  On-ramp merging areas are deemed to be typical bottlenecks for freeway
networks 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 and
precise motion control, hold an opportunity to promote ramp merging operation
through enhanced cooperation. The existing CAV cooperation strategies are
mainly designed for single-lane freeways, although multilane configurations are
more prevailing in the real-world. In this paper, we present a flow-level CAV
coordination 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 for
enhanced benefits in traffic flow stability and efficiency. The strategy is
formulated under an optimization framework, where the optimal control plan is
determined based on real-time traffic conditions. The impacts of tunable model
parameters on the produced control plan are discussed in detail. The efficiency
of the proposed multilane strategy is demonstrated in a micro-simulation
environment. The results show that the coordination can substantially improve
the overall ramp merging efficiency and prevent recurrent traffic congestions,
especially under high traffic volume conditions.
