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按通行证类型发现共享单车系统的时空使用模式：以首尔为例的研究

Discovering spatiotemporal usage patterns of a bike-sharing system by type of pass: a case study from Seoul.

作者信息

Kim Kyoungok

机构信息

Information Technology Management Programme, International Fusion School, Seoul National University of Science and Technology (SeoulTech), 232 Gongreungno, Nowon-gu, Seoul, Republic of Korea.

出版信息

Transportation (Amst). 2023 Feb 21:1-35. doi: 10.1007/s11116-023-10371-7.

DOI:10.1007/s11116-023-10371-7
PMID:36846545
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9942648/
Abstract

UNLABELLED

Determining bike-sharing usage patterns and their explanatory factors on demand is essential for the effective and efficient operation of bike-sharing systems (BSSs). Most BSSs provide different passes that vary with the period of use. However, studies investigating the differences in usage patterns are rare compared to studies conducted at the system level, even though explanatory factors depending on the type of pass may cause different characteristics in terms of usage patterns. This study explores the differences in the usage patterns of BSSs and the impact of explanatory factors on the demand depending on the type of pass. Various machine learning techniques, including clustering, regression, and classification, are used, in addition to basic statistical analysis. As observed, long-term season passes of over six months are mainly used for transportation (especially commuting), whereas one-day or short-term season passes seem to be used more for leisure than for other purposes. Furthermore, differences in the purpose of bike rentals seem to cause differences in usage patterns and variations in demand over time and space. This study improves ther understanding of the usage patterns that appear differently for each pass type, and provides insights into the efficient operation of BSSs in urban areas.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s11116-023-10371-7.

摘要

未标注

确定共享单车的使用模式及其需求的解释因素对于共享单车系统（BSS）的有效和高效运营至关重要。大多数共享单车系统提供随使用期限而异的不同通行证。然而，与在系统层面进行的研究相比，调查使用模式差异的研究很少，尽管取决于通行证类型的解释因素可能会在使用模式方面导致不同的特征。本研究探讨了共享单车系统使用模式的差异以及取决于通行证类型的解释因素对需求的影响。除了基本的统计分析外，还使用了包括聚类、回归和分类在内的各种机器学习技术。如观察到的，超过六个月的长期季票主要用于交通（特别是通勤），而一日票或短期季票似乎更多地用于休闲而非其他目的。此外，自行车租赁目的的差异似乎会导致使用模式的差异以及需求在时间和空间上的变化。本研究增进了对每种通行证类型呈现出的不同使用模式的理解，并为城市地区共享单车系统的高效运营提供了见解。

补充信息

在线版本包含可在10.1007/s11116-023-10371-7获取的补充材料。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bcdf/9942648/8b37f6a2dc75/11116_2023_10371_Fig10_HTML.jpg
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Examining spatiotemporal changing patterns of bike-sharing usage during COVID-19 pandemic.审视新冠疫情期间共享单车使用的时空变化模式。
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