Improved Annual Average Daily Traffic Estimation Processes

Abstract

Annual average daily traffic (AADT) volume is estimated for federal, state, and local uses for roadway segments throughout the United States. The AADT estimates derived from permanent or portable counts are critical to roadway planning, system operations, and distribution of funding. The AASHTO AADT estimation formula is the most commonly used method, in part because it can be used under many circumstances when hourly traffic volume observations are missing, which is a common measurement issue with permanent traffic-counting sites. Despite its utility, the AASHTO AADT method has limitations in that it requires complete hourly data for any day that is included, and it does not account for variations in the numbers of each day of the week within a month or variations in the number of days within a month. This research evaluated new AADT estimation methods that incorporate days in which some, but not all, hourly observations are available and adjusts volume for the number of times each day of the week occurs in a month and the number of days per month. The bias and precision of four methods were examined for AADT estimation from hundreds of permanent traffic-counting sites. The analysis used more than 48 million records from the FHWA Travel Monitoring Analysis System, covering 14 years (2000 through 2013). This research quantified the improvement in accuracy and precision of the new methods, which effectively allow for a greater proportion of data to be retained in the estimation formula.