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dc.contributor.authorJou, YJen_US
dc.contributor.authorLo, SCen_US
dc.date.accessioned2014-12-08T15:44:30Z-
dc.date.available2014-12-08T15:44:30Z-
dc.date.issued2001en_US
dc.identifier.isbn0-309-07229-8en_US
dc.identifier.issn0361-1981en_US
dc.identifier.urihttp://hdl.handle.net/11536/30046-
dc.description.abstractMost dynamic flow models are developed under deterministic assumptions or simple linear models. Although these models can describe dynamic phenomena, they cannot adapt a variance of the real world. However, in the developing trend of intelligent transportation systems, operators have to understand and accurately predict traffic flow to predict, evaluate, and manage the performance of present and future systems. Thus, a model capable of describing variant traffic phenomena, which encompasses both nonlinearity and stochasticity, is necessary. This study formulates nonlinear stochastic dynamic traffic flow models based on conventional macroscopic models; the nonlinear terms are decomposed by polynomials to reduce the complexity of the models. Then, the 116 equation is introduced to convert the deterministic model to a stochastic one. Also considered here is the traffic flow model with a diffusion effect.en_US
dc.language.isoen_USen_US
dc.titleModeling of nonlinear stochastic dynamic traffic flowen_US
dc.typeArticle; Proceedings Paperen_US
dc.identifier.journalTRANSPORTATION NETWORK MODELING 2001: PLANNING AND ADMINIATRATIONen_US
dc.citation.issue1771en_US
dc.citation.spage83en_US
dc.citation.epage88en_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:000176595300011-
Appears in Collections:Conferences Paper