Comparing the Effects of False Alarms and Misses on Humans’ Trust in (Semi)Autonomous Vehicles
dc.contributor.author | Azevedo-Sa, Hebert | |
dc.contributor.author | Jayaraman, Suresh | |
dc.contributor.author | Esterwood, Connor | |
dc.contributor.author | Yang, X. Jessie | |
dc.contributor.author | Robert, Lionel + "Jr" | |
dc.contributor.author | Tilbury, Dawn | |
dc.date.accessioned | 2020-01-29T01:16:03Z | |
dc.date.available | 2020-01-29T01:16:03Z | |
dc.date.issued | 2020-01-28 | |
dc.identifier.citation | Azevedo-Sa, H., Jayaraman, S., Esterwood, C., Yang, X.J. and Robert, L. P. and Dawn M. Tilbury. 2020. Comparing the Effects of False Alarms and Misses on Humans’ Trust in (Semi)Autonomous Vehicles. In Companion of the 2020 ACM/IEEE International Conference on Human-Robot Interaction (HRI 2020), March 23 26, 2020, Cambridge, United Kingdom. ACM, New York, NY, USA. | en_US |
dc.identifier.uri | https://hdl.handle.net/2027.42/153524 | |
dc.description.abstract | Trust in automated driving systems is crucial for effective driver- (semi)autonomous vehicles interaction. Drivers that do not trust the system appropriately are not able to leverage its benefits. This study presents a mixed design user experiment where participants conducted a non-driving task while traveling in a simulated semi-autonomous vehicle with forward collision alarm and emergency braking functions. Occasionally, the system missed obstacles or provided false alarms.We varied these system error types as well as road shapes, and measured the effects of these variations on trust development. Results reveal that misses are more harmful to trust development than false alarms, and that these effects are strengthened by operation on risky roads. Our findings provide additional insight into the development of trust in automated driving systems, and are useful for the design of such technologies. | en_US |
dc.description.sponsorship | Automotive Research Center at the University of Michigan, through the U.S. Army CCDC/GVSC | en_US |
dc.language.iso | en_US | en_US |
dc.publisher | HRI 2020 | en_US |
dc.subject | Automated driving systems | en_US |
dc.subject | Trust | en_US |
dc.subject | Human-robot teaming | en_US |
dc.subject | Driving simulation | en_US |
dc.subject | automated driving system | en_US |
dc.subject | advance driving systems | en_US |
dc.subject | vehicle trust | en_US |
dc.subject | automated vehicles | en_US |
dc.subject | autonomous vehicles | en_US |
dc.subject | human automated vehicle interaction | en_US |
dc.subject | advanced driving systems | en_US |
dc.subject | false alarms | en_US |
dc.subject | Autonomous Navigation Virtual Environment Laboratory | en_US |
dc.subject | Semi-Autonomous Vehicles | en_US |
dc.subject | self driving cars | en_US |
dc.subject | trust in automation | en_US |
dc.subject | automated vehicle trust | en_US |
dc.subject | advance driving system trust | en_US |
dc.subject | autonomous vehicle trust | en_US |
dc.subject | human robot interaction | en_US |
dc.subject | overtrusting | en_US |
dc.title | Comparing the Effects of False Alarms and Misses on Humans’ Trust in (Semi)Autonomous Vehicles | en_US |
dc.type | Conference Paper | 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.affiliationum | Robotics Institute | en_US |
dc.contributor.affiliationumcampus | Ann Arbor | en_US |
dc.description.bitstreamurl | https://deepblue.lib.umich.edu/bitstream/2027.42/153524/1/Azevedo-Sa et al. 2020.pdf | |
dc.identifier.doi | https://doi.org/10.1145/3371382.3378371. | |
dc.identifier.source | Companion of the 2020 ACM/IEEE International Conference on Human-Robot Interaction | en_US |
dc.identifier.orcid | 0000-0002-1410-2601 | en_US |
dc.description.filedescription | Description of Azevedo-Sa et al. 2020.pdf : Mainfile | |
dc.identifier.name-orcid | Robert, Lionel P.; 0000-0002-1410-2601 | en_US |
dc.owningcollname | Information, School of (SI) |
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