Replicating Bus Trajectories in SUMO based on Tracking Experiments with Implications for Energy Consumption

Replicating Bus Trajectories in SUMO based on Tracking Experiments with Implications for Energy Consumption | 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 Replicating Bus Trajectories in SUMO based on Tracking Experiments with Implications for Energy Consumption Andreas Keler, Satoshi Nakao, Jan-Dirk Schmöcker This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7872908/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 11 You are reading this latest preprint version Abstract We present a methodology for creating a bus route microsimulation model from open-source data to assess electric bus (e-bus) energy consumption under varying traffic, vehicle, and driving behavior conditions. The approach aims to provide transport planners and researchers with a testbed for evaluating the impact of e-bus adoption. While datasets such as OpenStreetMap (OSM) and GTFS enable large-scale modeling, they often require corrections, particularly to speed limits, to ensure realistic outcomes. For e-buses, accurate energy estimation depends on calibrating driver behavior using observed speed trajectories, making parameter fitting and network refinement essential. Our case study focuses on Kyoto, Japan, replicating operations of the city’s only current e-bus line. Combining corrected map data, limited tracking experiments, and traffic data, we generate realistic simulation scenarios with the opensource microsimulation SUMO. Speed trajectories from tracking are used to calibrate vehicle and driver parameters to explore vehicle- and route-specific energy use. The proposed method is transferable to other contexts. The results demonstrate that realistic e-bus simulations can be achieved with modest data inputs, but that OSM network data need to be carefully revisited by the analyst and that calibration of driver behavior is important to obtain realistic energy consumption estimates. Physical sciences/Engineering Physical sciences/Mathematics and computing Electric Bus Traffic Microscopic Traffic Flow Simulation Tracking Experiments Energy Consumption Modeling Estimation Methods Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: Revision requested 24 Nov, 2025 Reviews received at journal 23 Nov, 2025 Reviews received at journal 19 Nov, 2025 Reviews received at journal 10 Nov, 2025 Reviewers agreed at journal 31 Oct, 2025 Reviewers agreed at journal 29 Oct, 2025 Reviewers agreed at journal 28 Oct, 2025 Reviewers invited by journal 28 Oct, 2025 Editor assigned by journal 28 Oct, 2025 Submission checks completed at journal 27 Oct, 2025 First submitted to journal 15 Oct, 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. 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-7872908","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":537812072,"identity":"010b85e3-55d2-4c44-881c-e1c9238fc269","order_by":0,"name":"Andreas Keler","email":"","orcid":"","institution":"Institute of Sakurajima Volcano Disaster Risk Reduction","correspondingAuthor":false,"prefix":"","firstName":"Andreas","middleName":"","lastName":"Keler","suffix":""},{"id":537812075,"identity":"0f039eb3-c837-47cf-a8db-e58f41ef3fe4","order_by":1,"name":"Satoshi Nakao","email":"","orcid":"","institution":"Kyoto 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