The Impact of Pedestrian Lane Formation by Obstacles on Fire Evacuation Efficiency in the Presence of Unfair Competition
Abstract
:1. Introduction
Pedestrian Behavior  References  Pros and Cons 

Faster is slower  Helbing et al. [20] 

Stopandgo  Yu et al. [40] 

Bidirectional pedestrian flow stratification  Helbing et al. [41] 

Overtaking  Yuen et al. [42] 

2. Model Description
2.1. Classical Social Force Model (SFM)
2.2. Modified Social Force Model (MSFM)
3. Experimental Data and Parameter Values
4. Results
5. Discussion
5.1. Influence of Desired Speed on Evacuation Efficiency
5.2. Influence of Obstacles on Evacuation Efficiency
6. Conclusions
 Under the premise of meeting functional requirements, indoor installation should avoid centralized placement of fixed facilities as much as possible. It is suggested to use fixed facilities to divide the room into multiple regular and independent areas, thereby forming multiple narrow evacuation paths. Each area should have independent evacuation paths leading to the exit to avoid congestion and confusion caused by pedestrian interaction in different queues.
 The layout of fixed facilities should consider that the evacuation path formed by them can lead directly to the exit. Even if the visibility is low in the fire environment, pedestrians can reach the exit quickly and smoothly by walking on the edge of the fixed facilities.
 Managers should regularly conduct fire safety education to increase pedestrians’ confidence in surviving during hazardous events. This helps to reduce tendencies towards unfair competition from a psychological perspective.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Appendix A
ID  Flame  Rotation Angle (°)  Effective Radius (Real)  Effective Radius (β = 0.25)  Effective Radius (β = 0.5)  Effective Radius (β = 0.75)  Effective Radius (β = 1) 
1  158  30  0.2341  0.2274  0.2286  0.2291  0.2291 
6  87  40  0.2252  0.2276  0.2293  0.2303  0.2308 
7  252  30  0.2341  0.2270  0.2276  0.2275  0.2271 
11  585  34.2  0.2304  0.2267  0.2269  0.2265  0.2261 
17  69    0.2250  0.2279  0.2304  0.2324  0.2341 
17  346  69  0.2048  0.2269  0.2273  0.2271  0.2267 
20  60  37  0.2279  0.2284  0.2321  0.2361  0.2400 
22  39  47  0.2192  0.2281  0.2311  0.2339  0.2364 
30  315  44.8  0.2210  0.2270  0.2277  0.2276  0.2273 
58  56  24.9  0.2384  0.2280  0.2307  0.2331  0.2351 
66  56  29.6  0.2344  0.2281  0.2309  0.2336  0.2359 
66  235  25.8  0.2377  0.2272  0.2281  0.2283  0.2281 
66  339  41.5  0.2239  0.2268  0.2272  0.2269  0.2265 
75  28  19.2  0.2427  0.2284  0.2326  0.2371  0.2415 
References
 Ma, Y.Y.; Zhang, Z.C.; Zhang, W.K.; Lee, E.W.; Shi, M. Development of a time pressurebased model for the simulation of an evacuation in a fire emergency. J. Build. Eng. 2024, 87, 109069. [Google Scholar] [CrossRef]
 García, A.; HernándezDelfin, D.; Lee, D.J.; Ellero, M. Limited visual range in the Social Force Model: Effects on macroscopic and microscopic dynamics. Phys. A Stat. Mech. Its Appl. 2023, 612, 128461. [Google Scholar] [CrossRef]
 Liu, J.; Zhang, H.; Ding, N.; Li, Y. A modified social force model for sudden attack evacuation based on Yerkes–Dodson law and the tendency toward low risk areas. Phys. A Stat. Mech. Its Appl. 2024, 633, 129403. [Google Scholar] [CrossRef]
 Sticco, I.M.; Cornes, F.E.; Frank, G.A.; Dorso, C.O. Beyond the fasterisslower effect. Phys. Rev. E 2017, 96, 052303. [Google Scholar] [CrossRef] [PubMed]
 Ghani, N.M.; Selamat, H.; Khamis, N.; Ghazalli, S.A. Crowd modelling validation for modified social force model. Int. J. Integr. Eng. 2020, 12, 10–18. [Google Scholar]
 Sticco, I.M.; Frank, G.A.; Cornes, F.E.; Dorso, C.O. A reexamination of the role of friction in the original Social Force Model. Saf. Sci. 2020, 121, 42–53. [Google Scholar] [CrossRef]
 RangelGalván, M.; BallinasHernández, A.L.; RangelGalván, V. Thermoinspired model of selfpropelled hard disk agents for heterogeneous bidirectional pedestrian flow. Phys. A Stat. Mech. Its Appl. 2024, 635, 129500. [Google Scholar] [CrossRef]
 Song, Y.; Hu, X.; Shen, L.; Weng, W. Modeling domino effect along the queue using an improved social force model. Phys. A Stat. Mech. Its Appl. 2023, 625, 129008. [Google Scholar] [CrossRef]
 Üsten, E.; Lügering, H.; Sieben, A. Pushing and nonpushing forward motion in crowds: A systematic psychological observation method for rating individual behavior in pedestrian dynamics. Collect. Dyn. 2022, 7, 1–16. [Google Scholar] [CrossRef]
