为提升高速公路应急车道的灵活性及车道资源利用率，并适应含智能网联车辆（Connected and Automated Vehicles, CAV）的混合交通流，提出了一种虚拟应急车道管控策略。首先，基于应急车辆优先的动态路权分配机制，建立事故位置主导的右侧车道动态开放模型；接着，采用元胞自动机构建含有应急车辆的混合交通流仿真模型；最后，通过MATLAB仿真平台对实际4车道高速公路设定不同交通密度和智能网联小汽车比例，验证该策略的可行性和有效性。仿真结果表明：与传统固定应急车道策略相比，该策略可显著提升交通通行能力；当卡车占车辆总数的20%、CAV占小汽车数量的30%时，系统流量峰值可达8 902.8 pcu/h，较传统策略提升30.2%，低中等密度（0~80 veh/km）范围内，拥堵车辆比例降低10%~27%；此外，在不同CAV比例下，该策略的通行能力均优于传统方案，系统平均通行能力提升约32%，最高提升幅度达36.6%。结果表明，该策略在提升道路通行能力和抗拥堵能力方面具有显著效果。

In order to enhance the flexibility of emergency lanes on expressways, improve lane resources utilization, and adapt to the mixed traffic flow containing Connected and Automated Vehicles (CAV), a virtual emergency lane control strategy is proposed in the study. Firstly, the study establishes a dynamic right lane opening model dominated by the accident location based on the dynamic right-of-way allocation mechanism of emergency vehicles priority. Then, it adopts cellular automata to construct a mixed traffic flow simulation model containing emergency vehicles. Finally, different traffic densities and proportions of CAV are set for the actual four-lane expressway through the MATLAB simulation platform, to verify the feasibility and validity of the strategy.The simulation results show that compared with the traditional fixed emergency lane strategy, this strategy can significantly improve the traffic capacity. As trucks account for 20% of the total vehicles, and CAV account for 30% of the cars (including HV), the peak system traffic flow can reach 8 902.8 pcu/h, which is 30.2% higher than the traditional strategy; the proportion of congestion is reduced by 10%~27% in the range of low to medium density (0~80 veh/km). In addition, under different CAV ratios, the traffic capacity of this strategy is superior to traditional scheme, with an average system capacity improvement of about 32% and a maximum improvement of 36.6%. The results show that the strategy has a significant effect in improving the highway capacity and congestion resistance.