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Citation |
Wang Y, Zhang Y, Li L, Liang G. Traffic Injury Prev. 2019; 20(7): 738-743. |
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Affiliation |
School of Highway, Chang'an University , Xi'an , Shaanxi , China. |
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Copyright |
(Copyright © 2019, Informa - Taylor and Francis Group) |
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DOI |
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PMID |
31442087 |
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Abstract |
Objective: Taxis provide an important mode of public transport in China, but there has been very little in-depth research on the crash involvement propensity of taxi drivers. Thus, this study was conducted to develop a quantitative model for predicting the crash rate of taxi drivers. Methods: A total of 2,391 taxi drivers from 29 companies in 4 Chinese cities completed a structured and anonymous face-to-face questionnaire reporting their demographic information, workload conditions, aberrant driving behaviors, and crash history within the 2 years prior to the survey. Using the self-reported variables, a negative binomial model was implemented to predict taxi drivers' property damage only (PDO) and personal injury (PI) crash rates and identify the factors contributing to this risk. Results: Descriptive analysis of the survey data revealed that the workload of taxi drivers in China is relatively heavy. Seven significant predictors of PDO and PI crash rates were identified, including crossing red lights, dangerous overtaking, honking at a slow driver, failure to use an indicator lamp, driving while fatigued, stopping in forbidden areas to pick up or drop off a passenger, and driving with one hand. Taxi drivers' average off-duty days per week, aggressive driving behaviors, and preventing another driver from merging had significant effects only on PDO crash rate, and sleep problems were found to be significantly correlated with PI crash rate. Conclusions: To improve the safety of taxi drivers, considerable measures should be strictly implemented, ranging from periodic driver training and safety education to workload reduction, with the cooperation of government agencies and taxi companies. The findings of this study contribute to the design of potentially useful policy initiatives as well as targeted safety promotion programs. Language: en |
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Keywords |
Taxi drivers; aberrant driving behaviors; crash rate; negative binomial model; workload conditions |