COALITION: CAVs-enabled Probabilistic Offloading of Congested Lanes for Reduced Urban Traffic Congestion

Soufiene Djahel, Yassine Hadjadj-Aoul, Renan Pincemin, Celimuge Wu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


The number of vehicles in developed countries has grown more rapidly than available road capacity, resulting in increased congestion, air pollution, and more accidents. A recent UN report predicts that the increasing size of cities and levels of population mobility will mean 2.9 billion vehicles on the road in cities alone by 2050. To mitigate the consequences of this increase without dramatically increasing the number of built roads, novel methods to better utilise existing road capacity are required. To that end, this paper introduces COALITION, a cognitive radio-enabled probabilistic offloading of congested lanes, as an innovative solution to efficiently handle traffic congestion in urban areas. This solution builds upon and improves the performance of our previous work, named CRITIC, and makes use of Electric Connected and Autonomous Vehicles (ECAVs) features to maximize the usage of road capacity through opportunistic exploitation of under-utilized reserved lanes while fostering the use of electric vehicles to support carbon neutral transportation objectives. Simulation results have proven the effectiveness of COALITION and its potential impact in real-world scenarios.
Original languageEnglish
Title of host publication2023 IEEE 98th Vehicular Technology Conference (VTC2023-Fall)
Number of pages7
Publication statusAccepted/In press - 31 Aug 2023
Event2023 IEEE 98th Vehicular Technology Conference - , Hong Kong
Duration: 10 Oct 202313 Oct 2023
Conference number: 98


Conference2023 IEEE 98th Vehicular Technology Conference
Abbreviated titleVTC2023-Fall
Country/TerritoryHong Kong
Internet address

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