Faculty Advisor

Yanhua Li

Faculty Advisor

Krishna Kumar Venkatasubramanian

Identifier

etd-041018-140537

Abstract

Emergence of autonomous vehicles (AVs) offers the potential to fundamentally transform the way how urban transport systems be designed and deployed, and alter the way we view private car ownership. In this thesis 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 -- most of personal vehicles, low ridership public buses, and taxis used in today€™s private and public transport systems -- 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 systems.

Publisher

Worcester Polytechnic Institute

Degree Name

MS

Department

Computer Science

Project Type

Thesis

Date Accepted

2018-04-10

Accessibility

Restricted-WPI community only

Subjects

Cloud Commuting, urban computing, queuing theory

Available for download on Friday, April 10, 2020

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