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dc.contributor.authorCho, Hsun-Jungen_US
dc.contributor.authorLi, Rih-Jinen_US
dc.date.accessioned2014-12-08T15:11:12Z-
dc.date.available2014-12-08T15:11:12Z-
dc.date.issued2007en_US
dc.identifier.isbn978-0-7354-0476-2en_US
dc.identifier.issn0094-243Xen_US
dc.identifier.urihttp://hdl.handle.net/11536/8579-
dc.description.abstractIntelligent transportation system (ITS) uses electronic technologies such as information and communication technologies to improve the efficiency of transportation management. In the theoretical framework of gas-kinetic traffic flow model, the probability of capable passing is essential for ITS. The probability of capable passing is assumed be a linear function of the traffic concentration, indicating that the probability of capable passing decreases proportionally with an increasing concentration. This work improves the model by introducing the speed desired by the driver into the original two-lane cellular automata (CA) model. This study also examines the accuracy of the linearity assumption. A capable passing principle is established to simulate the capable passing probability for different concentrations and can be embedded in a system on chip of ITS.en_US
dc.language.isoen_USen_US
dc.subjectgas-kinetic modelen_US
dc.subjectcapable passingen_US
dc.subjectcellular automataen_US
dc.subjectintelligent transportation systemen_US
dc.titleA passing probability model for intelligent transportation systemen_US
dc.typeProceedings Paperen_US
dc.identifier.journalCOMPUTATION IN MODERN SCIENCE AND ENGINEERING VOL 2, PTS A AND Ben_US
dc.citation.volume2en_US
dc.citation.spage1005en_US
dc.citation.epage1008en_US
dc.contributor.department運輸與物流管理系 註:原交通所+運管所zh_TW
dc.contributor.departmentDepartment of Transportation and Logistics Managementen_US
dc.identifier.wosnumberWOS:000252602900249-
Appears in Collections:Conferences Paper