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

Dick Apronti · Khaled Ksaibati

17 citations0/0 files storedTransportation Planning and Technology

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Transportation Planning and Optimization Traffic control and management Traffic Prediction and Management Techniques

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.

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References

2007The Four-Step Model 2016Estimating traffic volume on Wyoming low volume roads using linear and logistic regression methods 1999Estimation of Annual Average Daily Traffic for Nonstate Roads in a Florida County 2000Estimation of Traffic Volume on Rural Local Roads 2009GIS-based travel demand modeling for estimating traffic on low-class roads 2013Estimating Annual Average Daily Traffic for Local Roads for Highway Safety Analysis 1999Urban transportation planning in the United States: an historical overview

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