A study of aberrant driving behaviors and road accidents in Chinese ride-hailing drivers

IF 2.4 3区 工程技术 Q3 TRANSPORTATION
Jingyuan Shi, Muhammad Hussain, Dandan Peng
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引用次数: 1

Abstract

Abstract This study aims at analyzing the factors of aberrant driving behaviors and road accidents among Chinese ride-hailing drivers. Four hundred and twenty ride-hailing drivers (Male = 65%) completed a web-based questionnaire survey that assessed personal attributes, work-condition factors, aberrant driving behaviors, and self-reported road accidents in the last three years. A 10-item violations Driver Behavior Questionnaire (DBQ) scale was adopted to explore the aberrant driving behaviors of ride-hailing drivers. The ordinal regression model was used to examine the effects of personal attributes and work-condition factors on aberrant driving behaviors. A binary logistic regression model was employed to investigate the predictors of road accidents. The descriptive statistics indicate that among ride-hailing drivers, the traditional taxi drivers were found to be more involved in aberrant driving behaviors than private car drivers. The results from the Principal Component Analysis (PCA) reveal that ride-hailing drivers were involved in "risky violations." Male and young ride-hailing drivers were found to be more involved in risky violations than their counterparts. Furthermore, it is revealed that a one-unit increase in risky violations increased the probability of being involved in road accidents by 60%. Furthermore, a one-unit increase in work-condition factors increased the likelihood of being involved in road accidents by 41%. The findings in this study can help better understand the aberrant driving behaviors of ride-hailing drivers and contribute to a more effective policy for reducing the road accidents caused by ride-hailing drivers.
中国网约车司机异常驾驶行为与道路交通事故研究
摘要本研究旨在分析中国网约车司机异常驾驶行为和道路交通事故的影响因素。420名网约车司机(男性占65%)完成了一项基于网络的问卷调查,评估了过去三年的个人属性、工作条件因素、异常驾驶行为和自我报告的道路交通事故。采用10项违规驾驶行为问卷(DBQ)调查网约车司机的异常驾驶行为。运用有序回归模型考察个人属性和工作条件因素对驾驶行为的影响。采用二元logistic回归模型研究道路交通事故的预测因素。描述性统计表明,在网约车司机中,传统出租车司机比私家车司机更容易出现异常驾驶行为。主成分分析(PCA)的结果显示,网约车司机参与了“危险违规”。男性和年轻的网约车司机比他们的同行更容易发生危险的违规行为。此外,研究显示,危险违规行为每增加一个单位,发生交通事故的概率就会增加60%。此外,工作条件因素每增加一个单位,发生交通事故的可能性就会增加41%。本研究的发现有助于更好地理解网约车司机的异常驾驶行为,并有助于制定更有效的政策来减少网约车司机造成的交通事故。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
6.00
自引率
15.40%
发文量
38
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