Abstract

Understanding the effects of panic on crowd dynamics in emergency situations has long been considered necessary for pedestrian evacuation control. In the case of disasters, stampedes caused by panic behaviors occur with high possibility, and pedestrians are crushed or trampled, leading to enormous casualties. To eliminate the computational errors accumulated in the traditional macromodel, a macro-microconversion model based on the SF (social force) model and the AR (Aw-Rascle) model is proposed in this paper. The purpose is to use the crowd parameters of the microscopic model as the input part of the macroscopic model and to combine the advantages of the two models to ensure accuracy and improve calculation performance. The concept of the “pressure term” is defined to measure the panic level of the crowd. In addition, a flowchart of the numerical simulation is designed based on the road network conditions at the trampling site. To validate the conversion model, a numerical simulation is conducted in a case study of the Mecca Hajj stampede in 2015. The simulation results display the whole process of crowd marching and meeting with the dynamic variations of the “pressure term.” The simulation results are compared with the traditional simulation results based on a Gaussian distribution, which verifies that the simulation results obtained by the proposed method are closer to the real situation. Moreover, in this study, a new micromacro transformation method for crowd evaluation dynamics, which can enhance computing speed and execution efficiency, is provided.

References

1.
Haghani
,
M.
,
2020
, “
Empirical Methods in Pedestrian, Crowd and Evacuation Dynamics: Part II. Field Methods and Controversial Topics
,”
Safety Sci.
,
129
, pp. 1–21.10.1016/j.ssci.2020.104760
2.
Haghani
,
M.
,
2022
, “
Crowd Dynamics Research in the Era of Covid-19 Pandemic: Challenges and Opportunities
,”
Saftey Sci.
,
153
(
153
), p.
105818
.10.1016/j.ssci.2022.105818
3.
Li
,
G.
, and
Deng
,
Y.
,
2021
, “
Crowd Dynamics Analysis Using a Bio-Inspired Model
,” IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers (
IPEC
),
IEEE
,
Dalian, China
, Apr. 14–16, pp. 931–934.10.1109/IPEC51340.2021.9421275
4.
Helbing
,
D.
,
1998
, “
A Fluid Dynamic Model for the Movement of Pedestrians
,”
Complex Syst.
,
6
(
5
), pp.
391
415
.https://www.researchgate.net/publication/1947066_A_Fluid_Dynamic_Model_for_the_Movement_of_Pedestrians
5.
Tajima
,
Y.
, and
Nagatani
,
T.
,
2001
, “
Scaling Behavior of Crowd Flow Outside a Hall
,”
Phys. A
,
292
(
1–4
), pp.
545
554
.10.1016/S0378-4371(00)00630-0
6.
Andreianov
,
B.
,
Donadello
,
C.
, and
Rosini
,
M. D.
,
2016
, “
A Second-Order Model for Vehicular Traffics With Local Point Constraints on the Flow
,”
Math. Models Methods Appl. Sci.
,
26
(
4
), pp.
751
802
.10.1142/S0218202516500172
7.
Andreianov
,
B. P.
,
Donadello
,
C.
,
Razafison
,
U.
,
Rolland
,
J. Y.
, and
Rosini
,
M. D.
,
2016
, “
Solutions of the Aw-Rascle-Zhang System With Point Constraints
,”
Networks Heterog. Media
,
11
(
1
), pp.
29
47
.10.3934/nhm.2016.11.29
8.
Vasilev
,
E. I.
,
Ben-Dor
,
G.
,
Elperin
,
T.
, and
Henderson
,
L. F.
,
2004
, “
The Wall-Jetting Effect in Mach Reflection: Navier–Stokes Simulations
,”
J. Fluid Mech.
,
511
, pp.
363
379
.10.1017/S0022112004009668
9.
Farooq
,
M. U.
,
Saad
,
M. N. B. M.
,
Malik
,
A. S.
,
Salih Ali
,
Y.
, and
Khan
,
S. D.
,
2020
, “
Motion Estimation of High Density Crowd Using Fluid Dynamics
,”
Imaging Sci. J.
