实时威胁态势感知的室内火灾疏散路径动态优化方法

丁雨淋; 何小波; 朱庆; 林珲; 胡明远

doi:10.11947/j.AGCS.2016.20160053

测绘学报 >

2016 , Vol. 45 >Issue 12: 1464 - 1475

DOI: https://doi.org/10.11947/j.AGCS.2016.20160053

地图学与地理信息

实时威胁态势感知的室内火灾疏散路径动态优化方法

丁雨淋 ,
何小波 ,
朱庆 ,
林珲 ,
胡明远

展开

1. 西南交通大学地球科学与环境工程学院, 四川成都 611756;
2. 西南交通大学高速铁路运营安全空间信息技术国家地方联合工程实验室, 四川成都 611756;
3. 香港中文大学太空与地球信息科学研究所香港;
4. 重庆市地理信息中心, 重庆 401121

丁雨淋(1987-),女,博士,副教授,研究方向为虚拟地理环境与多维动态地理信息系统。E-mail:rainforests@126.com

收稿日期: 2016-01-22

修回日期: 2016-10-28

网络出版日期: 2017-01-02

基金资助

国家自然科学基金（41501421；41471320）；空间信息智能感知与服务深圳市重点实验室（深圳大学）开放基金资助项目；测绘遥感信息工程国家重点实验室资助项目（15I01）

收起

A Dynamic Optimization Method of Indoor Fire Evacuation Route Based on Real-time Situation Awareness

DING Yulin ,
HE Xiaobo ,
ZHU Qing ,
LIN Hui ,
HU Mingyuan

Expand

1. Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu 611756, China;
2. State-Province Joint Engineering Laboratory of Spatial Information Technology of High-speed Rail Safety, Southwest Jiaotong University, Chengdu 611756, China;
3. Institute of Space and Earth Information Science, The Chinese University of Hong Kong, Hong Kong, China;
4. Chongqing Geomatics Center, Chongqing 401121, China

Received date: 2016-01-22

Revised date: 2016-10-28

Online published: 2017-01-02

Supported by

The National Natural Science Foundation of China (Nos.41501421,41471320),The Foundation of Key Laboratory for Geo-Environmental Monitoring of Coastal Zone of the National Administration of Surveying,Mapping and Geoinformation,Open Research Fund of State Key Laboratory of Information Engineering in Surveying,Mapping and Remote Sensing (No.15I01)

Fold

摘要

如何在火灾态势迅速演变的复杂室内环境下选择安全有效的疏散路线是正确引导人群疏散、减少人员伤亡的重要保障。传统静态寻径方法难以顾及火灾态势演变过程，导致疏散决策的盲目性和滞后性突出。本文提出了一种实时威胁态势感知的室内火灾疏散路径动态优化方法，充分利用实时接入的火场状态和室内建筑环境状态等火灾威胁态势场信息，动态调整和优化疏散路径。该方法建立了室内火灾实时威胁态势信息在语义空间的统一表示模型，并对多源、多尺度火灾传感器观测数据在语义空间进行统一建模，从实时接入的动态观测数据中提取室内火灾三维威胁态势信息，用于约束疏散路径的动态优化。模拟试验证明，本方法可根据火灾态势演变准确可靠地动态调整疏散路径，从而显著提高应急疏散的精准性。

关键词： 传感器数据; 室内火灾; 动态疏散; 态势感知; 路径优化

本文引用格式

丁雨淋 , 何小波 , 朱庆 , 林珲 , 胡明远 . 实时威胁态势感知的室内火灾疏散路径动态优化方法[J]. 测绘学报, 2016 , 45(12) : 1464 -1475 . DOI: 10.11947/j.AGCS.2016.20160053

