A proposed pedestrian waiting-time model for improving space—time use efficiency in stadium evacuation scenarios

Abstract Efficiency is a fundamental requirement in evacuation planning and operations. The “faster-is-slower” phenomenon in pedestrian evacuation has been observed and deemed a significant obstacle to evacuation efficiency. This paper thus focuses on two aspects of evacuation planning in the case of stadium evacuation. The first is to define a space–time use efficiency measure for evaluating the utility of both space and time resources. The second is to propose a pedestrian waiting-time model for directing evacuees to alleviate evacuation bottlenecks. An agent-based simulation approach was employed to test the proposed model in stadium evacuation scenarios. The results demonstrate that compelled, or mandatory, waiting time strategy generated by this model is helpful in improving the space–time use efficiency of network links in the evacuation process by virtue of the strategically timed moving–waiting–restarting movement pattern of evacuees. The analysis of space–time evacuation paths in this study provides a practical and insightful alternative for measuring evacuation effectiveness. Results of this study compared reasonably against an existing cellular automaton based simulation both in microscopic and macroscopic perspectives. A number of future research directions were presented.

[1]  Carlos F. Daganzo,et al.  Managing Evacuation Routes , 2009 .

[2]  Erik Vanem,et al.  Evaluating the Cost-effectiveness of a Monitoring System for Improved Evacuation From Passenger Ships , 2010 .

[3]  Kai Nagel,et al.  The representation and implementation of time-dependent inundation in large-scale microscopic evacuation simulations , 2010 .

[4]  Hao Wu,et al.  Experiment and modeling of exit-selecting behaviors during a building evacuation , 2010 .

[5]  Michael K. Lindell.  EMBLEM2: An empirically based large scale evacuation time estimate model , 2008 .

[6]  Alexander Stepanov,et al.  Production , Manufacturing and Logistics Multi-objective evacuation routing in transportation networks , 2009 .

[7]  Wan Ki Chow.  ‘Waiting time’ for evacuation in crowded areas , 2007 .

[8]  Gunnar G. Løvås,et al.  On performance measures for evacuation systems , 1995 .

[9]  Robert L. Smith,et al.  A MIXED INTEGER LINEAR PROGRAMMING MODEL FOR DYNAMIC ROUTE GUIDANCE , 1998 .

[10]  Yu-Chun Wang,et al.  Integrated network approach of evacuation simulation for large complex buildings , 2009 .

[11]  Edwin R. Galea,et al.  Adaptive decision-making in response to crowd formations in building EXODUS , 1999 .

[12]  Elvezia Maria Cepolina,et al.  Phased evacuation: An optimisation model which takes into account the capacity drop phenomenon in pedestrian flows , 2009 .

[13]  S. Travis Waller,et al.  A dynamic evacuation network optimization problem with lane reversal and crossing elimination strategies , 2010 .

[14]  Pascal Stucki,et al.  Hybrid Techniques for Pedestrian Simulations , 2004, ACRI.

[15]  Sathaporn Opasanon.  On finding paths and flows in multicriteria, stochastic and time-varying networks , 2004 .

[16]  Edwin R. Galea,et al.  The EXODUS evacuation model applied to building evacuation scenarios , 1996 .

[17]  Xiaoping Zheng,et al.  Modeling crowd evacuation of a building based on seven methodological approaches , 2009 .

[18]  Linda B. Dixon.  Bicycle and Pedestrian Level-of-Service Performance Measures and Standards for Congestion Management Systems , 1996 .

[19]  Richard L. Francis,et al.  Network models for building evacuation , 1982 .

[20]  Edwin R. Galea,et al.  Evacuation modelling analysis within the operational research context : A combined approach for improving enclosure designs , 2009 .

[21]  Xianting Li,et al.  Evaluating emergency ventilation strategies under different contaminant source locations and evacuation modes by efficiency factor of contaminant source (EFCS) , 2010 .

[22]  Peter T. Martin,et al.  Stochastic optimization of traffic control and transit priority settings in VISSIM , 2008 .

[23]  M. Granié.  Effects of gender, sex-stereotype conformity, age and internalization on risk-taking among adolescent pedestrians , 2009 .

