安全容量限制下人群分类对应急疏散影响研究
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摘要
为了在疏散路段与交叉路口安全容量限制下研究人群分类对应急疏散计划的影响,首先,根据待疏散人员的年龄、性别、健康状况、知识结构和对疏散信息的掌握程度进行人群分类,为不同类别的人群设置不同的疏散优先权;其次,考虑疏散优先权和安全容量,建立了基于离散时间的动态应急疏散混合整数规划模型;最后,通过疏散场景设计与仿真,分析人群分类疏散策略对疏散效率的影响。结果表明,相较于不分类的疏散策略,对人群进行分类的疏散策略的疏散效率约下降10%。设置交叉口缓存容量与增大疏散路段能力能有效提高疏散效率,降低疏散人员的等待时间,研究结论对设计应急疏散策略和疏散网络具有参考价值。
This work studies the impacts of population classification on emergency evacuation plans under safety capacities of evacuation routes and road intersections. Firstly,evacuees are classified based on their ages,genders,health statuses,knowledge structures,and degrees of mastering evacuation information. Evacuation priority is set for different classes of populations.Furthermore,by considering evacuation priorities and safety capacities,this paper proposes a mixed integer programming model for the dynamic emergency evacuation whose planning time is divided into discrete intervals. Finally,through designing scenarios and simulations,the impacts of population classification strategy on evacuation efficiency are analyzed. Experimental results show that the population classification strategy leads to a decrease of 10% in the evacuation efficiency,compared to a strategy of no classification. Setting the caching capacity of intersections and increasing the safety capacity of evacuation routes can significantly improve the evacuation efficiency and reduce the waiting time of evacuees. The result is valuable to the design of emergency evacuation strategies and networks when considering population classification.
This work studies the impacts of population classification on emergency evacuation plans under safety capacities of evacuation routes and road intersections. Firstly,evacuees are classified based on their ages,genders,health statuses,knowledge structures,and degrees of mastering evacuation information. Evacuation priority is set for different classes of populations.Furthermore,by considering evacuation priorities and safety capacities,this paper proposes a mixed integer programming model for the dynamic emergency evacuation whose planning time is divided into discrete intervals. Finally,through designing scenarios and simulations,the impacts of population classification strategy on evacuation efficiency are analyzed. Experimental results show that the population classification strategy leads to a decrease of 10% in the evacuation efficiency,compared to a strategy of no classification. Setting the caching capacity of intersections and increasing the safety capacity of evacuation routes can significantly improve the evacuation efficiency and reduce the waiting time of evacuees. The result is valuable to the design of emergency evacuation strategies and networks when considering population classification.
引文
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[15] WANG J H,LO S M,SUN J H,et al. Qualitative simulation of the panic spread in large-scale evacuation[J]. Simulation,2012,88(12):1465-1474.
[16] KINATEDER M,PAULI P,MULLER M,et al. Human behaviour in severe tunnel accidents:effects of information and behavioural training[J]. Transportation Research Part F:Traffic Psychology and Behaviour,2013(17):20-32.
[17] PIRES T T. An approach for modeling human cognitive behavior in evacuation models[J]. Fire Safety Journal,2005,40(2):177-189.
[18] KOBES M,HELSLOOT I,DE VRIES B,et al. Way finding during fire evacuation; an analysis of unannounced fire drills in a hotel at night[J]. Building and Environment,2010,45(3):537-548.
[19] NILSSON D,JOHANSSON M,FRANTZICH H. Evacuation experiment in a road tunnel:a study of human behaviour and technical installations[J]. Fire Safety Journal,2009,44(4):458-468.
[20]张江华,刘治平,朱道立.多源点突发灾害事故应急疏散模型与算法[J].管理科学学报,2009,12(3):111-118.
[21] VORST H C M. Evacuation models and disaster psychology[J]. Procedia Engineering,2010(3):15-21.
[22] JOO J,KIM N,WYSK R A,et al. Agent-based simulation of affordance-based human behaviors in emergency evacuation[J]. Simulation Modelling Practice and Theory,2013(32):99-115.
[23]高明霞,贺国光,考虑交叉口延误和通行能力优化疏散救援路线的最小费用流模型[J].系统工程,2006,24(9):6-10.
