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This project aims to improve multi-vehicle heavy-duty truck platooning efficiency and safety through the use of automated controls, advanced communications, real-world testing, data analysis, and simulation development. This project aims to autonomously control the entire fleet of three following vehicles – throttle, brake, and steering – while optimizing the entire platoon for fuel efficiency and safety.

This project will explore micro-transit solutions for public transit resulting in coordinated multi-modal movement of people.

The objective of the project is to develop and demonstrate a replicable data collection and training framework that supports energy consumption prediction that will enable real-time energy consumption and mobility optimization.

The objective of the project is to develop and demonstrate a replicable community-level real-time data driven transportation model capable of predicting and enabling synergistic traffic management system (TMS) and energy management systems (EMS) optimization.

The objective of this project is to develop a Multi-Unit Dwelling and Curbside Residential Charging Toolkit including all necessary information (e.g., technical considerations, business case, sample agreements, and sample policies) to evaluate and implement innovative, cost-effective, and flexibly-expandable charging solutions that will enhance residential MUD and curbside plug-in electric vehicle (PEV) charging systems to attract and retain customers. Project results and the Toolkit will be broadly disseminated to ensure a meaningful and lasting market impact.

The objective of this project is to expand the availability of electric vehicle (EV) charging at low cost in urban settings using existing electrical infrastructure on the streetlight system to provide on-street EV charging, as well as charging for multi-family dwelling units (MFDU).