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Psychophysiological responses to takeover requests in conditionally automated driving

dc.contributor.authorDu, Na
dc.contributor.authorYang, X. Jessie
dc.contributor.authorZhou, Feng
dc.date.accessioned2020-09-29T16:01:44Z
dc.date.available2020-09-29T16:01:44Z
dc.date.issued2020-09-23
dc.identifier.urihttps://hdl.handle.net/2027.42/162593
dc.description.abstractIn 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.sponsorshipUniversity of Michigan Mcityen_US
dc.language.isoen_USen_US
dc.rightsAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectHuman-automation interaction, Automated driving, Transition of control, Psychophysiological measuresen_US
dc.titlePsychophysiological responses to takeover requests in conditionally automated drivingen_US
dc.typeArticleen_US
dc.subject.hlbsecondlevelIndustrial and Operations Engineering
dc.subject.hlbtoplevelEngineering
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumUniversity of Michigan, Dearbornen_US
dc.contributor.affiliationumUniversity of Michigan, Ann Arboren_US
dc.contributor.affiliationumcampusDearbornen_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/162593/1/AAP_physiological_responses_HF_template.pdfen_US
dc.identifier.sourceAccident Analysis & Preventionen_US
dc.identifier.orcidhttps://orcid.org/0000-0001-6123-073Xen_US
dc.description.depositorSELFen_US
dc.identifier.name-orcidZhou, Feng; 0000-0001-6123-073Xen_US
dc.owningcollnameIndustrial and Manufacturing Systems Engineering (IMSE, UM-Dearborn)


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