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

Sanket Salvi, Pramod Jain Sa, S. S., Nithin D Jacob, Suhas M V, Shubham S, H. K
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Abstract

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.
基于计算机视觉的队列即服务实验研究
在过去的几十年里,电动汽车和非电动汽车的数量都在增加。自动驾驶汽车正变得越来越受欢迎,因为有人观察到,车辆自动驾驶可能是提高道路和燃油效率的可能解决方案。然而,由于解决方案的高成本性质,因此越来越需要低成本、易于适应和准备部署的解决方案。车辆队列行驶(vehicle Platooning)就是这样一种可能的解决方案,在这种方案中,一组车辆按照一定的模式行驶,以避免空气阻力,从而提高燃油效率。本文提出并评估了一种计算成本低廉的基于计算机视觉的距离不可知车辆跟随技术。还以附加服务的形式提出了支持底层方法的受云计算体系结构启发的业务模型。最后,构建一个移动应用程序来与建议的系统交互并监视服务的使用情况。该系统的性能是根据乘客的舒适度进行评估的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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