A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Effect of traffic monitoring period on mechanistic-empirical pavement design
Highlights AADTT, VCD, ALS, and number of axles per truck are the main traffic inputs affected by the traffic monitoring duration. Traffic monitoring data collected over all days of the week are more representative than partial week traffic data for pavement design. Roadways with lower truck traffic generally show higher variability in traffic data; hence, a longer traffic monitoring period is required for such locations in order to obtain reliable traffic inputs for use in pavement design.
Abstract The mechanistic-empirical pavement design approach requires defining detailed axle load spectra for each truck class and axle group that can be obtained from continuous site-specific weigh-in-motion (WIM) data. However, it is challenging to collect reliable WIM data over an extended period of time as these systems may experience technical or equipment problems leading to incomplete WIM data. As a result, there may be a need to rely on WIM data collected over shorter traffic monitoring periods to generate the required traffic inputs for use in mechanistic-empirical pavement design. This study examined the effect of the traffic monitoring period on the resulting traffic inputs and the associated pavement performance as predicted using the mechanistic-empirical pavement design approach. The analysis results revealed higher variability in traffic inputs and predicted performance when using shorter traffic monitoring periods. This was more obvious for WIM sites with lower truck traffic. This study also presented a framework for selecting the minimum required traffic monitoring period to achieve a target accuracy level in predicting the pavement service life. The results of this study are expected to assist highway transportation agencies in understanding the impact of the traffic data collection effort on mechanistic-empirical pavement design.
Effect of traffic monitoring period on mechanistic-empirical pavement design
Highlights AADTT, VCD, ALS, and number of axles per truck are the main traffic inputs affected by the traffic monitoring duration. Traffic monitoring data collected over all days of the week are more representative than partial week traffic data for pavement design. Roadways with lower truck traffic generally show higher variability in traffic data; hence, a longer traffic monitoring period is required for such locations in order to obtain reliable traffic inputs for use in pavement design.
Abstract The mechanistic-empirical pavement design approach requires defining detailed axle load spectra for each truck class and axle group that can be obtained from continuous site-specific weigh-in-motion (WIM) data. However, it is challenging to collect reliable WIM data over an extended period of time as these systems may experience technical or equipment problems leading to incomplete WIM data. As a result, there may be a need to rely on WIM data collected over shorter traffic monitoring periods to generate the required traffic inputs for use in mechanistic-empirical pavement design. This study examined the effect of the traffic monitoring period on the resulting traffic inputs and the associated pavement performance as predicted using the mechanistic-empirical pavement design approach. The analysis results revealed higher variability in traffic inputs and predicted performance when using shorter traffic monitoring periods. This was more obvious for WIM sites with lower truck traffic. This study also presented a framework for selecting the minimum required traffic monitoring period to achieve a target accuracy level in predicting the pavement service life. The results of this study are expected to assist highway transportation agencies in understanding the impact of the traffic data collection effort on mechanistic-empirical pavement design.
Effect of traffic monitoring period on mechanistic-empirical pavement design
Alzioud, Mahmoud (author) / Abbas, Ala (author) / Huang, Qindan (author)
2022-10-22
Article (Journal)
Electronic Resource
English
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