Understanding Cycling Trip Purpose and Route Choice Using GPS Traces and Open Data
Understanding Cycling Trip Purpose and Route Choice Using GPS Traces and Open Data
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DOI：
10.1145/3314407
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发表时间：
2019-03
影响因子：
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通讯作者：
Suraj Nair;Kiran Javkar;Jiahui Wu;V. Frías-Martínez
中科院分区：
文献类型：
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作者：
Suraj Nair;Kiran Javkar;Jiahui Wu;V. Frías-Martínez
许多移动应用程序，如Strava或MapMyRide，允许骑自行车的人出于健康或路线共享的目的收集他们旅程的详细GPS痕迹。然而，从城市规划的角度来看，骑自行车的GPS痕迹也有很大的潜力。在本文中，我们关注两个表征城市骑车人行为的重要问题：出行目的和路线选择。骑自行车出行的目的通常是使用调查数据进行分析的。在这里，我们提出了一种方法，使用骑自行车的人的个人数据、GPS轨迹和从公开数据集中提取的各种内置和社会环境特征来自动推断骑自行车旅行的目的。我们使用来自费城7,000多条自行车路线的GPS轨迹对所提出的方法进行了评估，当考虑到四种出行目的时，报告的F1分数高达86%。另一方面，我们还提出了一种新的统计方法来识别某些表征内置和社会环境的变量在特定骑行路线选择中所起的作用。我们的结果显示，费城的骑车人倾向于选择绿色区域、安全和中心的路线。
Many mobile applications such as Strava or Mapmyride allow cyclists to collect detailed GPS traces of their trips for health or route sharing purposes. However, cycling GPS traces also have a lot of potential from an urban planning perspective. In this paper, we focus on two important issues to characterize urban cyclist behavior: trip purpose and route choice. Cycling trip purpose has been typically analyzed using survey data. Here, we present a method to automatically infer the purpose of a cycling trip using cyclists' personal data, GPS traces and a variety of built-in and social environment features extracted from open datasets characterizing the streets cycled. We evaluate the proposed method using GPS traces from over 7, 000 cycling routes in the city of Philadelphia and report F1 scores of up to 86% when four trip purposes are considered. On the other hand, we also present a novel statistical method to identify the role that certain variables characterizing the built-in and social environment play in the selection of a specific cycling route. Our results show that cyclists in Philadelphia tend to favor routes with green areas, safety and centrality.