Alaskan Study Found Road Weather Information Systems (RWIS) Can Reduce Fatal and Serious Winter Crashes by 36 Percent.
Statewide Study in Alaska Analyzed Safety Impacts of RWIS Implementation Across 26 Road Segments Spanning 1,030 Miles.
Alaska, United States
Road Weather Information System Contributions to Road Safety
Summary Information
Road Weather Information Systems (RWIS) is an integrated system that collects, processes, and communicates real-time data on roadway and weather conditions through sensor stations. While RWIS has become a widely adopted tool for winter maintenance planning, its direct safety benefits, particularly in reducing crash risks, remain less well understood. This study evaluated 26 of Alaska’s 75 statewide RWIS stations to assess their impact on vehicle crashes during winter conditions. The objective was to quantify the safety benefits of RWIS deployment and identify promising locations for future implementation, considering both safety outcomes and maintenance-related needs.
METHODOLOGY
Statistical modeling and analysis were conducted using crash, weather, traffic, and roadway geometry data from 26 RWIS-equipped segments across approximately 1,030 miles. The winter crash data was extracted from Alaska DMV reports, limited to winter crashes over three seasons before and after RWIS deployment, approximately establishing a study period from 2000 to 2010. The study developed two safety performance models (i.e., where the predicted crash frequency is a function of both segment length and annual average daily traffic) to evaluate factors in winter combined crashes and winter fatal crashes. The study also calculated a crash modification factor to show how the number of winter crashes would change after RWIS stations were installed in Alaska.
FINDINGS
- RWIS deployment resulted in a 16 percent reduction in total winter crashes, and a 36 percent reduction in fatal and serious injury winter crashes.
- The calculated cost-to-benefit ratio of deploying RWIS throughout the state’s highway segments was approximately 1:27.
