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使用两水平逻辑回归模型分析安全氛围和个体因素对公交司机事故参与的影响。

Analysis of safety climate and individual factors affecting bus drivers' crash involvement using a two-level logit model.

机构信息

School of Transportation Engineering, Tongji University, Shanghai, 201804, China; The Key Laboratory of Road and Traffic Engineering, Ministry of Education, Shanghai, 201804, China; National Engineering Laboratory for Integrated Optimization of Road Traffic and Safety Analysis Technologies, 88 Qianrong Rd, Wuxi, 214151, China.

School of Transportation Engineering, Tongji University, Shanghai, 201804, China.

出版信息

Accid Anal Prev. 2021 May;154:106087. doi: 10.1016/j.aap.2021.106087. Epub 2021 Mar 15.

Abstract

Although traffic crashes involving buses are less frequent than those involving other vehicle types, the consequences of bus crashes are high due to the potential for multiple injuries and casualties. As driver error is a primary factor affecting bus crashes, driver safety education is one of the main countermeasures used to mitigate crash risk. In China, however, safety education is not as focused as it should be, largely due to the limited research identifying the specific driver behaviors, and potential influences on those behaviors, that are correlated with crashes. The aim of this study is, therefore, to explore the fleet- and driver-level risk factors underlying bus drivers' self-reported crash involvement, including analyzing the effect of psychological distress on the most influential driver-level factors. A survey was conducted of 725 drivers from a large Shanghai bus company, and a random-effects two-level logit model was developed to integrate fleet and individual variables. Results showed that: 1) the fleet-level safety climate explained about 8.5% of the model's variance, indicating it was a valid predictor of self-reported crash involvement; 2) the driver-level factors of drivers' age, seniority, marital status, positive behavior, and driving anger influenced drivers' self-reported crash involvement, but ordinary violations, lapses, aggressive violations, and insomnia were the most influential variables; 3) psychological distress appeared to associate with the high frequency of risky driving behavior and the high severity of driving anger. This study's findings will help bus companies to give more attention to their safety climate and implement more targeted improvements to their driver safety education programs.

摘要

虽然涉及公共汽车的交通事故比其他类型车辆的交通事故频率要低,但由于可能造成多人受伤和死亡,公共汽车事故的后果较为严重。由于驾驶员失误是影响公共汽车事故的主要因素之一,因此驾驶员安全教育是降低事故风险的主要对策之一。然而,在中国,安全教育并没有得到应有的重视,主要是因为缺乏确定与事故相关的具体驾驶员行为以及这些行为潜在影响的研究。因此,本研究旨在探讨公共汽车驾驶员自我报告事故参与的车队和驾驶员层面的风险因素,包括分析心理困扰对最有影响力的驾驶员层面因素的影响。对来自上海一家大型巴士公司的 725 名驾驶员进行了调查,并建立了一个随机效应两水平逻辑模型,以整合车队和个人变量。结果表明:1)车队层面的安全氛围解释了模型方差的 8.5%左右,表明其是自我报告事故参与的有效预测指标;2)驾驶员层面的驾驶员年龄、驾龄、婚姻状况、积极行为和驾驶愤怒等因素影响驾驶员的自我报告事故参与,但普通违章、疏忽、攻击性违章和失眠是最有影响力的变量;3)心理困扰似乎与危险驾驶行为的高频度和驾驶愤怒的高严重度有关。本研究的结果将有助于巴士公司更加关注其安全氛围,并实施更有针对性的改进措施,以加强驾驶员安全教育计划。

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