A Hierarchical Control Framework for Proactive Traffic Flow Organization on Freeway

Traditional freeway traffic management relies on indirect measures inadequate for proactive congestion prevention. However, the emergence of a connected vehicle environment enables direct and reliable control over a subset of vehicles, facilitating a paradigm shift towards proactive traffic flow organization. This paper proposes a two-layer hierarchical framework for flow shaping on freeways. The upper Flow Strategy Layer identifies macroscopic lane imbalances and computes an optimal flow redistribution plan to minimize total system delay. The lower Vehicle Execution Layer translates this plan into microscopic actions, using a novel multi-criteria mechanism to prioritize vehicles for lane changes based on feasibility, local traffic impact, and path consistency. Commands are then implemented through safe, cooperative lane changes. Validated in a SUMO simulation of a 9.3 km freeway, the framework effectively mitigates congestion and adaptively intervenes. This study confirms the potential of using deterministic control over high-compliance vehicles to systematically organize traffic flow and enhance freeway efficiency.