The SmartPedalTM technology was evaluated using six Caltrans vehicles, each monitored for two data collection periods: 1) without the SmartPedalTM device, to collect the baseline data sets, and 2) with the SmartPedalTM device, to collect a comparison data set with the “Smart Pedal” technology. The collected data is presented here.
The aim of this script is to automate the process of directed network graph formation, i.e., creation of incidence matrix, node adjacency matrix, and map the sensors to appropriate links.
This project creates a sensor to measure the fuel quality of natural gas, with the intention of advancing renewable natural gas as a vehicular fuel source.
This project provides energy and environment policy makers with both an up-to-date review of eco-driving outcomes and an understanding of how those outcomes depend on the behavioral contexts in which they are measured.
In this project, the researchers present an agent-based online adaptive signal control strategy based on real-time traffic information available from vehicles equipped with Connected Vehicle technology, with the goal of making freight operations more sustainable.
This project contributes research on information technology, operational modernization at distribution nodes, and planning and policy for the California Sustainable Freight Strategy.
The objective of this dissertation is to develop and refine methods of assessing the life cycle environmental impacts and economic costs of electric vehicle technologies and policies.
Researchers developed a variety of eco-driving technologies for trucks. They then tested how effective these technologies were in reducing emissions and fuel consumption.
