重大疫情下的列车动态编组与调度

为了降低疫情大爆发背景下旅客在乘坐城市轨道交通出行的过程中感染疾病的风险, 以列车编组与调度为研究对象, 提出重大疫情下基于虚拟编组的列车动态编组与调度方法; 为了提高城市轨道交通列车编组与调度的灵活性, 应用虚拟编组技术对城市轨道交通列车进行编组; 建立了基于客流的列车动态编组非线性规划模型, 对城市轨道交通列车的调度进行优化, 以提高城市轨道交通的运输效率, 降低车站人员密度, 进而降低疾病的感染风险; 应用改进的Wells-Riley模型进行感染分析; 应用基于社会力的行人运动模型对改进的Wells-Riley模型中的相关参数进行计算, 用于分析虚拟编组动态调度下旅客地铁出行全过程的感染风险; 使用MATLAB对虚拟编组制式下的传染概率进行仿真并与传统制式下的传染概率进行对比。研究结果表明; 虚拟编组技术可以显著提高城市轨道交通列车运输效率, 可将列车间追踪时间间隔缩短至34.6 s, 基于虚拟编组的列车动态编组与调度方法可以有效降低旅客的感染风险, 在相同条件下应用所提方法旅客的感染风险仅为传统方式的85.1%, 在车厢和通道中的感染风险分别为传统方式的50.0%和8.7%。如果将提出的方法配合错峰出行和客流控制及进站防疫检测等措施, 可以进一步降低旅客的感染风险。 

Dynamic marshalling and scheduling of trains in major epidemics

In order to reduce the infection risk of passengers who travel by urban rail transit in the context of the global epidemics outbreak, the marshalling and scheduling of trains were taking as the research objects, and a dynamic marshalling and scheduling method of trains based on the virtual coupling under the major epidemic was proposed. In order to improve the flexibility of train marshalling and scheduling in urban rail transit, the virtual coupling was applied to the train marshalling in urban rail transit. The nonlinear programming model of train dynamic marshalling based on the passenger flow was established to optimize the scheduling of urban rail transit trains, so as to improve the transport efficiency of urban rail transit, reduce the station personnel density and consequently reduce the risk of disease infection. The improved Wells-Riley model was used for the infection analysis. The pedestrian movement model based on the social force was used to calculate the parameters in the improved Wells-Riley model, so as to analyze the infection risk of passengers who travel under the dynamic marshalling of virtual coupling. The infection probability under the virtual coupling system was simulated and compared with the result under the traditional method by using the MATLAB. Analysis result shows that the virtual coupling technology can significantly improve the train transport efficiency of urban rail transit and shorten the tracking time interval between trains to 34.6 s. The dynamic marshalling and scheduling method of trains based on the virtual coupling can effectively reduce the infection risk of passengers. In the same conditions, the infection risk of passengers from the proposed method is only 85.1% of that from the traditional way, and the infection risks in the carriages and channel are 50.0% and 8.7% of those from the traditional way, respectively. If the proposed method is combined with the measures such as the control of off-peak travel and passenger flow, the in-station epidemic prevention and testing, the infection risk of passengers can reduce further.