The motivation of this research is to explore the contributing factors of driving distraction and compare the contributing factors for three typical distracted driving behaviours: drinking water, answering a phone and using mobile phone application (APP) while driving. An online survey including a driving behaviour scale and the Theory of Planned Behaviour Questionnaire (TPB Questionnaire) was conducted to obtain data related to these driving distractions. An integral structural equation model based on the Theory of Planned Behaviour (TPB) was established to explain the factors causing three typical distracted behaviours, and the causes of differences for three typical distracted behaviours were compared. The result shows that the attitudes and perceived behaviour control are the main factors causing distracted behaviours, and the subjective norm has a significant impact on answering a phone while driving. The occurrence of a distracted driving behaviour is the consequence of behaviour intention and perceived behaviour control. These conclusions provide insights for implementing behaviour modification and traffic laws education.
Beanland V, Fitzharris M, Young KL. Driver inattention and driver distraction in serious casualty crashes: Data from the Australian National Crash In-depth Study. Accident Analysis & Prevention. 2013;54: 99-107.
Carney C, Harland, KK, McGehee DV. Using event-triggered naturalistic data to examine the prevalence of teen driver distractions in rear-end crashes. Journal of Safety Research. 2016;57: 47-52.
Prat F, Planes M, Gras ME. An observational study of driving distractions on urban roads in Spain. Accident Analysis & Prevention. 2015;74: 8-16.
Haque MM, Washington S. The impact of mobile phone distraction on the braking behaviour of young drivers: a hazard-based duration model. Transportation Research Part C: Emerging Technologies. 2015;50: 13-27.
Dozza M, Flannagan CA, Sayer JR. Real-world effects of using a phone while driving on lateral and longitudinal control of vehicles. Journal of Safety Research. 2015;55: 81-87.
Saifuzzaman M, Haque MM, Zheng Z, Washington S. Impact of mobile phone use on car-following behaviour of young drivers. Accident Analysis & Prevention. 2015;82:10-19.
Huth V, Sanchez Y, Brusque C. Driver’s phone use at red traffic lights: A roadside observation study comparing calls and visual–manual interactions. Accident Analysis & Prevention. 2015;74: 42-48.
Xiong H, Narayanaswamy P, Bao S. How do drivers behave during indecision zone maneuvers?. Accident Analysis & Prevention. 2015;96: 274-279.
Severely Punished Heavy Penalties "bow driver". [homepage on the Internet]. c2017 [updated 2017 May 5; cited 2017 May 9]. Available from: http://mini.eastday.com/a/170502090747672.html
Ajzen I. The theory of planned behaviour. Organizational Behaviour and Human Decision Processes. 1991;50(2): 179-211.
Holland C, Hill R. The effect of age, gender and driver status on pedestrians’ intentions to cross the road in risky situations. Accident Analysis & Prevention. 2007;39(2): 224-237.
Walsh SP, White KM, Hyde MK. Dialing and driving: Factors influencing intentions to use a mobile phone while driving. Accident Analysis & Prevention. 2008;40(6): 1893-1900.
Zhou R, Wu C, Rau PP. Young driving learners' intention to use a handheld or hands-free mobile phone when driving. Transportation Research Part F: Traffic Psychology and Behaviour. 2006;12(3): 208-217.
Zhou R, Rau PP, Zhang W. Mobile phone use while driving: Predicting driver’s answering intentions and compensatory decisions. Safety Science. 2012;50(1): 138-149.
Chen HYW, Donmez B, Hoekstra-Atwood L, Marulanda S. Self-reported engagement in driver distraction: An application of the Theory of Planned Behaviour. Transportation Research Part F: Traffic Psychology and Behaviour. 2016;38: 151-163.
Xiao Y. Analyzing and modeling of the influence of driving distraction on traffic safety and traffic efficiency. Tsinghua University; 2016.
Shi J, Bai Y, Ying X. Aberrant driving behaviours: A study of drivers in Beijing. Accident Analysis & Prevention. 2010;42(4): 1031-1040.
Wu J, Xu H. The influence of road familiarity on distracted driving activities and driving operation using naturalistic driving study data. Transportation Research Part F: Traffic Psychology and Behaviour. 2018;52: 75-85.
Shi J, Liu M. Impacts of differentiated per-lane speed limit on lane changing behaviour: A driving simulator-based study. Transportation Research Part F: Traffic Psychology and Behaviour. 2019;60: 93-104.
Charlton JL, Catchlove M, Scully M, Koppel S, Newstead S. Older driver distraction: a naturalistic study of behaviour at intersections. Accident Analysis & Prevention. 2013;58: 271-278.
Trisko J, Ferraro FR. Younger and Older adults’ opinions on driver distractions and potential cellular phone Laws. Psychological Record. 2014;64(3): 503-507.
Wu J, Yan X, Radwan E. Discrepancy analysis of driving performance of taxi drivers and non-professional drivers for red-light running violation and crash avoidance at intersections. Accident Analysis & Prevention. 2016;91: 1-9.
Lin PC, Chen SI. The effects of gender differences on the usability of automotive on-board navigation systems – A comparison of 2D and 3D display. Transportation Research Part F: Traffic Psychology and Behaviour. 2013;19: 40-51.
Papadakaki M, Tzamalouka G, Gnardellis C, Lajunen TJ, Chliaoutakis J. Driving performance while using a mobile phone: a simulation study of Greek professional drivers. Transportation Research Part F: Traffic Psychology and Behaviour. 2016;38: 164-170.
Cohen AA, Lemish D. Real time and recall measures of mobile phone use: Some methodological concerns and empirical applications. New Media & Society. 2003;5: 167-183.
Podsakoff PM, Organ DW. Self-report in organizational research: problems and prospects. Journal of Management. 1986;12: 531-544.
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