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Estimating the Potential for Shared Autonomous Scooters
Name
1909.03679.pdf
Description
Accepted version
Size
2.09 MB
Format
Adobe PDF
Checksum (MD5)
faf9b252847dd8d7a74c1cf4a37dad8c
Author(s)
Kondor, Daniel
Zhang, Xiaohu
Meghjani, Malika
Santi, Paolo
Zhao, Jinhua
Ratti, Carlo
Date Issued
2021
Journal
IEEE Transactions on Intelligent Transportation Systems
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Kondor, Daniel, Zhang, Xiaohu, Meghjani, Malika, Santi, Paolo, Zhao, Jinhua et al. 2021. "Estimating the Potential for Shared Autonomous Scooters." IEEE Transactions on Intelligent Transportation Systems.
Version
Author's final manuscript
Abstract
IEEE Recent technological developments have shown significant potential for transforming urban mobility. Considering first- and last-mile travel and short trips, the rapid adoption of dockless bike-share systems showed the possibility of disruptive change, while simultaneously presenting new challenges, such as fleet management or the use of public spaces. In this paper, we evaluate the operational characteristics of a new class of shared vehicles that are being actively developed in the industry: scooters with self-repositioning capabilities. We do this by adapting the methodology of shareability networks to a large-scale dataset of dockless bike-share usage, giving us estimates of ideal fleet size under varying assumptions of fleet operations. We show that the availability of self-repositioning capabilities can help achieve up to 10 times higher utilization of vehicles than possible in current bike-share systems. We show that actual benefits will highly depend on the availability of dedicated infrastructure, a key issue for scooter and bicycle use. Based on our results, we envision that technological advances can present an opportunity to rethink urban infrastructures and how transportation can be effectively organized in cities.
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
10.1109/TITS.2020.3047141
