Four-step travel demand model implementation for estimating traffic volumes on rural low-volume roads in Wyoming

Dick T. Apronti and Khaled Ksaibati

Transportation Planning and Technology, 2018, vol. 41, issue 5, 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.

Date: 2018
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DOI: 10.1080/03081060.2018.1469288

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