Development of Strategies for Improving Traffic Safety and Operations in Winter

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Winter driving can be very challenging due to slippery roads and reduced visibility caused by falling and/or blowing snow. Due to reduced road surface friction and limited visibility, drivers are generally reluctant to use the desired acceleration and/or breaking power to react to traffic events. It is also common that pavement markings are completely covered by packed snow, and the effective lane width or the number of available lanes for moving traffic is reduced due to accumulation of snow caused by snow plow operations. These particular conditions suggest significant variations in physical characteristics of road network and driver behavior in winter. A clear understanding of such variations and their influence on traffic flow characteristics and safety are very important for highway agencies to plan for safe, efficient, and effective traffic management policies.The main purpose of this research is to investigate the effect of winter weather conditions on microscopic and macroscopic traffic flow characteristics on highways and intersections and evaluate the operational issues and safety risks caused by winter weather and winter road maintenance operations in order to develop traffic management strategies to minimize these impacts. Study sites will include several highway locations in Alberta and Saskatchewan and signalized intersections in Regina, Saskatchewan. Video surveys will be used to collect traffic data. Weather data will be collected using portable temperature and precipitation sensors installed at study sites. Road surface conditions will be monitored through video cameras and visual inspections. This research will also utilize traffic and weather data available from highway agencies and Environment Canada. A majority of parameters to be analyzed in this study have stochastic properties (e.g. following headway, capacity, etc.). The distribution of the parameter of interest will be obtained through empirical data, and statistical methods will be used to compare the distributions across different weather and road surface conditions. Regression and cross-classification analyses will be conducted to develop predictive models for describing these parameters considering various weather and road surface conditions.The research findings will allow calibration of driver behavior and car-following parameters in traffic micro-simulation models to account for winter weather conditions and provide better insights into seasonal fluctuations of highway capacity and intersection saturation flow rate. Furthermore, the investigations conducted in this study will provide clear guidelines for adjusting signal timing parameters to improve the operations and safety of signalized intersections in winter and assist highway agencies in maximizing the safety benefits of their winter road maintenance operations.