BACKGROUND: Annual average daily traffic (AADT) which represents traffic on a typical day of the year is used by transportation agencies for reporting requirements, allocating resources, informing decision-making, and supporting various agency functions. Transportation agencies use different methods to derive AADT estimates from short-duration counts of traffic data from permanent and portable traffic counting equipment installed at selected locations.

Commonly used methods for estimating AADT do not adequately address how short-duration counts should be assigned to adjustment factor groups. Also, there are concerns about the inherent errors in these methods, their applicability to roadways with insufficient traffic data, and the accuracy of the derived AADT estimates. There was a need to improve existing methods and develop new methods for functional classes of roadway where insufficient continuous counting exists to improve accuracy of AADT estimates. These methods will help transportation agencies improve the quality of traffic information and support the decisions regarding capital investment programs and budgets as well as design and maintenance programs.

OBJECTIVE: The objective of this research was to develop rational methods for assigning short-duration traffic volume counts to adjustment factor groups for estimating AADT (the research was to consider all functional classes of roadways and traffic volumes).

Status: Research is complete. The guide eveloped in this research has been published as NCHRP Research Report 1124 available at https://doi.org/10.17226/27925 and the supporting report as an NCHRP Web-Only Document available at https://doi.org/10.17226/27926.