*WINNER* Improving Accuracy of Annual Average Daily Traffic Estimates from Short-Period Traffic Counts

Abstract

This won best graduate poster for Civil and Environmental Engineering.

A key transportation performance measure is the annual average daily traffic (AADT) which is estimated from daily volume counts. U.S. Federal reporting requirements require that each state develop estimates of the AADT for the different sections of its road network. Each State Department of Transportation (DOT) has a traffic count program, specifically a permanent traffic count (PTC) program and a short period traffic count (SPTC) program, for the collection of volume data based on Federal Highway Administration (FHWA) recommendations. Data collected in the PTC program are used to determine the AADT. Data collected in the SPTC program are adjusted to AADT estimates using the appropriate SFs estimated at the PTC stations. Notable differences exist among the states in methodologies for computing SFs and performing SPTCs in terms of count duration and cycle. Therefore, the research objectives were to investigate key aspects of PTC and SPTC programs in terms of SF development, and count duration and cycle to determine what procedures will give superior quality estimates of AADTs on road sections. The research data was collected by Tennessee Department of Transportation. Central to obtaining more accurate estimates of AADT is good quality data hence a procedure, rooted in statistics, for identifying and deleting outlier volume data has been successfully developed. Statistical prediction of AADT at SPTC stations based on a sample count duration of 48 hours on a 3-year cycle was found to provide more accurate AADT estimates compared to 24-hour counts on a 1-year cycle.