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- Publisher Website: 10.1109/TITS.2017.2740438
- Scopus: eid_2-s2.0-85047094764
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Article: Data-Driven Resilient Fleet Management for Cloud Asset-enabled Urban Flood Control
Title | Data-Driven Resilient Fleet Management for Cloud Asset-enabled Urban Flood Control |
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Authors | |
Keywords | Resilience engineering Emergency fleet management Cloud asset Data-driven applications Urban flood control |
Issue Date | 2018 |
Publisher | IEEE. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6979 |
Citation | IEEE Transactions on Intelligent Transportation Systems, 2018, v. 19 n. 6, p. 1827-1838 How to Cite? |
Abstract | Emergency fleet management has become one of the determinant success factors for post-disaster responses in urban flood control. However, it is challenging as multiple types of emergency vehicles are involved, and its performance is frequently threatened by the fluctuation of rescue demands and fleet capacity. Aiming at coping with the imbalances between rescue demands and vehicle supplies, and maintaining required service level of fleet management after flood occurs, this paper proposes a data-driven resilient fleet management solution under the context of cloud asset-enabled urban flood control. First, the problem of resilient fleet management is quantitatively defined, and then a data-driven dynamic management mechanism is proposed, which is highly effective on realizing resilient fleet management. Furthermore, considering the cooperation among different types of emergency vehicles, a greedy-based algorithm is proposed for resilient vehicle dispatching based on real-time scenarios. Finally, a simulation case is also conducted to verify the effectiveness and performance of the proposed solution. |
Persistent Identifier | http://hdl.handle.net/10722/245037 |
ISSN | 2023 Impact Factor: 7.9 2023 SCImago Journal Rankings: 2.580 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Xu, G | - |
dc.contributor.author | Wang, J | - |
dc.contributor.author | Huang, GQ | - |
dc.contributor.author | Chen, C | - |
dc.date.accessioned | 2017-09-18T02:03:31Z | - |
dc.date.available | 2017-09-18T02:03:31Z | - |
dc.date.issued | 2018 | - |
dc.identifier.citation | IEEE Transactions on Intelligent Transportation Systems, 2018, v. 19 n. 6, p. 1827-1838 | - |
dc.identifier.issn | 1524-9050 | - |
dc.identifier.uri | http://hdl.handle.net/10722/245037 | - |
dc.description.abstract | Emergency fleet management has become one of the determinant success factors for post-disaster responses in urban flood control. However, it is challenging as multiple types of emergency vehicles are involved, and its performance is frequently threatened by the fluctuation of rescue demands and fleet capacity. Aiming at coping with the imbalances between rescue demands and vehicle supplies, and maintaining required service level of fleet management after flood occurs, this paper proposes a data-driven resilient fleet management solution under the context of cloud asset-enabled urban flood control. First, the problem of resilient fleet management is quantitatively defined, and then a data-driven dynamic management mechanism is proposed, which is highly effective on realizing resilient fleet management. Furthermore, considering the cooperation among different types of emergency vehicles, a greedy-based algorithm is proposed for resilient vehicle dispatching based on real-time scenarios. Finally, a simulation case is also conducted to verify the effectiveness and performance of the proposed solution. | - |
dc.language | eng | - |
dc.publisher | IEEE. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6979 | - |
dc.relation.ispartof | IEEE Transactions on Intelligent Transportation Systems | - |
dc.rights | IEEE Transactions on Intelligent Transportation Systems. Copyright © IEEE. | - |
dc.rights | ©20xx IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, 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 component of this work in other works. | - |
dc.subject | Resilience engineering | - |
dc.subject | Emergency fleet management | - |
dc.subject | Cloud asset | - |
dc.subject | Data-driven applications | - |
dc.subject | Urban flood control | - |
dc.title | Data-Driven Resilient Fleet Management for Cloud Asset-enabled Urban Flood Control | - |
dc.type | Article | - |
dc.identifier.email | Wang, J: jwwang@hku.hk | - |
dc.identifier.email | Huang, GQ: gqhuang@hku.hk | - |
dc.identifier.authority | Wang, J=rp01888 | - |
dc.identifier.authority | Huang, GQ=rp00118 | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1109/TITS.2017.2740438 | - |
dc.identifier.scopus | eid_2-s2.0-85047094764 | - |
dc.identifier.hkuros | 279126 | - |
dc.identifier.volume | 19 | - |
dc.identifier.issue | 6 | - |
dc.identifier.spage | 1827 | - |
dc.identifier.epage | 1838 | - |
dc.identifier.isi | WOS:000433910400012 | - |
dc.publisher.place | United States | - |
dc.identifier.issnl | 1524-9050 | - |