Literature DB >> 33128991

Psychophysiological responses to takeover requests in conditionally automated driving.

Na Du1, X Jessie Yang1, Feng Zhou2.   

Abstract

In SAE Level 3 automated driving, taking over control from automation raises significant safety concerns because drivers out of the vehicle control loop have difficulty negotiating takeover transitions. Existing studies on takeover transitions have focused on drivers' behavioral responses to takeover requests (TORs). As a complement, this exploratory study aimed to examine drivers' psychophysiological responses to TORs as a result of varying non-driving-related tasks (NDRTs), traffic density and TOR lead time. A total number of 102 drivers were recruited and each of them experienced 8 takeover events in a high fidelity fixed-base driving simulator. Drivers' gaze behaviors, heart rate (HR) activities, galvanic skin responses (GSRs), and facial expressions were recorded and analyzed during two stages. First, during the automated driving stage, we found that drivers had lower heart rate variability, narrower horizontal gaze dispersion, and shorter eyes-on-road time when they had a high level of cognitive load relative to a low level of cognitive load. Second, during the takeover transition stage, 4 s lead time led to inhibited blink numbers and larger maximum and mean GSR phasic activation compared to 7 s lead time, whilst heavy traffic density resulted in increased HR acceleration patterns than light traffic density. Our results showed that psychophysiological measures can indicate specific internal states of drivers, including their workload, emotions, attention, and situation awareness in a continuous, non-invasive and real-time manner. The findings provide additional support for the value of using psychophysiological measures in automated driving and for future applications in driver monitoring systems and adaptive alert systems.
Copyright © 2020 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Automated driving; Human–automation interaction; Psychophysiological measures; Transition of control

Mesh:

Year:  2020        PMID: 33128991     DOI: 10.1016/j.aap.2020.105804

Source DB:  PubMed          Journal:  Accid Anal Prev        ISSN: 0001-4575


  2 in total

1.  Exploring Physiological Signal Responses to Traffic-Related Stress in Simulated Driving.

Authors:  Pamela Zontone; Antonio Affanni; Alessandro Piras; Roberto Rinaldo
Journal:  Sensors (Basel)       Date:  2022-01-26       Impact factor: 3.576

2.  Gender differences in professional drivers' fatigue level measured with BAlert mobile app: A psychophysiological, time efficient, accessible, and innovative approach to fatigue management.

Authors:  Ricardo De La Vega; Hector Anabalon; Kyran Tannion; Helena Purto; Cristian Jara D
Journal:  Front Psychol       Date:  2022-08-01
  2 in total

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