This project aims to develop a comprehensive knowledge of the capabilities of different last-mile strategies and policies for varied markets and delivery environments.
This project concentrates on policy-focused research supporting the design and implementation of medium- and heavy-duty zero-emission vehicle policies with a team of researchers from UC Davis' Institute of Transportation Studies. The study focuses on policy considerations for increasing fleets’ share of ZEVs' purchases.
This research investigates these two crucial components of climate mitigation that have proven to be politically obstinate. Three studies will focus on the context in which land use and transportation policies are created – the "who, what, and why" of political influence – in order to better understand the barriers to and opportunities for policy change.
The objective of this project will be to analyze and explore the current literature available on resilient transportation, especially with regards to climate change and extreme weather events.
The goal of this project is to understand barriers to potential ridership including a dearth of first- and last-mile connections, reliability of service, bicycle and pedestrian facilities near stations, cost, changes in attitudes, changes in demand for travel (induced by work from home preferences), and station level amenities including parking.
Principal InvestigatorSeshadri Srinivasa Raghavan, Ph.D.
University of California, Davis
The goal of this study intends to understand the relative share of vehicle miles traveled (VMT) between a plug-in hybrid vehicle and a battery electric vehicle.
This research aims to develop an Artificial Neural Network (ANN) to forecast EVs’ trip destinations and charging behavior–information that is essential for electricity load aggregators to effectively manage charging loads.
This research is focused on the optimization of transportation system management by developing statistical models involving dynamic network modeling, spatiotemporal analysis, and theories of AI.
