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了解德克萨斯州奥斯汀市共享电动滑板车的出行情况。

Understanding the Shared E-scooter Travels in Austin, TX.

作者信息

Jiao Junfeng, Bai Shunhua

机构信息

Urban Information Lab, The University of Texas at Austin, Austin, TX 78712, USA.

出版信息

ISPRS Int J Geoinf. 2020 Feb;9(2). doi: 10.3390/ijgi9020135. Epub 2020 Feb 24.

DOI:10.3390/ijgi9020135
PMID:38818355
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11139225/
Abstract

This paper investigated the travel patterns of 1.7 million shared E-scooter trips from April 2018 to February 2019 in Austin, TX. There were more than 6000 active E-scooters in operation each month, generating over 150,000 trips and covered approximately 117,000 miles. During this period, the average travel distance and operation time of E-scooter trips were 0.77 miles and 7.55 min, respectively. We further identified two E-scooter usage hotspots in the city (Downtown Austin and the University of Texas campus). The spatial analysis showed that more trips originated from Downtown Austin than were completed, while the opposite was true for the UT campus. We also investigated the relationship between the number of E-scooter trips and the surrounding environments. The results show that areas with higher population density and more residents with higher education were correlated with more E-scooter trips. A shorter distance to the city center, the presence of transit stations, better street connectivity, and more compact land use were also associated with increased E scooter usage in Austin, TX. Surprisingly, the proportion of young residents within a neighbourhood was negatively correlated with E-scooter usage.

摘要

本文调查了2018年4月至2019年2月期间德克萨斯州奥斯汀市170万次共享电动滑板车出行的模式。每月有6000多辆电动滑板车投入运营,产生了超过15万次出行,行驶里程约为11.7万英里。在此期间,电动滑板车出行的平均行驶距离和运营时间分别为0.77英里和7.55分钟。我们进一步确定了该市的两个电动滑板车使用热点地区(奥斯汀市中心和德克萨斯大学校园)。空间分析表明,奥斯汀市中心始发的出行比结束的出行更多,而德克萨斯大学校园的情况则相反。我们还研究了电动滑板车出行次数与周边环境之间的关系。结果表明,人口密度较高且受过高等教育的居民较多的地区,电动滑板车出行次数也较多。距离市中心较近、有公交站点、街道连通性较好以及土地利用更紧凑,也与德克萨斯州奥斯汀市电动滑板车使用量的增加有关。令人惊讶的是,一个社区内年轻居民的比例与电动滑板车的使用呈负相关。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe41/11139225/06dd5b460687/nihms-1913004-f0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe41/11139225/4085ff190ec9/nihms-1913004-f0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe41/11139225/00d15d63469d/nihms-1913004-f0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe41/11139225/06dd5b460687/nihms-1913004-f0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe41/11139225/4085ff190ec9/nihms-1913004-f0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe41/11139225/00d15d63469d/nihms-1913004-f0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe41/11139225/06dd5b460687/nihms-1913004-f0003.jpg

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2
Promoting public bike-sharing: A lesson from the unsuccessful Pronto system.推广公共自行车共享:从失败的Pronto系统中吸取的教训。
Transp Res D Transp Environ. 2018 Aug;63:533-547. doi: 10.1016/j.trd.2018.06.021. Epub 2018 Jun 28.
3
Freedom from the Station: Spatial Equity in Access to Dockless Bike Share.
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4
Comparing alcohol involvement among injured pedalcycle and motorcycle riders across three national public-use datasets.比较三个国家级公共使用数据集中心因伤骑行自行车和骑摩托车者的酒精摄入情况。
Traffic Inj Prev. 2024;25(8):1023-1030. doi: 10.1080/15389588.2024.2364358. Epub 2024 Jun 26.
5
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6
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