Volume 42 Issue 4
Aug.  2024
Turn off MathJax
Article Contents
WAN Ping, QIU Gangao, CHEN Peidong, MA Xiaofeng. A Model of Associations Between Expressions of Driving Anger and Inducements for Extreme Commuting Group[J]. Journal of Transport Information and Safety, 2024, 42(4): 154-163. doi: 10.3963/j.jssn.1674-4861.2024.04.017
Citation: WAN Ping, QIU Gangao, CHEN Peidong, MA Xiaofeng. A Model of Associations Between Expressions of Driving Anger and Inducements for Extreme Commuting Group[J]. Journal of Transport Information and Safety, 2024, 42(4): 154-163. doi: 10.3963/j.jssn.1674-4861.2024.04.017

A Model of Associations Between Expressions of Driving Anger and Inducements for Extreme Commuting Group

doi: 10.3963/j.jssn.1674-4861.2024.04.017
  • Received Date: 2024-04-19
    Available Online: 2024-11-25
  • The extreme commuting population (individuals with commuting time exceeding 60 minutes) is susceptible to driving anger due to prolonged and high-stress commuting environments, which can adversely affect traffic safety. This study focuses on the phenomenon of "road rage" among extreme commuters and develops a model to quantify the associations between driving anger expressions and driving anger inducements within this group. The driving anger scale for extreme commuting group (EC_DAS) and the driving anger expression inventory for extreme commuting group (EC_DAX) are designed and surveyed to a cohort of 450 commuters traveling between Yanjiao and Beijing, China. Based on the survey data, scales are revised through exploratory factor analysis and tests of reliability and validity. Next, a model of association between expressions of driving anger and inducements for extreme commuting group is developed with discourtesy, traffic obstructions, slow driving, extreme commuting, and illegal driving as exogenous latent variables, and use of the vehicle to express anger and verbal aggression as endogenous latent variables. The impact of these anger triggers on the expression of driving anger in the extreme commuting group is quantified using a structural equation model. The results are as follows: ①In the EC_DAS, the highest score is observed for slow driving (3.37), followed by extreme commuting (3.07), with illegal driving receiving the lowest score (2.95). In the EC_DAX, verbal aggression scored higher (2.99) than the use of the vehicle to express anger (2.90). ②The structural equation model exhibits a strong goodness of fit, whose results show that use of the vehicle to express anger and verbal aggression are significantly and positively influenced by driving anger inducements including discourtesy, traffic obstructions, slow driving, extreme commuting, and illegal driving. Moreover, it is noted that these factors explain a higher variance in verbal aggression (38%) than in use of the vehicle to express anger (37%). ③Additionally, slow driving, extreme commuting, and traffic obstructions emerge as the three most significant inducements of use of the vehicle to express anger, with standardized effect coefficient of 0.221, 0.169 and 0.162, respectively, while traffic obstructions, slow driving, and discourtesy are identified as the three most significant inducements of verbal aggressive, with standardized effect efficient of 0.215, 0.189, and 0.148, respectively. ④Gender and monthly income do not have significant impacts on anger levels under different driving inducements or anger expression. However, age is significantly negative-correlated with anger levels induced by discourtesy, traffic obstructions, and illegal driving. Driving experience is significantly negative-correlated with anger levels induced by extreme commuting, education level is significantly negative-correlated with anger levels induced by slow driving, and job position is significantly negative-correlated with anger levels induced by traffic obstructions.

     

  • loading
  • [1]
    黄欣然. 国土空间规划统领下的城市通勤优化路径探讨—基于《中国主要城市通勤监测报告》[J]. 城市建筑, 2024, 21 (10): 103-106, 131.

    HUANG X R. Discussion on the optimization path of urban commuting under the guidance of territorial spatial planning: based on the commuting monitoring report of major cities in China[J]. Urbanism and Architecture, 2024, 21(10): 103-106, 131. (in Chinese)
    [2]
    万平, 吴超仲, 林英姿, 等. 基于置信规则库的驾驶人愤怒情绪识别模型[J]. 交通运输系统工程与信息, 2015, 15(5): 96-102.

    WAN P, WU C Z, LIN Y Z, et al. A recognition model of driving anger based on belief rule base[J]. Journal of Transportation Systems Engineering and Information Technology, 2015, 15(5): 96-102. (in Chinese)
    [3]
    邓院昌, 金杰灵. 关于驾驶员"路怒症"的研究综述[J]. 重庆交通大学学报(自然科学版), 2018, 37(11): 105-111.

    DENG Y C, JIN J L. Review on driver's road rage[J]. Journal of Chongqing Jiaotong University(Natural Science), 2018, 37 (11): 105-111. (in Chinese)
    [4]
    DEFFENBACHER J L, OETTING E R, LYNCH R S. Development of a driving anger scale[J]. Psychological Reports, 1994, 74(1): 83-91. doi: 10.2466/pr0.1994.74.1.83
    [5]
    DEFFENBACHER J L, LYNCH R S, OETTING E R, et al. The driving anger expression inventory: a measure of how people express their anger on the road[J]. Behaviour Research and Therapy, 2002, 40(6): 717-737. doi: 10.1016/S0005-7967(01)00063-8
    [6]
    李琼, 汪勇杰, 陈文强, 等. 公交驾驶员组织认同感对驾驶愤怒的影响: 职业倦怠的中介作用[J]. 中国安全科学学报, 2022, 32(5): 8-13.

