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

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  • Dick T. Apronti
  • Khaled Ksaibati

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.

Suggested Citation

  • Dick T. Apronti & Khaled Ksaibati, 2018. "Four-step travel demand model implementation for estimating traffic volumes on rural low-volume roads in Wyoming," Transportation Planning and Technology, Taylor & Francis Journals, vol. 41(5), pages 557-571, July.
    • Handle: RePEc:taf:transp:v:41:y:2018:i:5:p:557-571
    DOI: 10.1080/03081060.2018.1469288
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    Cited by:

    1. Vitalii Naumov & Andrzej Szarata & Hanna Vasiutina, 2022. "Simulating a Macrosystem of Cargo Deliveries by Road Transport Based on Big Data Volumes: A Case Study of Poland," Energies, MDPI, vol. 15(14), pages 1-23, July.
    2. Krug, Jean & Burianne, Arthur & Bécarie, Cécile & Leclercq, Ludovic, 2021. "Refining trip starting and ending locations when estimating travel-demand at large urban scale," Journal of Transport Geography, Elsevier, vol. 93(C).

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