Vehicle with Learning Capabilities: A Study on Advancement in Urban Intelligent Transport Systems

Vehicular Ad-hoc Network is subclass of Mobile Ad-hoc networks and plays a vital role in Intelligent Transportation System implementation for smart cities. In the transportation scenario finding out an optimized path and locating the malicious vehicle is a big challenge. Routing is challenging in this technology because of reasons like high mobility of the node, rapid change in topology, interruption in connectivity, etc. The mobility of nodes affects the link stability and congestion is the effect of limited node resources. It also degrades the Quality-of-Service performance. Unmanned Ariel Vehicle helps to mitigate such conditions with the combination of learning capability. In this paper, the contribution of the Unmanned Ariel Vehicle to a smart transportation system has been studied and the working of different protocols is also analyzed. This paper gives a complete overview of the advancement of the system and implementation concept of different smart traffic management systems in urban areas.