Average annual daily traffic (AADT) is one of the most important parameters in transportation engineering, used by transportation agencies for reporting, allocating resources, informing decision-making, and supporting various agency functions. At locations where vehicles are counted continuously with permanent counters, estimates of AADT will be fairly accurate. However, short-duration traffic counts, those conducted manually or with temporary equipment, cannot reflect traffic for all days and all seasons. Adjustment factor groups are intended to remove bias caused by potentially unrepresentative data, but methods commonly used to estimate AADT do not adequately address how data from short duration counts should be assigned to adjustment factor groups. 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. The objective of this research, conducted by the Texas A&M Transportation Institute (TTI) with advisory input from TRAC researchers, is to develop rational methods for assigning short-duration traffic volume counts to adjustment factor groups to improve estimates of AADT.
Principal Investigator: Mark E. Hallenbeck, Washington State Transportation Center, UW
Sponsors:
Texas A&M Transportation Institute
National Cooperative Highway Research Program
Project Manager: Ioannis Tsapakis, TTI
Scheduled completion: November 2023