Effect of Winter Weather and Road Surface Conditions on Macroscopic Traffic Parameters
Tae Jung Kwon, Liping Fu, Chaozhe Jiang
Abstract
Tae Jung Kwon, Liping Fu, Chaozhe Jiang
Abstract
This paper presents an empirical study focusing on identifying the main factors that affect the capacity and free-flow speed (FFS) of urban freeways under inclement winter weather conditions. The weather and road surface condition factors examined include air temperature, wind speed, hourly snow intensity, visibility, snow on ground, and road surface condition describing the road slipperiness caused mainly by snow events. Data on traffic operations and the associated weather and road conditions observed at two freeway locations over the 2010–2012 winter seasons were used in an extensive statistical analysis. Linear regression models were calibrated for both capacity and FFS reductions as related to various weather and road condition variables. It was found that visibility and road surface conditions had a statistically significant effect on both capacity and FFS. Snow intensity was found to be significant only when the visibility factor was excluded; this finding suggests a refutation of these two factors on capacity and FFS. The modeling results were compared with those recommended by the Highway Capacity Manual 2010, showing that, in many cases, the manual could underestimate or overestimate the effects of winter weather conditions and that the proposed models provided a more reasonable estimate at a higher level of granularity.
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This paper presents an empirical study focusing on identifying the main factors that affect the capacity and free-flow speed (FFS) of urban freeways under inclement winter weather conditions. The weather and road surface condition factors examined include air temperature, wind speed, hourly snow intensity, visibility, snow on ground, and road surface condition describing the road slipperiness caused mainly by snow events. Data on traffic operations and the associated weather and road conditions observed at two freeway locations over the 2010–2012 winter seasons were used in an extensive statistical analysis. Linear regression models were calibrated for both capacity and FFS reductions as related to various weather and road condition variables. It was found that visibility and road surface conditions had a statistically significant effect on both capacity and FFS. Snow intensity was found to be significant only when the visibility factor was excluded; this finding suggests a refutation of these two factors on capacity and FFS. The modeling results were compared with those recommended by the Highway Capacity Manual 2010, showing that, in many cases, the manual could underestimate or overestimate the effects of winter weather conditions and that the proposed models provided a more reasonable estimate at a higher level of granularity.
Key concepts: Visibility, Snow, Wind speed, Environmental science, Meteorology, Road surface, Model output statistics, Weather station