AI traffic lights promise to reduce commuter jams

The Fraunhofer Institute researchers have received funding from the German Federal Ministry of Transport and Digital Infrastructure for a project that could eventually improve traffic flow.

Conventional traffic lights use rule-based controls, but this rigid approach does not work for all traffic situations. In addition, the sensors currently in use such as induction loop technology embedded in the road surface provide only a rough impression of the actual traffic situation.

Instead of conventional sensors, the researchers used high-resolution cameras and radar sensors to more precisely capture the actual traffic situation. This allows the number of vehicles waiting at a junction to be determined accurately in real time.

The technology also detects the average speed of the cars and the waiting times. The real-time sensors are combined with AI, which replaces the usual rigid control rules. It uses deep reinforcement learning (DRL) algorithms, a method of machine learning that focuses on finding intelligent solutions to complex control problems.

“We used a junction in Lemgo, where our testing is carried out, to build a realistic simulation and trained the AI on countless iterations within this model,” researcher Arthur Müller said.

“Prior to running the simulation, we added the traffic volume measured during rush hour into the model, enabling the AI to work with real data. This resulted in an agent trained using deep reinforcement learning: a neural network that represents the lights control.”

The algorithms trained in this way calculate the optimum switching behaviour for the traffic lights and the best phase sequence to shorten waiting times at the junction, reduce journey times, and thus lower the noise and CO₂ pollution caused by queuing traffic.

The AI algorithms run in an edge computer in the control box at the junction. One advantage of the algorithms is that they can be tested, used and scaled up to include neighbouring lights that form a wider network.

The simulation phases carried out on the congested Lemgo junction fitted with intelligent lights demonstrated that the use of artificial intelligence could improve traffic flow by 10-15 per cent, the researchers said.

The testing will now consider the influence of the traffic metrics on parameters like noise pollution and emissions. The team wants to test the technology in a real-life scenario as they believe there will be an “unavoidable” gap between their simulation and real-life traffic movements.

“The assumptions about traffic behaviour that were used in the simulation are not a 1:1 representation of reality. So, the agent will need to be adjusted accordingly,” Müller said. “If this is successful, the effects of scaling up will be huge. Just think of the large number of traffic lights even in a small town like Lemgo.”

The EU estimates that traffic jams cause economic damage totalling €100bn per year for its member states.