The objective of this study is to establish the minimum traffic data collection effort required for pavement design applications satisfying a maximum acceptable error under a prescribed confidence level. The approach consists of simulating the traffic data input to the 2002 National Cooperative Highway Research Program (NCHRP) 1-37A design a guide for 17 distinct traffic data collection scenarios using extended-coverage, weigh-in-motion (WIM) data from the Long-Term Pavement Performance database. They include a combination of site-specific, regional, and national WIM, automated vehicle classification, and automated traffic recorder data of various lengths of coverage. Regional data were obtained using clustering techniques. Pavement life was estimated using mean traffic input and low-percentile input to the NCHRP 1-37A design guide for three levels of confidence: 75 percent, 85 percent, and 95 percent. For each confidence level, ranges in pavement life prediction errors were estimated. A three-dimensional plot was produced, indicating the maximum error by confidence level for each of the traffic data collection scenarios analyzed. This plot can be used to establish the minimum required traffic data collection effort, given the acceptable error and the desirable level of confidence.
Optimization of Traffic Data Collection for Specific Pavement Design Applications
2006
134 pages
Report
Keine Angabe
Englisch
Transportation & Traffic Planning , Highway Engineering , Transportation , Pavements , Traffic plans , Design applications , Clustering , Tolerable errors , Optimizations , Confidence levels , Error acceptibility , Traffic data collection , Three dimensional plots , Pavement life , Long-Term Pavement Performance Database , NCHRP 1-37A design guide
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