Search Results

Vehicle to Everything (V2X) communication has enabled on-board access to information from other vehicles and infrastructure. This information, traditionally used for safety applications, is increasingly being used for improving vehicle fuel economy [1-5]. This work aims to demonstrate energy consumption reductions in heavy/medium duty vehicles using an eco-driving algorithm. The algorithm is enabled by V2X communication and uses data contained in Basic Safety Messages (BSMs) and Signal Phase and Timing (SPaT) to generate an energy-efficient velocity trajectory for the vehicle to follow. An urban corridor was modeled in a microscopic traffic simulation package and was calibrated to match real-world traffic conditions. A nominal reduction of 7% in energy consumption and 6% in trip time was observed in simulations of eco-driving trucks.

While initial Connected Vehicle research in the United States was focusing almost exclusively on passenger vehicles, a program was envisioned that would enhance highway safety, mobility, and operational efficiencies through the application of the technology to commercial vehicles. This program was realized in 2009 by funding from the I-95 Corridor Coalition, led by the New York State Department of Transportation, and called the Commercial Vehicle Infrastructure Integration (CVII) program. The CVII program focuses on developing, testing and deploying Connected Vehicle technology for heavy vehicles. Since its inception, the CVII program has developed numerous Vehicle-to-Vehicle and Vehicle-to-Infrastructure applications for trucks that leverage communication with roadside infrastructure and other light and heavy duty vehicles to meet the objectives of the program.

Eco-driving algorithms enabled by Vehicle to Everything (V2X) communications in Connected and Automated Vehicles (CAVs) can improve fuel economy by generating an energy-efficient velocity trajectory for vehicles to follow in real time. Southwest Research Institute (SwRI) demonstrated a 7% reduction in energy consumption for fully loaded class 8 trucks using SwRI’s eco-driving algorithms. However, the impact of these schemes on vehicle emissions is not well understood. This paper details the effort of using data from SwRI’s on-road vehicle tests to measure and evaluate how eco-driving could impact emissions. Two engine and aftertreatment configurations were evaluated: a production system that meets current NOX standards and a system with advanced aftertreatment and engine technologies designed to meet low NOX 2031+ emissions standards.