{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,17]],"date-time":"2026-06-17T06:01:13Z","timestamp":1781676073332,"version":"3.54.5"},"reference-count":25,"publisher":"MDPI AG","issue":"23","license":[{"start":{"date-parts":[[2022,12,6]],"date-time":"2022-12-06T00:00:00Z","timestamp":1670284800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"EU project HADRIAN","award":["875597"],"award-info":[{"award-number":["875597"]}]},{"name":"EU project HADRIAN","award":["953426"],"award-info":[{"award-number":["953426"]}]},{"name":"European Union\u2019s Horizon 2020 research and innovation programme","award":["875597"],"award-info":[{"award-number":["875597"]}]},{"name":"European Union\u2019s Horizon 2020 research and innovation programme","award":["953426"],"award-info":[{"award-number":["953426"]}]},{"name":"EU project PANACEA","award":["875597"],"award-info":[{"award-number":["875597"]}]},{"name":"EU project PANACEA","award":["953426"],"award-info":[{"award-number":["953426"]}]},{"name":"European Union\u2019s Horizon 2020 research and innovation programme","award":["875597"],"award-info":[{"award-number":["875597"]}]},{"name":"European Union\u2019s Horizon 2020 research and innovation programme","award":["953426"],"award-info":[{"award-number":["953426"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>A difficult challenge for today\u2019s driver monitoring systems is the detection of cognitive distraction. The present research presents the development of a theory-driven approach for cognitive distraction detection during manual driving based on temporal control theories. It is based solely on changes in the temporal variance of driving-relevant gaze behavior, such as gazes onto the dashboard (TDGV). Validation of the detection method happened in a field and in a simulator study by letting participants drive, alternating with and without a secondary task inducing external cognitive distraction (auditory continuous performance task). The general accuracy of the distraction detection method varies between 68% and 81% based on the quality of an individual prerecorded baseline measurement. As a theory-driven system, it represents not only a step towards a sophisticated cognitive distraction detection method, but also explains that changes in temporal dashboard gaze variance (TDGV) are a useful behavioral indicator for detecting cognitive distraction.<\/jats:p>","DOI":"10.3390\/s22239556","type":"journal-article","created":{"date-parts":[[2022,12,7]],"date-time":"2022-12-07T05:50:52Z","timestamp":1670392252000},"page":"9556","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Temporal Dashboard Gaze Variance (TDGV) Changes for Measuring Cognitive Distraction While Driving"],"prefix":"10.3390","volume":"22","author":[{"given":"Cyril","family":"Marx","sequence":"first","affiliation":[{"name":"Virtual Vehicle Research GmbH, 8010 Graz, Austria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Elem G\u00fczel","family":"Kalayci","sequence":"additional","affiliation":[{"name":"Virtual Vehicle Research GmbH, 8010 Graz, Austria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Peter","family":"Moertl","sequence":"additional","affiliation":[{"name":"Virtual Vehicle Research GmbH, 8010 Graz, Austria"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,12,6]]},"reference":[{"key":"ref_1","unstructured":"European Commission (2018). 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