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

ABSTRACT

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.

Acknowledgments

This research was supported by the Cooperative Mobility for Competitive Megaregions (CM2) center Year 3 grant at The University of Texas at Austin. The authors would also like to thank Eliezer Pearl for technical support during the data collection process.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the Cooperative Mobility and Competitive Megaregions University Transportation Center.

Notes on contributors

Junfeng Jiao

Shunhua Bai is a PhD student in the University of Texas at Austin School of Architecture and a graduate research assistant in the Urban Information Lab. His research focuses on using spatiotemporal big data to understand human behavior and urban environment interactions.

Junfeng Jiao is an associate professor in the University of Texas at Austin School of Architecture and director of the Urban Information Lab. His research focuses on urban informatics, shared mobility, and smart cities.