Driver behaviour and traffic accident involvement among professional urban bus drivers in China. (October 2020) - Han, Wanli; Zhao, Jianyou
Highlights: A comprehensive driving behavior scale was developed for Chinese urban bus drivers. Identify the driving behaviors of urban bus drivers in China based on DBQ. Investigate the relationship between driver characteristics and traffic accidents. Put forward suggestions to prevent traffic accidents of urban bus drivers in China Abstract: The present research aimed to investigate specific behaviors of professional urban bus drivers in China with the revised Driver Behavior Questionnaire (DBQ), and to define the relationships among various driving behaviors (errors, positives, inattention errors, violations), background information (age, years of driving experience, mobility, etc.), self-assessment, and traffic accident. To achieve such goals, the present research designed a four-dimensional DBQ with 20 items for professional urban bus drivers in China. The KMO coefficient of the whole scale was 0.835, and Bartlett's test was statistically significant (p < 0.000), which demonstrated strong validity of the scale and should be suitable for factor analysis. The four loading factors accounted for 58.991%. In addition, the reliability and effectiveness of the present 20-item scales were measured. The coefficient of internal consistency-Cronbach's alpha coefficient was 0.881 and the Cronbach's Alpha Based on Standardized Items was 0.911. This showed that driving behavior scale of professional bus drivers in China was of high reliability and validity. The analysis showed that among the four factors, positive driving behaviors were significantly associated with errors, inattention errors and violations, respectively. Errors, inattention errors and violations correlated positively with each other. This verified that the correlation coefficient of each factor was medium and high, which indicated that the scale had good difference validity. The test content of the total scale was also highly consistent with the test content of each factor, which indicated that the revised scale had good standard related validity. According to the accident prediction model, the variables that significantly affected the occurrence of traffic accidents were daily driving time, positive driving behavior, SE2 (Driving safety), SE3 (Aberrant driver behaviors). The results showed that professional bus drivers often working overtime were most likely to have accidents. The probability of traffic accidents decreased by 53% for every unit of positive driving behavior frequency of professional bus drivers. The more they felt that they had the tendency of aberrant driving behavior, the more likely they were to have traffic accidents. To summary, the present research contributed to validating and improving the DBQ for professional urban drivers in China.