Automotive Ethernet System with Object Detection Using Deep Learning
In-vehicle networking is an essential block in the automotive industry nowadays; this is since the number of electronic control units (ECUs) in a modern car is continuously increasing. Some examples of these ECUs are the windows controls, the back camera, the bumper sensors, … etc. In fact, it is expected that by 2019 there would be an average of 42 ECUs that need to communicate in a car. Our project aims to introduce a new communication scheme, Automotive Ethernet, that is currently a topic of study in the industry. This scheme would fulfill the high bandwidth requirements for the automotive applications and would cope with the increased number of connected devices to the system.