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

机译:基于活动的中型城市模型考虑外部活动 - 旅行:增强羽毛框架

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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:旅行需求建模已经从传统的四步模型演变为基于旅游的模型,最终成为基于先进的基于活动的模型(ABM)的基础。 ABM对他人的附加值是通过考虑生活在该地区的个人的完整活动旅行模式来测试各种政策情景的能力。然而,大多数ABM限制了居民在研究区内的活动,导致旅行模式扭曲。外部旅行通过外部模型单独建模,外部模型对ABM能够分析的策略测试不敏感。因此,为了最大限度地减少外部旅行,传输规划人员倾向于定义更大的研究区域。然而,这种方法需要巨大的资源,从而显着阻碍了ABM的全球渗透。为了克服这些限制,本研究将框架呈现在研究区域以外的居民旅行和活动的框架,作为完整活动旅行时间表的一部分。这是通过包括集水区(CA),研究区域之外的区域,在目的地选择模型中实现。在目的地选择模型中,引入了顶级模型,指定研究区域内或外部目的地的每个活动。对于在研究区域内进行的活动,使用详细的土地使用信息来确定确切的位置。然而,对于CA的活动,提出了另一系列模型,该模型使用从开源平台获得的土地利用信息,以最大限度地减少数据收集工作。这些修改是在羽毛中实施的,对法兰德斯,比利时和方法进行的ABM运营在佛兰德斯的三个中等区域上进行测试。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的模型输出的改进。此外,许多情况下也发现兴趣点(POI)密度是显着的。最后,提出了一个全面的验证框架,以比较ABM的中型区域对佛兰德斯的ABM的结果。验证包括(DIS)的活动,旅行和旅行中的汇总分布,空间和结构(例如,使用的运输模式和所使用的类型)通过11措施。结果表明,两个ABM(即,用于中型地区的ABM和佛兰德斯的ABM之间的类似分布,从而证实了所提出的方法的有效性。因此,这项研究将导致中大区域的ABM的发展。 (c)2019 Elsevier B.v.保留所有权利。

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