The Effect Of Mobile Phone Use While Driving On Response Time: Driving Simulator Study
Engineering and Technology Journal,
2021, Volume 39, Issue 12, Pages 1806-1813
AbstractMobile phone use is one of the most common daily tasks and this is normal, however, this task could be problematic while driving. The use of mobile phones while driving has become a major cause of road accidents and poses a threat to public health. This study investigated the effect of mobile phone usage while driving on response time, as it investigated four mobile phone tasks (hands-free calling, hand calls, reading text messages, and sending text messages) in addition to basic driving. A total of 42 participants, ranging in age from (19 to 55), with a mean age (mean = 33.14, SD = 10.26) participated in the driving simulation at the University of Technology and all participants performed five tasks. The participants had to interact with voice commands by performing the throttle maneuver. The results concluded with a delay in response, which means an increase in cognitive reaction time when using a mobile phone compared to basic driving. It has also been found that the response time increases with the age of drivers.
- Using driving simulator to assess mobile phones distraction on driving performance.
- The response time is increased while using smart phones while driving.
- The results indicate that the response time increases with task difficulty.
- Young participants are less affected when compared with older people.
 M. Zhu, T. M. Rudisill, K. J. Rauscher, D. M. Davidov, and J. Feng, Risk perceptions of cellphone use while driving: Results from a Delphi survey, Int. J. Environ. Res. Public Health, 15 (2018), doi: 10.3390/ijerph15061074.
 Global status report on road safety (2018) summary, (2018). Accessed: Apr. 17, (2021). [Online]. Available: http://apps.who.int/bookorders.
 A. Benedetto, A. Calvi, and F. D’Amico, Effects of mobile telephone tasks on driving performance: A driving simulator study, Adv. Transp. Stud. 41 (2012) 29–44, doi: 10.4399/97888548465863.
 C. Huisingh, R. Griffin, and G. McGwin, The Prevalence of Distraction Among Passenger Vehicle Drivers: A Roadside Observational Approach Traffic Inj. Prev., 16 (2015) 140–146, doi: 10.1080/15389588.2014.916797.
 Geneva, A Growing problem of driver distraction 2011 who library cataloguing-in-publication data contentsts, World Heal. Organ.
 C. Hallett, A. Lambert, and M. A. Regan, Text messaging amongst New Zealand drivers: Prevalence and risk perception, Transp. Res. Part F Traffic Psychol. Behav., 15 (2012) 261–271, doi: 10.1016/j.trf.2011.12.002.
 N. C. for S. and Analysis, Distracted driving in fatal crashes, 2017. US Department of Transportation, National Highway Traffic Safety …, (2019).
 P. Choudhary and N. R. Velaga, Modelling driver distraction effects due to mobile phone use on reaction time, Transp. Res. Part C Emerg. Technol., 77 (2017) 351–365, doi: 10.1016/j.trc.2017.02.007.
 M. M. Haque and S. Washington, A parametric duration model of the reaction times of drivers distracted by mobile phone conversations, Accid. Anal. Prev., 62 (2014) 42–53, doi: 10.1016/j.aap.2013.09.010.
 W. Consiglio, P. Driscoll, M. Witte, and W. P. Berg, Effect of cellular telephone conversations and other potential interference on reaction time in a braking response, Accid. Anal. Prev., 35 (2003) 495–500, doi: 10.1016/S0001-4575(02)00027-1.
 J. Törnros and A. Bolling, Mobile phone use - effects of conversation on mental workload and driving speed in rural and urban environments, Transp. Res. Part Of Traffic Psychol. Behav., 9(2006) 298–306, doi: 10.1016/j.trf.2006.01.008.
 A. Subhi, Estimating the passenger car eqaivalent (PCE) for different type of vehicles on the signalized Intersections, Eng. Technol. J., 31 (2013), Accessed: May 29, (2021). [Online]. Available: https://www.iasj.net/iasj/article/83893.
 A. S. Abdul-Jabbar, Studying Alternatives and Traffic Solutions to Change an Existing Three Legs intersection to an interchange, Eng. Technol. J., 31 (2013), Accessed: May 29,( 2021). [Online]. Available: https://www.iasj.net/iasj/article/71413.
 S. S. Mahmood and L. J. Saud, An efficient approach for detecting and classifying moving vehicles in a video based monitoring system, Eng. Technol. J., 38 (2020) Accessed: May 29, (2021). [Online]. Available: https://www.iasj.net/iasj/article/194690.
 P. Droździel, S. Tarkowski, I. Rybicka, and R. Wrona, Drivers ’reaction time research in the conditions in the real traffic, Open Eng., 10 (2020) 35–47, doi: 10.1515/eng-2020-0004.
 A. Urs and H. R. Urs, Effect of cellphone conversation and text messaging on driver behaviour: distracted driving,( 2016).
 M. F. Lesch and P. A. Hancock, Driving performance during concurrent cell-phone use: Are drivers aware of their performance decrements?, Accid. Anal. Pr 36 (2004) 471–480, doi: 10.1016/S0001-4575(03)00042-3.
 I. Spyropoulou and M. Linardou, Modelling the effect of mobile phone use on driving behaviour considering different use modes, J. Adv. Transp., (2019), doi: 10.1155/2019/2196431.
 R. West, K. J. Murphy, M. L. Armilio, F. I. M. Craik, and D. T. Stuss, Lapses of intention and performance variability reveal age-related increases in fluctuations of executive control Brain Cogn., 49 (2002) 402–419.
 J. K. Caird, K. A. Johnston, C. R. Willness, M. Asbridge, and P. Steel, A meta-analysis of the effects of texting on driving, Accid. Anal. Prev., 71 (2014) 311–318, doi: 10.1016/j.aap.2014.06.005.
 C. V. Oramas, Effect of Cellphone Conversation and Text Messaging on Driver Behaviour: Distracted Driving, (2016).
 M. Green, ‘How long does it take to stop?’ Methodological Analysis of Driver Perception-Brake Times, Transp. Hum. Factors, 2 (2000) 195–216, doi: 10.1207/sthf0203_1.
 https://www.itp.gov.iq/ar/qanwn-rqm-8-lsnt-(2019) (accessed Apr. 21, (2021).
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