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CRITIC: A Cognitive Radio Inspired Road Traffic Congestion Reduction Solution

Abstract : According to recent forecasts, constant population growth and urbanization will bring an additional load of 2.9 billion vehicles to road networks by 2050. This will certainly lead to increased air pollution concerns, highly congested roads putting more strain on an already deteriorated infrastructure, and may increase the risk of accidents on the roads as well. Therefore, to face these issues we need not only to promote the usage of smarter and greener means of transportation but also to design advanced solutions that leverage the capabilities of these means along with modern cities' road infrastructure to maximize its utility. To this end, we propose an original Cognitive Radio inspired algorithm, named CRITIC, that aims to mimic the principle of Cognitive Radio technology used in wireless networks on road networks. The key idea behind CRITIC is to temporarily grant regular vehicles access to priority (e.g., bus or carpool) lanes whenever they are underutilized in order to reduce road traffic congestion. The performance evaluation results of CRITIC using grid and random road network topologies with varying traffic load have proven its effectiveness.
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https://hal.inria.fr/hal-01934058
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Submitted on : Sunday, November 25, 2018 - 7:43:18 AM
Last modification on : Friday, February 26, 2021 - 3:30:26 AM
Long-term archiving on: : Tuesday, February 26, 2019 - 12:13:30 PM

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Soufiene Djahel, Adam Jones, Yassine Hadjadj-Aoul, Ashfaq Khokhar. CRITIC: A Cognitive Radio Inspired Road Traffic Congestion Reduction Solution. WD 2018 - 10th Wireless Days Conference, Apr 2018, Dubai, United Arab Emirates. pp.151-157, ⟨10.1109/WD.2018.8361711⟩. ⟨hal-01934058⟩

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