Traffic Light Evolution: The White Phase for the Future
Modern traffic lights, unchanged for a century, are based on a universal code: red — stop, yellow — prepare, green — go. However, researchers from North Carolina University propose a revolutionary change — adding a fourth white-colored signal. This initiative aims to optimize traffic flow in conditions of shared road use by autonomous and conventional vehicles.
Key Aspects of the New System
The white phase is activated only when a sufficient number of autonomous vehicles are present at the intersection. Connected autonomous vehicles act as mobile traffic regulators, helping to reduce congestion through collective data.
The Role of Technology in Traffic Coordination
This strategy, which scientists call distributed coordination, allows for the creation of a “collective mind” for traffic. Each autonomous vehicle interacts with others, determining optimal routes and timing, avoiding collisions and idling.
Ali Hajbabaie, the study’s author, notes:
This “white phase” concept utilizes the computational capabilities of autonomous vehicles. The new signal will help human drivers navigate: red — stop, green — go, and white — follow the vehicle in front.
The system’s effectiveness is confirmed by simulation results: delays are reduced by 3.2–94%, and overall performance increases by almost 99% compared to traditional traffic lights.
Implementation Prospects
Despite optimistic forecasts, the large-scale implementation of the system requires time. Fully autonomous vehicles have not yet become ubiquitous, and the infrastructure needs updating — about 75% of existing systems require modernization. This concept demonstrates the potential of the future, where technologies contribute to the efficiency and safety of road traffic.
The implementation of the white phase could become the key to solving urban congestion problems, especially with the growing number of autonomous vehicles. It is important to consider that the success of such a system will depend not only on technologies but also on societal readiness and legislative changes regulating the use of artificial intelligence in the transport sector.