Transportation is the largest source of greenhouse gas emissions in the country, accounting for nearly 30 percent of all annual emissions in the United States. Passenger cars and medium- to heavy-duty trucks combined make up 80 percent of that carbon footprint. From the vehicles themselves to the routes drivers take, researchers at the University of Minnesota (UMN) are exploring solutions to reduce these emissions and make driving more sustainable. A November 2025 CTS webinar examined two new approaches to energy-efficient transportation.
Zongxuan Sun, a professor in the UMN Department of Mechanical Engineering, explained how synchronizing a vehicle’s operation with real-time traffic and infrastructure data can improve energy efficiency. The efficiency of a vehicle is determined by two components: power demand, which is dictated by driving behavior, traffic, and infrastructure; and power generation, which involves the design and control of the vehicle. Historically, these components have been managed separately in manufacturing, but Sun suggested that integrating them could maximize energy savings.
This integration is enabled by leveraging vehicle connectivity and automation. First, connectivity provides vehicles with real-time information about their immediate surroundings—including other vehicles and infrastructure—and predicts future conditions. This aspect supports vehicle-level optimization, allowing a driver or vehicle to adjust speed and acceleration accordingly. Second, automation—ranging from driver-assistive to fully automated systems—enables more efficient driving behaviors and reduces human errors.
Using model predictive control, Sun and his team developed a framework and then real-time optimal control strategies across all powertrain types, with energy gains ranging from 10 to 20 percent.
Next, Michael Levin, an associate professor in the UMN’s civil, environmental, and geo- engineering department and a CTS scholar, discussed the challenges and complexities of route choice in lowering greenhouse gas emissions. Levin began by explaining eco-routing—the process of modifying a vehicle’s route choice to minimize individual gas consumption. Since 2021, Google Maps defaults to these kinds of route options—intended to reduce a vehicle’s CO2 emissions. Eco-route options differ from the shortest routes in that they prioritize the most sustainable paths over the most efficient—routes that limit fuel-wasting behaviors such as frequent braking, idling, and acceleration.
However, individual eco-routing can actually increase total system emissions by changing congestion patterns, Levin said. While well intentioned, if everyone chooses the Google Maps route to minimize their emissions, their collective behavior could make congestion worse along that path, consequently increasing individual emissions. Simulations run in various cities, including Chicago and Barcelona, Spain, have demonstrated this counterproductive effect of individual eco-routing.
To effectively reduce total system emissions with route choice, Levin proposed a system-optimal algorithm that considers both the impact of routes on congestion and individual vehicle emissions. Numerical results from a simulation in Bologna, Italy, predict reductions in emissions ranging from 6 to 13 percent.
The potential solutions described by the researchers show promising results for reducing total emissions from the transportation system. In addition, they demonstrate that sustainable transportation requires research across all areas of roadway travel—from vehicle technology to navigation apps and the routes themselves.
—Krysta Rzeszutek, CTS digital editor
