Integrated risk reduction framework to improve railway hazardous materials transportation safety

•An integrated framework is developed to optimize risk reduction.•A negative binomial regression model is developed to analyze accident-cause-specific railcar derailment probability.•A Pareto-optimality technique is applied to determine the lowest risk given any level of resource.•A multi-attribute decision model is developed to determine the optimal amount of investment for risk reduction.•The models could aid the government and rail industry in developing cost-efficient risk reduction policy and practice. Rail transportation plays a critical role to safely and efficiently transport hazardous materials. A number of strategies have been implemented or are being developed to reduce the risk of hazardous materials release from train accidents. Each of these risk reduction strategies has its safety benefit and corresponding implementation cost. However, the cost effectiveness of the integration of different risk reduction strategies is not well understood. Meanwhile, there has been growing interest in the U.S. rail industry and government to best allocate resources for improving hazardous materials transportation safety. This paper presents an optimization model that considers the combination of two types of risk reduction strategies, broken rail prevention and tank car safety design enhancement. A Pareto-optimality technique is used to maximize risk reduction at a given level of investment. The framework presented in this paper can be adapted to address a broader set of risk reduction strategies and is intended to assist decision makers for local, regional and system-wide risk management of rail hazardous materials transportation.