簡易檢索 / 詳目顯示

研究生: 吳俊毅
Wu, Chun Yi
論文名稱: 結合人物模組與SOP在災難模擬之中的方法
Approach to Model People and SOP in Disaster Scenarios
指導教授: 張韻詩
Liu, Jane W.S.
口試委員: 金仲達
朱宗賢
蔡佩璇
學位類別: 碩士
Master
系所名稱: 電機資訊學院 - 資訊工程學系
Computer Science
論文出版年: 2015
畢業學年度: 103
語文別: 英文
論文頁數: 60
中文關鍵詞: 災難模擬
外文關鍵詞: Agent-Based Model, Disaster Simulator
相關次數: 點閱:3下載:0
分享至:
查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報
  • 這篇論文提出如何將人物與SOP模組化,並結合在一起的方法。這個方法用於解決在大部分的模擬環境之中,人物的行為設計綁訂在特定的模組上。透過這個方法,實驗者能夠透過改變輸入的SOP達到改變人物在模擬之中的行為,並且能夠輕鬆結合人物模組與SOP在災難環境之上,構築出需要的模擬環境,藉此達到調整並確認SOP設計的目的。
    這個結合人與SOP模組在災難環境的方法透過使用 Goal Operation Methods and Selection rule(GOMS)的方式模組化SOP,以及 Cognitive, Perceptive and Motor - GOMS(CPM-GOMS) 與 Agent-Based Model(ABM)的方式模組化人。同時,這篇也論文提出 Bottom-up 以及 Top-down 兩種方式用來達到結合模組在災難環境之中。最後,這邊論文所提到的方式透過實作在 Agent-Based Disaster Simulation Environment(ABDiSE)這個模擬環境之上作為論證。


    This thesis presents approaches to model people and SOP in disaster scenarios. The purposed approaches remove the shortcoming that most behaviors of agent are bound to models in disaster simulators and make experimenters can change behaviors through SOP input. As a result, experimenters can easily build simulators he/she wanted through combining models of people, models of SOP and disaster scenarios together for the purpose of tuning SOP.
    The approaches considered here make use of Goal Operations Methods and Selection rules(GOMS) Model for modeling SOP, and Cognitive, Perceptive and Motor - GOMS(CPM-GOMS) and Agent-Based Model(ABM) for modeling individual people. Moreover, there are two approaches: Bottom-up and Top-down approaches to combines models together in disaster scenarios. Finally, this purposed approaches are implemented and demonstrated in the framework of Agent-Based Disaster Simulation Environment(ABDiSE) as an extension.

    Abstract i 中文摘要 ii Acknowledgement iii Contents iv List of Figures vii 1 Introduction ............................................ 1 1.1 Motivation 2 1.2 Models and Tools 6 1.3 Contributions 7 1.4 Organization 8 2 Related Work ............................................ 9 2.1 Agent-Based models 9 2.1.1 AnyLogic 9 2.1.2 MASON 11 2.1.3 ASCAPE 13 2.1.4 ABDiSE 14 2.2 CPM-GOMS 16 3 Overview ............................................... 20 3.1 Model Of SOP 20 3.2 Model of People 22 3.3 Approaches to Integrating People and SOP Models 24 4 Model of SOP ........................................... 26 4.1 Definition of SOP 26 4.2 SOP Node 29 4.2.1 Condition 29 4.2.2 Behavior 32 4.2.3 Next Node List 34 5 Model of People ........................................ 37 5.1 CPM-GOMS Modeling 37 5.2 Perceptual Processor 39 5.2.1 Event Condition Method 40 5.2.2 Event Checking Module 40 5.3 Cognitive Processor 42 5.3.1 Event Handling Module 42 5.3.2 Decision Making Module 43 5.4 Motor Processor 44 5.4.1 Action Executing Module 45 5.4.2 Action Method 46 5.5 Attribute and Characteristic 46 6 Approaches ............................................. 48 6.1 Bottom-up Approach 48 6.2 Top-down Approach 50 7 Implementation in ABDiSE ............................... 52 7.1 Model of SOP 52 7.2 Model of Human 53 8 Conclusion and Future Works ............................ 56

    [1] Wikipedia, “Standard operating procedure.” http://en.wikipedia.org/wiki/Standard_
    operating_procedure, Oct. 2014. [Nov. 3, 2014].
    [2] U. of Washington, “Emergency evacuation and operations plan (eeop).” https://www.com.
    washington.edu/faculty-staff/assets/EEOP.pdf, June 2008. [Nov. 3, 2014].
