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How internal and external risks affect the relationships between trust and driver behavior in automated driving systems

dc.contributor.authorAzevedo Sá, Hebert
dc.contributor.authorZhao, Huajing
dc.contributor.authorEsterwood, Connor
dc.contributor.authorYang, Xi Jessie
dc.contributor.authorTilbury, Dawn
dc.contributor.authorRobert, Lionel + "Jr"
dc.date.accessioned2021-01-09T20:15:28Z
dc.date.available2021-01-09T20:15:28Z
dc.date.issued2021-01-09
dc.identifier.citationAzevedo-Sa, H., Zhao, H., Jayaraman, S., Esterwood, C., Yang, X.J., Tilbury, D. Robert, L. P. (2021). How Internal and External Risk Impacts the Relationships between Trust and Diver Behavior in Automated Driving Systems, Transportation Research Part C: Emerging Technologies, 123, https://doi.org/10.1016/j.trc.2021.102973.en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/164966
dc.identifier.urihttps://doi.org/10.1016/j.trc.2021.102973
dc.description.abstractAutomated driving systems (ADSs) allow vehicles to engage in self-driving under specific conditions. Along with the potential safety benefits, the increase in productivity through non-driving-related tasks (NDRTs) is often cited as a motivation behind the adoption of ADSs. Although advances have been made in understanding both the promotion of ADS trust and its impact on NDRT performance, the influence of risk remains largely understudied. To fill this gap, we conducted a within-subjects experiment with 37 licensed drivers using a simulator. Internal risk was manipulated by ADS reliability and external risk by visibility, producing a 2 (ADS reliability) × 2 (visibility) design. The results indicate that high reliability increases ADS trust and further enhances the positive impact of ADS trust on NDRT performance, while low visibility reduces the negative impact of ADS trust on driver monitoring. Results also suggest that trust increases over time if the system is reliable and that visibility did not have a significant impact on ADS trust. These findings are important for the design of intelligent ADSs that can respond to drivers’ trusting behaviors.en_US
dc.description.sponsorshipThis research was supported in part by the Automotive Research Center at the University of Michigan, with funding from government contract Department of the Army W56HZV14-2-0001 through the U.S. Army Tank Automotive Research, Development, and Engineering Center (TARDEC) and in part by the National Science Foundation. The authors acknowledge and greatly appreciate the guidance of Victor Paul (TARDEC), Ben Haynes (TARDEC), and Jason Metcalfe (ARL) in helping design the study. The authors would also like to thank Quantum Signal, LLC, for providing its ANVEL software and invaluable development support.en_US
dc.language.isoen_USen_US
dc.publisherTransportation Research Part C: Emerging Technologiesen_US
dc.subjectTrusten_US
dc.subjectSemi-automated Drivingen_US
dc.subjectHuman-Automation Interactionen_US
dc.subjectHuman-Automation Teamingen_US
dc.subjectRisken_US
dc.subjectAutomated driving systemsen_US
dc.subjectself-driving caren_US
dc.subjectnon-driving-related tasksen_US
dc.subjectAutomated Vehiclesen_US
dc.subjectAutomated Drivingen_US
dc.subjectVehiclesen_US
dc.subjectautomotiveen_US
dc.subjectSAE J3016 standarden_US
dc.subjectAutomated Driving trusten_US
dc.subjectdrivingen_US
dc.subjectAutomated Navigation Virtual Environment Laboratoryen_US
dc.subjectPupil Lab’s Mobileyeen_US
dc.subjectcontrolen_US
dc.subjectdriving risken_US
dc.subjectdriving visibilityen_US
dc.subjectunreliable Automated Vehiclesen_US
dc.subjectsimulated driving environmenten_US
dc.subjectlow visibilityen_US
dc.subjectintelligent machinesen_US
dc.subjecthuman car interactionen_US
dc.subjecthuman factorsen_US
dc.subjecthuman factors engineeringen_US
dc.subjectautonomous vehiclesen_US
dc.subjectunmanned vehiclesen_US
dc.subjectunmanned ground vehiclesen_US
dc.titleHow internal and external risks affect the relationships between trust and driver behavior in automated driving systemsen_US
dc.typeArticleen_US
dc.subject.hlbsecondlevelInformation and Library Science
dc.subject.hlbtoplevelSocial Sciences
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumInformation, School ofen_US
dc.contributor.affiliationumCollege of Engineeringen_US
dc.contributor.affiliationotherUniversity of California, Los Angelesen_US
dc.contributor.affiliationumcampusAnn Arboren_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/164966/1/Azevedo-Sa et al. 2021 [accepted post].pdf
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/164966/3/Azevedo-Sa et al. 2021.pdfen
dc.identifier.doi10.1016/j.trc.2021.102973
dc.identifier.sourceTransportation Research Part C: Emerging Technologiesen_US
dc.identifier.orcid0000-0002-1410-2601en_US
dc.description.depositorSELFen_US
dc.identifier.name-orcidRobert, Lionel P.; 0000-0002-1410-2601en_US
dc.owningcollnameInformation, School of (SI)


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