The Fraunhofer Institute for Optronics, System Technologies and Image Exploitation IOSB announced that the researchers in the institute branch for industrial automation INA in Lemgo are using artificial intelligence for smart traffic light control as part of the “KI4LSA” and “KI4PED” projects.
In the future, self-learning algorithms combined with new sensors should ensure better traffic flow and shorter waiting times, while providing improved safety for pedestrians at crossings. Arthur Müller, project manager and scientist at the Fraunhofer IOSB-INA, explains the DRL approach:
“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. 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 light’s control.”
The sensors that are currently in use — induction loop technology embedded in the road surface — provide only a rough impression of the actual traffic situation. The researchers at Fraunhofer IOSB-INA are working to address these problems. Instead of conventional sensors, they are using high-resolution cameras and radar sensors to more precisely capture the actual traffic situation, according to the release.
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 artificial intelligence, which replaces the usual rigid control rules. The AI uses deep reinforcement learning (DRL) algorithms, a method of machine learning that focuses on finding intelligent solutions to complex control problems.
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 neighboring lights that form a wider network.