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On-ramp merging areas are deemed to be typical bottlenecks for freewaynetworks due to the intensive disturbances induced by the frequent merging,weaving, and lane-changing behaviors. The Connected and Autonomous Vehicles(CAVs), benefited from their capabilities of real-time communication andprecise motion control, hold an opportunity to promote ramp merging operationthrough enhanced cooperation. The existing CAV cooperation strategies aremainly designed for single-lane freeways, although multilane configurations aremore prevailing in the real-world. In this paper, we present a flow-level CAVcoordination strategy to facilitate merging operation in multilane freeways.The coordination integrates lane-change rules between mainstream lanes,proactive creation of large merging gaps, and platooning of ramp vehicles forenhanced benefits in traffic flow stability and efficiency. The strategy isformulated under an optimization framework, where the optimal control plan isdetermined based on real-time traffic conditions. The impacts of tunable modelparameters on the produced control plan are discussed in detail. The efficiencyof the proposed multilane strategy is demonstrated in a micro-simulationenvironment. The results show that the coordination can substantially improvethe overall ramp merging efficiency and prevent recurrent traffic congestions,especially under high traffic volume conditions.

Flow-level Coordination of Connected and Autonomous Vehicles in Multilane Freeway Ramp Merging Areas