Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/105687
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dc.contributorDepartment of Computing-
dc.creatorLi, PH-
dc.creatorYiu, ML-
dc.creatorMouratidis, K-
dc.date.accessioned2024-04-15T07:35:54Z-
dc.date.available2024-04-15T07:35:54Z-
dc.identifier.issn1384-6175-
dc.identifier.urihttp://hdl.handle.net/10397/105687-
dc.language.isoenen_US
dc.publisherSpringer New York LLCen_US
dc.rights© Springer Science+Business Media New York 2016en_US
dc.rightsThis version of the article has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature’s AM terms of use(https://www.springernature.com/gp/open-research/policies/accepted-manuscript-terms), but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: http://dx.doi.org/10.1007/s10707-016-0265-y.en_US
dc.subjectRoad networksen_US
dc.subjectRoad trafficen_US
dc.titleDiscovering historic traffic-tolerant paths in road networksen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage1-
dc.identifier.epage32-
dc.identifier.volume21-
dc.identifier.issue1-
dc.identifier.doi10.1007/s10707-016-0265-y-
dcterms.abstractHistoric traffic information is valuable in transportation analysis and planning, e.g., evaluating the reliability of routes for representative source-destination pairs. Also, it can be utilized to provide efficient and effective route-search services. In view of these applications, we propose the k traffic-tolerant paths (TTP) problem on road networks, which takes a source-destination pair and historic traffic information as input, and returns k paths that minimize the aggregate (historic) travel time. Unlike the shortest path problem, the TTP problem has a combinatorial search space that renders the optimal solution expensive to find. First, we propose an exact algorithm with effective pruning rules to reduce the search time. Second, we develop an anytime heuristic algorithm that makes ‘best-effort’ to find a low-cost solution within a given time limit. Extensive experiments on real and synthetic traffic data demonstrate the effectiveness of TTP and the efficiency of our proposed algorithms.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationGeoinformatica, Jan. 2017, v. 21, no. 1, p. 1-32-
dcterms.isPartOfGeoinformatica-
dcterms.issued2017-01-
dc.identifier.scopus2-s2.0-84990996532-
dc.identifier.eissn1573-7624-
dc.description.validate202402 bcch-
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumberCOMP-1343en_US
dc.description.fundingSourceOthersen_US
dc.description.fundingTextPolyU internal granten_US
dc.description.pubStatusPublisheden_US
dc.identifier.OPUS6685627en_US
dc.description.oaCategoryGreen (AAM)en_US
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