A UAV-Assisted Coordination Framework for Emergency Vehicle Priority and CAV Speed Optimization in Hybrid Human–Machine Driving on Expressways

Providing convenient passage conditions for emergency vehicles (EVs) is crucial for ensuring their safe and swift arrival at the rescue scene. To optimize the efficiency of EVs within mixed human-machine driving environments on expressways, an innovative collaborative control framework that synergizes uncrewed aerial vehicle (UAV) surveillance with multi-vehicle dynamic coordination strategies on expressways is proposed in this study. First, a real-time vehicle coordination framework is developed, leveraging UAV-aided data collection and control to enable EV yielding. Second, an integer nonlinear programming model is constructed to achieve coordinated control of human-machine hybrid traffic flows under dynamic constraints, and a rolling speed-coordinated robust optimization control (SROC) method is proposed to reduce the uncertainty caused by manual vehicle lane-changing. Then, a UAV-assisted trajectory planning approach is established, which integrates quintic polynomial modeling and uncertainty set analysis for hybrid traffic lane-changing. Next, an O-CAV (connected autonomous vehicle in the objective lane) speed adjustment mechanism is introduced to alleviate cascading deceleration effects on subsequent traffic. Finally, a bi-level particle swarm optimization (PSO) model is designed to validate EV avoidance algorithm effectiveness and platform performance. The results show that the method constructed in this study effectively enhances the traffic efficiency of EVs. The rolling SROC method reduces vehicle evacuation time by 17.3%, EV travel time by 12.5%, advances vehicle lane-changing time by 14.2%, and decreases acceleration by 21.0% compared with the one-time SROC method. Increasing the penetration rate and selecting appropriate initial positions for O-CAV and EV can effectively improve the traffic efficiency of EVs. Limited time delays do not significantly affect the applicability of the method. The travel distance of O-CAV increases by 25.1% after the implementation of the O-CAV speed recovery mechanism. These findings demonstrate the potential of UAV-assisted coordination to significantly enhance road safety and traffic efficiency in hybrid human-machine driving environments.