AI-NAAV: An AI enabled Neurocognition Aware Autonomous Vehicle

Smart cars or Autonomous Vehicles (AV), capable of replicating human cognitive behaviour supported with a digital autopilot, shall make better drivers than humans in the near future. Driving in a complex and competitive environment is a challenging task. Driver health monitoring serves to be a pivotal contributor to autonomous driving. The human factors, including cognitive, psychomotor and physiological abilities, should be continuously monitored in an autonomous vehicle. On the road, neurocognitive impairments are very often reported, where the driver suffers a stroke or heart attack or unconsciousness and is incapacitated from driving. In this paper, we present AI-NAAV (AI enabled Neurocognition Aware Autonomous Vehicle), a deep learning assisted AI-empowered autonomous vehicle, which has the combined capabilities of a) detecting impaired driving capabilities in the driver b) shift to autopilot mode and hence enabling a safe drive. AI-NAAV is simulated on CARLA platform. The exteroceptive sensor combinations used for surround view, blind spot detection, rear collision warning and parking assistance, are used in a complementary mode for a safe drive on autopilot. The paper discusses the sensors deployed, methodologies and the results from simulations that perform an accurate transition of autonomy from Level 0 to Level 5, as defined in SAE (Society of Automotive Engineers).