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Best Practices for Road Weather Management Version 2.0

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Title:

Consideration of Weather Conditions for Estimation of Missing Traffic Data

Abstract:

Estimation of missing traffic data is an essential task for transportation agencies. Several imputation methods have been developed in literature to estimate the missing traffic volumes. But, none of them have considered the variation in traffic patterns due to severe winter weather conditions. Literature indicates that highway traffic volumes are highly influenced by weather conditions. Therefore, a detailed investigation is carried out in this study to develop relationships between weather and highway traffic volumes and use them for reliable estimation of missing traffic volumes. The study is based on hourly traffic data from permanent traffic counter sites located on provincial highways of Alberta, Canada, using 11 years of data from 1995 to 2005. The weather data are obtained from Environment Canada weather stations located within 10 miles distance from the chosen permanent traffic counter sites. Cold and snowfall are chosen to represent the winter conditions. Multiple regression analysis is used to develop relationships between hourly traffic volumes, categorized cold and total snowfall. The study models show a strong association between traffic volumes and weather conditions. The results indicated that weekend traffic is more susceptible to weather than weekdays. In case of extreme cold (below -250 degrees C), the peak hours experience less reductions in traffic (6 to 13 percent) than off-peak hours (10 to 17 percent). The amount of reduction in traffic volume due to each centimeter of snowfall varies from 0.5 to 2.0 percent. The traffic-weather relationships developed in this study are used to estimate missing hourly volumes. The estimation accuracies of study models are compared with one of the most efficient imputation methods used by transportation agencies. The study models resulted 30 to 75 percent less estimation errors as compared to the agency method.

Source(s):

87th Transportation Research Board (TRB) Annual Meeting, University of Regina (Canada). For an electronic copy of this resource, please direct your request to WeatherFeedback@dot.gov.

Date: 2007

Author:

Datla, Sharma

Keywords:


Air temperature
Snow
Winter storm

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