A Bayesian Network Approach for Systemic Risk Analysis in Unmanned Aerial Vehicle (UAV) Operations

A Bayesian Network Approach for Systemic Risk Analysis in Unmanned Aerial Vehicle (UAV) Operations | 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 Article A Bayesian Network Approach for Systemic Risk Analysis in Unmanned Aerial Vehicle (UAV) Operations Lu Wang, Maoran Zhu, Na Li This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7605133/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 14 Mar, 2026 Read the published version in Scientific Reports → Version 1 posted 11 You are reading this latest preprint version Abstract Unmanned Aerial Vehicle (UAV) operations confront complex systemic risks that challenge traditional analytical methods. This paper develops a hierarchical Bayesian Network (BN) to quantitatively model these risks. Our model establishes causal pathways from foundational drivers to key performance indicators (KPIs): Safety, Mission Success, and Third-Party Risk. The baseline risk assessment reveals significant operational vulnerabilities. It identifies degraded pilot performance, evidenced by a 54% probability of 'Poor' Decision Making, as a primary contributor to a 56% baseline probability of an 'Accident'. However, a comprehensive sensitivity analysis demonstrates a more critical insight: the operational environment, specifically 'Adverse Weather' and 'Terrain & Obstacles', constitutes the single most dominant risk driver across all KPIs. This finding underscores the strategic importance of rigorous pre-flight environmental assessment over in-flight reactive measures. Furthermore, the analysis reveals the necessity for differentiated mitigation strategies; Mission Success exhibits unique sensitivity to 'Signal Interference', a factor less critical for direct safety outcomes. This framework provides a data-driven, causal tool to support UAV operators in resource prioritization and systemic resilience enhancement within a complex operational landscape. Physical sciences/Engineering Physical sciences/Mathematics and computing Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 14 Mar, 2026 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 17 Dec, 2025 Reviews received at journal 11 Dec, 2025 Reviews received at journal 30 Nov, 2025 Reviewers agreed at journal 24 Nov, 2025 Reviewers agreed at journal 15 Nov, 2025 Reviewers agreed at journal 17 Sep, 2025 Reviewers invited by journal 17 Sep, 2025 Editor assigned by journal 17 Sep, 2025 Editor invited by journal 17 Sep, 2025 Submission checks completed at journal 16 Sep, 2025 First submitted to journal 16 Sep, 2025 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. 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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-7605133","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":521627261,"identity":"360860f3-ba6d-4912-80a8-e28ea62bbbc3","order_by":0,"name":"Lu Wang","email":"","orcid":"","institution":"Shanghai Civil Aviation College","correspondingAuthor":false,"prefix":"","firstName":"Lu","middleName":"","lastName":"Wang","suffix":""},{"id":521627262,"identity":"179e7f5c-b535-40d5-9ee6-d67cb082ccba","order_by":1,"name":"Maoran Zhu","email":"","orcid":"","institution":"Tongji 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