In a pavement management system, the performance evaluation indexes and their prediction methods are important aspects for assessing the overall pavement condition. Therefore, an accurate location reference system is necessary for managing pavement evaluations and maintenance. In this regard, the length of the pavement section selected for evaluation may also have significant impact on the assessment, irrespective of the type of performance indexes. This study investigated the variability in pavement performance evaluation and maintenance decisions attributed to change in pavement section lengths. It considered rut depth, pavement condition index, and international roughness index as performance indexes. Data from 27 road segments of Ontario, Canada, with a total length of 172.5 km were selected for empirical investigation. The distributions of these indexes were compared by grouping various segment lengths ranging from 50, 500, 1,000, and 10,000 m. The variations of performance assessment attributable to changing section length were investigated on the basis of their impacts on maintenance decisions. A Monte Carlo simulation was carried out by varying section lengths to estimate probabilities of the necessity of maintenance works. Results of this empirical investigation revealed that most of the longer sections were evaluated with low rut depth and the shorter sections were evaluated with higher rut depth. Monte Carlo simulation also revealed that 50-m sections have a higher probability of maintenance requirement than 500-m sections. Although the results are related to the Ontario highway system, these methods can also be applied elsewhere with similar conditions.


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    Title :

    Road Section Length Variability on Pavement Management Decision Making for Ontario, Canada, Highway Systems


    Additional title:

    Transportation Research Record: Journal of the Transportation Research Board


    Contributors:


    Publication date :

    2016-01-01




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



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