A Hierarchical Approach to Trajectory Planning for Autonomous Vehicles on Curvy Roads

A Hierarchical Approach to Trajectory Planning for Autonomous Vehicles on Curvy Roads | 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 Hierarchical Approach to Trajectory Planning for Autonomous Vehicles on Curvy Roads Fuzhou Zhao, Heye Huang, Xuemei Wang, Ling Han, Fei Ye, Mingyang Cui, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6270718/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 This paper is dedicated to enhancing the planning speed and kinematics of intelligent vehicles navigating dynamic traffic environments on curvy roads by introducing a three-layer trajectory planner. Within the coarse trajectory layer, we introduce the innovative jump node dynamic programming (DP) algorithm, designed to circumvent trajectory searches for overlapping nodes. In contrast to the conventional DP algorithm, the decision-making efficiency achieved with the jump node DP algorithm demonstrates a substantial improvement of up to 30.6% within simulated environments. Transitioning to the reference trajectory layer, we put forth an improved DP strategy. This strategy is forged through the integration of the jump node DP algorithm and the joint interpolation method, permitting the generation of a crafted reference trajectory. In the alternate trajectory layer, segments of the trajectory characterized by substantial curvature, as planned by the improved DP strategy, undergo initial replanning through the adaptive cruise control (ACC) strategy. Subsequently, these trajectory segments revert to the improved DP strategy after traversing specific waypoints within the receding horizon. Simulation cases illustrate that the minimum radius of curvature in the planned trajectory can be augmented by up to 12.7%. All proposed algorithms have undergone dynamic simulation experiments, affirming their effectiveness. Physical sciences/Engineering Physical sciences/Engineering/Electrical and electronic engineering Physical sciences/Engineering/Mechanical engineering 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. 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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-6270718","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":437408657,"identity":"e3545518-3bde-440b-896a-ec19d55e6010","order_by":0,"name":"Fuzhou 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