An examination of traffic volume during snow events in northeast Ohio

Daniel Burow () and Christopher Atkinson
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Daniel Burow: University of Tennessee, Knoxville
Christopher Atkinson: University of North Dakota

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2019, vol. 99, issue 2, No 29, 1179-1189

Abstract: Abstract Snowfall presents a hazard to drivers by reducing visibility and increasing safe stopping distances. Some drivers cancel trips if snowfall is occurring or forecast, and traffic volumes often decrease on snowy days. Lake-effect snow is very localized and is thus hypothesized to have a lesser influence on traffic volume than synoptic-scale snow, which usually covers a broader areal extent. We analyze traffic volume in northeast Ohio during 25 snow events and use a matched-pair analysis to determine whether volumes differ between lake-effect and synoptic-scale snowfall in these regions. We also examine the rate at which traffic volume decreases during snow events by time of day and day of week. Results indicate that there is little difference in mean traffic volume decreases when comparing lake-effect and synoptic-scale snow. Hourly trends suggest that traffic volume is most sensitive to snowfall during the midday on weekdays and late afternoon on weekends and least sensitive to snowfall during the overnight hours. Findings presented herein can assist in transportation planning, risk analysis and roadway safety.

Keywords: Traffic volume; Snow; Transportation; Great Lakes (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (4)

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DOI: 10.1007/s11069-019-03786-y

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