Abstract

How to provide safe and effective evacuation routes is an important safeguard to correctly guide evacuation and reduce the casualties during the fire situation rapidly evolving in complex indoor environment. The traditional static path finding method is difficult to adjust the path adaptively according to the changing fire situation, which lead to the evacuation decision-making blindness and hysteresis. This paper proposes a dynamic method which can dynamically optimize the indoor evacuation routes based on the real-time situation awareness. According to the real-time perception of fire situation parameters and the changing indoor environment information, the evacuation route is optimized dynamically. The integrated representation of multisource indoor fire monitoring sensor observations oriented fire emergency evacuation is presented at first, real-time fire threat situation information inside building is then extracted from the observation data of multi-source sensors, which is used to constrain the dynamical optimization of the topology of the evacuation route. Finally, the simulation experiments prove that this method can improve the accuracy and efficiency of indoor evacuation routing.

Key words： sensor data; indoor fire; dynamic emergency evacuation; situation awareness; route optimization

参考文献

[1] 朱庆, 胡明远, 许伟平, 等. 面向火灾动态疏散的三维建筑信息模型[J]. 武汉大学学报(信息科学版), 2014, 39(7):762-766, 872. ZHU Qing, HU Mingyuan, XU Weiping, et al. 3D Building Information Model for Facilitating Dynamic Analysis of Indoor Fire Emergency[J]. Geomatics and Information Science of Wuhan University, 2014, 39(7):762-766, 872.
[2] KWAN M P, LEE J. Emergency Response after 9/11:The Potential of Real-time 3D GIS for Quick Emergency Response in Micro-spatial Environments[J]. Computers, Environment and Urban Systems, 2005, 29(2):93-113.
[3] TAN Lu, HU Mingyuan, LIN Hui. Agent-based Simulation of Building Evacuation:Combining Human Behavior with Predictable Spatial Accessibility in a Fire Emergency[J]. Information Sciences, 2015, 295:53-66.
[4] KOBES M, HELSLOOT I, DE VRIES B, et al. Building Safety and Human Behaviour in Fire:A Literature Review[J]. Fire Safety Journal, 2010, 45(1):1-11.
[5] 李清泉, 李秋萍, 方志祥. 一种基于时空拥挤度的应急疏散路径优化方法[J]. 测绘学报, 2011, 40(4):517-523. LI Qingquan,LI Qiuping, FANG Zhixiang. An Emergency Evacuation Routing Optimization Method Based on Space-time Congestion Concept[J]. Acta Geodaetica et Cartographica Sinica, 2011, 40(4):517-523.
[6] TANG Fangqin, REN Aizhu. GIS-based 3D Evacuation Simulation for Indoor Fire[J]. Building and Environment, 2012, 49:193-202.
[7] 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.
[8] CHEN L C, WU C H, SHEN T S, et al. The Application of Geometric Network Models and Building Information Models in Geospatial Environments for Fire-fighting Simulations[J]. Computers, Environment and Urban Systems, 2014, 45:1-12.
[9] WU C H, CHEN L C. 3D Spatial Information for Fire-Fighting Search and Rescue Route Analysis within Buildings[J]. Fire Safety Journal, 2012, 48:21-29.
[10] LEE J, KWAN M P. A Combinatorial Data Model for Representing Topological Relations among 3D Geographical Features in Micro-spatial Environments[J]. International Journal of Geographical Information Science, 2005, 19(10):1039-1056.
