@article{ref1,
title="Four-step travel demand model implementation for estimating traffic volumes on rural low-volume roads in Wyoming",
journal="Transportation planning and technology",
year="2018",
author="Apronti, Dick T. and Ksaibati, Khaled",
volume="41",
number="5",
pages="557-571",
abstract="This study develops a four-step travel demand model for estimating traffic volumes for low-volume roads in Wyoming. The study utilizes urban travel behavior parameters and processes modified to reflect the rural and low-volume nature of Wyoming local roads. The methodology disaggregates readily available census block data to create transportation analysis zones adequate for estimating traffic on low-volume rural roads. After building an initial model, the predicted and actual traffic volumes are compared to develop a calibration factor for adjusting trip rates. The adjusted model is verified by comparing estimated and actual traffic volumes for 100 roads. The R-square value from fitting predicted to actual traffic volumes is determined to be 74% whereas the Percent Root Mean Square Error is found to be 50.3%. The prediction accuracy for the four-step travel demand model is found to be better than a regression model developed in a previous study.<p /> <p>Language: en</p>",
language="en",
issn="0308-1060",
doi="10.1080/03081060.2018.1469288",
url="http://dx.doi.org/10.1080/03081060.2018.1469288"
}