[2] MURRAY-TUITE P, WOLSHON B. Evacuation transportation modeling:an overview of research,development,and practice[J]. Transportation Research Part C:Emerging Technologies,2013(27):25-45.
[3] GE X X,DONG W,JIN H Y. Study on the social psychology and behaviors in a subway evacuation drill in China[J]. Procedia Engineering,2011(11):112-119.
[4]吴丹,杨赛霓.考虑优先权的人群安全疏散动态模型[J].中国安全科学学报,2012,22(2):56-62.
[5] HELBING D,FARKAS I,VICSEK T. Simulating dynamical features of escape panic[J]. Nature,2000,407(6803):487.
[6] FARAHMAND M,GARETTO C,BELLOTTI E,et al. Monte Carlo simulation of electron transport in the III-nitride wurtzite phase materials system:binaries and ternaries[J]. IEEE Transactions on Electron Devices,2001,48(3):535-542.
[7] CHIU Y C,ZHENG H. Real-time mobilization decisions for multi-priority emergency response resources and evacuation groups:model formulation and solution[J]. Transportation Research Part E:Logistics and Transportation Review,2007,43(6):710-736.
[8] GUPTA A K,YADAV P K. SAFE-R:a new model to study the evacuation profile of a building[J]. Fire Safety Journal,2004,39(7):539-556.
[9] CAMPOS V B G,SILVA P A L,NETTO P O B. Evacuation transportation planning:a method of identifying optimal independent routes[C]∥Proceedings of Urban Transport V:Urban Transport and the Environment for the 21st Century. Southampton:WIT Press,2000:555-564.
[10] PEL A J,HOOGENDOORN S P,BLIEMER M C J.Evacuation modeling including traveler information and compliance behavior[J]. Procedia Engineering,2010(3):101-111.
[11] HELIOVAARA S,KUUSINEN J M,RINNE T,et al. Pedestrian behavior and exit selection in evacuation of a corridor:an experimental study[J]. Safety Science,2012,50(2):221-227.
[12] ZHENG X,ZHONG T,LIU M. Modeling crowd evacuation of a building based on seven methodological approaches[J]. Building and Environment,2009,44(3):437-445.
[13] PELECHANO N,MALKAWI A. Evacuation simulation models:challenges in modeling high rise building evacuation with cellular automata approaches[J]. Automation in Construction,2008,17(4):377-385.
[14] ALIZADEH R. A dynamic cellular automaton model for evacuation process with obstacles[J]. Safety Science,2011,49(2):315-323.
[15] WANG J H,LO S M,SUN J H,et al. Qualitative simulation of the panic spread in large-scale evacuation[J]. Simulation,2012,88(12):1465-1474.
[16] KINATEDER M,PAULI P,MULLER M,et al. Human behaviour in severe tunnel accidents:effects of information and behavioural training[J]. Transportation Research Part F:Traffic Psychology and Behaviour,2013(17):20-32.
[17] PIRES T T. An approach for modeling human cognitive behavior in evacuation models[J]. Fire Safety Journal,2005,40(2):177-189.
[18] KOBES M,HELSLOOT I,DE VRIES B,et al. Way finding during fire evacuation; an analysis of unannounced fire drills in a hotel at night[J]. Building and Environment,2010,45(3):537-548.
[19] NILSSON D,JOHANSSON M,FRANTZICH H. Evacuation experiment in a road tunnel:a study of human behaviour and technical installations[J]. Fire Safety Journal,2009,44(4):458-468.
[20]张江华,刘治平,朱道立.多源点突发灾害事故应急疏散模型与算法[J].管理科学学报,2009,12(3):111-118.
[21] VORST H C M. Evacuation models and disaster psychology[J]. Procedia Engineering,2010(3):15-21.
[22] JOO J,KIM N,WYSK R A,et al. Agent-based simulation of affordance-based human behaviors in emergency evacuation[J]. Simulation Modelling Practice and Theory,2013(32):99-115.
[23]高明霞,贺国光,考虑交叉口延误和通行能力优化疏散救援路线的最小费用流模型[J].系统工程,2006,24(9):6-10.