Improving the estimation of total and direction-based heavy-duty vehicle annual average daily traffic

Abstract

The estimation of annual average daily traffic (AADT) is an important parameter collected and maintained by all US departments of transportation. There have been many past research studies that have focused on ways to improve the estimation of AADT. This paper builds upon previous research and compares eight methods, both traditional and cluster-based methodologies, for aggregating monthly adjustment factors for heavy-duty vehicles (US Department of Transportation Federal Highway Administration (FHWA) vehicle classes 4–13). In addition to the direct comparison between the methodologies, the results from the analysis of variance show at the 95% confidence level that the four cluster-based methods produce statistically lower variance and coefficient of variation over the more traditional approaches. In addition to these findings – which are consistent with previous total volume studies – further analysis is performed to compare total heavy-duty monthly adjustment factors, both directions of traffic, with direction-based monthly adjustment factors. The final results show that the variance as well as the coefficient of variation improve on average by 25% when directional aggregate monthly adjustment factors are used instead of total direction.

Keywords:

• AADT
• heavy-duty truck
• cluster analysis
• function class groupings

Acknowledgements

The authors would like to thank the Ohio Department of Transportation for the generous financial support and time. The authors would specifically like to thank Mr Dave Gardner, Mr Tony Manch and Ms Lindsey Pflum for their valuable advice and help. Finally the authors would like to thank the reviewers of this paper for the time and suggestions on how to improve this paper. The research was performed at the University of Akron and the contents reflect the views of the authors who are responsible for the facts and the accuracy of the data presented herein. The contents do not necessarily reflect the official views or polices of U.S.DOT or ODOT.