    [3] F. S. A. Centre, “Fire emergency evacuation plan and the fire procedure.” http://www.firesafe.
    org.uk/fire-emergency-evacuation-plan-or-fire-procedure/. [Nov. 3, 2014].
    [4] C. Office, “Preparation and planning for emergencies: responsibilities of responder agencies and
    others.” https://www.gov.uk/, Feb. 2013. [Nov. 3, 2014].
    [5] Wikipedia, “Simulation.” http://en.wikipedia.org/wiki/Simulation, Oct. 2014. [Oct. 14, 2014].
    [6] M. Okaya, S. Yotsukura, and T. Takahashi, “Robocup 2009,” ch. A Hybrid Agent Simulation System
    of Rescue Simulation and USARSim Simulations from Going to Fire-escape Doors to Evacuation to
    Shelters, pp. 414–424, Berlin, Heidelberg: Springer-Verlag, 2010.
    [7] T. Takahashi, “Agent-based disaster simulation evaluation and its probability model interpretation,”
    Proceedings of ISCRAM, 2007.
    [8] C.-A. Tai, Y.-L. Lee, and C.-Y. Lin, “Earthquake disaster prevention area planning considering residents’
    demand,” in Advanced Computer Control (ICACC), 2010 2nd International Conference on,
    vol. 1, pp. 381–385, March 2010.
    [9] T. Takahashi and J. Nobe, “Evaluation methods for rescue activities by agents and a disaster prevention
    plan,” in SICE 2002. Proceedings of the 41st SICE Annual Conference, vol. 2, pp. 858–859
    vol.2, Aug 2002.
    [10] Y. Fukuda, K. Natsume, N. Ito, E. Yamada, Y. Kuwata, K. Iwata, and K. Wada, “Evaluation
    of situated-optimal planning strategy with integrate disaster simulation system,” in SICE Annual
    Conference, 2008, pp. 433–438, Aug 2008.
    [11] S. Winter, K.-F. Richter, M. Shi, and H.-S. Gan, “Get me out of here: Collaborative evacuation based
    on local knowledge,” in Proceedings of the 3rd ACM SIGSPATIAL International Workshop on Indoor
    Spatial Awareness, ISA ’11, (New York, NY, USA), pp. 35–42, ACM, 2011.
    [12] S. Lee, J. W. Bae, J. Lee, J. H. Hong, and I.-C. Moon, “Simulation experiment of routing strategy for
    evacuees and disaster responders,” in Proceedings of the 2014 Symposium on Agent Directed Simulation,
    ADS ’14, (San Diego, CA, USA), pp. 2:1–2:8, Society for Computer Simulation International,
    2014.
    [13] N. Wagner and V. Agrawal, “An agent-based simulation system for concert venue crowd evacuation
    modeling in the presence of a fire disaster,” Expert Systems with Applications, vol. 41, no. 6, pp. 2807
    – 2815, 2014.
    [14] S. Casadesús-Pursals and F. Garriga-Garzón, “Building evacuation: Principles for the analysis of
    basic structures through dynamic flow networks,” Journal of Industrial Engineering and Management,
    vol. 6, no. 4, pp. 831–859, 2013.
    [15] L. Hochstein, “Goms.” http://www.cs.umd.edu/class/fall2002/cmsc838s/tichi/goms.html,
    Oct. 2002. [Oct. 14, 2014].
    [16] B. E. John and D. E. Kieras, “The goms family of user interface analysis techniques: Comparison
    and contrast,” ACM Trans. Comput.-Hum. Interact., pp. 320–351, Dec 1996.
    [17] B. E. John and D. E. Kieras, “Using goms for user interface design and evaluation: Which technique?,”
    ACM Trans. Comput.-Hum. Interact., vol. 3, pp. 287–319, Dec. 1996.
    [18] D. V. Beard, S. Entrikin, P. Conroy, N. C. Wingert, C. D. Schou, D. K. Smith, and K. M. Denelsbeck,
    “Quick goms: A visual software engineering tool for simple rapid time-motion modeling,” interactions,
    vol. 4, pp. 31–36, May 1997.
    [19] B. E. John and W. D. Gray, “Cpm-goms: An analysis method for tasks with parallel activities,” in
    Conference Companion on Human Factors in Computing Systems, CHI ’95, (New York, NY, USA),
    pp. 393–394, ACM, 1995.
    [20] B. John, A. Vera, M. Matessa, M. Freed, and R. Remington, “Automating cpm-goms,” in Proceedings
    of the SIGCHI Conference on Human Factors in Computing Systems, CHI ’02, (New York, NY, USA),
    pp. 147–154, ACM, 2002.
