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Building a multimodal network and determining individual accessibility by public transportation

机译:建立多式联运网络并确定公共交通的个人可及性

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The increased availability of transit schedules from web sites or travel planners as well as more disaggregate data has led to a growing interest in creating individual public transportation accessibility measures. However, used extensively, standard GIS software does not have direct capabilities to integrate transit schedules into multimodal networks and measure space-time-based accessibility. This has caused authors to either simplify travel time elements or develop tools to overcome these challenges. In this paper we aim to describe and implement a method that enables integrating time-table data from a travel planner into a multimodal network model using simple SQL (structured query language) programming and standard GIS. The method presented here integrates all parts of travelling by public transportation from individual home addresses to all reachable transit stops within different travel time thresholds. The method is used successfully to create a multimodal travel-time network model of the Capital Region of Denmark comprising bus, train, light rail, metro, and ferry as well as integrating walking or cycling to stops. Here, the individual accessibility is defined as accessibility areas. The accessibility areas are created at morning rush hour for a study population of 29 447 individuals and a few examples of accessibility areas are presented. The results show a big difference in individual public transportation accessibility in the region. In addition, how the transit network is accessed, whether it is at the nearest stop or at all stops within 1 km walking distance or 3 km cycling distance, leads to very different accessibility areas.
机译:网站或旅行计划者提供的运输时间表的增加,以及分类数据的增多,导致人们对制定个人公共交通无障碍措施的兴趣日益浓厚。但是,广泛使用的标准GIS软件没有直接的功能,无法将运输时间表集成到多式联运网络中,也无法测量基于时空的可访问性。这导致作者要么简化旅行时间要素,要么开发工具来克服这些挑战。在本文中,我们旨在描述和实现一种方法,该方法可以使用简单的SQL(结构化查询语言)编程和标准GIS将旅行计划者的时间表数据集成到多模式网络模型中。这里介绍的方法将公共交通的各个部分集成在一起,从各个家庭住址到不同旅行时间阈值内的所有可到达的公交车站。该方法已成功用于创建丹麦首都地区的多模式旅行时间网络模型,该模型包括公交车,火车,轻轨,地铁和轮渡,以及将步行或骑自行车整合到车站。在此,将个人可访问性定义为可访问性区域。在29.447个人的研究高峰时段创建了可访问区域,并提供了一些可访问区域的示例。结果表明,该地区个人公共交通的可及性差异很大。此外,如何访问公交网络,无论是在最近的车站还是步行距离在1 km或自行车距离3 km之内的所有车站,都导致可到达区域的差异很大。

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