{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,23]],"date-time":"2026-10-23T12:46:05Z","timestamp":1792759565188,"version":"4.5.0"},"reference-count":53,"publisher":"SAGE Publications","license":[{"start":{"date-parts":[[2026,10,20]],"date-time":"2026-10-20T00:00:00Z","timestamp":1792454400000},"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"],"abstract":"<jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>Evaluate the sensitivity of eye-tracking metrics to variations in mental workload in rail traffic control, and how they may be modulated by operator experience.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Rail traffic control is a safety-critical domain characterized by high cognitive demands. While subjective workload measures are widely used, objective, real-time indicators, particularly eye-tracking metrics, remain underexplored.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Method<\/jats:title>\n                    <jats:p>Eighteen professional rail traffic controllers (9 novice, 9 experienced) performed a simulation-based experiment involving four different scenarios with varying traffic density and task complexity, while wearing a head-mounted eye tracker. Measures of gaze behavior and visual strategies (fixations in different areas of interest (AOI)) were computed, and compared to subjective workload measures, to assess the effects of task difficulty and experience.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Some measures like pupil dilation showed substantial changes (by \u223c100%), while others like stationary gaze entropy showed more modest changes (\u223c40%), with increased task demand. Measures such as fixation rate revealed significant interaction effects with experience, indicating distinct visual strategies of novices vs. experts. Compared to experts, novices relied more on global overview displays under higher workload, and reduced planning-related information use, as revealed by AOI analysis. Subjective workload measures corroborated with increases in perceived demand.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>This study advances mental workload assessment in rail traffic control by demonstrating that eye-tracking metrics are sensitive to workload variations, and also reveal underlying cognitive strategies unique to expertise.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Application<\/jats:title>\n                    <jats:p>These findings support the development of real-time workload monitoring systems and inform training interventions focused on information integration and cognitive strategies in rail traffic control operations.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1177\/00187208261494303","type":"journal-article","created":{"date-parts":[[2026,10,20]],"date-time":"2026-10-20T13:35:46Z","timestamp":1792503346000},"update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":0,"title":["\u201cEyes on the Network\u201d \u2013 Task Complexity and Expertise Shape Visual Strategies and Mental Workload in Rail Traffic Control"],"prefix":"10.1177","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2833-1130","authenticated-orcid":false,"given":"Vishwajeet","family":"Ransing","sequence":"first","affiliation":[{"name":"Clemson University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3328-5968","authenticated-orcid":false,"given":"Satyajit","family":"Upasani","sequence":"additional","affiliation":[{"name":"Virginia Tech"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Konstantinos","family":"Triantis","sequence":"additional","affiliation":[{"name":"Virginia Tech"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5068-3001","authenticated-orcid":false,"given":"Bart","family":"Roets","sequence":"additional","affiliation":[{"name":"Infrabel Belgian Railways"},{"name":"Ghent University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9327-6177","authenticated-orcid":false,"given":"Divya","family":"Srinivasan","sequence":"additional","affiliation":[{"name":"Clemson University"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2026,10,20]]},"reference":[{"key":"e_1_3_4_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/3171221.3171287"},{"key":"e_1_3_4_3_1","doi-asserted-by":"publisher","DOI":"10.1146\/annurev.neuro.28.061604.135709"},{"key":"e_1_3_4_4_1","doi-asserted-by":"publisher","DOI":"10.3389\/fpsyg.2021.702538"},{"key":"e_1_3_4_5_1","volume-title":"Appropriate automation of rail signalling systems: A human factors study","author":"Balfe N.","year":"2010","unstructured":"Balfe N. 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