The system uses deep reinforcement learning to learn from its mistakes. 🚦
Aston University researchers have engineered a new artificial intelligence system that could put an end to long queues at traffic lights,, meaning it actually adapts its processes when it is not doing well and continues improving when it makes progress.
“We have set this up as a traffic control game. The program gets a ‘reward’ when it gets a car through a junction. Every time a car has to wait or there’s a jam, there’s a negative reward. There’s actually no input from us; we simply control the reward system," said Dr. Maria Chli, a reader in Computer Science at Aston University.
The researchers noted that the new system significantly outperformed all other conventional methods of tackling traffic. This is because it was built on a state-of-the-art photo-realistic traffic simulator called Traffic 3D.This simulator has been trained to handle different traffic and weather scenarios and was, therefore, able to quickly adapt to real traffic intersections, making it effective in many real-world settings.
“The reason we have based this program on learned behaviors is so that it can understand situations it hasn’t explicitly experienced before. We’ve tested this with a physical obstacle that is causing congestion, rather than traffic light phasing, and the system still did well. As long as there is a causal link, the computer will ultimately figure out what that link is. It’s an intensely powerful system," concluded Dr.
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