Safety is the top priority for every rail system in the world. A widely used measure for rail safety is the accident rate, which is the number of train accidents normalized by traffic exposure. Of interest in rail safety research is understanding the temporal trend of accident rates, the significant factors affecting the trend, and how to predict accident rates. This paper uses a negative binomial regression model to present a statistical analysis of U.S. Class I railroad freight train derailment rates on main tracks by year and accident cause for 2000 to 2012. The accident and traffic data used in the analysis come from FRA. The analysis led to several observations. There is a significant temporal decline in freight train derailment rate (-5.9% per year). The rate of change in accident rate varied by accident cause. Rates of freight train derailment caused by broken rails or welds and track geometry defects declined by 6% and 5% annually, respectively; the rate of derailment caused by bearing failure decreased by 11% annually; and rate of derailment caused by train handling errors fell by 7% annually. The regression model is used to project train derailment rates by accident causes and can be used to evaluate the safety benefit of potential accident prevention strategies. This research provides policy makers and practitioners with a statistical method for analyzing the temporal trend of train accident rate for development of rail safety policy and practice.
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