Smart vehicle monitoring and assistance using cloud computing in vehicular Ad Hoc networks

Abstract

The increasing number of on road vehicles has become a major cause for congestion accidents and pollution. Intelligent Transportation Systems (ITS) might be the key to achieve solutions that help in reducing these problems significantly. The connected vehicular networks stream is a rapidly growing field for research and development of various real-time applications. In this paper novel techniques have been proposed to serve the speed based lane changing collision avoidance and time of arrival (TOA) based localization in Vehicular Ad Hoc Networks (VANETs). As GPS requires clear line-of-sight for accurate services of positioning and localization applications we designed a Time of Arrival (ToA) based algorithm for areas where strong GPS signals are unavailable. Collision avoidance using automatic braking and camera-based surveillance are a few other applications that we addressed. The feasibility and the viability of the algorithms were demonstrated through simulations in Simulation of Urban Mobility (SUMO) and Network Simulator-2 (NS-2). We prototyped a working hardware and tested it on actual vehicles to assess the effectiveness of the proposed system. We designed a mobile app interface for the on-board unit for smart efficient and remote traffic monitoring. The integrated VANET Cloud Computing architecture acts as the platform for the proposed applications. © 2022 Elsevier B.V. All rights reserved.