Develop Local Functional Classification VMT and AADT Estimation Method

Principle Investigator: Srinivas S. Pulugurtha
Research Staff: Sonu Mathew, Venkata R. Duddu, Sarvani Duvvuri, Chandan Mannem, Chaithanya Bhure
Funding Agency: United States Department of Transportation

Rapid growth in population over the past two decades has led to an increase in travel demand, resulting in congestion and an exponential increase in conflicts that arise because of human interaction, off- and on network characteristics, and other associated factors. To better cater the increase in demand and reduce congestion, a federally-funded, state-administered program known as Highway Safety Implementation Program (HSIP) is legislated. The goal of HSIP is to achieve a significant reduction in fatalities and serious injuries on public roads. One of the requirements of HSIP for state agencies is to report annual average daily traffic (AADT) on all paved public roads (includes functionally classified major and local roads) and develop safety performance measures. The main objective of this research was to estimate AADT for local roads in the state of North Carolina. Recommendations were made to estimate AADT and VMT based on the count-based AADT at traffic count stations, model outputs, and growth factors for the reporting year. The application of the proposed AADT estimation method minimizes the costs associated with lapses in traffic count data collection programs and plans.