异质动态交通流下区域应急疏散路线规划

交通运输系统工程与信息 ›› 2012, Vol. 12 ›› Issue (3): 147-153.

异质动态交通流下区域应急疏散路线规划

薛白^a,b，王剑^*a，b

华中科技大学 a.系统工程研究所;b.“图像信息处理与智能控制”教育部重点实验室,武汉 430074

收稿日期:2011-12-14 修回日期:2012-01-19 出版日期:2012-06-24 发布日期:2012-07-03
作者简介:薛白（1987-），女，湖北仙桃人，硕士生.
基金资助:
中央高校专项资金资助（2011QN149）；国家自然科学基金（90924301）.

Regional Emergency Evacuation Route Planning Based on Heterogeneous Dynamic Traffic Flowing

XUE Bai ^a,b,WANG Jian ^a,b

a.System Engineering Institute;b.Key Laboratory of Image Processing and Intelligent  Control,Huazhong University of Science and Technology,Wuhan 430074, China

Received:2011-12-14 Revised:2012-01-19 Online:2012-06-24 Published:2012-07-03

摘要/Abstract

摘要：

在重大灾害事件中，交通需求是影响区域疏散路线规划效果的关键因素之一.考虑实际应急疏散过程中的异质动态交通流差异性装载和分配过程，建立了一种基于受灾人员和应急物资两种异质动态交通流的最小费用流模型;然后针对两种异质流不能混合分配、网络流占用随时间变化更新等特点,提出了一种基于时间扩展的最小费用路线启发式算法，最后给出了相应的算例验证了模型和算法的可行性.结果表明：受灾人员响应行为的快慢影响着疏散时间、拥塞程度、分配的有向路数目；同时针对不同的受灾人员响应行为，调整应急物资装载时刻和装载量，可以有效缩短疏散时间.

关键词: 综合交通运输, 疏散路线规划, 交通流装载与分配, 异质动态交通流, 受灾人员响应行为

Abstract:

In many hazardous events, traffic demand is one of the key factors significantly influencing the regional evacuation route planning effect. This paper considers the different process of the loading and dispatching between heterogeneous dynamic traffic flows in the actual emergency evacuation process. First, a minimum cost flow model based on two heterogeneous dynamic traffic flows of evacuees and emergency supplies is developed. Second, a heuristic algorithm based on the minimum cost path and time extension is designed to solve the problems of two heterogeneous flows which cannot be dispatched with mixed and network flows change with time update. Finally, a case study is conducted to validate the feasibility and efficiency of the model and algorithm. The result shows that human response behavior affects the evacuation times, the degree of congestion and the amount of directed path. Meanwhile, adjusting the emergency supplies’ loading time and quantity according to the different evacuees’ response behavior parameters can effectively reduce the evacuation time. 

Key words: integrated transportation, evacuation route planning, traffic flows loading and dispatching, heterogeneous dynamic traffic flows, human response behavior

中图分类号:

U121

薛白, 王剑. 异质动态交通流下区域应急疏散路线规划[J]. 交通运输系统工程与信息, 2012, 12(3): 147-153.

XUE Bai, WANG Jian. Regional Emergency Evacuation Route Planning Based on Heterogeneous Dynamic Traffic Flowing[J]. Journal of Transportation Systems Engineering and Information Technology, 2012, 12(3): 147-153.

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链接本文: http://www.tseit.org.cn/CN/abstract/abstract18416.shtml

http://www.tseit.org.cn/CN/Y2012/V12/I3/147

参考文献

［1］CovaT J,Johnson J P. A network flow model for lanebased evacuation routing［J］. Transportation Research Part A: Policy and Practice, 2003, 37(7): 579-604.
［2］Sayyady F, Eksioglu S D. Optimizing the use of public transit system during nonotice evacuation of urban areas［J］. Computers & Industrial Engineering, 2010, 59(4): 488-495.
［3］袁媛, 汪定伟. 灾害扩散实时影响下的应急疏散路径选择模型［J］.系统仿真学报, 2008, 20(6): 1563-1566.［YUAN Y,WANG D W. Route selection model in emergency evacuation under real time effect of disaster extension［J］.Journal of System Simulation, 2008, 20(6): 1563-1566.］
［4］Ng M,Waller S T. Reliable evacuation planning via demand inflation and supply deflation［J］. Transportation Research Part E: Logistics and Transportation Review, 2010, 46(6): 1086-1094.
［5］Yi L, zdamar L. A dynamic logistics coordination model for evacuation and support in disaster response activities［J］. European Journal of Operational Research, 2007,179(3): 1177-1193.
［6］Ozbay K, Anil Yazici M.Analysis of networkwide impacts of behavioral response curves for evacuation conditions［C］. Proceedings of the 9th International IEEE Conference on Intelligent Transportation Systems.Toronto,2006: 157-162.
［7］Kang J E,Lindell M K,Prater C S.Hurricane evacuation expectations and actual behavior in Hurricane Lili［J］.Journal of Applied Social Psychology, 2007, 37(4): 887-903.
［8］Salazar F, Skutella M. Singlesource ksplittable mincost flows［J］. Operations Research Letters, 2009,37(2): 71-74.
［9］Fathabadi H S, Hosseini S A. Maximum flow problem on dynamic generative network flows with timevarying bounds［J］. Applied Mathematical Modelling, 2010, 34(8): 2136-2147.
［10］程德文,吴育华. 求最小费用最大流的改进标号法［J］. 系统管理学报, 2009, 18(2): 237-240.［CHENG D W,WU Y H. An improved labeling method for minimal cost flow［J］. Journal of Systems & Management, 2009, 18(2): 237-240.］
［11］Wu J J, Gao Z Y, Sun H J. Optimal traffic networks topology: A complex networks perspective［J］.Physica A, 2008, 387(4): 1025-1032.

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