Safe vehicle speed estimation is essential for road traffic management and traffic safety. Improper truck speed on downgrades may lead to brake fade and/or failure, resulting in severe truck accidents such as runaway or out-of-control. This paper presents a model for predicting the safe speed of trucks from the perspective of preventing brake failure. The proposed model can be used to control the speed limit or as a reference for the revision of highway geometric design standards. In addition, by considering the downgrade design speeds recommended by AASHTO, the study offers an approach to deciding the downgrades that need escape ramps, those that need different speed limits, and those that may need exclusions for trucks over a certain weight. First, we simplify the downgrade driving status of a heavy truck into three types: speed control, emergency braking, and speed recovery according to the speed change status. The prediction model of the brake drum temperature with speed variables has been established in our previous study based on Newton’s energy conservation law. Finally, the boundary conditions for brake fade and failure temperature are determined. Results of parameter analysis show that the gross truck weight is the most significant variable. Other significant variables are grade, grade length, and emergency braking time. Compared with previous research results, the advantage of this method is that the permitted speed can be derived using the brake temperature prediction model supported by theory, without the need for extensive field tests.


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    Titel :

    Safe Speed Prediction Model for Heavy Trucks on Consecutive Mountain Downgrade Routes Based on Energy Conservation Law


    Weitere Titelangaben:

    Transportation Research Record


    Beteiligte:
    Yan, Menghua (Autor:in) / Xu, Jinliang (Autor:in) / Han, Shuo (Autor:in) / Ma, Fangchen (Autor:in)


    Erscheinungsdatum :

    2021-07-07




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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