Estimation of Average Daily Traffic on Low-Volume Roads in Alabama

Estimation of Annual Average Daily Traffic (AADT) is vital for departments of transportation (DOTs) work because AADT provides the basic information for planning new road construction, determination of roadway geometry, traffic control needs, congestion management strategies and safety considerations. AADT is used to determine state wide vehicle miles travelled on all roads and are used by transportation agencies to determine compliance with federal and state rules and regulations. DOTs spend heavily to collect traffic counts on state roads,but mostly traffic counts are not available for off-system, or low volume roads. Often estimates rely on a comparison with roads that are subjectively considered to be similar. Such comparisons are inherently subject to large errors, and also may not be repeated often enough to remain current. Therefore, a better method is needed for estimating AADT for off-system roads. This research developed a technique to estimate AADT for local roads in Alabama incorporating various facets from previous studies. A model has been developed using linear regression using known AADTs and collection of socio-economic and location variables as a means to estimate the AADT. The model relied upon five independent variables: nearby population, number of households in the area, employment in the area, population to job ratio and access to major roads. The model was used to generate AADT estimates on low-volume rural, local roads for counties in Alabama. The model was developed using 70 percent of the collected data and validate to the remaining 30 percent of the data. Consistent with the recent literature on AADT estimation, a log transformation was attempted to determine if any improvements were determined. The paper concludes that a straight linear regression model can be used to predict the AADT for low-volumes roadways in Alabama for future applications.

• Supplemental Notes:
  • This paper was sponsored by TRB committee ADB40 Standing Committee on Transportation Demand Forecasting.
• Authors:
  • Raja, Prithiviraj
  • Doustmohammadi, Mehrnaz
  • Anderson, Michael D
• Conference:
  • Transportation Research Board 97th Annual Meeting
  • Location: Washington DC, United States
  • Date: 2018-1-7 to 2018-1-11
• Date: 2018

Language

• English

Media Info

• Media Type: Digital/other
• Features: Figures; References;
• Pagination: 13p

Subject/Index Terms

• TRT Terms: Annual average daily traffic; Low volume roads; Traffic counts; Traffic estimation
• Geographic Terms: Alabama
• Subject Areas: Highways; Planning and Forecasting;

Filing Info

• Accession Number: 01663011
• Record Type: Publication
• Report/Paper Numbers: 18-03444
• Files: TRIS, TRB, ATRI
• Created Date: Mar 20 2018 5:04PM