,
68
(
3
), pp.
141
155
.10.1080/13682199.2020.1767843
10.
Colombo
,
R. M.
, and
Rosini
,
M. D.
,
2005
, “
Pedestrian Flows and Non-Classical Shocks
,”
Math. Methods Appl. Sci.
,
28
(
13
), pp.
1553
1567
.10.1002/mma.624
11.
Colombo
,
R. M.
, and
Rosini
,
M. D.
,
2009
, “
Existence of Nonclassical Solutions in a Pedestrian Flow Model
,”
Nonlinear Anal. Real World Appl.
,
10
(
5
), pp.
2716
2728
.10.1016/j.nonrwa.2008.08.002
12.
Zhao
,
R.
,
Wang
,
D.
,
Wang
,
Y.
,
Han
,
C.
,
Jia
,
P.
,
Li
,
C.
, and
Ma
,
Y.
,
2021
, “
Macroscopic View: Crowd Evacuation Dynamics at T-Shaped Street Junctions Using a Modified Aw-Rascle Traffic Flow Model
,”
IEEE Trans. Intelligent Transportation Systems
,
22
(
10
), pp.
6612
6621
.10.1109/TITS.2021.3095829
13.
Francesco
,
M. D.
,
Fagioli
,
S.
, and
Rosini
,
M. D.
,
2017
, “
Many Particle Approximation of the Aw-Rascle-Zhang Second Order Model for Vehicular Traffic
,”
Math. Biosci. Eng.
,
14
(
1
), pp.
127
141
.10.3934/mbe.2017009
14.
Rosini
,
M. D.
,
2013
, “
Macroscopic Models for Vehicular Flows and Crowd Dynamics: Theory and Applications
,”
Understanding Complex Systems
, Vol.
8
,
Springer
,
Basel, Switzerland
, pp.
111
120
.
15.
Rosini
,
M. D.
,
2020
, “
Microscopic and Macroscopic Models for Vehicular and Pedestrian Flows
,”
Order, Disorder Criticality: Advanced Problems of Phase Transition Theory
, Vol.
6
, World Scientific Publishing Co, Singapore, pp.
223
277
.
16.
Yang
,
S.
,
Li
,
T.
,
Gong
,
X.
,
Peng
,
B.
, and
Hu
,
J.
,
2020
, “
A Review on Crowd Simulation and Modeling
,”
Graphical Models
,
111
, p.
101081
.10.1016/j.gmod.2020.101081
17.
Shahhoseini
,
Z.
, and
Sarvi
,
M.
,
2019
, “
Pedestrian Crowd Flows in Shared Spaces: Investigating the Impact of Geometry Based on Micro and Macro Scale Measures
,”
Transp. Res. Part B Methodol. J.
,
122
, pp.
57
87
.10.1016/j.trb.2019.01.019
18.
Aw
,
A.
, and
Rascle
,
M.
,
2000
, “
Reconstruction of 'Second Order' Models of Traffic Flow
,”
SIMA J. Appl. Math.
,
60
(
3
), pp.
916
938
.10.1137/S0036139997332099
19.
Helbing
,
D.
, and
Molnar
,
P.
,
1995
, “
Social Force Model for Pedestrian Dynamics
,”
Phys. Rev. E
,
51
(
5
), pp.
4282
4286
.10.1103/PhysRevE.51.4282
20.
Cornes
,
F. E.
,
Frank
,
G. A.
, and
Dorso
,
C. O.
,
2021
, “
Microscopic Dynamics of the Evacuation Phenomena in the Context of the Social Force Model
,”
Phys. A
,
568
(
4
), p.
125744
.10.1016/j.physa.2021.125744
21.
Wang
,
C.
,
2007
, “
Theory and Application of Crowd Risk Concentration in Urban Public Places
,” doctoral dissertation,
Nankai University, Tianjin, China
.
22.
Hu
,
C. P.
,
Feng
,
J.
, and
Wang
,
Y. L.
,
2012
, “
Evaluation Model of Operational Efficiency of Integrated Passenger Transport Hub Based on Pedestrian Dynamics
,”
Logistics Technol.
