- ICRAT 2004 - Dipl.-Wirtsch.-Ing. Michael Schultz Dipl.-Ing. Susann Lehmann

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 SchultzDipl.-Ing. Susann Lehmann

Prof. Dr.-Ing. habil. Hartmut Fricke

Zilina, 23.11.2004

A statistical approach to handle unpredictable passenger behaviour M. Schultz, S. Lehmann, Prof. H. Fricke 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


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


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


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


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


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


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


• independency of longitudinal p und transversal q motion components

• probability distribution by variance , mean value and probability

• explicit probability is given by

4. Cellular Automaton Approach- statistical model -

)(2

1 221 w

)(2

1 221 w

)(1 220 w

iIi

Iii

Iii

wi

wi

w

22 )(

1

jiij qpM

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

pi

qj

w


• variance p

and mean value p of longitudinal component p

• variance q

and mean value q of transversal component q

4. Cellular Automaton Approach- statistical model -

10 p

222

12

1

4

1ppp

0q

10 2 q


• 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

5. Model Details


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)

5. Model Details - layer model -

1. layer

2. layer

3. layer

4. layer

n. layer


• tests of different evacuation strategies

• identification of safety parameters in addition to walking range and evacuation time

• recommendations for evacuation strategies (rescue management)

6. Conclusion And Perspective


Thank you for your attention!

Contact: [email protected]

- ICRAT 2004 - Dipl.-Wirtsch.-Ing. Michael Schultz Dipl.-Ing. Susann Lehmann

Documents

Transcript of - ICRAT 2004 - Dipl.-Wirtsch.-Ing. Michael Schultz Dipl.-Ing. Susann Lehmann