Date of Graduation
Statler College of Engineering and Mineral Resources
Civil and Environmental Engineering
David R. Martinelli.
Reliable estimates of truck volumes are important in transportation planning and design applications, such as pavement design and management. This study evaluates different statistical methods based on their accuracy and data requirements, to calculate the truck growth rates by developing statistical models. Nine years of data from 1995 to 2003 was used to develop these models for calculating the truck growth rates at non-interstate highways of West Virginia. The literature review and the current practices for the state DOT was conducted to better understand and select the different forecasting methods that could be applicable to the given data. As a result, the two techniques namely, the regression analysis and the growth factor method were used for the purpose. These techniques were applied to each site and for each truck classification. For a clear perspective of truck traffic patterns across the state, the sites were grouped based on the location of the counters, i.e., the rural and the urban, and trucks were grouped according to the number of axles. Precision test was then conducted to validate the models. All the results from the methods used for this study were compared and was concluded that the regression analysis is the best suited method for the given data, in West Virginia. The comprehensive approach to the evaluation can be used by the state DOT.
Gopisetty, Sundeep, "Forecasting truck traffic growth at West Virginia non-interstate highways" (2006). Graduate Theses, Dissertations, and Problem Reports. 1770.