Transcript 142 Development of a Computer-Aided Model for Reliable Terminal

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
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
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1. Institute Of Aviation
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director of the institute: Professor Hartmut Fricke
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young team (9 assistants) of aviation experts and engineers
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key aspects of research:
–
–
–
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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
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2. Motivation
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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
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unpredictable human behavior in emergency cases
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identification of bottlenecks and comparison of possible evacuation
strategies
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proposed security assessment systematic to validate strategies
A statistical approach to handle unpredictable passenger behaviour
M. Schultz, S. Lehmann, Prof. H. Fricke
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3. Motion Behavior Of People
- In Emergency Cases •
The motion pattern of people in emergency cases differ heavily from normal,
well-known motion patterns.
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An experiment in a Japanese supermarket shows the motion behavior under
stress conditions [1]:
– 46,7 %
– 16,7 %
uses the information of warning and information signs and
follows properly staff instructions
move away from impact zone and intend to leave the consequence
area
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
– 26,3 %
[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
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3. Motion Behavior Of People
- In Emergency Cases -
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classification of escape behavior according to SCHNEIDER[2]
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approx. 10 - 15 %
act rational and are able to lead other persons out of
the hazard area
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approx. 70 %
are astonished and composed, they can be led by clear
instructions
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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
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4. Cellular Automaton Approach
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microscopic model (simulation of individuals)
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two dimensional
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spatial, time and state discrete
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regular lattice with Moore neighbourhood relationship
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one cell has two states  empty, occupied
A statistical approach to handle unpredictable passenger behaviour
M. Schultz, S. Lehmann, Prof. H. Fricke
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4. Cellular Automaton Approach
- model description -
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one person per cell  dimension 40 cm x 40 cm
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person moves one cell per time step (single speed model)
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max. walking speed according to WEIDMANN [3] vmax= 1,34 ms
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renunciation of acceleration, persons reach vmax within 0,5 s [4]
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time step t = 0,3 s
-1
[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
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4. Cellular Automaton Approach
- statistical model •
independency of longitudinal p und transversal q motion components
M ij = pi  q j
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probability distribution by variance s , mean value m and probability w
1=
w
iI
i
m =  i wi
iI
s 2 =  (i  m ) wi
M-1 -1
M 0 -1
M 1 -1
M 0 -1
M0
0
M0
1
M 1 -1
M 0 +1
M1
1
2
iI
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explicit probability is given by
1
w1 = (s 2  m 2  m )
2
w 0 = 1  (s 2  m 2 )
1
w1 = (s 2  m 2  m )
2
A statistical approach to handle unpredictable passenger behaviour
M. Schultz, S. Lehmann, Prof. H. Fricke
pi
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qj
4. Cellular Automaton Approach
- statistical model •
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variance sp and mean value mp of longitudinal component p
0  mp  1
1
1
 mp  
4
2
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2
 s p2  1  m p
2
2
variance sq and mean value mq of transversal component q
mq = 0
0  s q2  1
A statistical approach to handle unpredictable passenger behaviour
M. Schultz, S. Lehmann, Prof. H. Fricke
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5. Model Details
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overlapping of
– spatial discrete cellular automaton
– spatial discretized continuous model
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 statistical model
 potential theory
statistical model
– changing of person motion behavior parameter
 velocity, purposefulness
– position of obstacles
– line of sight
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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
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5. Model Details
- layer model using a layer structure to
describe scenarios, where each
layer contains specific information
1. layer
example for layers:
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building structure
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obstacles and barriers
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guidance, evacuation system
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person traces (active walker)
2. layer
3. layer
4. layer
n. layer
A statistical approach to handle unpredictable passenger behaviour
M. Schultz, S. Lehmann, Prof. H. Fricke
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6. Conclusion And Perspective
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tests of different evacuation strategies
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identification of safety parameters in addition to walking range and
evacuation time
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recommendations for evacuation strategies (rescue management)
A statistical approach to handle unpredictable passenger behaviour
M. Schultz, S. Lehmann, Prof. H. Fricke
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Thank you for your attention!
Contact: [email protected]
A statistical approach to handle unpredictable passenger behaviour
M. Schultz, S. Lehmann, Prof. H. Fricke
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