Potential of Augmented Reality for Intelligent Transportation Systems

June 11, 2018 Β· Declared Dead Β· πŸ› Encyclopedia of Computer Graphics and Games

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Authors Adnan Mahmood, Bernard Butler, Brendan Jennings arXiv ID 1806.04724 Category cs.HC: Human-Computer Interaction Cross-listed cs.CY Citations 5 Venue Encyclopedia of Computer Graphics and Games Last Checked 4 months ago
Abstract
Rapid advances in wireless communication technologies coupled with ongoing massive development in vehicular networking standards and innovations in computing, sensing, and analytics have paved the way for intelligent transportation systems (ITS) to develop rapidly in the near future. ITS provides a complete solution for the efficient and intelligent management of real-time traffic, wherein sensory data is collected from within the vehicles (i.e., via their onboard units) as well as data exchanged between the vehicles, between the vehicles and their supporting roadside infrastructure/network, among the vehicles and vulnerable pedestrians, subsequently paving the way for the realization of the futuristic Internet of Vehicles. The traditional intent of an ITS system is to detect, monitor, control, and subsequently reduce traffic congestion based on a real-time analysis of the data pertinent to certain patterns of the road traffic, including traffic density at a geographical area of interest, precise velocity of vehicles, current and predicted travelling trajectories and times, etc. However, merely relying on an ITS framework is not an optimal solution. In case of dense traffic environments, where communication broadcasts from hundreds of thousands of vehicles could potentially choke the entire network (and so could lead to fatal accidents in the case of autonomous vehicles that depend on reliable communications for their operational safety), a fall back to the traditional decentralized vehicular ad hoc network (VANET) approach becomes necessary. It is therefore of critical importance to enhance the situational awareness of vehicular drivers so as to enable them to make quick but well-founded manual decisions in such safety-critical situations.
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