Analytical study to find the impacts of using a mobile phone on driver's inattentions while driving – A case study of Lahore

Jamil, Arslan; Tabassum, Saadia; Younis, Muhammad Waqas; Khan, Ammad Hassan; Rehman, Zia ur; Sanaullah, Irum

doi:10.1016/j.aap.2021.106132

Cited by 7 publications

(1 citation statement)

References 30 publications

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“…Past studies associated with measuring the impact of distracted driving on safety can be categorized into three types, including data analysis (Peng and Boyle, 2012; Qin et al , 2019; Jamil et al , 2021), driving simulator studies (Nowosielski et al , 2018; Xu and Lin, 2018; Arkonac et al , 2019; Zhang et al , 2019; Baldo et al , 2020) and field studies (Dingus et al , 2016; Ma et al , 2018; Arvin et al , 2019; Hernández-Rojas et al , 2019; Arvin and Khattak, 2020; Gao et al , 2021). Due to driving simulation providing a low-cost method for driver behavior data collection, most distracted driving studies were conducted in a simulator environment.…”

Section: Introductionmentioning

confidence: 99%

Revealing driver psychophysiological response to emergency braking in distracted driving based on field experiments

Zhao

Gao

et al. 2022

JICV

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Purpose The purpose of this paper is to characterize distracted driving by quantifying the response time and response intensity to an emergency stop using the driver’s physiological states. Design/methodology/approach Field tests with 17 participants were conducted in the connected and automated vehicle test field. All participants were required to prioritize their primary driving tasks while a secondary nondriving task was asked to be executed. Demographic data, vehicle trajectory data and various physiological data were recorded through a biosignalsplux signal data acquisition toolkit, such as electrocardiograph for heart rate, electromyography for muscle strength, electrodermal activity for skin conductance and force-sensing resistor for braking pressure. Findings This study quantified the psychophysiological responses of the driver who returns to the primary driving task from the secondary nondriving task when an emergency occurs. The results provided a prototype analysis of the time required for making a decision in the context of advanced driver assistance systems or for rebuilding the situational awareness in future automated vehicles when a driver’s take-over maneuver is needed. Originality/value The hypothesis is that the secondary task will result in a higher mental workload and a prolonged reaction time. Therefore, the driver states in distracted driving are significantly different than in regular driving, the physiological signal improves measuring the brake response time and distraction levels and brake intensity can be expressed as functions of driver demographics. To the best of the authors’ knowledge, this is the first study using psychophysiological measures to quantify a driver’s response to an emergency stop during distracted driving.

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