RideMatcher: Peer-to-peer matching of passengers for efficient ridesharing

Nicolae Vladimir Bozdog, Marc X. Makkes, Aart Van Halteren, Henri Bal

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Abstract

The daily home-office commute of millions of people in crowded cities puts a strain on air quality, traveling time and noise pollution. This is especially problematic in western cities, where cars and taxis have low occupancy with daily commuters. To reduce these issues, authorities often encourage commuters to share their rides, also known as carpooling or ridesharing. To increase the ridesharing usage it is essential that commuters are efficiently matched. In this paper we present RideMatcher, a novel peer-to-peer system for matching car rides based on their routes and travel times. Unlike other ridesharing systems, RideMatcher is completely decentralized, which makes it possible to deploy it on distributed infrastructures, using fog and edge computing. Despite being decentralized, our system is able to efficiently match ridesharing users in near real-time. Our evaluations performed on a dataset with 34,837 real taxi trips from New York show that RideMatcher is able to reduce the number of taxi trips by up to 65%, the distance traveled by taxi cabs by up to 64%, and the cost of the trips by up to 66%.

Original languageEnglish
Title of host publicationProceedings - 18th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, CCGRID 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages263-272
Number of pages10
ISBN (Electronic)9781538658154
DOIs
Publication statusPublished - 13 Jul 2018
Event18th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, CCGRID 2018 - Washington, United States
Duration: 1 May 20184 May 2018

Conference

Conference18th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, CCGRID 2018
CountryUnited States
CityWashington
Period1/05/184/05/18

Keywords

  • Ad hoc networking
  • Distributed systems
  • Fog computing
  • Peer to peer
  • Ridesharing

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