A Real-Time Context-Dependent Driver Attention AssessmentSystem Using Pupil Orientation and Head Posture

A Real-Time Context-Dependent Driver Attention AssessmentSystem Using Pupil Orientation and Head Posture | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article A Real-Time Context-Dependent Driver Attention AssessmentSystem Using Pupil Orientation and Head Posture Weiwei Zhang, Wei Zhang, Wangpengfei Yu, Wenfeng Guo, Yang Chen, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6321607/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract With the popularization of social media andInternet technology, people are more and more easilydistracted when driving, which has a serious adverseimpact on the safety of expected functions, and reducesthe efficiency of control transmission between humanand computer. This article proposes a real-time pupil re-construction (PURE) algorithm for real-time detectionof pupil direction, and combines it with a 3D eye modelto obtain the gaze direction of the pupil in real time.Subsequently, the Posit algorithm was used to obtain real-time head posture, and the head posture and pupil gaze direction were used as improved input features toestimate the driver’s gaze area in real-time using a random forest model. Finally, this article comprehensivelyconsiders the impact of multiple real-time indicatorson driving attention, such as the number of eye gazeareas, eye scanning areas, road conditions, brain latency,and driving tasks, and proposes a prototype framework for real-time driver multi indicator attention evaluation.Through various real-time evaluation experiments,we have demonstrated that: 1) these context relatedattention features are universal when tested in real-timeon 16 drivers in a driving simulator; 2) The proposeddriver attention evaluation model performs well underreal-time conditions and can produce reliable results invarious driving scenarios. Real time driving attention assessment pupil reconstruction head posture multi-indicator attention evaluation Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6321607","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":439669781,"identity":"9d688dc5-50b1-4990-870e-4164f6d28c00","order_by":0,"name":"Weiwei Zhang","email":"","orcid":"","institution":"School of Automotive Studies, Tongji University, shanghai, China","correspondingAuthor":false,"prefix":"","firstName":"Weiwei","middleName":"","lastName":"Zhang","suffix":""},{"id":439669782,"identity":"729e6fa3-f757-4daf-b52f-af3210f9cbd0","order_by":1,"name":"Wei 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This article proposes a real-time pupil re-construction (PURE) algorithm for real-time detectionof pupil direction, and combines it with a 3D eye modelto obtain the gaze direction of the pupil in real time.Subsequently, the Posit algorithm was used to obtain real-time head posture, and the head posture and pupil gaze direction were used as improved input features toestimate the driver’s gaze area in real-time using a random forest model. 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