Skip to Main Content (Press Enter)

Logo CNR
  • ×
  • Home
  • People
  • Outputs
  • Organizations
  • Expertise & Skills

UNI-FIND
Logo CNR

|

UNI-FIND

cnr.it
  • ×
  • Home
  • People
  • Outputs
  • Organizations
  • Expertise & Skills
  1. Outputs

Estimating the Potential for Shared Autonomous Scooters

Academic Article
Publication Date:
2021
abstract:
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.
Iris type:
01.01 Articolo in rivista
Keywords:
smart mobility; micro mobility; autonomous vehicles
List of contributors:
Santi, Paolo
Authors of the University:
SANTI PAOLO
Handle:
https://iris.cnr.it/handle/20.500.14243/395896
Published in:
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS (ONLINE)
Journal
  • Overview

Overview

URL

http://www.scopus.com/inward/record.url?eid=2-s2.0-85100460048&partnerID=q2rCbXpz
  • Use of cookies

Powered by VIVO | Designed by Cineca | 26.5.0.0 | Sorgente dati: PREPROD (Ribaltamento disabilitato)