In this paper, a fundamental diagram is calibrated for observed traffic data on a freeway segment using triangular regression analysis and the fixed capacity of the freeway is derived. Stochastic capacity analysis is then conducted to investigate the nature of the breakdown phenomenon and its effect on freeway capacity. The Weibull distribution function as a generalized extreme value distribution model is fit to the data. For both deterministic and stochastic capacity analysis, the influence of the weather is evaluated for four types of weather conditions that include clear, rainy, snowy, and low visibility. The statistical analysis results show that weather conditions have a significant effect on both the fixed and stochastic value of freeway capacity. One of the other important findings of this study is that jam density is shown to be significantly affected by weather conditions and needs to be incorporated when developing advanced freeway control and management strategies such as queue detection and management schemes.


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    Titel :

    Deterministic and Stochastic Freeway Capacity Analysis Based on Weather Conditions


    Beteiligte:
    Heshami, Seiran (Autor:in) / Kattan, Lina (Autor:in) / Gong, Zhengyi (Autor:in) / Aalami, Soheila (Autor:in)


    Erscheinungsdatum :

    08.03.2019




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Unbekannt



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