    [21] B. E. John and D. E. Kieras, “The goms family of user interface analysis techniques: Comparison
    and contrast,” ACM Trans. Comput.-Hum. Interact., vol. 3, pp. 320–351, Dec. 1996.
    [22] Wikipedia, “Agent-based model.” http://en.wikipedia.org/wiki/Agent-based_model, Nov. 2014.
    [Nov. 24, 2014].
    [23] Wikipedia, “Comparison of agent-based modeling software.” http://en.wikipedia.org/wiki/
    Comparison_of_agent-based_modeling_software, Oct. 2014. [Nov. 24, 2014].
    [24] E. Bonabeau, “Agent-based modeling: Methods and techniques for simulating human systems,” Proceedings
    of the National Academy of Sciences of the United States of America, vol. 99, no. Suppl 3,
    pp. 7280–7287, 2002.
    [25] C. Nikolai and G. Madey, “Tools of the trade: A survey of various agent based modeling platforms,”
    Journal of Artificial Societies and Social Simulation, vol. 12, no. 2, p. 2, 2009.
    [26] C. Macal and M. North, “Introductory tutorial: Agent-based modeling and simulation,” in Simulation
    Conference (WSC), Proceedings of the 2011 Winter, pp. 1451–1464, Dec 2011.
    [27] H. Reza and E. Grant, “A formal approach to software architecture of agent-base systems,” in Information
    Technology: Coding and Computing, 2004. Proceedings. ITCC 2004. International Conference
    on, vol. 1, pp. 591–595 Vol.1, April 2004.
    [28] C. Sansores, J. Pavón, and J. Gómez-Sanz, “Visual modeling for complex agent-based simulation
    systems,” in Proceedings of the 6th International Conference on Multi-Agent-Based Simulation,
    MABS’05, (Berlin, Heidelberg), pp. 174–189, Springer-Verlag, 2006.
    [29] V. Grimm, U. Berger, F. Bastiansen, S. Eliassen, V. Ginot, J. Giske, J. Goss-Custard, T. Grand, S. K.
    Heinz, G. Huse, A. Huth, J. U. Jepsen, C. Jørgensen, W. M. Mooij, B. Müller, G. Pe’er, C. Piou,
    S. F. Railsback, A. M. Robbins, M. M. Robbins, E. Rossmanith, N. Rüger, E. Strand, S. Souissi, R. A.
    Stillman, R. Vabø, U. Visser, and D. L. DeAngelis, “A standard protocol for describing individualbased
    and agent-based models,” Ecological Modelling, vol. 198, no. 1–2, pp. 115 – 126, 2006.
    [30] M. J. North and C. M. Macal, Managing business complexity: discovering strategic solutions with
    agent-based modeling and simulation. Oxford University Press, 2007.
    [31] L. J. W. S. Hsu T. L., “An agent-based disaster simulation environment,” in RITMAN Workshop
    2012, (Taipei, Taiwan), 2012.
    [32] F. Wafda, R. Saputra, Y. Nurdin, Nasaruddin, and K. Munadi, “Agent-based tsunami evacuation
    simulation for disaster education,” in ICT for Smart Society (ICISS), 2013 International Conference
    on, pp. 1–4, June 2013.
    [33] T. Kokawa, Y. Takeuchi, R. Sakamoto, H. Ogawa, and V. Kryssanov, “An agent-based system for the
    prevention of earthquake-induced disasters,” in Tools with Artificial Intelligence, 2007. ICTAI 2007.
    19th IEEE International Conference on, vol. 2, pp. 55–62, Oct 2007.
    [34] F. Xu, X. Chen, A. Ren, and X. Lu, “Earthquake disaster simulation for an urban area, with gis, cad,
    fea, and vr integration,” Tsinghua Science and Technology, vol. 13, pp. 311–316, Oct 2008.
    [35] G. Jakovljevic and D. Basch, “Implementing multiscale traffic simulators using agents,” in Information
    Technology Interfaces, 2004. 26th International Conference on, pp. 519–524 Vol.1, June 2004.
    [36] B. Cui, H. Gao, C. Zuo, and X. Xu, “Simulation of flood disaster by use of breadth-first-search
    algorithm integrated with gis,” in Intelligent Control and Automation, 2004. WCICA 2004. Fifth
    World Congress on, vol. 6, pp. 5365–5369 Vol.6, June 2004.
