Mining bicycle sharing data for generating insights into sustainable transport systems
Mining bicycle sharing data for generating insights into sustainable transport systems
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DOI：
10.1016/j.jtrangeo.2013.06.007
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发表时间：
2014-01-01
影响因子：
6.1
通讯作者：
Batty, Michael
中科院分区：
文献类型：
--
作者：
O'Brien, Oliver;Cheshire, James;Batty, Michael
自行车共享系统(共享单车)在世界各地的城镇越来越受欢迎。它们被视为在密集的城市环境中导航的一种廉价、高效和健康的手段。这篇论文通过分析来自欧洲、中东、亚洲、澳大拉西亚和美洲的38个共享单车系统的数据，首次对共享单车的特征进行了全球视角的分析。为了实现这一目标，多年来创建了一个庞大的数据库，描述了特定系统内每个停靠站的地理位置和自行车占有率，以绘制所选系统(和其他系统)的使用情况图表，并提供一致的基础来进行比较和分类。对入住率随时间变化的分析，以及整个系统范围的比较，可以推断用户群体可能的人口统计和意图。建议根据地理足迹和入住率的日、周和空间变化对共享单车进行分类。从数据集中识别的这种模式和特征的知识有一系列的应用，包括告知运营商和政策制定者如何在整个系统范围内保持适当的自行车平衡(对于许多自行车共享来说，这是一个不小的问题)，新停靠站和自行车道的位置，以及更好地针对促销材料以鼓励新用户。在交通研究的背景下，这里使用的系统是相对较小的封闭环境的一部分，可以更容易地建模和验证。这项工作通过对不同系统进行分类，为分析更大规模的交通系统奠定了基础，并试图证明，共享单车作为一种有效的交通方式和丰富的数据来源都有很大的价值。(C)2013爱思唯尔有限公司。保留所有权利。
Bicycle sharing systems (bike-shares) are becoming increasingly popular in towns and cities around the world. They are viewed as a cheap, efficient, and healthy means of navigating dense urban environments. This paper is the first to take a global view of bike-sharing characteristics by analysing data from 38 systems located in Europe, the Middle East, Asia, Australasia and the Americas. To achieve this, an extensive database depicting the geographical location and bicycle occupancy of each docking station within a particular system has been created over a number of years to chart the usage in the chosen systems (and others) and provide a consistent basis on which to compare and classify them. Analysis of the variation of occupancy rates over time, and comparison across the system's extent, infers the likely demographics and intentions of user groups. A classification of bike-shares, based on the geographical footprint and diurnal, day-of-week and spatial variations in occupancy rates, is proposed. The knowledge of such patterns and characteristics identifiable from the dataset has a range of applications, including informing operators and policymakers about the maintenance of a suitable balance of bicycles throughout the system area (a nontrivial problem for many bike-shares), the location of new docking stations and cycle lanes, and better targeting of promotional materials to encourage new users. Within the context of transport research, the systems utilised here are part of relatively small, closed environments that can be more easily modelled and validated. Such work lays foundations for the analysis of larger scale transport systems by creating a classification of the different systems and seeks to demonstrate that bike-shares have a lot to offer both as an effective method of transport and a rich source of data. (C) 2013 Elsevier Ltd. All rights reserved.