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An efficient ride-sharing framework for maximizing shared Routes
Na Ta1; Guoliang Li2; Tianyu Zhao2; Jianhua Feng2; Hanchao Ma3; Zhiguo Gong4
2018-10-25
Conference NameInternational Conference on Data Engineering
Source PublicationProceedings - IEEE 34th International Conference on Data Engineering, ICDE 2018
Pages1795-1796
Conference Date16-19 April 2018
Conference PlaceParis, France
Abstract

Ride-sharing (RS) has great values in saving energy and alleviating traffic pressure. In this paper, we propose a new ride-sharing model, where each driver requires that the shared route percentage (SRP, the ratio of the shared route's distance to the driver's total traveled distance) exceeds her expected rate (e.g., 0.8) when sharing with a rider. We consider two variants of this problem. The first considers multiple drivers and multiple riders, and aims to compute a set of driver-rider pairs to maximize the overall SRP. We model this problem as the maximum weighted bigraph matching problem. We propose an effective exact algorithm, and an efficient approximate solution with error-bound guarantee. The second considers multiple drivers and a single rider and aims to find the top-k drivers for the rider with the largest SRP. We devise pruning techniques and propose a best-first algorithm to progressively selects drivers with high probability to be in the top-k results.

KeywordBigraph Matching Join Based Sharing Ride Sharing Search Based Sharing Shared Route Percentage
DOI10.1109/ICDE.2018.00255
URLView the original
Indexed ByCPCI-S
Language英語English
WOS Research AreaComputer Science
WOS SubjectComputer Science, Information Systems ; Computer Science, Theory & Methods
WOS IDWOS:000492836500247
Scopus ID2-s2.0-85057115638
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Document TypeConference paper
CollectionDEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
Affiliation1.School of Journalism and Communication, Renmin University of China, Beijing, China
2.Department of Computer Science, Tsinghua University, Beijing, China
3.Department of Electronic Engineering and Computer Science, Washington State University, Pullman, USA
4.Department of Computer Science, Macau University, Macau, China
Recommended Citation
GB/T 7714
Na Ta,Guoliang Li,Tianyu Zhao,et al. An efficient ride-sharing framework for maximizing shared Routes[C], 2018, 1795-1796.
APA Na Ta., Guoliang Li., Tianyu Zhao., Jianhua Feng., Hanchao Ma., & Zhiguo Gong (2018). An efficient ride-sharing framework for maximizing shared Routes. Proceedings - IEEE 34th International Conference on Data Engineering, ICDE 2018, 1795-1796.
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