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Title	Sccs: Smart Cloud Commuting System With Shared Autonomous Vehicles
ID_Doc	47370
Authors	Pan M.; Li Y.; Zhang Z.-L.; Luo J.
Year	2022
Published	IEEE Transactions on Big Data, 8, 5
DOI	http://dx.doi.org/10.1109/TBDATA.2020.3041263
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 article 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 framework can serve the trip demands with 22 percent fewer vehicles and 37 percent more vehicle utilization, which shed lights on the design feasibility of future smart transportation systems. © 2015 IEEE.
Author Keywords	Cloud commuting; queuing theory; urban computing

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