[11] ZHAO Haifeng, WINTER S. A Time-aware Routing Map for Indoor Evacuation[J]. Sensors, 2016, 16(1):112.
[12] WANG Jing, ZHAO Haifeng, WINTER S. Integrating Sensing, Routing and Timing for Indoor Evacuation[J]. Fire Safety Journal, 2015, 78:111-121.
[13] BERNARDINI G, AZZOLINI M, D'ORAZIO M, et al. Intelligent Evacuation Guidance Systems for Improving Fire Safety of Italian-style Historical Theatres without Altering Their Architectural Characteristics[J]. Journal of Cultural Heritage, 2016. DOI:10.1016/j.culher.2016.06.008.
[14] KO B C, CHEONG K H, NAM J Y. Fire Detection Based on Vision Sensor and Support Vector Machines[J]. Fire Safety Journal, 2009, 44(3):322-329.
[15] SADAHIRO Y, KOBAYASHI T. Exploratory Analysis of Time Series Data:Detection of Partial Similarities, Clustering,and Visualization[J].Computers, Environment and Urban Systems, 2014, 45:24-33.
[16] HASOFER A M, THOMAS I. Analysis of Fatalities and Injuries in Building Fire Statistics[J]. Fire Safety Journal, 2006, 41(1):2-14.
[17] 陈能成, 狄黎平, 龚健雅, 等. 基于Web目录服务的地学传感器观测服务注册和搜索[J]. 遥感学报, 2008, 12(3):411-419. CHEN Nengcheng, DI Liping, GONG Jianya, et al. Sensor Observation Service Registry and Search Based on Catalogue Service for Web[J]. Journal of Remote Sensing, 2008, 12(3):411-419.
[18] W3C. Semantic Web Activity Statement[EB/OL]. https://www.w3.org/2001/sw/Activity.
[19] The Semantic Toolbox:Building Semantics on Top of XML-RDF[EB/OL]. https://www.w3.org/DesignIssues/Toolbox.html.
[20] 陈家赢, 陈能成, 王伟, 等. 基于SensorML的遥感卫星传感器建模方法[J]. 武汉大学学报(信息科学版), 2010, 35(8):971-974. CHEN Jiaying, CHEN Nengcheng, WANG Wei, et al. A Remotey Sensing Satellite Sensor Modeling Approach Based on SensorML[J]. Geomatics and Information Science of Wuhan University, 2010, 35(8):971-974.
[21] 陈章其, 吴冲若. 火灾传感器[J]. 电子器件, 1995, 18(1):55-58. CHEN Zhangqi, WU Chongruo. Fire Sensor[J]. Journal of Electron Devices, 1995, 18(1):55-58.
[22] WHITESIDE A, EVANS J D. Web Coverage Service (WCS) Implementation Specification[S].1.1.2 ed. Wayland, Massachusetts, USA:OGC, 2008.
[23] 吕广宪, 潘懋, 王占刚, 等. 面向体数据的虚拟八叉树模型研究[J]. 计算机应用, 2006, 26(12):2856-2859. LÜ Guangxian,PAN Mao,WANG Zhangang,et al. Study of Virtual Octree Model for Volume Data[J]. Computer Applications, 2006, 26(12):2856-2859.
[24] LEE J. A 3D Data Model for Representing Topological Relationships between Spatial Entities in Built-environments[D]. Ohio:The Ohio State University, 2001.
[25] 徐艳秋, 王振东. 基于Pathfinder和FDS的火场下人员疏散研究[J]. 中国安全生产科学技术, 2012, 8(2):50-54. XU Yanqiu, WANG Zhendong. Study on Evacuation Simulation of Fire Ground Based on Pathfinder and FDS[J]. Journal of Safety Science and Technology, 2012, 8(2):50-54.
[26] RONCHI E, ALVEAR D, BERLOCO N, et al. Human Behaviour in Road Tunnel Fires:Comparison between Egress Models (FDS+ Evac, STEPS, Pathfinder)[C]//Proceedings of the International Conference on Fire Science and Engineering Interflam. Nottingham.[s.n.]:2010:837-848.
[27] 党会森, 赵宇宁. 基于Pathfinder的人员疏散仿真[J]. 中国公共安全(学术版), 2011(4):46-49. DANG Huisen, ZHAO Yuning. Simulation of Crowd Evacuation Based on Pathfinder[J]. China Public Security (Academy Edition), 2011(4):46-49.

Options

文章导航

模态框（Modal）标题

摘要

本文引用格式

Abstract

参考文献