Statistical Model for Terminal Evacuation Simulation

1. Development of a computer-aided model for reliable terminal evacuation simulation – a statistical approach to handle unpredictable passenger behavior - ICRAT 2004 - Dipl.-Wirtsch.-Ing. Michael Schultz Dipl.-Ing. Susann Lehmann Prof. Dr.-Ing. habil. Hartmut Fricke Zilina, 23.11.2004

2. Structure Of Presentation 1. Institute Of Aviation 2. Motivation 3. Motion Behavior Of People 4. Cellular Automaton Approach 5. Model Details 6. Conclusion And Perspective A statistical approach to handle unpredictable passenger behaviour M. Schultz, S. Lehmann, Prof. H. Fricke

3. 1. Institute Of Aviation • director of the institute: Professor Hartmut Fricke • young team (9 assistants) of aviation experts and engineers • key aspects of research: • Air Transport Infrastructure Planning • Air Transport System Technologies • Optimizing Ground Handling and Passenger Flow Processes • Capacity Analysis: Correlating Capacity and Safety A statistical approach to handle unpredictable passenger behaviour M. Schultz, S. Lehmann, Prof. H. Fricke

4. 2. Motivation • airport terminal • complex infrastructure ( passenger dispatch vs. leisure) • high passenger frequency, capacity often nearly saturated • accentuation of security conditions • highest security/safety standards in transportation  terminal as a reference for granting security in buildings • unpredictable human behavior in emergency cases • identification of bottlenecks and comparison of possible evacuation strategies • proposed security assessment systematic to validate strategies A statistical approach to handle unpredictable passenger behaviour M. Schultz, S. Lehmann, Prof. H. Fricke

5. 3. Motion Behavior Of People- In Emergency Cases - • The motion pattern of people in emergency cases differ heavily from normal, well-known motion patterns. • An experiment in a Japanese supermarket shows the motion behavior under stress conditions [1]: • 46,7 % uses the information of warning and information signs and follows properly staff instructions • 26,3 % move away from impact zone and intend to leave the consequence area • 16,7 % use the next reachable exit • 3 % follow other persons • 3 % avoid gathering • 2,3 % prefer the "brightest" exit • 1,7 % choose arbitrarily any door to escape [1] Abe "Human Science of Panic", Brain Pub. Co., Tokyo, 1986 A statistical approach to handle unpredictable passenger behaviour M. Schultz, S. Lehmann, Prof. H. Fricke

6. 3. Motion Behavior Of People- In Emergency Cases - • classification of escape behavior according to SCHNEIDER[2] • approx. 10 - 15 % act rational and are able to lead other persons out of the hazard area • approx. 70 % are astonished and composed, they can be led by clear instructions • approx. 10 - 15 % act unpredictable, do freeze or start to stampede [2] Schneider "Evakuierung bei Brandereignissen", lecture at Technische Akademie Esslingen, Institute for Building Materials, Building Physics, and Fire Protection, Vienna University of Technology, 2004 A statistical approach to handle unpredictable passenger behaviour M. Schultz, S. Lehmann, Prof. H. Fricke

7. 4. Cellular Automaton Approach • microscopic model (simulation of individuals) • two dimensional • spatial, time and state discrete • regular lattice with Moore neighbourhood relationship • one cell has two states  empty, occupied A statistical approach to handle unpredictable passenger behaviour M. Schultz, S. Lehmann, Prof. H. Fricke

8. 4. Cellular Automaton Approach- model description - • one person per cell  dimension 40 cm x 40 cm • person moves one cell per time step (single speed model) • max. walking speed according to WEIDMANN [3] vmax= 1,34 ms-1 • renunciation of acceleration, persons reach vmax within 0,5 s [4] • time step t = 0,3 s [3] Weidmann "Transporttechnik der Fußgänger", Schriftenreihe des IVT, 90, Zürich, 1992 [4] Henderson "The Statistics of Crowd Fluids", p381, Nature 229, 1971 A statistical approach to handle unpredictable passenger behaviour M. Schultz, S. Lehmann, Prof. H. Fricke

9. 4. Cellular Automaton Approach- statistical model - M-1 -1 M 0 -1 M 1 -1 M 0 -1 M 0 0 M 0 1 M 1 -1 M 0 +1 M 1 1 • independency of longitudinal p und transversal q motion components • probability distribution by variance s2, mean value m and probability • explicit probability is given by qj pi A statistical approach to handle unpredictable passenger behaviour M. Schultz, S. Lehmann, Prof. H. Fricke

10. 4. Cellular Automaton Approach- statistical model - • variance sp2 and mean value mp of longitudinal component p • variance sq2 and mean value mq of transversal component q A statistical approach to handle unpredictable passenger behaviour M. Schultz, S. Lehmann, Prof. H. Fricke

11. 5. Model Details • overlapping of • spatial discrete cellular automaton  statistical model • spatial discretized continuous model  potential theory • statistical model • changing of person motion behavior parameter  velocity, purposefulness • position of obstacles • line of sight • potential model • changing of person motion behavior parameter  repulsion, attraction effects due to signs, marks, walls  repulsion, attraction effects due to persons, traces A statistical approach to handle unpredictable passenger behaviour M. Schultz, S. Lehmann, Prof. H. Fricke

12. 5. Model Details - layer model - 1. layer 2. layer 3. layer 4. layer n. layer using a layer structure to describe scenarios, where each layer contains specific information example for layers: • building structure • obstacles and barriers • guidance, evacuation system • person traces (active walker) A statistical approach to handle unpredictable passenger behaviour M. Schultz, S. Lehmann, Prof. H. Fricke

13. 6. Conclusion And Perspective • tests of different evacuation strategies • identification of safety parameters in addition to walking range and evacuation time • recommendations for evacuation strategies (rescue management) A statistical approach to handle unpredictable passenger behaviour M. Schultz, S. Lehmann, Prof. H. Fricke

14. Thank you for your attention! Contact: schultz@ifl.tu-dresden.de A statistical approach to handle unpredictable passenger behaviour M. Schultz, S. Lehmann, Prof. H. Fricke