Show simple item record

dc.contributor.authorShang, Shuo
dc.contributor.authorchen, Lisi
dc.contributor.authorWei, Zhewei
dc.contributor.authorJensen, Christian
dc.contributor.authorWen, Ji-Rong
dc.contributor.authorKalnis, Panos
dc.date.accessioned2015-12-29T10:14:57Z
dc.date.available2015-12-29T10:14:57Z
dc.date.issued2015-12-17
dc.identifier.citationCollective Travel Planning in Spatial Networks 2015:1 IEEE Transactions on Knowledge and Data Engineering
dc.identifier.issn1041-4347
dc.identifier.doi10.1109/TKDE.2015.2509998
dc.identifier.urihttp://hdl.handle.net/10754/592626
dc.description.abstractTravel planning and recommendation are important aspects of transportation.We propose and investigate a novel Collective Travel Planning (CTP) query that finds the lowest-cost route connecting multiple sources and a destination, via at most k meeting points. When multiple travelers target the same destination (e.g., a stadium or a theater), they may want to assemble at meeting points and then go together to the destination by public transport to reduce their global travel cost (e.g., energy, money, or greenhouse-gas emissions). This type of functionality holds the potential to bring significant benefits to society and the environment, such as reducing energy consumption and greenhouse-gas emissions, enabling smarter and greener transportation, and reducing traffic congestions. The CTP query is Max SNP-hard. To compute the query efficiently, we develop two algorithms, including an exact algorithm and an approximation algorithm. The exact algorithm is capable finding the optimal result for small values of k (e.g., k = 2) in interactive time, while the approximation algorithm, which has a 5-approximation ratio, is suitable for other situations. The performance of the CTP query is studied experimentally with real and synthetic spatial data.
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.relation.urlhttp://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=7360162
dc.rights(c) 2015 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.
dc.subjectCollective Travel Planning
dc.subjectLocation Based Services
dc.subjectSpatial Databases
dc.subjectSpatial Networks
dc.titleCollective Travel Planning in Spatial Networks
dc.typeArticle
dc.contributor.departmentComputer Science Program
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.identifier.journalIEEE Transactions on Knowledge and Data Engineering
dc.eprint.versionPost-print
dc.contributor.institutionDepartment of Computer Science, China University of Petroleum, Beijing, P.R.China
dc.contributor.institutionSchool of Computer Engineering, Nanyang Technological University, Singapore
dc.contributor.institutionSchool of Information, Renmin University of China, P.R.China
dc.contributor.institutionDepartment of Computer Science, Aalborg University, DK-9220 Aalborg East, Denmark
dc.contributor.affiliationKing Abdullah University of Science and Technology (KAUST)
kaust.personKalnis, Panos
refterms.dateFOA2018-06-13T18:23:35Z
dc.date.published-online2015-12-17
dc.date.published-print2016-05-01


Files in this item

Thumbnail
Name:
07360162.pdf
Size:
923.6Kb
Format:
PDF
Description:
Main article

This item appears in the following Collection(s)

Show simple item record