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大客流干扰下多层公交-地铁网络的韧性评估

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为评估车站失效对公交-地铁网络结构和服务质量的影响,研究大客流干扰下公交-地铁网络的韧性是十分必要的.提出有向时间加权的多层公交-地铁网络建模方法,采用改进的耦合映像格子模型,从乘客和运营视角分别提出乘客出行效率比和网络服务效率比作为韧性评估指标,采用德尔菲法-熵权法和博弈论综合赋权法确定指标的综合权重.构建以多层公交-地铁网络韧性指标最大化为目标的时序优化模型,采用自适应遗传算法进行求解.以西安市多层公交-地铁网络为例,考虑大客流提出4种干扰情景,对比分析最优恢复策略与随机恢复策略、优先恢复策略在4种大客流干扰场景下对网络韧性恢复效果的差异.结果表明:在4种大客流干扰场景下,仅考虑车站在运营网络中的重要程度无法得到最优策略,应以网络韧性最大化角度构建模型求解最优恢复次序,最大程度地减少网络性能的损失;增加恢复资源可以缩短恢复时间和提高恢复效率,但恢复资源的增加与网络韧性的提升不成正比.研究结论可以为公交、地铁网络的韧性评估与抢修恢复提供决策依据.
Resilience Assessment of Multilayer Bus-metro Network Under Large Passenger Flow Interference
To assess the impact of station failure on the structure and service quality of a bus-metro network,it is necessary to study the stability of the bus-metro network under large passenger flow disturbances.A directed time-weighted multilayer bus-metro network modelling method is proposed,and an improved coupled mapping lattice model is employed.Two resilience assessment indicators,passenger travel efficiency ratio and network service efficiency ratio,are proposed from the perspective of passengers and operation.The composite weights of the indicators were determined using the Delphi-entropy weighting method.A time series optimization model was constructed with the objective of maximizing the resilience indicators of the multilayer bus-metro network,and an adaptive genetic algorithm was applied to solve the developed model.With the Xi'an multilayer bus-metro network as an example,four types of disturbance scenarios are proposed considering a large passenger flow,and the differences in network resilience recovery effects between the optimal recovery strategy and random and priority recovery strategies were compared and analyzed.The optimal strategy cannot be obtained by only considering the importance of stations in the operation network under the four types of large passenger flow disturbance scenarios.A model should be constructed to solve the optimal recovery order from the perspective of network resilience maximization to minimize the loss of network performance.Increasing recovery resources can reduce the recovery time and improve the recovery efficiency,but the increase in recovery resources is not proportional to the improvement in network resilience.The conclusions can provide a decision-making basis for the resilience assessment and emergency repair of a bus-metro network.

traffic engineeringmultilayer bus-metro networkresilience assessmentlarge pas-senger disturbanceimproved coupled mapping lattice model

马壮林、程会媛、邵逸恒、刘悦、程泽农、马飞

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长安大学运输工程学院,陕西西安 710064

比亚迪汽车有限公司,陕西西安 710119

交通运输部科学研究院,北京 100029

城市公共交通智能化交通运输行业重点实验室,北京 100029

长安大学经济与管理学院,陕西西安 710064

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交通工程 多层公交-地铁网络 韧性评估 大客流干扰 改进的耦合映像格子模型

国家社会科学基金项目陕西省自然科学基础研究计划项目城市公共交通智能化交通运输行业重点实验室开放课题

18BGL2582024JC-YBMS-3592022-APTS-05

2024

10.19721/j.cnki.1001-7372.2024.06.022

中国公路学报
中国公路学会

中国公路学报

CSTPCD北大核心
影响因子：1.607
ISSN：1001-7372
年,卷(期)：2024.37(6)
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