Transportation agencies devote significant resources toward the collection of highly detailed and accurate pavement roughness data by using profiler vans to support pavement maintenance decisions. However, these agencies often cannot afford to measure roughness annually for the whole pavement network. This study introduced an improved acceleration-based metric, an index normalized by vehicle operating speed, to be used on a regular basis to screen pavement segments that are likely to be deficient; then a profile van can be sent to accurately measure the roughness condition. A profile van collected pavement profile data on 50 mi (80 km) of roadway; these data were then used to calculate the international roughness index (IRI). Meanwhile, two tablet computers were placed on the vehicle floor to collect data, including three-way accelerations, GPS coordinates, and vehicle speeds. A normalized acceleration-based index was created by incorporating a speed factor. Furthermore, logistic regression models were created to evaluate the effectiveness of the proposed index in identifying deficient pavement sections [IRI ≥ 140 in./mi (2.21 m/km)]. The proposed acceleration-based metric was able to identify between 80% and 93% of all deficient pavement sections. This research points to the feasibility of using a cost-effective acceleration-based application for network screening, a process that will reduce the total mileage of pavement sections needing to be measured and meanwhile still identify locations for which maintenance work is necessary.


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    Titel :

    Identifying Deficient Pavement Sections by Means of an Improved Acceleration-Based Metric


    Weitere Titelangaben:

    Transportation Research Record


    Beteiligte:


    Erscheinungsdatum :

    2015-01-01




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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