Abstract
Autonomous vehicles (AVs) are revolutionizing transportation by offering increased safety and efficiency. However, they face challenges in detecting and responding to road hazards. The unpredictable nature of road hazards can lead to accidents and inefficiencies in autonomous vehicle operations. Current systems often rely on isolated sensors and historical data, which can be insufficient for real-time hazard detection.
Researchers at FAU have developed a Road-Risk Awareness System (RAS) that enhances AV safety by providing real-time hazard warnings. This system leverages cloud computing, AI, and machine learning to analyze data from diverse sources, such as state and federal transportation departments, to predict potential hazards. It quantifies risk factors and provides timely warnings to AVs, significantly enhancing their ability to avoid accidents. This innovation leads to improved safety, reduced insurance costs, and increased operational efficiency for autonomous vehicles.
FAU seeks to advance this innovation into the marketplace through licensing or development partnerships.
Benefit
Enhanced Safety - Real-time hazard detection and alertsOperational Efficiency - Reduces accident-related delaysCost Reduction - Lowers insurance premiumsMarket Application
Autonomous TrucksRobotaxi ServicesAutonomous Delivery Vehicles
Brochure
