Abstract: As the core nodes of urban traffic networks, intersections are confronted with the inefficiency of conventional traffic signal control and stop-yield mechanisms in catering to the rapid growth of traffic volume. Such traditional approaches also fail to adapt to the complex mixed-traffic scenarios involving connected and automated vehicles (CAV) and human-driven vehicles (HDV). This paper systematically reviews four key technologies for cooperative control, including vehicleto-everything (V2X) sensing and communication, cooperative control architecture design, mixed traffic flow modeling, and core algorithm optimization. It further conducts an in-depth analysis of the current research challenges, such as time delays in multi-source sensing and the imbalance between cooperative control architecture and algorithm efficiency. Accordingly, the development trends are proposed, including multimodal perception fusion, robust disturbance rejection control, and green low-carbon multi-objective optimization, providing references for further research in this field.

Key words: intelligent connected technology; intersections; mixed traffic flow; coordinated control

摘要： 作为城市交通网络的核心节点，交叉口面临着传统交通信号控制与停车让行机制难以 匹配交通流量的快速增长的问题，无法适配网联自动驾驶汽车（CAV）与人类驾驶车辆（HDV） 混行的复杂场景。文章系统梳理了车联网（V2X）感知与通信、协同控制架构设计、混合交 通流建模、核心算法优化等四大协同控制关键技术，深入分析当前研究面临的多源感知时延、 协同控制架构与算法效率失衡等挑战，在此基础上，提出多模态感知融合、鲁棒抗扰控制、 绿色低碳多目标优化发展方向，为该领域的进一步研究提供参考。

关键词: 智能网联技术；交叉口；混合交通流；协同控制