An aerial intelligent relay-road side unit (AIR-RSU) framework for modern intelligent transportation system

Abstract

In transportation environment, Intelligent Transportation System (ITS) is being used in various stages of every transport mode (road, rail, air & sea). The aim of intelligent transportation system is to provide the On-Road Vehicles (ORVs) with reliable Internet access connectivity, emergency notification and other safety information via infrastructure-based Road Side Units (RSUs). In the past decade, intelligent transportation system has been started in many countries where RSUs are provided with all type of communication services to connect, compute, communicate and share the information between its neighboring RSUs and on-road vehicles. However, there are certain diffcuilties in which the information cannot be delivered reliably such as Line Of Sight (LOS) communication with on-road vehicles, packet loss, latency, retransmission overhead and multiple target tracking of objects over time-to-time etc. Thus, the intelligent transportation system becomes a complex network of entities. Modern intelligent transportation systems use relay-RSU nodes (i.e., small sized Unmanned Aerial Vehicles) also referred as RRSU node network deployed between satellites and on-road vehicles as they provide many advanages like coverage, reliability and information sharing without depending more on knowledge provided by satellites. In this paper, a novel Aerial Intelligent Relay-Road Side Unit (AIR-RSU) framework has been proposed to determine the network connectivity status level and analyze the communication link stability among RRSUs, and between RRSUs and on-road vehicles for every time instants Ti based on certain performance metrics discussed in this paper. The proposed AIR-RSU framework holds the precise status/information about the network connectivity needed in the transportation environment carefully and effectively accounting the frequent changes in positions. The performance of the proposed AIR-RSU framework is evaluated using rectangle waypoint mobility model for on-road vehicles and steady state random waypoint mobility model for RRSU nodes, which measures the network connectivity status and the performance metrics periodically. Furthermore, a comparative analysis is done to both individual nodes and entire network in terms of network load.