    LI Q, WANG Y J, CHEN W Q, et al. Impact of bus drivers'organizational identity on driving anger: mediating role of burnout[J]. China Safety Science Journal, 2022, 32(5): 8-13. (in Chinese)
    [7]
    FENG Z X, LEI Y W, LIU H C, et al. Driving anger in China: a case study on professional drivers[J]. Transportation Research Part F: Traffic Psychology and Behaviour, 2016, 42 (2): 255-266.
    [8]
    李圳. 驾驶愤怒现状及其对道路交通安全影响的研究[D]. 南京: 东南大学, 2018.

    LI Z. A study on epidemic status and influencing factors of driving anger and road traffic injuries[J]. Nanjing: Southeast University, 2018. (in Chinese)
    [9]
    雷虎. 愤怒情绪下的汽车驾驶行为特征及其对交通安全的影响研究[D]. 武汉: 武汉理工大学, 2011.

    LEI H. The characteristics of angry driving behaviors and its effects on traffic safety[D]. Wuhan: Wuhan University of Technology, 2011. (in Chinese)
    [10]
    SULLMAN M J M, STEPHENS A N, YONG M. Anger, aggression and road rage behaviour in Malaysian drivers[J]. Transportation Research Part F: Traffic Psychology and Behaviour, 2015, 29: 70-82.
    [11]
    HERRERO-FERNÁNDEZ D. Psychometric adaptation of the driving anger expression inventory in a Spanish sample: differences by age and gender[J]. Transportation Research Part F: Traffic Psychology and Behaviour, 2011, 14(4): 324-329.
    [12]
    刘洋, 陈红, 肖赟, 等. 货运驾驶员路怒情绪对愤怒表达行为的影响研究[J]. 交通运输工程与信息学报, 2023, 21 (3): 130-144.

    LIU Y, CHEN H, XIAO Y, et al. Influence of road rage on anger expression among freight drivers[J]. Journal of Transportation Engineering and Information, 2023, 21(3): 130-144. (in Chinese)
    [13]
    STANOJEVIĆ P, SULLMAN M J M, JOVANOVIĆ D, et al. The impact of police presence on angry and aggressive driving[J]. Accident Analysis & Prevention, 2018, 110: 93-100.
    [14]
    ZHANG T, CHAN A H S, ZHANG W. Dimensions of driving anger and their relationships with aberrant driving[J]. Accident Analysis & Prevention, 2015, 81: 124-133.
    [15]
    LI Z M, MAN S S, CHAN A H S, et al. Driving anger scale validation: relationship of driving anger with the aberrant driving behaviour of truck drivers[J]. Transportation Research Part F: Traffic Psychology and Behaviour, 2021, 81 (3): 364-372.
    [16]
    GE Y, QU W, ZHANG Q, et al. Psychometric adaptation of the driving anger expression inventory in a Chinese sample[J]. Transportation Research Part F: Traffic Psychology and Behaviour, 2015, 33(2): 75-86.
    [17]
    李佳硕, 郑展骥, 顾欣, 等. 考虑快速路交织区驾驶人强行变道行为的交通冲突机理分析[J]. 交通信息与安全, 2023, 41(3): 1-11. doi: 10.3963/j.jssn.1674-4861.2023.03.001

    LI J S, ZHENG Z J, GU X, et al. An analysis of the mechanism of traffic conflicts considering risky lane-changing behavior in weaving sections of expressways[J]. Journal of Transport Information and Safety, 2023, 41(3): 1-11. (in Chinese) doi: 10.3963/j.jssn.1674-4861.2023.03.001
    [18]
    袁野, 萧文龙, 于媛, 等. 结构方程模型的应用准则: CB-SEM和PLS-SEM研究范式的比较与启示[J]. 信息资源管理学报, 2023, 13(3): 6-22.

    YUAN Y, XIAO W L, YU Y, et al. Criteria of Structural Equation Modeling: comparisons and enlightenments of CB-SEM and PLS-SEM[J]. Journal of Information Resources Management, 2023, 13(3): 6-22. (in Chinese)
    [19]
    HASSAN Z. Impact of social, epistemic and conditional values on customer satisfaction and loyalty in automobile industry: a structural equation modelling[J]. Journal of Marketing and Consumer Behaviour in Emerging Markets, 2017, 5(1): 29-44.
    [20]
    MOHAMMED Z C, NGENO V, LAGAT C. Environmentally sustainable supply chain practices, organisation culture on firm performance: a mediation approach[J]. International Journal of Emerging Trends in Social Sciences, 2019, 6(2): 34-45.
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Figures(4)  / Tables(9)

    Article Metrics

    Article views (33) PDF downloads(7) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return