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Spatiotemporal variation in travel regularity through transit user profiling

机译：通过公交用户分析的出行规律时空变化

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New smart card datasets are providing new opportunities to explore travel behaviour in much greater depth than anything accomplished hitherto. Part of this quest involves measuring the great array of regular patterns within such data and explaining these relative to less regular patterns which have often been treated in the past as noise. Here we use a simple method called DBSCAN to identify clusters of travel events associated with particular individuals whose behaviour over space and time is captured by smart card data. Our dataset is a sequence of three months of data recording when and where individual travellers start and end rail and bus travel in Greater London. This dataset contains some 640 million transactions during the period of analysis we have chosen and it enables us to begin a search for regularities at the most basic level. We first define measures of regularity in terms of the proportions of events associated with temporal, modal (rail and bus), and service regularity clusters, revealing that the frequency distributions of these clusters follow skewed distributions with different means and variances. The analysis then continues to examine how regularity relative to irregular travel across space, demonstrating high regularities in the origins of trips in the suburbs contrasted with high regularities in the destinations in central London. This analysis sets the agenda for future research into how we capture and measure the differences between regular and irregular travel which we discuss by way of conclusion.
机译：新的智能卡数据集为探索旅行行为提供了新的机会，其深度远比迄今完成的任何事物都要深。此任务的一部分涉及测量此类数据中的大量常规模式，并相对于过去通常被视为噪声的次常规模式进行解释。在这里，我们使用一种称为DBSCAN的简单方法来识别与特定个人相关联的旅行事件的集群，这些个人在空间和时间上的行为被智能卡数据捕获。我们的数据集是三个月的数据记录序列，记录了各个旅行者在大伦敦开始和结束铁路和公共汽车旅行的时间和地点。在我们选择的分析期间，该数据集包含约6.4亿笔交易，它使我们能够从最基本的层次开始搜索规律性。我们首先根据与时间，模态（铁路和公交）和服务规则性集群相关的事件的比例来定义规则性的度量，揭示这些集群的频率分布遵循具有不同均值和方差的偏态分布。然后，分析继续检查相对于不定期穿越太空的规律性，证明郊区出行的高规律性与伦敦市中心目的地的高规律性形成对比。该分析为我们如何捕获和测量常规和非常规旅行之间的差异设定了未来研究的议程，我们将通过总结的方式进行讨论。

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