Exploring the potential of disaggregated connected vehicle probe data in freeway congestion analysis: Insights from the I-20/59 freeway

Exploring the potential of disaggregated connected vehicle probe data in freeway congestion analysis: Insights from the I-20/59 freeway | 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 Exploring the potential of disaggregated connected vehicle probe data in freeway congestion analysis: Insights from the I-20/59 freeway Vamshi Chaitanya Annimalla, Alexander Hainen, Praveena Penmetsa This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6872751/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 Traditional traffic data sources, such as sensors (including radar, Bluetooth, and inductive loops) and aggregated probe vehicle data, provide insights but remain constrained by limited coverage, fragmentation, and low granularity. This study uses disaggregated connected vehicle probe (DCVP) data to provide high-resolution insights into congestion dynamics. Advanced trajectory alignment and clustering techniques identify congestion clusters, analyze queue lengths, and examine shockwave propagation. Driver behavior analysis, such as sudden deceleration and illegal turns, reveal safety risks and secondary crash potential. A comparative analysis of freeway and alternate routes evaluates the impact of congestion on travel efficiency. Additionally, a congestion scoring framework quantifies severity, validated against regional incident data to detect disruptions not tied to reported incidents. The study observed queue lengths reaching up to 7 miles and recovery times as long as 6 hours during major crash events. Furthermore, 74 significant congestion events were detected exclusively through DCVP data, indicating persistent bottlenecks that are not reflected in regional incident records which highlight the value of DCVP data in diagnosing traffic patterns and enabling adaptive decision-making. Connected Vehicle Data Congestion Analysis Shockwave Propagation Traffic Bottlenecks Freeway Management 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. 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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-6872751","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":479385214,"identity":"12d17dbb-b991-4f6b-b3f0-c611e0e0851d","order_by":0,"name":"Vamshi Chaitanya Annimalla","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/0lEQVRIie3RMUsDMRTA8XcUnsvDrAlt/QwPDroova9y4UCXqzgWHAx0FV0t+CEKQuaTgl3OXbnFLp1uKS4KBb3cIkLT4uaQ//jIj5cQgFDov5YC9A6hUwDwzzAyewghYPoHAi0h/jXxEl48P70t8yHhQbl+H1/YRHQNyg846c8KDynPz1jbjJBGD6rkSk/vC1TXcBr7iDL5QGrbaS42spHhKuWXFCXBXHvJbe3IFaGoV44kjqgNfHmJkO2WOaHM0ZFo1pAuQbGDtFsWDVnFyri33OnJcY+zeOohKPKB+rSXR0Jky7XZVImQ2eNrPR72bzxkW+5HeO+pUCgUCu3oG02/VeqFTcUAAAAAAElFTkSuQmCC","orcid":"","institution":"University of Alabama","correspondingAuthor":true,"prefix":"","firstName":"Vamshi","middleName":"Chaitanya","lastName":"Annimalla","suffix":""},{"id":479385216,"identity":"99e58130-769b-4fea-b57a-53b576afd1ed","order_by":1,"name":"Alexander Hainen","email":"","orcid":"","institution":"University of Alabama","correspondingAuthor":false,"prefix":"","firstName":"Alexander","middleName":"","lastName":"Hainen","suffix":""},{"id":479385218,"identity":"a917fb5c-5a53-4265-9bba-634981341041","order_by":2,"name":"Praveena Penmetsa","email":"","orcid":"","institution":"University of Alabama","correspondingAuthor":false,"prefix":"","firstName":"Praveena","middleName":"","lastName":"Penmetsa","suffix":""}],"badges":[],"createdAt":"2025-06-11 14:23:11","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6872751/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6872751/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":89331715,"identity":"52002557-10af-4ea5-a655-2493913881bb","added_by":"auto","created_at":"2025-08-18 23:46:30","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":6964063,"visible":true,"origin":"","legend":"","description":"","filename":"DCVPfreewaySpringerNatureDSforTSubmissionR1.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6872751/v1_covered_95d85750-b962-451c-861b-ee22741a4ebb.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Exploring the potential of disaggregated connected vehicle probe data in freeway congestion analysis: Insights from the I-20/59 freeway","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Connected Vehicle Data, Congestion Analysis, Shockwave Propagation, Traffic Bottlenecks, Freeway Management","lastPublishedDoi":"10.21203/rs.3.rs-6872751/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6872751/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eTraditional traffic data sources, such as sensors (including radar, Bluetooth, and inductive loops) and aggregated probe vehicle data, provide insights but remain constrained by limited coverage, fragmentation, and low granularity. 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