electrification

Researchers present a simulation-based quasi-statistical approach to estimate electric vehicle energy consumption under various on-road vehicle operating conditions.

This dissertation sets out to 1) explore the feasibility of implementing a per-mile road-usage charge (RUC) in replacement of the motor fuel taxes, 2) estimate the changes in vehicles-miles travelled (VMT) and the revenues generated from motor fuel taxes under the backdrop of vehicle electrification, and 3) quantify the effects of vehicle class and fuel type portfolios in ZEV-adopting households’ vehicle replacement decisions.

To add insights into air travelers’ ground transportation choices, this study collected a dataset with a survey administered among travelers using four major airports in Northern California in the post-pandemic era.

This is the dataset for project "Understanding Real-World Brake Activity: A Key to Assessing Non-Tailpipe Emission Sources for Sustainable Transportation and Communities" (UCR-DOT-1013).

This dataset is collected during the project "Air travelers’ Ground Transportation Choice at Four Airports in Northern California."It contains the survey responses regarding the use of the four airports in Northern California.

This is the dataset for the project "Electric Truck Fleet Management Under Limited and Uncertain Charging Infrastructure Availability". This dataset supports research on optimizing battery electric vehicle (BEV) fleet dispatching in last-mile freight logistics under uncertainty.

This dataset is comprised of a .csv file for the synthetic population employed by a research project to show the effect of vehicle body type on EV spatial distribution and home-charging access in California.

This report discusses an EV adoption model that employs synthetic population at the census tract level to show the effect of vehicle body type on EV spatial distribution and home-charging access in California.

This study develops a comprehensive optimization framework for electric truck fleet management, addressing the interplay between infrastructure limitations, operational uncertainties, and energy cost fluctuations. This research will also provide scalable insights for policymakers and industry leaders, supporting the broader transition to sustainable freight transportation.