The George Washington University Center for Intelligent Systems Research (CISR) is developing a new, inconspicuous drowsy-driver detection system.
Using artificial neural networks that attempt to mimic the brain's neuron processing for pattern recognition, signal processing, and control systems, CISR researchers can track and classify steering behavior, the college said. The system can detect differences between drowsy versus non-drowsy driver behavior with 90% accuracy, researchers said.
CISR's drowsy driver experiments in the simulators have revealed drivers' steering behavior deteriorates for up to two to three minutes before an eminent crash. This dangerous behavior can be detected by CISR's smart signal processing.
Driver fatigue is the cause of an estimated 100,000 crashes annually, resulting in more than 40,000 injuries, according to the National Highway Transportation Safety Administration. The agency's Fatality Analysis Reporting System (FARS) indicates an annual average of 1,544 fatalities due to driver drowsiness-related accidents, with fatigue involved in 10% to 40% of crashes on long motorways and 15% of fatal single-vehicle truck crashes.