Inferring the trip purposes and uncovering spatio-temporal activity patterns from dockless shared bike dataset in Shenzhen, China
Inferring the trip purposes and uncovering spatio-temporal activity patterns from dockless shared bike dataset in Shenzhen, China
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从中国深圳无桩共享单车数据集中推断出行目的并揭示时空活动模式
DOI：
10.1016/j.jtrangeo.2021.102974
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发表时间：
2021-02
影响因子：
6.1
通讯作者：
Zhifeng Wu
中科院分区：
文献类型：
--
作者：
Shaoying Li;Caigang Zhuang;Zhangzhi Tan;Feng Gao;Zhipeng Lai;Zhifeng Wu
出行目的与出行方式密切相关，在城市规划和交通管理中起着重要作用。最近，人们越来越感兴趣的是研究无码头共享自行车使用的时空模式及其影响机制。然而，很少有人专注于通过推断个人层面的无桩共享自行车旅行的目的来揭示旅行模式。我们提出了一个框架来推断无桩共享自行车用户的目的，基于重力模型和贝叶斯规则，并在中国深圳进行。我们考虑的综合因素，包括距离，时间，环境，活动类型的比例，和服务能力的兴趣点（POI），其中后两个因素通常被忽视，在以往的交通研究。特别是，本文综合了兴趣区（AOI）和腾讯社交媒体用户密度（TUD）数据，对兴趣区的服务能力进行了表征，反映了不同兴趣区类别的面积和规模差异。通过两种改进模型与基本模型的比较，证明了引入POI的活动类型比例和服务能力可以提高模型对无码头共享单车出行目的推断的有效性。基于获得的出行目的，我们进一步探索不同活动的时空模式，并获得一些关于自行车出行需求的见解，这可以为自行车基础设施规划和无码头共享自行车管理提供科学决策。
Trip purpose is closely related to travel patterns and plays an important role in urban planning and transportation management. Recently, there has been a growing interest in investigating the spatio-temporal patterns of dockless shared-bike usage and its influencing mechanisms. Few, however, have focused on revealing the travel patterns by inferring the purpose of dockless shared-bike trips at the individual level. We present a framework for inferring the purpose of dockless shared-bike users, based on gravity model and Bayesian rules, and conduct it in Shenzhen, China. We consider the comprehensive factors including distance, time, environment, activity type proportion, and service capacity of points of interest (POIs), the last two factors of which were usually neglected in previous transport studies. Especially, we integrated areas of interest (AOIs) and Tencent User density (TUD) social media data characterize the service capacity of POIs, which reflect the area and scale differences of different POI categories. Through the comparison between two improved models and the basic model, it is demonstrated that the introduction of activity type proportion and service capacity of POIs can improve the effectiveness of model for inferring the purposes of dockless shared-bike trips. Based on the obtained trip purposes, we further explore the spatio-temporal patterns of different activities and gain some insights into bike travel demand, which can inform scientific decisions for bicycle infrastructure planning and dockless shared- bike management.
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DOI：
10.1061/(asce)up.1943-5444.0000273
发表时间：
2016-03
期刊：
--
影响因子：
--
作者：
Xize Wang;G. Lindsey;J. Schoner;Andrew Harrison
通讯作者：
Xize Wang;G. Lindsey;J. Schoner;Andrew Harrison
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影响因子：
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作者：
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DOI：
10.1080/13658816.2020.1863410
发表时间：
2021-01-06
影响因子：
5.7
作者：
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DOI：
10.1016/j.tra.2019.01.004
发表时间：
2019-03-01
影响因子：
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作者：
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影响因子：
4.3
作者：
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Habib, Khandker Nurul