第29卷第4期2023年8月（自然科学版）JOURNALOFSHANGHAIUNIVERSITY(NATURALSCIENCEEDITION)Vol.29No.4Aug.2023DOI:10.12066/j.issn.1007-2861.2433•城市交通与环境•基于AnyLogic的轨道交通车站大客流瓶颈识别与疏散组织优化陈雷钰,张汝华,马明迪(山东大学齐鲁交通学院,山东济南250012)摘摘摘要要要:以济南园博园地铁站为研究对象,通过分析行人在不同设备设施处的行为特性,建立行人流模型,运用AnyLogic软件搭建仿真实验平台,针对3种不同类型的大客流情况进行紧急疏散模拟.仿真结果表明:在发生可预见性大客流情况下,当车站客流增加幅度较小时,站台层客流密度较大,可通过缩短列车运行间隔来提高车站疏散能力;而车站客流大幅增加时,车站安检区域发生拥堵,需增设一条安检通道.在发生不可预见性大客流时,车站大多数情况下都能满足疏散标准,但楼梯通道和出站闸机处仍是客流瓶颈所在,故高峰期客流疏散需要人为采取一定措施合理引导.通过模拟2种类型大客流情况下的车站应急疏散过程,识别出车站的瓶颈,并对瓶颈做出有效改善措施,对保障乘客疏散安全和效率、提高车站服务能力及制订应急疏散方案具有重要意义.关关关键键键词词词:地铁车站;应急疏散;瓶颈识别;疏散优化;AnyLogic中中中图图图分分分类类类号号号:U298文文文献献献标标标志志志码码码:A文文文章章章编编编号号号:1007-2861(2023)04-0694-11Anylogic-basedbottleneckidentificationandevacuationorganizationoptimizationoflargepassengerflowinrailtransitstationsCHENLeiyu,ZHANGRuhua,MAMingdi(SchoolofQiluTransportation,ShandongUniversity,Jinan250012,Shandong,China)Abstract:ThisstudytakesJinanYuanboyuanMetroStationastheresearchobjectandestablishesapedestrianflowmodelbyanalyzingthebehaviorcharacteristicsofpedestri-ansatdifferentequipmentandfacilities.AnyLogicsoftwareisusedtobuildasimulationexperimentplatformtosimulateemergencyevacuationforthreedifferenttypesoflargepassengerflowsituations.Thesimulationresultsrevealthefollowing:Inthecaseofpre-dictablelargepassengerflow,whentheincreaseinstationpassengerflowissmall,thepassengerflowdensityontheplatformlayerislarge,andtheevacuationcapacityofthestationcanbeimprovedbyshorteningthetrainrunninginterval.Whenthestationpassen-gerflowincreasessignificantly,thestationsecuritycheckareaiscon...
