Cloud-enabled vehicular congestion estimation: An ITS application

Milad Mahbadi, M. M.Manohara Pai, Sanoop Mallissery, Radhika M. Pai

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

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.

Original languageEnglish
Title of host publication2016 IEEE Canadian Conference on Electrical and Computer Engineering, CCECE 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Volume2016-October
ISBN (Electronic)9781467387217
DOIs
Publication statusPublished - 31-10-2016
Event2016 IEEE Canadian Conference on Electrical and Computer Engineering, CCECE 2016 - Vancouver, Canada
Duration: 14-05-201618-05-2016

Conference

Conference2016 IEEE Canadian Conference on Electrical and Computer Engineering, CCECE 2016
CountryCanada
CityVancouver
Period14-05-1618-05-16

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All Science Journal Classification (ASJC) codes

  • Hardware and Architecture
  • Electrical and Electronic Engineering

Cite this

Mahbadi, M., Pai, M. M. M., Mallissery, S., & Pai, R. M. (2016). Cloud-enabled vehicular congestion estimation: An ITS application. In 2016 IEEE Canadian Conference on Electrical and Computer Engineering, CCECE 2016 (Vol. 2016-October). [7726829] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CCECE.2016.7726829