{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,1]],"date-time":"2025-11-01T19:34:53Z","timestamp":1762025693942,"version":"build-2065373602"},"reference-count":38,"publisher":"MDPI AG","issue":"14","license":[{"start":{"date-parts":[[2020,7,9]],"date-time":"2020-07-09T00:00:00Z","timestamp":1594252800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001871","name":"Funda\u00e7\u00e3o para a Ci\u00eancia e a Tecnologia","doi-asserted-by":"publisher","award":["PTDC\/ECI-TRA\/28526\/2017 - POCI-01-0145-FEDER-028526"],"award-info":[{"award-number":["PTDC\/ECI-TRA\/28526\/2017 - POCI-01-0145-FEDER-028526"]}],"id":[{"id":"10.13039\/501100001871","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Driver inattention is a major contributor to road crashes. The emerging of new driver monitoring systems represents an opportunity for researchers to explore new data sources to understand driver inattention, even if the technology was not developed with this purpose in mind. This study is based on retrospective data obtained from two driver monitoring systems to study distraction and drowsiness risk factors. The data includes information about the trips performed by 330 drivers and corresponding distraction and drowsiness alerts emitted by the systems. The drivers\u2019 historical travel data allowed defining two groups with different mobility patterns (short-distance and long-distance drivers) through a cluster analysis. Then, the impacts of the driver\u2019s profile and trip characteristics (e.g., driving time, average speed, and breaking time and frequency) on inattention were analyzed using ordered probit models. The results show that long-distance drivers, typically associated with professionals, are less prone to distraction and drowsiness than short-distance drivers. The driving time increases the probability of inattention, while the breaking frequency is more important to mitigate inattention than the breaking time. Higher average speeds increase the inattention risk, being associated with road facilities featuring a monotonous driving environment.<\/jats:p>","DOI":"10.3390\/s20143836","type":"journal-article","created":{"date-parts":[[2020,7,10]],"date-time":"2020-07-10T09:25:28Z","timestamp":1594373128000},"page":"3836","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["Exploring Monitoring Systems Data for Driver Distraction and Drowsiness Research"],"prefix":"10.3390","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7614-7605","authenticated-orcid":false,"given":"Ant\u00f3nio","family":"Lobo","sequence":"first","affiliation":[{"name":"Research Centre for Territory, Transports and Environment, Faculty of Engineering of the University of Porto, 4200-465 Porto, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7469-3186","authenticated-orcid":false,"given":"Sara","family":"Ferreira","sequence":"additional","affiliation":[{"name":"Research Centre for Territory, Transports and Environment, Faculty of Engineering of the University of Porto, 4200-465 Porto, Portugal"}]},{"given":"Ant\u00f3nio","family":"Couto","sequence":"additional","affiliation":[{"name":"Research Centre for Territory, Transports and Environment, Faculty of Engineering of the University of Porto, 4200-465 Porto, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2020,7,9]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"159","DOI":"10.1016\/j.aap.2015.01.005","article-title":"The restless mind while driving: Drivers\u2019 thoughts behind the wheel","volume":"76","author":"Lemercier","year":"2015","journal-title":"Accid. 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