Attendees at the Consumer Electronics Show, or CES, got to try out cooperative merging technology created at the Center for Environmental Research and Technology, or CE-CERT, using a high-fidelity driving simulator.
This white paper presents a statistical meta-analysis of eco-driving feedback studies in order to determine a pooled estimate of the impact on fuel economy and explore how characteristics of feedback interventions influence their impact.
This project will evaluate the design, operation, and impacts of advanced optimization strategies for traffic operations over transportation networks with Connected and Automated Vehicles (CAVs) under complicated dynamic traffic conditions.
The purpose of this project is to integrate solutions for eco-routing and practical constraints, and develop a more practical model for eco-routing in the trucking industry.
This dissertation developed predictive models and trajectory planning algorithms using machine learning and optimization techniques to address four key challenges of energy efficient driving of connected and automated vehicles.
This webinar featured a discussion of the state-of-the knowledge on eco-driving solutions specific to transit vehicles and the potential impacts of driver behavior and other fuel conservation strategies.
Kanok Boriboonsomsin from the University of California, Riverside shared the state-of-the-knowledge on eco-driving practices and programs applied to heavy-duty trucks; the effectiveness of tested or implemented programs; and key challenges and barriers in implementing and sustaining a successful truck eco-driving program.
