致了出行方式的扭曲。外部旅行是通过外部模型分别建模的,这些外部模型对ABM能够分析的策略测试不敏感。因此,为了尽量减少外部旅行,运输计划者倾​​向于定义更大的研究区域。但是,这种方法需要大量资源,这极大地阻碍了ABM在全球的普及。为了克服这些局限性,本研究提出了一个框架,以模拟居民在研究区域外的旅行和活动,这是完整的活动旅行时间表的一部分。这是通过在目标选择模型中包括集水区(CA)(研究区域之外的区域)来实现的。在目的地选择模型中,引入了一个顶级模型,该模型为每个活动指定其在研究区域之内或之外的目的地。对于要在研究区域内进行的活动,利用详细的土地使用信息来确定确切的位置。但是,对于CA中的活动,提出了另一系列的模型,这些模型使用从开源平台获得的土地使用信息,以最大程度地减少数据收集工作。这些修改是在FEATHERS中进行的,FEATHERS是比利时法兰德斯的ABM业务,并且对该方法在法兰德斯内的三个中型地区进行了测试。结果表明,与定义大型研究区域相比,通过将中型区域定义为研究区域,模型输出得到了改善。此外,在许多情况下,兴趣点(POI)的密度也很重要。最后,提出了一个全面的验证框架,以比较中型地区的ABM与法兰德斯的ABM的结果。验证包括通过11种措施在时间,空间和结构上(活动),旅行和旅行的(非)总体分布(例如使用的运输方式和进行的活动类型)。结果证明了两种ABM(即中型地区和佛兰德地区的ABM)之间的相似分布,因此证实了所提出方法的有效性。因此,这项研究将导致中等规模地区反导系统的发展。 (C)2019 Elsevier B.V.保留所有权利。

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