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Axis of travel: Modeling non-work destination choice with GPS data

机译:行驶轴:使用GPS数据为非工作目的地选择建模

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The advent of GIS and GPS has revolutionized how we monitor and model destination choice. New methodologies in building choice sets can be developed and new insights on travel behavior can be gained given the real-time GPS travel data. To this end, this research investigates how land use, road network structure, and axis of travel influence home-based, non-work destination choice based on in-vehicle GPS travel data in the Minneapolis-St. Paul Metropolitan Area in 2008. We propose a novel choice set formation approach combining survival analysis and random selection and a new approach to deciding choice set size. Mixed-effects logit models are used to model our data with repeated observations for each participant. Our findings identify the following factors that influence non-work destination choice: (1) Walkable opportunities and diversity of services at destinations, (2) Route-specific factors such as turn index and speed discontinuity, and (3) Axis of travel measured by relative travel time to work, home, and downtown. A destination closer to the axis of home and work, all else equal, is more likely to be selected. A destination far away from downtown is more attractive to auto users. This research contributes to methodologies in building choice sets for modeling non-work destination choice. The results enhance our understanding of non-work destination choice and have implications for transportation and land use planning. Published by Elsevier Ltd.
机译:GIS和GPS的出现彻底改变了我们监视和模拟目的地选择的方式。借助实时GPS旅行数据,可以开发出建筑选择集的新方法,并且可以获得关于旅行行为的新见解。为此,本研究基于明尼阿波利斯街的车载GPS旅行数据,研究了土地利用,道路网络结构和旅行轴如何影响基于家庭的非工作目的地的选择。保罗都会区(Paul Metropolitan Area)在2008年。我们提出了一种将生存分析和随机选择相结合的新颖选择集形成方法,以及一种确定选择集大小的新方法。混合效应logit模型用于对我们的数据进行建模,并对每个参与者进行重复观察。我们的发现确定了以下因素,这些因素会影响非工作目的地的选择:(1)目的地的可步行机会和服务多样性;(2)特定于路线的因素,例如转弯指数和速度不连续性;以及(3)上班,回家和市区的相对旅行时间。在其他条件相同的情况下,更可能选择更接近住所和工作中心的目的地。远离市区的目的地对汽车用户更具吸引力。这项研究有助于建立用于建模非工作目的地选择的选择集的方法。结果增强了我们对非工作目的地选择的理解,并且对运输和土地使用规划产生了影响。由Elsevier Ltd.发布

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