Collective Travel Planning in Spatial Networks

Handle URI:
http://hdl.handle.net/10754/624983
Title:
Collective Travel Planning in Spatial Networks
Authors:
Shang, Shuo; Chen, Lisi; Wei, Zhewei; Jensen, Christian S.; Wen, Ji-Rong; Kalnis, Panos ( 0000-0002-5060-1360 )
Abstract:
We propose and investigate a novel query, the Collective Travel Planning (CTP) query, that finds the lowest-cost route connecting multiple query sources and a destination via at most k meeting points. This type of query is useful in organizing large events, and it can bring significant benefits to society and the environment: it can help optimize the allocation of transportation resources, reduce resource consumption, and enable smarter and greener transportation; and it can help reduce greenhouse-gas emissions and traffic congestion.
KAUST Department:
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Citation:
Shang S, Chen L, Wei Z, Jensen CS, Wen J-R, et al. (2017) Collective Travel Planning in Spatial Networks. 2017 IEEE 33rd International Conference on Data Engineering (ICDE). Available: http://dx.doi.org/10.1109/ICDE.2017.36.
Publisher:
IEEE
Journal:
2017 IEEE 33rd International Conference on Data Engineering (ICDE)
Issue Date:
18-May-2017
DOI:
10.1109/ICDE.2017.36
Type:
Conference Paper
Sponsors:
This work is partly supported by the National Natural Science Foundation of China (NSFC.61402532), and Beijing Nova Program.
Additional Links:
http://ieeexplore.ieee.org/document/7929932/
Appears in Collections:
Conference Papers; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

Full metadata record

DC FieldValue Language
dc.contributor.authorShang, Shuoen
dc.contributor.authorChen, Lisien
dc.contributor.authorWei, Zheweien
dc.contributor.authorJensen, Christian S.en
dc.contributor.authorWen, Ji-Rongen
dc.contributor.authorKalnis, Panosen
dc.date.accessioned2017-06-13T09:17:13Z-
dc.date.available2017-06-13T09:17:13Z-
dc.date.issued2017-05-18en
dc.identifier.citationShang S, Chen L, Wei Z, Jensen CS, Wen J-R, et al. (2017) Collective Travel Planning in Spatial Networks. 2017 IEEE 33rd International Conference on Data Engineering (ICDE). Available: http://dx.doi.org/10.1109/ICDE.2017.36.en
dc.identifier.doi10.1109/ICDE.2017.36en
dc.identifier.urihttp://hdl.handle.net/10754/624983-
dc.description.abstractWe propose and investigate a novel query, the Collective Travel Planning (CTP) query, that finds the lowest-cost route connecting multiple query sources and a destination via at most k meeting points. This type of query is useful in organizing large events, and it can bring significant benefits to society and the environment: it can help optimize the allocation of transportation resources, reduce resource consumption, and enable smarter and greener transportation; and it can help reduce greenhouse-gas emissions and traffic congestion.en
dc.description.sponsorshipThis work is partly supported by the National Natural Science Foundation of China (NSFC.61402532), and Beijing Nova Program.en
dc.publisherIEEEen
dc.relation.urlhttp://ieeexplore.ieee.org/document/7929932/en
dc.rights(c) 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.en
dc.subjectquery processingen
dc.subjecttransportationen
dc.subjectApproximation algorithmsen
dc.subjectComputer scienceen
dc.subjectMeasurementen
dc.subjectPlanningen
dc.subjectSpatial databasesen
dc.subjectTime complexityen
dc.subjectTransportationen
dc.titleCollective Travel Planning in Spatial Networksen
dc.typeConference Paperen
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
dc.identifier.journal2017 IEEE 33rd International Conference on Data Engineering (ICDE)en
dc.eprint.versionPost-printen
dc.contributor.institutionDepartment of Computer Science, Hong Kong Baptist University, Hong Kongen
dc.contributor.institutionSchool of Information, Renmin University, Chinaen
dc.contributor.institutionDepartment of Computer Science, Aalborg University, Denmarken
kaust.authorShang, Shuoen
kaust.authorKalnis, Panosen
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