    [37] M. Tanigawa, T. Takahashi, T. Koto, K. Takeuchi, and I. Noda, “Urban flood simulation as a component
    of integrated earthquake disaster simulation,” in Safety, Security and Rescue Robotics, Workshop,
    2005 IEEE International, pp. 248–252, June 2005.
    [38] R. Wang, B. Chen, F. Huang, and Y. Fang, “Using collaborative virtual geographic environment for
    fire disaster simulation and virtual fire training,” in Geoinformatics (GEOINFORMATICS), 2012
    20th International Conference on, pp. 1–4, June 2012.
    [39] S. Homma, K. Fujita, T. Ichimura, M. Hori, S. Citak, and T. Hori, “A physics-based monte carlo
    earthquake disaster simulation accounting for uncertainty in building structure parameters,” Procedia
    Computer Science, vol. 29, no. 0, pp. 855 – 865, 2014. 2014 International Conference on Computational
    Science.
    [40] G. I. Hawe, G. Coates, D. T. Wilson, and R. S. Crouch, “Agent-based simulation for large-scale emergency
    response: A survey of usage and implementation,” ACM Comput. Surv., vol. 45, pp. 8:1–8:51,
    Dec. 2012.
    [41] K. Mustapha, H. Mcheick, and S. Mellouli, “Modeling and simulation agent-based of natural disaster
    complex systems,” Procedia Computer Science, vol. 21, no. 0, pp. 148 – 155, 2013. The 4th International
    Conference on Emerging Ubiquitous Systems and Pervasive Networks (EUSPN-2013) and
    the 3rd International Conference on Current and Future Trends of Information and Communication
    Technologies in Healthcare (ICTH).
    [42] K. Mustapha, H. Mcheick, and S. Mellouli, “Modeling and simulation of agent-based complex systems
    and application to natural disasters,” in Proceedings of the 8th ACM Workshop on Performance
    Monitoring and Measurement of Heterogeneous Wireless and Wired Networks, PM2HW2N ’13, (New
    York, NY, USA), pp. 75–82, ACM, 2013.
    [43] S. Wu, L. Shuman, B. Bidanda, M. Kelley, B. Lawson, K. Sochats, and C. Balaban, “System implementation
    issues of dynamic discrete disaster decision simulation system (d4s2) - phase i,” in
    Simulation Conference, 2007 Winter, pp. 1127–1134, Dec 2007.
    [44] K. Fujita, T. Ichimura, M. Hori, M. Wijerathne, and S. Tanaka, “A quick earthquake disaster estimation
    system with fast urban earthquake simulation and interactive visualization,” Procedia Computer
    Science, vol. 29, no. 0, pp. 866 – 876, 2014. 2014 International Conference on Computational Science.
    [45] G. Wagner and M. Diaconescu, “Aor-simulation.org: Cognitive agent simulation,” in Proceedings
    of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2,
    AAMAS ’09, (Richland, SC), pp. 1405–1406, International Foundation for Autonomous Agents and
    Multiagent Systems, 2009.
    [46] K. Uno and K. Kashiyama, “Development of simulation system for the disaster evacuation based on
    multi-agent model using gis,” Tsinghua Science and Technology, vol. 13, pp. 348–353, Oct 2008.
    [47] L. Hluchy, M. Kvassay, S. Dlugolinský, B. Schneider, H. Bracker, B. Kryza, and J. Kitowski, “Handling
    internal complexity in highly realistic agent-based models of human behaviour,” in Applied
    Computational Intelligence and Informatics (SACI), 2011 6th IEEE International Symposium on,
    pp. 11–16, May 2011.
    [48] M. Young, “Human performance models as semi-autonomous agents,” in AI, Simulation, and Planning
    in High Autonomy Systems, 1993. Integrating Virtual Reality and Model-Based Environments.
    Proceedings. Fourth Annual Conference, pp. 74–80, Sep 1993.
    [49] L. Luo, S. Zhou, W. Cai, M. Lees, and M. Low, “Modeling human-like decision making for virtual
    agents in time-critical situations,” in Cyberworlds (CW), 2010 International Conference on,
    pp. 360–367, Oct 2010.
    [50] D. Djordjevich, P. Xavier, M. Bernard, J. Whetzel, M. Glickman, and S. Verzi, “Preparing for the
    aftermath: Using emotional agents in game-based training for disaster response,” in Computational
    Intelligence and Games, 2008. CIG ’08. IEEE Symposium On, pp. 266–275, Dec 2008.
    [51] B. Baster, J. Duda, A. Maciol, and B. Rebiasz, “Rule-based approach to human-like decision simulating
    in agent-based modeling and simulation,” in System Theory, Control and Computing (ICSTCC),
    2013 17th International Conference, pp. 739–743, Oct 2013.
