为针对不同的交通流状态选取合适的干线协调控制策略，基于线圈、视频、微波获取的多 源实时交通数据，利用车队离散模型和卡尔曼滤波模型获取各转向流量，采用HCM（Highway Capacity Manual） 公式计算排队长度和延误，并根据干道交叉口排队长度界定干线交通流状态： 欠饱和、接近饱和、过饱和，从而选择相应的干线协调控制策略：在欠饱和状态下采用最大绿波 带法，在接近饱和状态下采用改进的多带宽协调模型，在过饱和状态下采用排队占比最小模型。 以青岛市香港中路为例，通过VISSIM 仿真软件对算法和策略进行仿真测试和评价，结果表明： 不同交通状态下的干线协调策略与原始控制方案相比，平均延误减少了19.4%，平均停车次数减 少了22.8%，平均排队长度减少了7.4%。

In order to select appropriate arterial coordinate control strategies for different traffic flow states, based on the multi-source data from coil, video and microwave, the turning flows were obtained by using Platoon Dispersion Model and Kalman Filter Model, while the queue length and delay were cal⁃ culated through the formula in Highway Capacity Manual. Traffic flow states, including under-saturated, near-saturated and over-saturated, were identified according to queue length and then corresponding ar⁃ terial coordination strategies were chosen. The MAX Green Wave Band Model was used in the undersaturated state, the improved Bandwidth Coordination Model in the near-saturated state and the Minimal Queue Proportion Model in the over-saturate state. Taking Hong Kong Road in Qingdao as the example, simulation assessment results of VISSIM show the proposed model decreases the average delay by 19.4％, average number of stops by 22.8％and average queue length by 7.4％ compared with original strategies.