[24]  Daniel R. Parisi,et al.  Why “Faster is Slower” in Evacuation Process , 2007 .

[25]  E. F. Codd,et al.  Cellular automata , 1968 .

[26]  R. Alizadeh,et al.  A dynamic cellular automaton model for evacuation process with obstacles , 2011 .

[27]  Atsushi Takizawa,et al.  An efficient algorithm for the evacuation problem in a certain class of networks with uniform path-lengths , 2009, Discret. Appl. Math..

[28]  P. V. Oosterom,et al.  GEO-INFORMATION FOR DISASTER MANAGEMENT , 2008 .

[29]  Chris T. Kiranoudis,et al.  Modeling emergency evacuation for major hazard industrial sites , 2007, Reliab. Eng. Syst. Saf..

[30]  Aizhu Ren,et al.  Agent-based evacuation model of large public buildings under fire conditions , 2009 .

[31]  Bernhard Steffen,et al.  New Insights into Pedestrian Flow Through Bottlenecks , 2009, Transp. Sci..

[32]  A. Millonig,et al.  A Navigation Algorithm for Pedestrian Simulation in Dynamic Environments , 2007 .

[33]  J. MacGregor Smith,et al.  An analytical queuing network computer program for the optimal egress problem , 1982 .

[34]  S. Zlatanova,et al.  Evacuation Route Calculation of Inner Buildings , 2005 .

[35]  Jaroslaw Was,et al.  Social Distances Model of Pedestrian Dynamics , 2006, ACRI.

[36]  Nuria Pelechano,et al.  Evacuation simulation models: challenges in modeling high rise building evacuation with cellular automata approaches , 2008 .

[37]  Harry J. P. Timmermans,et al.  A Multi-Agent Cellular Automata System for Visualising Simulated Pedestrian Activity , 2000, ACRI.

[38]  Fang Yuan,et al.  Improving Evacuation Planning with Sensible Measure of Effectiveness Choices , 2009 .

[39]  Siuming Lo,et al.  On the use of multi-stage time-varying quickest time approach for optimization of evacuation planning , 2008 .

[40]  J. Cole Smith,et al.  Decomposition algorithms for the design of a nonsimultaneous capacitated evacuation tree network , 2009 .

[41]  Wan Ki Chow,et al.  Waiting time in emergency evacuation of crowded public transport terminals , 2008 .

[42]  Lee D. Han,et al.  What Is An Effective Evacuation Operation , 2007 .

[43]  Franziska Klügl-Frohnmeyer,et al.  Large-Scale Agent-Based Pedestrian Simulation , 2007, MATES.

[44]  Bauke de Vries,et al.  Building safety and human behaviour in fire : a literature review , 2010 .

[45]  Stefania Bandini,et al.  Agent Based Modeling and Simulation: An Informatics Perspective , 2009, J. Artif. Soc. Soc. Simul..

[46]  Kien A. Hua,et al.  Dynamic Plan Generation and Real-Time Management Techniques for Traffic Evacuation , 2008, IEEE Transactions on Intelligent Transportation Systems.

[47]  Konrad Kulakowski,et al.  Multi-agent Systems in Pedestrian Dynamics Modeling , 2009, ICCCI.

[48]  T. Vicsek,et al.  Simulation of pedestrian crowds in normal and evacuation situations , 2002 .

[49]  J. MacGregor Smith,et al.  RESOURCE ALLOCATION IN STATE-DEPENDENT EMERGENCY EVACUATION NETWORKS , 1996 .

[50]  Dirk Helbing,et al.  Simulating dynamical features of escape panic , 2000, Nature.

[51]  Mao-Jiun J. Wang,et al.  The comparisons of anthropometric characteristics among four peoples in East Asia. , 2004, Applied ergonomics.

[52]  John J. Fruin,et al.  Pedestrian planning and design , 1971 .

[53]  Valerii V. Kholshevnikov,et al.  Parameters of Pedestrian Flow for Modeling Purposes , 2010 .

[54]  T Urbanik,et al.  Evacuation time estimates for nuclear power plants. , 2000, Journal of hazardous materials.

[55]  Torsten Hägerstraand.  WHAT ABOUT PEOPLE IN REGIONAL SCIENCE , 1970 .