Developing a Risk Assessment Model for a Highway Site during the Winter Season and Quantifying the Functional Loss in Terms of Traffic Reduction Caused by Winter Hazards Conditions
Publication: Journal of Transportation Engineering, Part A: Systems
Volume 148, Issue 7
Abstract
This paper introduces a methodology to quantify traffic change triggered by the combined effect of weather hazards based on winter weather hazards models. The winter weather hazards models for three vehicle types were developed with weigh-in-motion (WIM) data collected in the commuter highway in the cold Canadian region for 5 years. The developed model was utilized to simulate the variations of the percentage reduction for each vehicle type based on the 239 pairs of weather combinations composed of six cold categories and various amounts of snowfall. The first phase involved measuring the marginal effect of weather factors such as cold category (or temperature) on the percentage reduction in traffic volume. The second phase involved utilizing the same winter weather traffic model to quantify the effect of combined weather factors on the percentage reduction. The percentage reduction of the total traffic and passenger cars increased as temperature deteriorated and snowfall increased. Truck traffic decreased as snowfall increased, but interestingly, as temperature deteriorated, it was estimated that the truck traffic volume increased. This phenomenon assumed that truck traffic moves from low-maintenance to high-maintenance highways as the weather deteriorates. The methodology to quantify traffic volume changes can be adopted by highway agencies to determine the timing of the snowplow operation based on the risk assessed in terms of traffic volume reduction. It can also be used to predict the percentage reduction of traffic and then determine whether to open or close a highway.
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Data Availability Statement
Some or all data, models, or codes that support the findings of this study are available from the corresponding author upon reasonable request:
1.
Data set for modeling conducted in the study.
2.
Raw weather and traffic data collected from the study WIM site and weather stations.
Acknowledgments
The author thanks Alberta Transportation for providing the WIM data used in this study.
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Published In
Journal of Transportation Engineering, Part A: Systems
Volume 148 • Issue 7 • July 2022
Copyright
© 2022 American Society of Civil Engineers.
History
Received: Apr 21, 2021
Accepted: Feb 18, 2022
Published online: Apr 21, 2022
Published in print: Jul 1, 2022
Discussion open until: Sep 21, 2022
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Cited by
- Hyuk-Jae Roh, A study on securing model usefulness through geographical scalability testing of winter weather model developed with big traffic data, Transportation Planning and Technology, 10.1080/03081060.2022.2132947, 45, 6, (473-497), (2022).