Pl-aaS: An Experimental Study of Computer Vision based Platooning as a Service

The past decades have witnessed an increase in the number of electric and non-electric vehicles. Autonomous vehicles are becoming more popular as it was observed that vehicular autonomy could be the possible solution towards increasing road and fuel efficiency. However, due high-cost nature of the solution there is an increasing need for low cost, easy to adapt, and ready to deploy solutions. Vehicular Platooning can be one such possible solution, where a group of vehicles travel in a pattern to avoid air resistance and thus increase fuel efficiency. In this paper, a distance agnostic computationally inexpensive computer vision-based vehicle following technique is proposed and evaluated. A cloud-computing architecture-inspired business model supporting the underlying methodology is also proposed in the form of add-on service. Finally, a mobile application is built to interact with the proposed system and monitor the service usage. The performance of the proposed system is evaluated based on Rider’s Comfort level.