Citation

Yasanthi RGN, Mehran B. Case Stud. Transp. Policy 2020; 8(1): 22-30.

Copyright

(Copyright © 2020, World Conference on Transport Research Society, Publisher Elsevier Publishing)

DOI

10.1016/j.cstp.2020.01.003

PMID

unavailable

Abstract

This study investigates driver behavior with respect to variations in desired driving speed under adverse road-weather conditions and explores the impacts of applying different data treatment methods in modeling such variations. The study site is located in a cold region highway in Alberta, Canada. The road-weather and traffic data collection devices are located alongside, permitting accurate measurement and association of exact pertaining road-weather and traffic conditions. The study has two main objectives: i) to investigate and model the impacts of road-weather events on the free-flow speed of vehicles, and ii) to explore the variability in models caused by adopting different data treatment methods. Linear and nonlinear regression models were developed with separate models for light and heavy vehicles travelling in shoulder and median lanes. Linear regression models developed with 20-minute aggregated free-flow speeds as dependent variable was found to be the best performing model for describing drivers' choice of desired speed under adverse road-weather conditions. The study results revealed that slight, moderate and heavy snow will respectively reduce the free-flow speed of light vehicles travelling in the shoulder lane by 0.2%, 3.4% and 0.8%, and by 0.3%, 0.4% and 1.5% when travelling in the median lane. Moreover, heavy vehicles travelling in slight, moderate and heavy snow were estimated to reduce their desired speeds by 1.7%, 0.1% and 1.3% in shoulder lane while the reduction factors for those travelling in slight and moderate snow in median lane was 1.1% and 1% respectively. Estimated reduction factors for free-flow speed variations under adverse road-weather conditions found to be significantly smaller than HCM (2016) recommendations and the findings of other studies. These figures signify the importance of winter road maintenance in extremely cold regions. The frequent snow and ice removal as a result of winter road maintenance operations obviates the need for reducing desired speed and eventually results in less weather-related delays. The significance of driver familiarity with prevailing geographical conditions, i.e. winter driving was also highlighted when investigating the impact of inclement road-weather conditions on traffic operations.

Language: en

Keywords

Adverse road-weather conditions; Driver behaviour; Free-flow speed; Regression modeling