{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,5]],"date-time":"2026-06-05T21:23:14Z","timestamp":1780694594997,"version":"3.54.1"},"reference-count":26,"publisher":"SAGE Publications","issue":"3","license":[{"start":{"date-parts":[[2012,2,29]],"date-time":"2012-02-29T00:00:00Z","timestamp":1330473600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Hum Factors"],"published-print":{"date-parts":[[2012,6]]},"abstract":"<jats:p>Objective: The aim of this study was to assess sensitivity of visual attention and driving performance for detecting changes in driver cognitive workload across different age groups.<\/jats:p>\n                  <jats:p>Background: The literature shows mixed results concerning the sensitivity of gaze concentration metrics to variations in cognitive demand. No studies appear showing how age affects gaze allocation during cognitive demand.<\/jats:p>\n                  <jats:p>Method: Recordings of drivers\u2019 gaze and driving performance by individuals in their 20s, 40s, and 60s were captured in actual driving conditions during three levels of cognitive demand.<\/jats:p>\n                  <jats:p>Results: Gaze concentration increased with task difficulty through the low and moderate levels of demand and then appeared to level out at the high demand level. At the moderate difficulty level, gaze concentration increased by 2.4 cm (\u22482\u00b0) from the reference period. The degree of gaze concentration with added cognitive demand is not related to age in the relatively healthy drivers studied. Driving performance measures did not show a consistent relationship with the objective demand level.<\/jats:p>\n                  <jats:p>Conclusion: Gaze concentration appears at low levels of cognitive demand prior to the appearance of marked decrements in driving control. There is no compelling evidence from this study that driving performance measures can be used to index differences in workload prior to capacity saturation.<\/jats:p>\n                  <jats:p>Application: Drivers\u2019 awareness of vehicle surroundings is incrementally affected by increases in cognitive demand. Developers of more advanced driver support systems should consider gaze concentration as a measure of driver cognitive workload. This recommendation is particularly relevant in light of the added benefits of gaze measurements for detecting visual demand.<\/jats:p>\n                  <jats:p>Keywords: mental workload, cognitive distraction, eye movements, visual tunneling, driving safety, situational awareness, voice interfaces, cellular telephones<\/jats:p>","DOI":"10.1177\/0018720812437274","type":"journal-article","created":{"date-parts":[[2012,3,1]],"date-time":"2012-03-01T01:12:48Z","timestamp":1330564368000},"page":"454-468","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":125,"title":["A Field Study on the Impact of Variations in Short-Term Memory Demands on Drivers\u2019 Visual Attention and Driving Performance Across Three Age Groups"],"prefix":"10.1177","volume":"54","author":[{"given":"Bryan","family":"Reimer","sequence":"first","affiliation":[{"name":"MIT AgeLab and New England University Transportation Center, Cambridge, Massachusetts"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bruce","family":"Mehler","sequence":"additional","affiliation":[{"name":"MIT AgeLab and New England University Transportation Center, Cambridge, Massachusetts"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ying","family":"Wang","sequence":"additional","affiliation":[{"name":"MIT AgeLab and New England University Transportation Center, Cambridge, Massachusetts"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Joseph F.","family":"Coughlin","sequence":"additional","affiliation":[{"name":"MIT AgeLab and New England University Transportation Center, Cambridge, Massachusetts"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2012,2,29]]},"reference":[{"key":"bibr1-0018720812437274","first-page":"132","volume-title":"Proceedings of the Fifth International Driving Symposium on Human Factors in Driver Assessment, Training and Vehicle Design","author":"Ahlstrom C.","year":"2009"},{"key":"bibr2-0018720812437274","doi-asserted-by":"publisher","DOI":"10.1177\/0018720810381072"},{"key":"bibr3-0018720812437274","doi-asserted-by":"publisher","DOI":"10.1016\/j.trf.2005.04.012"},{"key":"bibr4-0018720812437274","doi-asserted-by":"publisher","DOI":"10.1016\/0022-3956(75)90026-6"},{"key":"bibr5-0018720812437274","volume-title":"Paper presented at the International Congress on Transportation Electronics (Convergence)","author":"Green P.","year":"2004"},{"key":"bibr6-0018720812437274","doi-asserted-by":"publisher","DOI":"10.1016\/j.aap.2006.08.013"},{"key":"bibr7-0018720812437274","doi-asserted-by":"publisher","DOI":"10.1016\/j.aap.2006.07.001"},{"key":"bibr8-0018720812437274","doi-asserted-by":"publisher","DOI":"10.1002\/acp.1638"},{"key":"bibr9-0018720812437274","doi-asserted-by":"publisher","DOI":"10.1016\/j.trf.2006.12.002"},{"key":"bibr10-0018720812437274","volume-title":"Driver distraction: Theory, effects, and mitigation","author":"Lee J. 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