MIT researchers have harnessed deep reinforcement learning to craft eco-driving strategies that reduce intersection CO₂ emissions citywide by 11–22%—without slowing traffic or compromising safety. Their simulations across thousands of intersections reveal that just 10% adoption of eco-driving techniques yields 25–50% of the total impact, and 20% of intersections account for 70% of emission reductions.
