Abstract
This study proposes a methodical approach to model desired speed distributions under different road-weather and traffic conditions followed by identification of road-weather conditions with potentially higher safety risks in rural divided highways located in extremely cold regions. Desired speed distributions encompassing unique combinations of adverse road-weather and traffic conditions are modelled as normal distributions characterized by their means and standard deviations formulated based on two principal statistical theorems and techniques i.e., Central Limit Theorem and Minimum Variance Unbiased Estimation. Combination of the precipitation conditions, road surface conditions, time of the day, temperature, traffic flow and the heavy vehicle percentage at the time of travel were considered in defining the combinations of road-weather and traffic conditions. The findings reveal that simultaneous occurrence of particular precipitation and pavement conditions significantly affect the characteristics of the desired speed distribution and potentially expose drivers to elevated safety risks. Jurisdictions experiencing extreme road-weather conditions may adapt the proposed methodology to assess speed behaviour under different road-weather conditions to establishing and deploying weather-responsive traffic management strategies such as variable speed limit to regulate speeding and improve traffic safety in winter.
Highlights
Highway safety, characterized by the ability of a person to travel freely without injury or death, has always been the primary objective of traffic engineering and is typically measured by the rate of crashes belonging to different severity levels [1]
Uncongested traffic streams operating at Level of Service (LOS) “A” or “B” with traffic flow values less than 1,000 veh/h/lane can be reasonably considered to represent “free-flow” conditions [11], where drivers are free to adopt their desired speeds
This study investigates the speed behavior observed in a rural highway, which mostly encounters traffic flow volumes less than 1,000 passenger cars per hour per lane (Fig 2)
Summary
Highway safety, characterized by the ability of a person to travel freely without injury or death, has always been the primary objective of traffic engineering and is typically measured by the rate of crashes belonging to different severity levels [1]. While using identical study data as used by [9], this study intends to fill the gaps identified in the literature by proposing a novel approach for modeling the distribution of desired speeds in uncongested highways under different combinations of road-weather and traffic conditions, rather than quantifying speed variations resulted by adverse road-weather conditions. The mean and standard deviation of speeds of vehicles travelling in the median lane at nighttime in temperature values more than 0 ̊C under a dry pavement and a moderate and heavy frozen precipitation recorded a comparatively higher mean speed which can potentially be attributed to the low sample size (44 five-minute intervals only). The frequency of samples for each sample size n tends to decrease as the sample size increases implying comparatively low traffic volumes observed at the study site, which is in an uncongested rural highway
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