Traffic volume is an important parameter in transportation planning. However, traffic volume estimation on low-volume roads is usually ignored compared to that on high-volume roads. This research developed a four-step travel demand model (TDM) to estimate average daily traffic (ADT) on low-volume roads in Wyoming. Four types of trips, including person trips, crop production freight trips, oil production freight trips, and tourism trips, were evaluated in the model to estimate ADT. The model outputs indicated that person trips and tourism trips are two main traffic generators on low-volume roads in Wyoming. Tourism trips play a significant role in Northwest Wyoming, where Yellowstone National Park is located. Crop production freight trips have impacts on low-volume roads near farms. The model developed in this study is capable to capture traffic flows on low-volume roads. The model is recommended for use by government agencies in other states or regions for traffic prediction and transportation planning on low-volume roads.
Dr. Er Yue obtained her Ph.D. degree in Civil Engineering at Oklahoma State University. With a multidisciplinary background, her research interests include transportation engineering, geographic information system (GIS), and remote sensing. As a postdoctoral researcher at Wyoming Technology Transfer Center, University of Wyoming (2017 – 2020), she led a research project on the estimation of traffic volume on Wyoming low-volume roads by using travel demand models. She was also involved in several projects that aim to address transportation issues, such as pavement management and traffic crash analysis.