Abstract

This study aims to investigate the individual and combined effects of working conditions, physical and mental conditions, and risky driving behaviors on taxi crashes in China. A total of 2,391 taxi drivers from four Chinese cities were invited to participate in a cross-sectional questionnaire survey. The questionnaire collected information on the demographic characteristics, working conditions, physical and mental conditions, risky driving behaviors, and crash frequency of taxi drivers. A Bayesian network (BN) model was developed to explore taxi crashes’ contributing effects. The modelling results showed that the constructed BN model has a reasonable structure and good predictive performance. Eight factors (i.e., driving violations, driving errors, aggressive behaviors, sleep problems, fatigue, age, working hours, and management fees) have significant effects on taxi crashes. Sleep problems showed greater effects on driving behaviors than driver fatigue. The combination of long working hours, sleep problems, and aggressive behaviors would lead to the highest probability of taxi crashes. These results can provide valuable suggestions for the order of safety measures to be taken in response to different risk factors affecting taxi crashes, and are particularly important for the government and industry to make optimal decisions for improving the taxi industry’s safety performance.

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