纠正通勤时间认知偏差,减轻雪天驾驶压力:中国哈尔滨的自然驾驶研究

IF 2 4区 工程技术 Q2 ENGINEERING, CIVIL
Zifeng Yang, Zhenwu Shi, Di Lu, Jie Liu
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引用次数: 0

摘要

作为一种负面情绪,职业驾驶员的压力水平严重影响驾驶行为,因此与驾驶安全问题有关。然而,目前的证据还远远不足以解释在特定场景下通勤驾驶时,私人司机的压力水平是否会受到影响,为什么会受到影响,以及如何缓解他们的压力水平。本研究旨在识别和分析在不同场景(晴朗或降雪天气条件)下通勤驾驶时造成司机压力水平的因素。在 2020 年 10 月 1 日至 2022 年 1 月 31 日期间的工作日,从中国哈尔滨市六个不同地点的商业区收集了 985 名私人司机的问卷数据。在自然驾驶研究(NDS)数据库的基础上,设计了一份7个项目的问卷,供参与者自我报告在各种场景下的驾驶压力水平,该问卷由感知压力量表(PSS)的缩短版改编而成。结果显示,在雪天条件下,参与者的压力水平明显增加,尤其是紧张和压力感,以及无法控制到达时间,这表明参与者对通勤时间的认知偏差高度增加可能是关键原因。分层线性回归模型的结果表明,通过参与者的社会人口学特征、驾驶经验、通勤驾驶和对通勤时间的认知偏差,可以预测总体压力得分。这种关联与通勤时间差距的关系明显最为密切,尤其是在雪天条件下。此外,这些结果还提出了一项建议,即纠正对通勤时间的认知偏差可以缓解参与者的压力水平。提醒信息的影响支持了这一建议。在晴朗天气条件下,通勤驾驶时每隔 10 分钟发送一次提醒信息,而在雪天条件下每隔 5 分钟发送一次提醒信息,参与者的压力水平明显降低。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Correcting the Cognitive Bias for Commuting Time to Relieve the Driving Stress Level in Snow Weather Condition: A Naturalistic Driving Study in Harbin, China

As a negative emotion, professional drivers’ stress levels significantly affected driving behavior and thus were related to driving safety issues. Nevertheless, current evidence fell considerably short of explaining whether and why private drivers’ stress levels might be influenced while commuting driving in a specific scenario and how to relieve their stress levels. This study aimed to identify and analyze the contributing factors of the drivers’ stress levels while commuting driving in various scenarios (clear or snow weather conditions). On weekdays between 1st October 2020 and 31st January 2022, the questionnaire data from a sample of 985 private drivers were collected from six different locations of business districts in Harbin, China. Based on the naturalistic driving study (NDS) database, a 7-item questionnaire was designed for participants to self-report their driving stress levels in various scenarios, which was generated from the shortened and adapted version of the Perceived Stress Scale (PSS). The results showed that participants’ stress levels had significantly increased in snow weather conditions, especially nervous and stressed feeling, and unable to control the arrival time, which indicated that participants’ highly increased cognitive bias for commuting time could be the critical reason. The results of hierarchical linear regression models indicated that overall stress scores could be predicted through participants’ sociodemographic characteristics, driving experience, commuting driving, and cognitive bias for commuting time. Such an association was significantly strongest with commuting time gaps, especially in snow weather conditions. In addition, a recommendation was derived from these results that correcting the cognitive bias for commuting time could relieve participants’ stress levels. The implication of the reminder message supported this recommendation. The participants’ stress levels were reduced significantly after providing a reminder message every 10 mins while commuting driving in clear weather conditions and every 5 mins in snow weather conditions.

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来源期刊
Journal of Advanced Transportation
Journal of Advanced Transportation 工程技术-工程:土木
CiteScore
5.00
自引率
8.70%
发文量
466
审稿时长
7.3 months
期刊介绍: The Journal of Advanced Transportation (JAT) is a fully peer reviewed international journal in transportation research areas related to public transit, road traffic, transport networks and air transport. It publishes theoretical and innovative papers on analysis, design, operations, optimization and planning of multi-modal transport networks, transit & traffic systems, transport technology and traffic safety. Urban rail and bus systems, Pedestrian studies, traffic flow theory and control, Intelligent Transport Systems (ITS) and automated and/or connected vehicles are some topics of interest. Highway engineering, railway engineering and logistics do not fall within the aims and scope of JAT.
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