Mobile Crowdsensing for Traffic Congestion Control
Kuldeep Jha1, Niranjan Ray2
1Kuldeep Jha, Department of Computer Science and Engineering, Kalinga Institute of Industrial Technology, Deemed to be University, Bhubaneswar, India.
2Niranjan Ray, Department of Computer Science and Engineering, Kalinga Institute of Industrial Technology, Deemed to be University, Bhubaneswar, India.
Manuscript received on 15 May 2019 | Revised Manuscript received on 22 May 2019 | Manuscript Published on 02 June 2019 | PP: 531-535 | Volume-8 Issue-7S2 May 2019 | Retrieval Number: G10900587S219/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Traffic Congestion Control is a major challenge for many urban transportation systems. The variations of volume and speed of vehicles during peak/normal hours severely affects the traffic monitoring activities. Also, due to increase in vehicular density and presence of other physical constraints resulting into traffic congestion. The existing traffic control mechanisms are not that much of efficient to tackle the congestions. In this paper, a mobile crowd sensing based approach is used to monitor and control the traffic congestions. To effectively control congestion and balance the traffic load, we have proposed a mechanism that reduces the congestion and provides better solution to handle this. The proposed approach uses Mobile Crowdsensing and Cloud computing technology to achieve better execution.
Keywords: Congestion Control, Cloud Computing, Traffic load Balancing
Scope of the Article: Computer Science and Its Applications