Cited time in webofscience Cited time in scopus

Full metadata record

DC Field Value Language
dc.contributor.author Zhang, Desheng -
dc.contributor.author He, Tian -
dc.contributor.author Zhang, Fan -
dc.contributor.author Lu, Mingming -
dc.contributor.author Liu, Yunhuai -
dc.contributor.author Lee, Haengju -
dc.contributor.author Son, Sang H. -
dc.date.available 2017-07-05T08:35:36Z -
dc.date.created 2017-04-10 -
dc.date.issued 2016-08 -
dc.identifier.issn 1550-4859 -
dc.identifier.uri http://hdl.handle.net/20.500.11750/2222 -
dc.description.abstract Carpooling has long held the promise of reducing gas consumption by decreasing mileage to deliver coriders. Although ad hoc carpools already exist in the real world through private arrangements, little research on the topic has been done. In this article, we present the first systematic work to design, implement, and evaluate a carpool service, called coRide, in a large-scale taxicab network intended to reduce total mileage for less gas consumption. Our coRide system consists of three components, a dispatching cloud server, passenger clients, and an onboard customized device, called TaxiBox. In the coRide design, in response to the delivery requests of passengers, dispatching cloud servers calculate cost-efficient carpool routes for taxicab drivers and thus lower fares for the individual passengers. To improve coRide's efficiency in mileage reduction, we formulate an NP-hard route calculation problem under different practical constraints. We then provide (1) an optimal algorithm using Linear Programming, (2) a 2-approximation algorithm with a polynomial complexity, and (3) its corresponding online version with a linear complexity. To encourage coRide's adoption, we present a win-win fare model as the incentive mechanism for passengers and drivers to participate.We test the performance of coRide by a comprehensive evaluation with a real-world trial implementation and a data-driven simulation with 14,000 taxi data from the Chinese city Shenzhen. The results show that compared with the ground truth, our service can reduce 33% of total mileage; with our win-win fare model, we can lower passenger fares by 49% and simultaneously increase driver profit by 76%. © 2016 ACM. -
dc.publisher Association for Computing Machinery -
dc.title Carpooling Service for Large-Scale Taxicab Networks -
dc.type Article -
dc.identifier.doi 10.1145/2897517 -
dc.identifier.scopusid 2-s2.0-84987927054 -
dc.identifier.bibliographicCitation ACM Transactions on Sensor Networks, v.12, no.3 -
dc.subject.keywordAuthor Algorithms -
dc.subject.keywordAuthor Design -
dc.subject.keywordAuthor Experimentation -
dc.subject.keywordAuthor Verification -
dc.subject.keywordAuthor Ridesharing -
dc.subject.keywordAuthor taxi network -
dc.subject.keywordAuthor fare model -
dc.subject.keywordAuthor application -
dc.subject.keywordPlus Algorithm -
dc.subject.keywordPlus Algorithms -
dc.subject.keywordPlus Application -
dc.subject.keywordPlus Applications -
dc.subject.keywordPlus Automobile Drivers -
dc.subject.keywordPlus Cloud Computing -
dc.subject.keywordPlus Complex Networks -
dc.subject.keywordPlus Comprehensive Evaluation -
dc.subject.keywordPlus Data-Driven Simulation -
dc.subject.keywordPlus DESIGN -
dc.subject.keywordPlus Experimentation -
dc.subject.keywordPlus Fare Model -
dc.subject.keywordPlus Incentive Mechanism -
dc.subject.keywordPlus Linear Complexity -
dc.subject.keywordPlus Linear Programming -
dc.subject.keywordPlus Optimal Algorithm -
dc.subject.keywordPlus Polynomial Complexity -
dc.subject.keywordPlus Ride-Sharing -
dc.subject.keywordPlus Ridesharing -
dc.subject.keywordPlus Route Calculations -
dc.subject.keywordPlus Taxi Network -
dc.subject.keywordPlus Taxicabs -
dc.subject.keywordPlus Transportation -
dc.subject.keywordPlus Verification -
dc.citation.number 3 -
dc.citation.title ACM Transactions on Sensor Networks -
dc.citation.volume 12 -

qrcode

  • twitter
  • facebook
  • mendeley

Items in Repository are protected by copyright, with all rights reserved, unless otherwise indicated.

BROWSE