Abstract
Accomplishing autonomous cars could make future cars that understand their environment. This indeed solves problems that were closely around the cars but it still doesn’t address basic commute problems such as traffic congestions, long commutes, lack of regional information, unknown road situations that impact safety and lead to accidents. A collective and cognitive intelligent agent long side the driver/driverless is imminent. In this paper, we call them as copilots who share their knowledge by means of not just vehicle-to-vehicle communications but by vehicle-to-vehicle conversations. Once every vehicle houses a supercomputer with ADAS functions and is connected to the internet, a future car is to evolve into a highly adaptive co-pilot that is always looking out for its passengers’ comfort and safety inside and outside the car for the entire mission. Whether it is an autonomous vehicle or self-piloted vehicle, a co-pilot who could learn, teach other cars and having a conversation with other cars co-pilot on the road is helpful. Teaching Cars are the teacher co-pilots of the cars that has recent regional specific information and rules (speed limits, local maps, mountain roads, road conditions, weather etc.,) that they learned from other cars/servers or from their ADAS functions through sensors, sensors, cameras, radar, LIDAR, GPS receivers, and sophisticated ECUs [4]. The Learning Cars are the learner co-pilots of the cars that broadcast ‘on-demand’ request to the teacher co-pilots for any trainable information. The received information is used to train itself with the new unknown regional knowledge.