Driver assistance through an autonomous safety management framework

摘要

The increasing need for mobility has revealed inefficiencies related to transportation, such as congestion, accidents and environmental pollution. An innovative solution to achieve more efficient and safer mobility is to attribute to vehicles embedded intelligence functionality. This paper introduces a framework for providing intelligence to vehicles. The framework operates by collecting contextual, profile, and policy information from the surrounding vehicles, traffic lights and road signs, processes it intelligently, integrating knowledge and experience, and visually informs the driver proactively for forthcoming emergencies, based on a set of warning functions. In order to reach the required driver-assisting decisions, a heuristic algorithm is used, based on rules-of-thumb. Extensive simulation results showcase the algorithm's advantages compared to current ADAS solutions in terms of response times, simplicity and scalability, since it acts proactively thus reducing response times, while it utilizes existing 3G/4G/5G infrastructures.