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dc.contributor.authorLin, Yi-Kueien_US
dc.contributor.authorHuang, Cheng-Fuen_US
dc.contributor.authorLin, Jsen-Shungen_US
dc.contributor.authorLi, Shin-Yingen_US
dc.date.accessioned2019-06-03T01:08:31Z-
dc.date.available2019-06-03T01:08:31Z-
dc.date.issued2019-01-01en_US
dc.identifier.urihttp://hdl.handle.net/11536/151904-
dc.description.abstractThe purpose of this study is to evaluate the service performance of a freeway system, in which the speed on each section is stochastic owing to user behavior, accidents, tunnels, road gradient, and road repairs. A stochastic-flow freeway network (SFFN) is constructed to model the freeway system with stochastic speed. System reliability is defined as the probability of a certain number of vehicles in a freeway system completing their journey smoothly within a restricted time. Two SFFN models were built to describe the relationships among traffic flow, system time and stochastic speed. After obtaining the probability distribution of speed by collecting historical data, two algorithms with respect to different models were proposed to generate all minimal speed vectors (MSVs). The system reliability can be subsequently computed in terms of MSVs. The Taiwan freeway system was considered as a case study to demonstrate the effectiveness of the proposed models and algorithms.en_US
dc.language.isoen_USen_US
dc.subjectsystem reliabilityen_US
dc.subjectstochastic-flow freeway network (SFFN)en_US
dc.subjectstochastic speeden_US
dc.subjecttraffic flowen_US
dc.subjectsystem timeen_US
dc.titleEVALUATION OF SYSTEM RELIABILITY FOR A FREEWAY SYSTEM WITH STOCHASTIC SPEEDen_US
dc.typeArticleen_US
dc.identifier.journalINTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING-THEORY APPLICATIONS AND PRACTICEen_US
dc.citation.volume26en_US
dc.citation.issue1en_US
dc.citation.spage12en_US
dc.citation.epage33en_US
dc.contributor.department工業工程與管理學系zh_TW
dc.contributor.departmentDepartment of Industrial Engineering and Managementen_US
dc.identifier.wosnumberWOS:000468305800002en_US
dc.citation.woscount0en_US
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