,
31
(
7
), pp.
185
187
.
23.
Ren
,
W.
,
Cheng
,
R.
, and
Ge
,
H.
,
2021
, “
Bifurcation Analysis of a Heterogeneous Continuum Traffic Flow Model
,”
Appl. Math. Modell.
,
94
, pp.
369
387
.10.1016/j.apm.2021.01.025
24.
Kaur
,
D.
, and
Sharma
,
S.
,
2020
, “
A New Two-Lane Lattice Model by Considering Predictive Effect in Traffic Flow
,”
Phys. A
,
539
, p.
122913
.10.1016/j.physa.2019.122913
25.
Duives
,
D. C.
,
Daamen
,
W.
, and
Hoogendoorn
,
S. P.
,
2015
, “
Continuum Modelling of Pedestrian flows-Part 2: Sensitivity Analysis Featuring Crowd Movement Phenomena
,”
Phys. A: Stat Mech. Appl.
, 447, pp.
36
48
.10.1016/j.physa.2015.11.025
26.
Kachroo
,
P.
,
Al-Nasur
,
S.
,
Wadoo
,
S.
, and
Shende
,
A.
,
2008
,
Pedestrian Dynamics: Feedback Control of Crowd Evacuation
, Springer, Berlin.
27.
Goatin
,
P.
,
Colombo
,
R. M.
, and
Rosini
,
M. D.
,
2010
, “
A Macroscopic Model for Pedestrian Flows in Panic Situations
,”
4th Pol.-Jpn. Days
,
32
, pp.
255
272
.https://www.researchgate.net/publication/50232096_A_macroscopic_model_for_pedestrian_flows_in_panic_situations
28.
Helbing
,
D.
,
Johansson
,
A.
, and
Alabideen
,
H. Z.
,
2007
, “
Dynamics of Crowd Disasters: An Empirical Study
,”
Phys. Rev. E
,
75
(
4
), p.
046109
.10.1103/PhysRevE.75.046109
29.
Yao
,
Z.
,
Xu
,
T.
,
Jiang
,
Y.
, and
Hu
,
R.
,
2021
, “
Linear Stability Analysis of Heterogeneous Traffic Flow Considering Degradations of Connected Automated Vehicles and Reaction Time
,”
Phys. A
,
561
, p.
125218
.10.1016/j.physa.2020.125218
30.
BBC News,
2015
, “
Hajj Stampede: What we Know so Far [DB/OL]
,” accessed Oct. 1, http://www.bbc.com/news/world-middle-east-34357952
31.
Moussaid
,
M.
,
Helbing
,
D.
, and
Theraulaz
,
G.
,
2011
, “
How Simple Rules Determine Pedestrian Behavior and Crowd Disasters
,”
PNAS
,
108
(
17
), pp.
6884
6888
.10.1073/pnas.1016507108
32.
Wang
,
D.
,
Zhao
,
R. Y.
,
Li
,
C. L.
,
Hu
,
Q. S.
,
Tian
,
X. K.
, and
Zhang
,
Q.
,
2017
, “
Simulation and Analysis of T-Shaped Road Junction Stampede Using Macroscopic Model
,”
Proceedings on Service System Engineering Conference & Symposium on Analysis and Risk
,
Shanghai, China
, July 7–9, pp. 51–58.
33.
Dal Santo
,
E.
,
Donadello
,
C.
,
Pellegrino
,
S. F.
, and
Rosini
,
M. D.
,
2019
, “
Representation of Capacity Drop at a Road Merge Via Point Constraints in a First Order Traffic Model
,”
ESAIM Math. Model. Numer. Anal
,
53
(
1
), pp.
1
34
.10.1051/m2an/2019002
34.
Haut
,
B.
,
Bastin
,
G.
, and
Chitour
,
Y.
,
2005
, “
A Macroscopic Traffic Model for Road Networks With a Representation of the Capacity Drop Phenomenon at the Junctions
,”
IFAC Proc. Vol.
,
38
(
1
), pp.
114
119
.10.3182/20050703-6-CZ-1902.02042
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