National Renewable Energy Laboratory (NREL)

Transportation accounts for more than 25% of total energy consumed in the United States. Efforts to minimize energy use have predominantly focused on improving vehicle fuel efficiency and expanding use and availability of public transit. However, other factors impact transportation energy use such as traffic congestion, stop-and-go traffic, and limited information on available routes. Now, due to increasing availability of real-time data on traffic flows, transit scheduling, parking, local weather, and activities linked to transportation use, it is additionally possible to empower individual travelers to meet their transportation needs in ways that reduce energy use. To address these opportunities, new methods of modeling real transportation networks, new network optimization approaches and personalized incentive strategies can be used to deliver individuals the information they need to make choices that provide them with quality of service while reducing energy utilization in our transportation systems.

The National Renewable Energy Laboratory (NREL) and its partners will create a network architecture that approaches sustainable transportation as a dynamic system of travelers and decision points, rather than one of vehicles and roads, in order to create personalized energy-saving opportunities. The project will use currently available demographic and transportation data from an urban U.S. city as a test bed for energy reduction. To incentivize travelers to pursue energy-efficient routes, the control architecture will develop algorithms to understand a traveler’s preferences, tailor recommendations to the user, and identify personal incentives that will enable transportation system energy benefits. The Connected Traveler framework will provide local transportation authorities and individual travelers with a tool to identify personal travel decisions that balance quality of service with energy efficiency.

If successful, NREL’s system will demonstrate that energy-efficiency gains in personal transportation can be accomplished through network controls that encourage individual travelers to take specific, energy-relevant actions.