An early warning system for self-driving vehicles developed by researchers at Germany's Technical University of Munich (TUM) leverages artificial intelligence (AI) to learn from real traffic situations.
During tests on public roads, the researchers identified about 2,500 situations that required driver intervention; they found the system issued warnings about potentially critical situations seven seconds in advance with more than 85% accuracy.
Using a recurrent neural network, the system recognizes patterns in the data collected by sensors and cameras and will warn drivers if it identifies a situation the control system has had difficulty handling in the past.
TUM's Eckehard Steinbach said, "We limit ourselves to the data based on what actually happens and look for patterns. In this way, the AI discovers potentially critical situations that models may not be capable of recognizing, or have yet to discover."
From Technical University of Munich (Germany)
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