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TicTac: From transfer-incapable carpooling to transfer-allowed carpooling

Authors: Yunfei Hou; Xu Li; Chunming Qiao;

TicTac: From transfer-incapable carpooling to transfer-allowed carpooling

Abstract

Current transfer-incapable carpooling (TIC) scheme cannot fully utilize vehicles' available space because a carpooling passenger has to go from her origin to her destination by getting a ride from only one vehicle. This is akin to insist on delivering some packets only using one-hop communications, which usually performs worse than allowing multi-hop communications. In this paper, inspired by the “Store-and-Forward” strategy used in Delay-Tolerant Networks (DTN), we propose a new carpooling paradigm called transfer-allowed carpooling (TAC), with which each passenger can be served by more than one vehicle to go from her origin to her destination, thus increasing the carpooling performance. In particular, when given a) a number of carpooling requests (each with a maximum waiting-time and a maximum number of transfers for a passenger), and b) a list of participating vehicles (each specifying a maximum detour distance for a driver), we address a new optimization problem called Transfer-Allowed Carpooling whose objective is to maximize the successful carpooling ratio (SCR). Two effective strategies have been proposed from a driver and passenger standpoint, respectively. In addition to conducting large-scale simulations, we also present a case study in a more realistic setting by utilizing real routes collected from taxis in the city of Shanghai. Our major results are: 1) the proposed TAC approach can significantly improve SCR (by 35% to 60%), compared to the traditional TIC approach; and 2) allowing one transfer (i.e., the maximum number of transfers=1) improves the carpooling efficiency most, while allowing more than one transfer does not bring any noticeable benefits.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
6
Average
Top 10%
Average
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