Revealing driver psychophysiological response to emergency braking in distracted driving based on field experiments
Journal article, 2022

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.

Driver distraction

Psychophysiological

Mobile phones

Psychophysiological measure

Emergency braking

Response time

Author

Ying Li

Changan University

Li Zhao

University of Nebraska - Lincoln

Kun Gao

Transportgruppen

Yisheng An

Changan University

Jelena Andric

Volvo Group

Journal of Intelligent and Connected Vehicles

23999802 (eISSN)

Vol. 5 3 270-282

Subject Categories

Infrastructure Engineering

Applied Psychology

Vehicle Engineering

DOI

10.1108/JICV-06-2022-0024

More information

Latest update

1/3/2024 9