Technical Notes
Feb 24, 2022

Visibility of Winter Operations Vehicles: The State of Practice in the United States

Publication: Journal of Cold Regions Engineering
Volume 36, Issue 2

Abstract

Despite precautions taken by the operators of maintenance vehicles, insufficient visibility of winter operations vehicles causes many collisions in the United States. Numerous methods have been developed to enhance the visibility of winter operations vehicles. Although these methods have improved the visibility of winter operations vehicles, information regarding the current state of practice of these methods is crucial for the safety of winter operations vehicles, and commuters. For safer winter operations, it is critical to investigate the differences, similarities, and challenges associated with the existing methods for enhancing the visibility of winter operations. This research examines the differences, similarities, and challenges associated with these methods using a survey to collect information from state transportation agencies. Questionnaire distribution included all 50 states to investigate patterns among the states and 25 Texas Dept. of Transportation (TxDOT) districts to gather the state of practice of the operations vehicles’ visibility methods. Results of the survey brought forward the inefficiencies of some current visibility methods. For example, rear airfoils were reported to be ineffective, while many state DOTs use and maintain the airfoils despite the inefficiencies. Although a wide range of dissimilarities was found in the use of message signs and retroreflective markings, they are reported to be inexpensive and effective. It is expected that the findings of this study help transportation agencies implement more effective methods for enhancing the visibility of winter operations vehicles.

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Acknowledgments

This research was conducted under a grant from the Research and Technology Implementation Division of the Texas Dept. of Transportation (TxDOT) under Project number 0-6996. In particular, the authors are grateful for the support and guidance provided by Joanne Steele, Glenn Allbritton, Aaron Bloom, Andrew Holick, Matthew Evans, Jeremy King, David Morren, Michaelle Anthony, Michaelle Stroope, Shawn Elliott, and Bobbly Pulliam. The contents of this paper reflect the views of the authors, who are responsible for the facts and the accuracy of the data presented herein. The contents do not necessarily reflect the official view or policies of the Federal Highway Administration (FHWA) or the Texas Dept. of Transportation (TxDOT).

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Go to Journal of Cold Regions Engineering
Journal of Cold Regions Engineering
Volume 36Issue 2June 2022

History

Received: Jul 18, 2020
Accepted: Dec 8, 2021
Published online: Feb 24, 2022
Published in print: Jun 1, 2022
Discussion open until: Jul 24, 2022

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Authors

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Wasiq Ameen, S.M.ASCE [email protected]
Graduate Student, Dept. of Civil Engineering, Univ. of Texas at Arlington, 416 S Yates St., Arlington, TX 76010. Email: [email protected]
Ferika Farooghi, S.M.ASCE [email protected]
Graduate Student, Dept. of Civil Engineering, Univ. of Texas at Arlington, 416 S Yates St., Arlington, TX 76010. Email: [email protected]
Mohsen Shahandashti, M.ASCE [email protected]
Associate Professor, Dept. of Civil Engineering, Univ. of Texas at Arlington, 416 S. Yates St., Arlington, TX 76010 (corresponding author). Email: [email protected]
Professor, Dept. of Civil Engineering, Univ. of Texas at Arlington, 416 S. Yates St., Arlington, TX 76010. ORCID: https://orcid.org/0000-0001-6515-6813. Email: [email protected]

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Cited by

  • Analysis of Construction Workers’ Health and Safety in Cold Weather Conditions, Journal of Cold Regions Engineering, 10.1061/JCRGEI.CRENG-687, 38, 1, (2024).
  • Enhancing Winter Maintenance Decision Making through Deep Learning-Based Road Surface Temperature Estimation, Construction Research Congress 2024, 10.1061/9780784485279.070, (701-711), (2024).
  • Developing a Cost-Effective Mobile-Based System for Collecting On-Demand Road Condition Images for Snowplow Operations Management, International Conference on Transportation and Development 2023, 10.1061/9780784484883.012, (127-137), (2023).

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