Augmenting CCAM Infrastructure for Creating Smart Roads and Enabling Autonomous Driving

Autonomous vehicles and smart roads are not new concepts the undergoing development to empower for higher levels of automation has achieved initial milestones. However, transportation industry relevant research communities still require making considerable efforts create intelligent autonomous driving. To achieve results such efforts, CCAM infrastructure is a game changer plays key role in achieving In this paper, we present driving capabilities enhanced by infrastructure. Meaning thereby, lay down technical requirements infrastructure: identify right set sensory infrastructure, their interfacing, integration platform, necessary communication interfaces be interconnected with upstream downstream solution components. Then, parameterize road network infrastructures (and automated vehicles) advanced evaluated during work, under very distinct scenarios conditions. For validation, demonstrate machine learning algorithms mobility applications as traffic flow mobile demands. Consequently, train multiple linear regression models accuracy over 94% predicting aforementioned demands on daily basis. This therefore equips readers information required enhancing It also encourages guides implement towards creating