Implementing passenger flow control strategies is an effective approach to reducing commuter travel delays and ensuring crowd safety in a congested metro network. Due to the intricacy of the interweaving of passenger flows between various lines and stations, the development of a scientific passenger flow control strategy is challenging in the networked mode of operation. The first-in-first-out (FIFO) rule can ensure service fairness and optimal operation by accurate modeling passenger queuing dynamics, but it is rarely considered in existing studies. Inspired by the traditional dynamic traffic assignment models, we propose a novel passenger flow control model with the FIFO rule to find a more reasonable control strategy for a metro network. Unlike road traffic systems, the FIFO rule is formulated as a set of linear constraints to explicitly capture the passenger queuing properties at origin stations. The passenger flow control problem with the FIFO rule is then modeled as a mixed integer linear programming model, which can significantly reduce the model complexity. To reach a high-quality solution, we propose an efficient rolling horizon decomposition approach. In the algorithm, the planning horizon is rolled forward from the current time, and the effects of subsequent periods are considered at each iteration. Besides, a dynamic procedure for loading passengers is developed to evaluate the bounds between the proposed approach and other flow control strategies. The proposed model and algorithm are then applied to solve the problems in test and real metro networks. The numerical results demonstrate the validity of the model’s properties and the algorithm’s performance.

中文翻译：

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FIFO 条件下城域网动态流控模型及算法


在拥挤的地铁网络中，实施客流控制策略是减少通勤出行延误和确保人群安全的有效方法。由于各线路和车站之间客流交织的复杂性，在网络化运营模式下，开发科学的客流控制策略具有挑战性。先进先出 （FIFO） 规则可以通过精确建模乘客排队动态来确保服务公平和最优运营，但在现有研究中很少考虑。受传统动态交通分配模型的启发，我们提出了一种具有 FIFO 规则的新型客流控制模型，以寻找更合理的地铁网络控制策略。与道路交通系统不同，FIFO 规则被表述为一组线性约束，用于显式捕获始发站的乘客排队属性。然后将 FIFO 规则的客流控制问题建模为混合整数线性规划模型，这可以显著降低模型复杂性。为了获得高质量的解决方案，我们提出了一种高效的滚动水平分解方法。在该算法中，计划跨度从当前时间向前滚动，并在每次迭代时考虑后续期间的影响。此外，还开发了一种加载乘客的动态程序，以评估所提出的方法与其他流量控制策略之间的界限。然后，将所提出的模型和算法应用于解决测试和真实城域网中的问题。数值结果证明了模型属性的有效性和算法的性能。