SCCS: Smart Cloud Commuting System with Shared Autonomous Vehicles

Menghai Pan, Yanhua Li, Zhi Li Zhang, Jun Luo

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

In this paper we advocate a forward-looking, ambitious and disruptive smart cloud commuting system (SCCS) for future smart cities based on shared AVs. Employing giant pools of AVs of varying sizes, SCCS seeks to supplant and integrate various modes of transport in a unified, on-demand fashion, and provides passengers with a fast, convenient, and low cost transport service for their daily commuting needs. To explore feasibility and efficiency gains of the proposed SCCS, we model SCCS as a queueing system with passengers' trip demands (as jobs) being served by the AVs (as servers). Using a 1-year real trip dataset from Shenzhen China, we quantify (i) how design choices, such as the numbers of depots and AVs, affect the passenger waiting time and vehicle utilization; and (ii) how much efficiency gains (i.e., reducing the number of service vehicles, and improving the vehicle utilization) can be obtained by SCCS comparing to the current taxi system. Our results demonstrate that the proposed SCCS system can serve the trip demands with 22% fewer vehicles and 37% more vehicle utilization, which shed lights on the design feasibility of future smart transportation system.

Original languageEnglish (US)
JournalIEEE Transactions on Big Data
DOIs
StatePublished - Oct 1 2022

Bibliographical note

Publisher Copyright:
IEEE

Keywords

  • Autonomous vehicles
  • Cloud computing
  • Multiplexing
  • Public transportation
  • Roads
  • Servers
  • Smart cities

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