Building Web App for Automated Vehicles Energy and Emissions Estimations

dc.contributor.authorCrumpacker, Katelynen
dc.contributor.authorWhite, Trevoren
dc.contributor.authorRankin, Daviden
dc.contributor.authorPaladugu, Harshaen
dc.date.accessioned2025-06-04T15:17:36Zen
dc.date.available2025-06-04T15:17:36Zen
dc.date.issued2025-05en
dc.descriptionWeb App for Automated Vehicles Energy and Emissions Estimationsen
dc.description.abstractAs transportation moves toward greater sustainability, accurately understanding and comparing vehicle energy consumption and emissions is increasingly essential. The transportation sector is one of the largest contributors to greenhouse gas emissions, highlighting the need for smarter, cleaner solutions. Data collection in this sector plays a critical role in sustainability efforts by enabling detailed analysis of vehicle emissions, energy use, and traffic behavior so that more efficient transportation systems can be developed. To support these efforts, our project delivers an intuitive web application built on energy consumption models for various vehicle types, including Internal Combustion Engine Vehicles (ICEVs), Battery Electric Vehicles (BEVs), Hybrid Electric Vehicles (HEVs), and Hydrogen Fuel Cell Vehicles (HFCVs). ICEVs rely on traditional gasoline-powered engines, while BEVs operate entirely on rechargeable batteries. HEVs combine internal combustion engines with electric motors powered by regenerative braking and engine energy. HFCVs generate electricity through a chemical reaction in a fuel cell, emitting only water vapor. Users can input speed and acceleration profiles to generate immediate visual comparisons of estimated energy consumption and particle emissions across these vehicle types. This enables informed comparisons based on multiple sustainability metrics. The platform is designed to serve a range of users, from researchers to drivers seeking to make environmentally conscious vehicle choices. Expanding on prior work, this project significantly enhances the user experience with an upgraded interface, improved responsiveness for large datasets, and advanced data visualizations. Additional features include streamlined file upload/download capabilities, better database integration, vehicle-specific input (make, model, and year), support for particulate matter analysis, and flexible data filtering for targeted comparisons. By offering a comprehensive and accessible tool, the platform empowers users to engage with meaningful transportation data and make decisions that support long-term environmental goals.en
dc.identifier.urihttps://hdl.handle.net/10919/135047en
dc.language.isoen_USen
dc.subjectEnergy Efficiencyen
dc.subjectSustainabilityen
dc.subjectData Collectionen
dc.titleBuilding Web App for Automated Vehicles Energy and Emissions Estimationsen

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