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DTCMS: Dynamic traffic congestion management in Social Internet of Vehicles (SIoV)

Roopa, MS and Ayesha Siddiq, S and Buyya, R and Venugopal, KR and Iyengar, SS and Patnaik, LM (2021) DTCMS: Dynamic traffic congestion management in Social Internet of Vehicles (SIoV). In: Internet of Things (Netherlands), 16 .

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Official URL: https://doi.org/10.1016/j.iot.2020.100311


With the augmentation of traffic exponentially, we observe that traffic congestion does not guarantee road safety or enhance the driving experience. In the recent past, Social Internet of Vehicles (SIoV), a social network paradigm permits social relationships among every vehicle in the network or with any road infrastructure to render a radically useful environment. SIoV is beneficial for the drivers, in improving road safety, avoiding mishaps, and providing a friendly-driving experience. In this paper, we propose a traffic scheduling algorithm to gain the maximum throughput for the flow of vehicles at a road intersection with the formation of social relationships among the vehicles and with the Road Side Units (RSUs). The algorithm estimates the flow rate of vehicles for lanes at the intersections exploiting the volume of traffic moving through the given road. A condition matrix is designed for the consistent movement of traffic considering different routes on the road segments. Social relationships are devised on various aspects of travel needs for a safe, agile, and better driving experience. Simulation results illustrate the efficacy of the proposed scheme with high traffic throughput, service rate and reduce the total travelling time, delay time, and average waiting time in comparison with Dynamic Throughput Maximization Framework and Adaptive Traffic Control Algorithm.

Item Type: Journal Article
Publication: Internet of Things (Netherlands)
Publisher: Elsevier B.V.
Additional Information: The copyright for this article belongs to Elsevier B.V.
Keywords: Dynamic traffic control; Social Internet of Vehicles (SIoV); Social relationships;
Department/Centre: Division of Electrical Sciences > Computer Science & Automation
Date Deposited: 18 Apr 2023 07:08
Last Modified: 18 Apr 2023 07:08
URI: https://eprints.iisc.ac.in/id/eprint/80649

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