This white paper evaluates different transportation funding reforms, with specific focus on funding sustainability, environmental sustainability, and social justice.
This project evaluates the relationships between EV adoption, home charger installation, and housing characteristics as well as the costs of home charging installation for homes of different types in the City of Burlington, Vermont. The project also investigates the sociodemographic makeup of residents living in homes with greater barriers to home charging using national data.
This research will apply climate vulnerability assessments and the TBL approach to sustainability to rail infrastructure planning and resource allocation decision making. The results will be validated by rail operators and administrators to support improved investments in rail that are resilient to extreme events, protect the natural environment, enhance economic competitiveness, and improve societal quality of life, equitably.
Transportation policies, plans, and projects all flow through state institutions because of the substantial cost of infrastructure and the need to assess transportation system performance, includin
This research aims to develop an equitable and sustainable freight‐oriented land use methodology to support future planning activities, facilitate the integration of freight activity across urban, suburban, and rural areas, and facilitate the transition of heavy‐ and medium‐duty vehicles toward zero‐emission. The project will analyze freight distribution patterns considering supply and demand and estimate social, environmental, and labor impacts in different communities.
This research responds to identified gaps within the field of life cycle analysis while contributing a more nuanced, accurate understanding of the lithium-ion batteries value chain.
In this study, the research team will: 1) measure real-world brake activities of a large volume of vehicles traversing major roadway segments (e.g., near signalized intersections) by leveraging advanced roadside sensing technologies, e.g., Light Detection and Ranging and/or high-definition camera, as well as deep learning-based computer vision algorithms; and 2) construct the real-world brake activity database and supplement for the non-tailpipe emissions inventory.
