This study demonstrates a model framework that combines a microscopic traffic simulation with emissions and microscale dispersion models to quantify the potential impacts of truck-only lanes on fuel consumption, emissions, and near-road pollutant concentrations.
In this research project, the research team developed an environmentally-friendly driving feedback system for heavy-duty trucks, which was adapted from a similar system previously developed for light-duty cars.
The NCST congratulates our UC Riverside and UC Davis dissertation grant and graduate fellowship recipients for the Fall 2020 cycle! Our recent awardees are contributing to research on electric vehicle charging infrastructure, pavement performance, highway traffic management, ridehailing, and disaster modeling!
This research will improve long-term sustainability by identifying how and why (or why not) transportation electrification (TE) projects align with regional and local transportation goals. The research will result in a deep dive case study that can serve as a template for evaluating future TE expenditures with respect to identifying and quantifying disadvantaged community benefits.