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The present study utilized a random parameter logit (RPL) model to explore the nonlinear relationship between explanatory variables and the likelihood of expressway crash severity. The potential unobserved heterogeneity of data brought by China’s road traffic characteristics was fully considered. A total of 1154 crashes happened on Hang-Jin-Qu Expressway from 2013 to 2018 were analyzed. In addition to the conventional impact factors considered in the past, variables related to road geometry were also introduced, which contributed to expressway accidents significantly. The overall stability of the model estimation was examined by likelihood ratio test. Then, the average elastic coefficient of the significant factors at each severity level was also calculated. Several factors that significantly increase the fatal crash probability were highlighted: rainy/snowy/cloudy weather condition, low visibility (100– m), night …