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The rapid increase in traffic volume and heavy vehicle loads is causing accelerated deterioration of pavement infrastructure worldwide. This research investigates the impact of overweight and dynamic axle loads on pavement performance, employing advanced weigh-in-motion (WIM) systems and machine learning...

The main objective of this study was to test both intrusive and non-intrusive data collection devices and to provide North Dakota Department of Transportation (NDDOT) with insight into the accuracy of the various data collection technologies and the applicability of the tested devices. All devices were...

This report describes a study conducted at the University of Wyoming to evaluate the various factors affecting the accuracy of Road Profilers measurements. Highway agencies across the U.S. use Road Profilers to measure roughness and rut-depth characteristics of pavements. These measurements are utilized...

The purpose of this project is to validate and implement computer-based statistical methods for the optimal placement of Automatic Traffic Recorders (ATR) on road sections to improve the overall efficiency and accuracy of Annual Average Daily Traffic (AADT) estimates. We developed two computer algorithims...