Modelling speed behaviour in rural highways: Safety analysis of driving under adverse road-weather conditions

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.

Application of Different Data Analytics for Evaluation of Heavy Vehicle Vulnerability in Cold-Region Rural Highways

“…In this study, speed distributions are modelled based on two assumptions: (i) observed speeds reasonably represent drivers’ desired speeds, and (ii) the population of individual desired speeds under a specific combination of speed-decisive factors can be modelled as a normal distribution characterized by a mean of μ and an SD of σ . Study data used in this investigation supports both assumptions ( 5 ). In fact, it is well documented that desired speed distributions can be modelled as normal distributions under most conditions ( 5 , 23 ).…”

“…Study data used in this investigation supports both assumptions ( 5 ). In fact, it is well documented that desired speed distributions can be modelled as normal distributions under most conditions ( 5 , 23 ). Yet, we hypothesize that drivers’ speed choice is dependent on the prevailing driving conditions; thus, the speed distribution parameters are expected to vary under different combinations of speed-decisive factors.…”

“…The site (Figure 2) was selected for this study for two reasons. First, it typically operates under levels of service ''A'' and ''B'' (see Figure 2 in Yasanthi et al [5])-that is, uncongested; thus, vehicle speeds collected reasonably represent drivers' desired speed (17). Second, the RWIS station precisely captures the microclimate data for each vehicle recorded by the WIM station as it is only 148.7 m away from the WIM (Figure 2).…”

“…Advanced automated traffic-data-collection techniques practiced today (e.g., loop detectors) enable reliable collection of vehicle-by-vehicle speed data ( 13 ), leading to large speed data sets. Accordingly, modelling population-level speed distributions is recommended in exploring the impacts of different driving conditions on drivers’ speed choice to effectively identify speed patterns present in such versatile and large speed data sets ( 5 ). Although several data analytics exist to model population-level speed distributions (“speed distributions” hereafter), the modelling results may be influenced by (i) the analysis approach and (ii) data-treatment methods (e.g., definition of sample) adapted.…”

“…CBA: The CBA, as proposed by Yasanthi et al ( 5 ), attempts to model μ and σ based on statistical inference techniques including CLT and minimum variance unbiased estimation (MVUE). Vehicle speeds collected within 5 min under a unique combination of speed-decisive factors are defined as a sample in the context of CBA.…”