Communication Based Sensing Technology Integrated In Levels of Vehicular Autonomy

Abstract

The automotive industry has been growing at a very fast pace with vehicles becoming autonomous and relying upon various sensors. With the increasing novelty in the automotive industry such as self-driving cars, an advanced communication system is a key requirement. Connected Vehicles (CVs) use big data exchange, increase mobility, and provide safety and an advanced transportation system. It is also an Internet of Things (IoT) technology that can communicate from Vehicle to Vehicle (V2V), Vehicle to Infrastructure (V2I), and falls under the umbrella of Vehicle to Everything (V2X) communication. SG/6G plays an important part in the communication of connected vehicles providing a wider range, greater bandwidth, and lower latency, enabling self-driving cars to communicate with each other. It opens reliable and approachable IOT for all consumers, providing a higher data rate, capacity, and lower latency with several uses. In this paper, we analyze communication in dif-ferent levels of vehicle autonomy, machine learning (ML), and deep learning in autonomous vehicles which can improve the performance of vehicles falling in existing levels of autonomy and the vehicles which are promised in the upcoming regime of SG/6G communication. This can open new horizons of research and development in the area of vehicular communication. We then observe the impact on radar measurements with different parameters which enables a fast and effective communication system.