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Cited 3 time in webofscience Cited 3 time in scopus
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Understanding drivers’ situation awareness in highly automated driving using SAGAT, SART, and eye-tracking data

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dc.contributor.authorKim, Young Woo-
dc.contributor.authorYoon, Sol Hee-
dc.date.accessioned2025-02-17T08:00:08Z-
dc.date.available2025-02-17T08:00:08Z-
dc.date.issued2025-02-
dc.identifier.issn1369-8478-
dc.identifier.issn1873-5517-
dc.identifier.urihttps://scholarworks.gnu.ac.kr/handle/sw.gnu/77160-
dc.description.abstractRapid and accurately forming situation awareness (SA) is essential when transitioning from autonomous to manual driving. This study examines how drivers’ SA is developed when a takeover request (TOR) is issued and compares SA levels across different environmental and time conditions. A laboratory experiment with 39 participants was performed to analyze the SA, perceived safety, and gaze behavior with different levels of traffic density (high and low), road type (urban and highway), and time budget factor (3 s, 10 s, free). The free time budget factor was determined by assessing the participants’ response times indicating when they perceived having acquired sufficient SA. The results revealed significant effects of traffic density, road type, and time budget on the Situation Awareness Global Assessment Technique (SAGAT), Situational Awareness Rating Technique (SART), and perceived safety. Post-hoc results for time budget factors revealed significant differences based on the SAGAT score, with the 10-second condition exhibiting the highest score. For the SART and perceived safety scores, the 3-second condition was significantly lower whereas no significant difference was observed between the free and 10-second conditions and the mean response time for the free condition ranged from 10–13 s, with the longest duration in high-traffic and urban conditions. Participants gazed at different AOI when provided with a longer lead time whereas in short lead time conditions, their gaze primarily focused on the front window. These results suggest that drivers develop SA differently based on time constraints, and environmental factors. This study provides valuable insights for developing and implementing autonomous systems, contributing to safer and more efficient transitions between automated and manual driving modes. © 2025-
dc.format.extent14-
dc.language영어-
dc.language.isoENG-
dc.publisherPergamon Press Ltd.-
dc.titleUnderstanding drivers’ situation awareness in highly automated driving using SAGAT, SART, and eye-tracking data-
dc.typeArticle-
dc.publisher.location영국-
dc.identifier.doi10.1016/j.trf.2025.02.003-
dc.identifier.scopusid2-s2.0-85217012541-
dc.identifier.wosid001424894400001-
dc.identifier.bibliographicCitationTransportation Research Part F: Traffic Psychology and Behaviour, v.109, pp 1437 - 1450-
dc.citation.titleTransportation Research Part F: Traffic Psychology and Behaviour-
dc.citation.volume109-
dc.citation.startPage1437-
dc.citation.endPage1450-
dc.type.docTypeArticle-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassssci-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaPsychology-
dc.relation.journalResearchAreaTransportation-
dc.relation.journalWebOfScienceCategoryPsychology, Applied-
dc.relation.journalWebOfScienceCategoryTransportation-
dc.subject.keywordPlusTAKEOVER PERFORMANCE-
dc.subject.keywordPlusTIME-
dc.subject.keywordPlusSCENARIOS-
dc.subject.keywordPlusREQUEST-
dc.subject.keywordPlusCAR-
dc.subject.keywordAuthorGaze behavior-
dc.subject.keywordAuthorHighly Automated Driving (HAD)-
dc.subject.keywordAuthorSituation Awareness (SA)-
dc.subject.keywordAuthorSituation Awareness Global Assessment Technique (SAGAT)-
dc.subject.keywordAuthorSituation Awareness Rating Technique (SART)-
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