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Factor analysis refers to a collection of statistical methods for reducing correlational data into a smaller number of dimensions or factors. In this study, factor analysis theory was used to determine the main influential factors of road traffic crashes with massive casualties. Twenty variables related to personnel, vehicles, roads, and environment were collected, and the significance of their correlations was tested for validity. A correlation coefficient matrix R was calculated, and its latent root Formula: see text was obtained based on the characteristic equation. A number of common factors were determined according to the value of latent root Formula: see text. Factor loading was used to express the relationship of each variable to the underlying main influential factors. An index system of accident factors was developed based on the results of factor loading, and the weight of each factor was calculated to classify the factor influence. The main influential factors of accidents were determined to be fault behavior, driving experience, condition of vehicle safety, purpose of vehicle, road lighting, driver, road surface condition, roadside protection facilities, and road terrain.
Chen et al. (Fri,) studied this question.