@inproceedings{32b147a829b2431f9653ab01edf743cd,
title = "Cloud-enabled vehicular congestion estimation: An ITS application",
abstract = "Increased traffic and hence congestion is a major problem in cities or urban areas. To mitigate this problem of congestion a real-time traffic density estimation model is essential. This research proposes one such model for estimating the traffic congestion level with the help of Vehicular Ad-hoc Network (VANET) and Cloud Computing. In this work, a novel architecture and algorithm has been proposed to estimate the density of vehicles on the road and the average speed. The fuzzy algorithm is then used to get the level of congestion. The algorithms are simulated using Network Simulator 3 (NS3) and Simulation of Urban Mobility (SUMO) to estimate the congestion level in an area of a city. The model proposed is deployed on Cloud and can be made available as Software as a Service (SaaS) in future.",
author = "Milad Mahbadi and Pai, \{M. M.Manohara\} and Sanoop Mallissery and Pai, \{Radhika M.\}",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 2016 IEEE Canadian Conference on Electrical and Computer Engineering, CCECE 2016 ; Conference date: 14-05-2016 Through 18-05-2016",
year = "2016",
month = oct,
day = "31",
doi = "10.1109/CCECE.2016.7726829",
language = "English",
volume = "2016-October",
series = "Canadian Conference on Electrical and Computer Engineering",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2016 IEEE Canadian Conference on Electrical and Computer Engineering, CCECE 2016",
address = "United States",
}
