Psychophysiological responses to takeover requests in conditionally automated driving

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dc.contributor.author Du, Na
dc.contributor.author Yang, X. Jessie
dc.contributor.author Zhou, Feng
dc.date.accessioned 2020-09-29T16:01:44Z
dc.date.available 2020-09-29T16:01:44Z
dc.date.issued 2020-09-23
dc.identifier.uri http://hdl.handle.net/2027.42/162593
dc.description.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, 4s lead time led to inhibited blink numbers and larger maximum and mean GSR phasic activation compared to 7s 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. en_US
dc.description.sponsorship University of Michigan Mcity en_US
dc.language.iso en_US en_US
dc.rights Attribution 4.0 International *
dc.rights.uri http://creativecommons.org/licenses/by/4.0/ *
dc.subject Human-automation interaction, Automated driving, Transition of control, Psychophysiological measures en_US
dc.title Psychophysiological responses to takeover requests in conditionally automated driving en_US
dc.type Article en_US
dc.subject.hlbsecondlevel Industrial and Operations Engineering
dc.subject.hlbtoplevel Engineering
dc.description.peerreviewed Peer Reviewed en_US
dc.contributor.affiliationum University of Michigan, Dearborn en_US
dc.contributor.affiliationum University of Michigan, Ann Arbor en_US
dc.contributor.affiliationumcampus Dearborn en_US
dc.description.bitstreamurl http://deepblue.lib.umich.edu/bitstream/null/1/AAP_physiological_responses_HF_template.pdf
dc.identifier.source Accident Analysis & Prevention en_US
dc.identifier.orcid https://orcid.org/0000-0001-6123-073X en_US
dc.description.depositor SELF en_US
dc.identifier.name-orcid Zhou, Feng; 0000-0001-6123-073X en_US
dc.owningcollname Industrial and Manufacturing Systems Engineering (IMSE, UM-Dearborn)
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