    [52] B. Schneider, “The reference model simpan - agent-based modelling of human behaviour in panic situations,”
    in Computer Modeling and Simulation, 2008. UKSIM 2008. Tenth International Conference
    on, pp. 599–604, April 2008.
    [53] T. Hanratty, R. Hammell, J. Yen, and X. Fan, “Utilizing concept maps to improve human-agent
    collaboration within a recognition-primed decision model,” in Intelligent Agent Technology, 2007.
    IAT ’07. IEEE/WIC/ACM International Conference on, pp. 116–120, Nov 2007.
    [54] AnyLogic, “About the anylogic company.” http://www.anylogic.com/about-us. [Oct. 14, 2014].
    [55] AnyLogic, “Emergency department 3d screenshots.” http://www.anylogic.com/screentshots.
    [Mar. 3, 2015].
    [56] A. Borshchev and A. Filippov, “From system dynamics and discrete event to practical agent based
    modeling: reasons, techniques, tools,” in Proceedings of the 22nd international conference of the
    system dynamics society, no. 22, 2004.
    [57] Mike, “Unified modeling language(uml) resource page.” http://www.uml.org/, Oct. 2014. [Dec. 2,
    2014].
    [58] S. Luke, C. Cioffi-Revilla, L. Panait, K. Sullivan, and G. Balan, “Mason: A multiagent simulation
    environment,” Simulation, vol. 81, pp. 517–527, July 2005.
    [59] S. Luke, C. Cioffi-Revilla, L. Panait, and K. Sullivan, “Mason: A new multi-agent simulation toolkit,”
    in Proceedings of the 2004 SwarmFest Workshop, vol. 8, 2004.
    [60] S. Luke, G. C. Balan, L. Panait, C. Cioffi-Revilla, and S. Paus, “Mason: A java multi-agent simulation
    library,” in Proceedings of Agent 2003 Conference on Challenges in Social Simulation, vol. 9, 2003.
    [61] M. T. Parker, “What is ascape and why should you care,” Journal of Artificial Societies and Social
    Simulation, vol. 4, no. 1, p. 5, 2001.
    [62] M. E. Inchiosa and M. T. Parker, “Overcoming design and development challenges in agent-based
    modeling using ascape,” Proceedings of the National Academy of Sciences of the United States of
    America, vol. 99, no. Suppl 3, pp. 7304–7308, 2002.
    [63] J. M. Epstein and R. Axtell, Growing artificial societies: social science from the bottom up. Brookings
    Institution Press, 1996.
    [64] ESRI, “What is gis?.” http://www.esri.com/what-is-gis. [Nov. 3, 2014].
    [65] N. Geographic, “Gis(geographic information system).” http://education.nationalgeographic.
    com/education/encyclopedia/geographic-information-system-gis/?ar_a=1. [Nov. 3, 2014].
    [66] S. K. Card, T. P. Moran, and A. Newell, “The model human processor: An engineering model of
    human performance,” Handbook of Human Perception, vol. 2, 1986.
    [67] Wikipedia, “Human processor model.” http://en.wikipedia.org/wiki/Human_processor_model.
    [Dec. 3, 2014].
    [68] S. K. Card, A. Newell, and T. P. Moran, The Psychology of Human-Computer Interaction. Hillsdale,
    NJ, USA: L. Erlbaum Associates Inc., 1983.
    [69] Y. Liu, R. Feyen, and O. Tsimhoni, “Queueing network-model human processor (qn-mhp): A computational
    architecture for multitask performance in human-machine systems,” ACM Trans. Comput.-
    Hum. Interact., vol. 13, pp. 37–70, Mar. 2006.
    [70] O. Tsimhoni and Y. Liu, “Steering a driving simulator using the queueing network-model human
    processor (qn-mhp),” in Driving Assessment 2003: International Symposium on Human Factors in
    Driver Assessment, Training, and Vehicle Design, 2003.
    [71] L. Luo, S. Zhou, W. Cai, M. Lees, M. Y. H. Low, and K. Sornum, “Humdpm: a decision process
    model for modeling human-like behaviors in time-critical and uncertain situations,” in Transactions
    on computational science XII, pp. 206–230, Springer, 2011.
    [72] Argent, “Fire evacuation instructions.” http://www.argentchambers.co.uk/site/about/
    procedures/fire/. [Nov. 15, 2014].

    無法下載圖示 全文公開日期 本全文未授權公開 (校內網路)
    全文公開日期 本全文未授權公開 (校外網路)

    QR CODE