Driver behaviour detection and vehicle rating using multi-UAV coordinated vehicular networks

Road accidents account for more than 2% of the total deaths across the globe with more than a million deaths each year due to road mishaps and improper traffic management. Traffic management is a major problem faced by modern cities due to a large number of vehicles operating at the same time. One of the major issues for road mishaps is driver's behaviour and skills. Thus, tracking vehicles and analyzing the driver behaviour is required for proper regulation of traffic. Some of the solutions are provided using infrastructure-based vehicular ad hoc networks (VANETs). However, their operations are constrained by the traffic itself, thus, limiting their scope. A new solution by forming VANETs using multiple unmanned aerial vehicles (UAVs) is proposed which is independent of using road side units (RSUs) for communications. The proposed approach is analyzed using simulations as well as real-time dataset. UAVs-coordinated VANETs is first proposed in this paper.Next, multi-UAVs coordinated behaviour analysis approach is presented.The approach can be scaled to n number of parameters based on the requirement.The proposed approach is analyzed using both simulative and real time data sets.This approach helps in lowering the number of accidents because of naive drivers.