Researchers use stop-light cameras to reduce fuel consumption of less-efficient vehicles via traffic management

The less efficient the vehicle, the shorter the wait at the traffic lights, and vice versa – electric cars and newer vehicles must wait longer. So the incentive lies with inefficiency – genius!

Approximately 6 billion gallons of fuel are wasted in the US each year as vehicles wait at stop lights or sit in dense traffic with engines idling, according to US Department of Energy estimates.

The least efficient of these vehicles are the large, heavy trucks used for hauling goods—they burn much more fuel than passenger cars consume when not moving, reports Green Car Congress.

Now, researchers at Oak Ridge National Laboratory (ORNL) have designed a computer vision system—using the preexisting stop-light cameras of GRIDSMART, a Tennessee-based company that specializes in traffic-management services—that can visually identify vehicles at intersections, determine their gas mileage estimates, and then direct traffic lights to keep less-efficient vehicles moving to reduce their fuel consumption.

The ORNL project is a first-year seed project funded by HPC4Mobility, the DOE Vehicle Technologies Office’s program for exploring energy efficiency increases in mobility systems.

Proving such a system could work with current technology was a complicated puzzle that required fitting together a lot of different pieces: high-tech cameras, vehicle datasets, artificial neural networks, and computerized traffic simulations.

Full report here.