Cooperative Control Strategies for Connected Automated Vehicles and Adaptive Traffic Light Systems in Mixed Traffic Intersections

With the gradual increase in the market penetration rate of Connected and Autonomous Vehicles(CAVs), the constraints imposed by fixed non-variable timing signals hinder additional enhancements in traffic efficiency. The prolonged coex-istence of CAVs and Human-Driven Vehicles(HDVs) necessitates the development of a tailored traffic light and CAV cooperation decision-making method for mixed traffic scenarios. This paper introduces a cooperative control algorithm designed specifically for mixed traffic scenarios, addressing traffic lights and mixed traffic. Initially, this paper proposes an analysis of the convergence time and feasibility boundaries for mixed platoons across various speed trajectories and mixed platoon sizes. Furthermore, a mixed platoon depth-first spanning tree algorithm is proposed, considering mixed platoons and free-driving HDVs as fundamental control units. Utilizing spanning tree geometry, communication topology, vehicle dynamic models, and safety constraints, an optimal control framework for mixed platoons is developed to realize traffic light and CAV cooperation decision-making in mixed traffic scenarios. This approach significantly enhances traffic efficiency and fuel economy, while also reducing the total evacuation time compared to alternative methods, as demonstrated by numerical simulation results.