From shared micro-mobility to shared responsibility: Using crowdsourcing to understand dockless vehicle violations in Austin, Texas

被引:15
|
作者
Bai, Shunhua [1 ,2 ]
Jiao, Junfeng [1 ,2 ]
机构
[1] Univ Texas Austin, Sch Architecture, Austin, TX 78712 USA
[2] Univ Texas Austin, Urban Informat Lab, Austin, TX 78712 USA
关键词
BIG DATA; PARTICIPATION; INFORMATION; GEOGRAPHY; ADVOCACY; PATTERNS; GIS;
D O I
10.1080/07352166.2020.1798244
中图分类号
TU98 [区域规划、城乡规划];
学科分类号
0814 ; 082803 ; 0833 ;
摘要
In recent years, many progressive U.S. cities have witnessed the rapid popularization of dockless small vehicles as a car-free travel alternative to meet the short distance travel demand. The research gap exists in revealing the social outcome of the massive influx of shared small vehicles on public space. To that end, this study analyzed 4,100 parking violation reports in Austin, Texas, crowdsourced from the Austin 311 non-emergency service request system. The results showed that sidewalk and other public space intrusions were the two most frequently reported violations. Additionally, it found that improperly parked vehicles in parks required the longest time to be cleaned. Among the three reporting methods included in this study, 91% were submitted through smartphone applications, compared to 5% by phone calls and 2% through the web interface. The response time of smartphone reports was significantly greater than that of phone call reports (17.4 hours vs. 2.5 hours). Finally, the GIS hotspot analysis showed that university campus and downtown were both violation clusters, yet campus violations were solved more quickly. This study proposed a shared responsibility framework of key players in shared micro-mobility management and suggested using crowdsourcing 311 system data to facilitate communications between stakeholders.
引用
收藏
页码:1341 / 1353
页数:13
相关论文
共 8 条
  • [1] The travel pattern difference in dockless micro-mobility: Shared e-bikes versus shared bikes
    Li, Qiumeng
    Zhang, Enjia
    Luca, Davide
    Fuerst, Franz
    TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT, 2024, 130
  • [2] A rule-enhanced clustering approach to planning virtual stations for dockless shared micro-mobility systems
    Chen, Jingxu
    Chen, Junyi
    Hua, Mingzhuang
    Yu, Xinlian
    Liu, Xize
    RESEARCH IN TRANSPORTATION BUSINESS AND MANAGEMENT, 2025, 59
  • [3] Shared Micro-mobility: Technologies, Challenges and Prospects of Using Collected Data
    Swessi, Rania
    EL Khalfi, Zeineb
    DISTRIBUTED COMPUTING FOR EMERGING SMART NETWORKS, DICES-N 2023, 2024, 2041 : 41 - 55
  • [4] A comparative analysis of the potential of carbon emission reductions from shared micro-mobility
    Zhang, Yongping
    Fu, Wenyan
    Chao, Hao
    Mi, Zhifu
    Kong, Hui
    SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS, 2024, 72
  • [5] Who uses shared micro-mobility services? Empirical evidence from Zurich, Switzerland
    Reck, Daniel J.
    Axhausen, Kay W.
    TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT, 2021, 94
  • [6] Analyzing the micro-mobility patterns of shared dockless bike and e-bike systems through multi-scale complex networks
    Shi, Xiaoying
    He, Jiaming
    Zhang, Yongping
    TRANSPORTATION, 2024,
  • [7] Analysis of residents' stated preferences of shared micro-mobility devices using regression-text mining approach
    Kutela, Boniphace
    Novat, Norris
    Adanu, Emmanuel Kofi
    Kidando, Emmanuel
    Langa, Neema
    TRANSPORTATION PLANNING AND TECHNOLOGY, 2022, 45 (02) : 159 - 178
  • [8] Evaluation of shared micro-mobility systems for sustainable cities by using a consensus-based Fermatean fuzzy multiple objective optimization and full multiplicative form
    Saha, Abhijit
    Gorcun, Omer Faruk
    Pamucar, Dragan
    Arya, Leena
    Simic, Vladimir
    ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2024, 134