Machine learning, Artificial Intelligence, Semantic Reasoning or other Knowledge creation mechanisms have recently been applied successfully to various connected automated automotive domains, such as hazard detection, automated driving or sensor fusion. Knowledge is highly promising but lacks cooperation to achieve its full potential. Instead of individually creating knowledge as done so far, what if knowledge could be shared, disseminated and used by other vehicles?
This doctoral work investigates means to characterize, create, and distribute knowledge in vehicular networks. Through selected use cases, this work aims at modeling and analyzing the benefits of knowledge in information gathering and dissemination, first to reduce the amount of information effectively required for knowledge, and second to enhance mechanisms involved in information-centric networks (ICN) or edge caching (EC) to fulfill the delay, reliability and availability required by next generation vehicular networks.
