This study analyzes how the number of traffic accidents can be effectively reduced by detailed study over the documented accidents. In this paper, we propose a new method called the traffic accident causes analysis based on dominance rough set theory. This method improvises on the limitations of Pawlak's rough set model in analyzing the causes of accidents, such as using discrete continuous attributes to obtain unreasonable rules. Furthermore, the paper combines facts about traffic accidents and the objective data processing ability of rough set theory. Specifically, every single cause of accidents is sorted according based on our experience and then relevant algorithms are applied to illustrate the relationship. Lastly, an example is demonstrated that shows that this method reduces the uncertainty of discretization of continuous attributes and excludes the causes that rule against human empirical knowledge.
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