Highlights A combined ANN-Fuzzy approach estimated AADT from one-week seasonal traffic counts. The accuracy of AADT estimates was satisfactory, according to FHWA requirements. AADT estimates were influenced by the period during which short counts were taken. The method is useful for planning of monitoring and minimizing traffic count costs.

    Abstract This paper presents an approach to estimation of the Annual Average Daily Traffic (AADT) from a one-week seasonal traffic count (STC) of a road section. The proposed method uses fuzzy set theory to represent the fuzzy boundaries of road groups and neural networks to assign a road segment to one or more predefined road groups. The approach was tested with data obtained in the Province of Venice, Italy, for the period of the year in which STCs are taken. The method produced accurate results, which may be of interest for proper planning of monitoring and minimizing traffic count costs.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Estimation of Annual Average Daily Traffic from one-week traffic counts. A combined ANN-Fuzzy approach


    Beteiligte:


    Erscheinungsdatum :

    2014-06-20


    Format / Umfang :

    14 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch






    Neural Networks as Alternative to Traditional Factor Approach of Annual Average Daily Traffic Estimation from Traffic Counts

    Sharma, Satish C. / Lingras, Pawan / Xu, Fei et al. | Transportation Research Record | 1999



    Improved Annual Average Daily Traffic Estimation Processes

    Jessberger, Steven / Krile, Robert / Schroeder, Jeremy et al. | Transportation Research Record | 2016