How internal and external risks affect the relationships between trust and driver behavior in automated driving systems
dc.contributor.author | Azevedo Sá, Hebert | |
dc.contributor.author | Zhao, Huajing | |
dc.contributor.author | Esterwood, Connor | |
dc.contributor.author | Yang, Xi Jessie | |
dc.contributor.author | Tilbury, Dawn | |
dc.contributor.author | Robert, Lionel + "Jr" | |
dc.date.accessioned | 2021-01-09T20:15:28Z | |
dc.date.available | 2021-01-09T20:15:28Z | |
dc.date.issued | 2021-01-09 | |
dc.identifier.citation | Azevedo-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.uri | https://hdl.handle.net/2027.42/164966 | |
dc.identifier.uri | https://doi.org/10.1016/j.trc.2021.102973 | |
dc.description.abstract | Automated 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.sponsorship | This 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.iso | en_US | en_US |
dc.publisher | Transportation Research Part C: Emerging Technologies | en_US |
dc.subject | Trust | en_US |
dc.subject | Semi-automated Driving | en_US |
dc.subject | Human-Automation Interaction | en_US |
dc.subject | Human-Automation Teaming | en_US |
dc.subject | Risk | en_US |
dc.subject | Automated driving systems | en_US |
dc.subject | self-driving car | en_US |
dc.subject | non-driving-related tasks | en_US |
dc.subject | Automated Vehicles | en_US |
dc.subject | Automated Driving | en_US |
dc.subject | Vehicles | en_US |
dc.subject | automotive | en_US |
dc.subject | SAE J3016 standard | en_US |
dc.subject | Automated Driving trust | en_US |
dc.subject | driving | en_US |
dc.subject | Automated Navigation Virtual Environment Laboratory | en_US |
dc.subject | Pupil Lab’s Mobileye | en_US |
dc.subject | control | en_US |
dc.subject | driving risk | en_US |
dc.subject | driving visibility | en_US |
dc.subject | unreliable Automated Vehicles | en_US |
dc.subject | simulated driving environment | en_US |
dc.subject | low visibility | en_US |
dc.subject | intelligent machines | en_US |
dc.subject | human car interaction | en_US |
dc.subject | human factors | en_US |
dc.subject | human factors engineering | en_US |
dc.subject | autonomous vehicles | en_US |
dc.subject | unmanned vehicles | en_US |
dc.subject | unmanned ground vehicles | en_US |
dc.title | How internal and external risks affect the relationships between trust and driver behavior in automated driving systems | en_US |
dc.type | Article | en_US |
dc.subject.hlbsecondlevel | Information and Library Science | |
dc.subject.hlbtoplevel | Social Sciences | |
dc.description.peerreviewed | Peer Reviewed | en_US |
dc.contributor.affiliationum | Information, School of | en_US |
dc.contributor.affiliationum | College of Engineering | en_US |
dc.contributor.affiliationother | University of California, Los Angeles | en_US |
dc.contributor.affiliationumcampus | Ann Arbor | en_US |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/164966/1/Azevedo-Sa et al. 2021 [accepted post].pdf | |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/164966/3/Azevedo-Sa et al. 2021.pdf | en |
dc.identifier.doi | 10.1016/j.trc.2021.102973 | |
dc.identifier.source | Transportation Research Part C: Emerging Technologies | en_US |
dc.identifier.orcid | 0000-0002-1410-2601 | en_US |
dc.description.depositor | SELF | en_US |
dc.identifier.name-orcid | Robert, Lionel P.; 0000-0002-1410-2601 | en_US |
dc.owningcollname | Information, School of (SI) |
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