 Tian, H.H.; Wei, Y.F.; Dong, L.Y.; Xue, Y.; Zheng, R.S. Resolution of conflicts in cellular automaton evacuation model with the gametheory. Phys. A Stat. Mech. Its Appl. 2018, 503, 991–1006. [Google Scholar] [CrossRef]
 Helbing, D.; Buzna, L.; Johansson, A.; Werner, T. Selforganized pedestrian crowd dynamics: Experiments, simulations, and design solutions. Transp. Sci. 2005, 39, 1–24. [Google Scholar] [CrossRef]
 Shi, M.; Lee, E.W.M.; Ma, Y. A dynamic impatiencedetermined cellular automata model for evacuation dynamics. Simul. Model. Pract. Theory 2019, 94, 367–378. [Google Scholar] [CrossRef]
 Fu, L.; Fang, J.; Cao, S.; Lo, S. A cellular automaton model for exit selection behavior simulation during evacuation processes. Procedia Eng. 2018, 211, 169–175. [Google Scholar] [CrossRef]
 Hu, X.; Chen, T.; Deng, K.; Wang, G. Effects of aggressiveness on pedestrian room evacuation using extended cellular automata model. Phys. A Stat. Mech. Its Appl. 2023, 619, 128731. [Google Scholar] [CrossRef]
 Guan, J.; Wang, K. Towards pedestrian room evacuation with a spatial game. Appl. Math. Comput. 2019, 347, 492–501. [Google Scholar] [CrossRef]
 von Schantz, A.; Ehtamo, H. Pushing and overtaking others in a spatial game of exit congestion. Phys. A Stat. Mech. Its Appl. 2019, 527, 121151. [Google Scholar] [CrossRef]
 Ma, L.; Chen, B.; Chen, L.; Xu, X.; Liu, S.; Liu, X. Data driven analysis of the desired speed in ordinary differential equation based pedestrian simulation models. Phys. A Stat. Mech. Its Appl. 2022, 608, 128241. [Google Scholar] [CrossRef]
 Yuan, Z.; Jia, H.; Zhang, L.; Bian, L. A social force evacuation model considering the effect of emergency signs. Simulation 2018, 94, 723–737. [Google Scholar] [CrossRef]
 Yang, X.; Yang, X.; Pan, F.; Kang, Y.; Zhang, J. The effect of passenger attributes on alighting and boarding efficiency based on social force model. Phys. A Stat. Mech. Its Appl. 2021, 565, 125566. [Google Scholar] [CrossRef]
 Helbing, D.; Farkas, I.; Vicsek, T. Simulating dynamical features of escape panic. Nature 2000, 407, 487–490. [Google Scholar] [CrossRef]
 Helbing, D.; Farkas, I.J.; Molnar, P.; Vicsek, T. Simulation of pedestrian crowds in normal and evacuation situations. Pedestr. Evacuation Dyn. 2002, 21, 21–58. [Google Scholar]
 Fukamachi, M.; Nagatani, T. Sidle effect on pedestrian counter flow. Phys. A Stat. Mech. Its Appl. 2007, 377, 269–278. [Google Scholar] [CrossRef]
 Guo, N.; Hu, M.B.; Jiang, R. Impact of variable body size on pedestrian dynamics by heuristicsbased model. Phys. A Stat. Mech. Its Appl. 2017, 465, 109–114. [Google Scholar] [CrossRef]
 Jin, C.J.; Jiang, R.; Yin, J.L.; Dong, L.Y.; Li, D. Simulating bidirectional pedestrian flow in a cellular automaton model considering the bodyturning behavior. Phys. A Stat. Mech. Its Appl. 2017, 482, 666–681. [Google Scholar] [CrossRef]
 Yamamoto, H.; Yanagisawa, D.; Feliciani, C.; Nishinari, K. Bodyrotation behavior of pedestrians for collision avoidance in passing and cross flow. Transp. Res. Part B Methodol. 2019, 122, 486–510. [Google Scholar] [CrossRef]
 Chraibi, M.; Seyfried, A.; Schadschneider, A. Generalized centrifugalforce model for pedestrian dynamics. Phys. Rev. E 2010, 82, 046111. [Google Scholar] [CrossRef] [PubMed]
 Zheng, X.; PalffyMuhoray, P. Distance of closest approach of two arbitrary hard ellipses in two dimensions. Phys. Rev. E 2007, 75, 061709. [Google Scholar] [CrossRef] [PubMed]
 Chen, H.; Zhang, X. Path planning for intelligent vehicle collision avoidance of dynamic pedestrian using AttLSTM, MSFM, and MPC at unsignalized crosswalk. IEEE Trans. Ind. Electron. 2021, 69, 4285–4295. [Google Scholar] [CrossRef]
 Fu, L.; Qin, H.; He, Y.; Shi, Y. Application of the social force modelling method to evacuation dynamics involving pedestrians with disabilities. Appl. Math. Comput. 2024, 460, 128297. [Google Scholar] [CrossRef]
 Zhao, Y.; Lu, T.; Su, W.; Wu, P.; Fu, L.; Li, M. Quantitative measurement of social repulsive force in pedestrian movements based on physiological responses. Transp. Res. Part B Methodol. 2019, 130, 1–20. [Google Scholar] [CrossRef]
 Hu, X.; Chen, T.; Song, Y. Anticipation dynamics of pedestrians based on the elliptical social force model. Chaos Interdiscip. J. Nonlinear Sci. 2023, 33, 073102. [Google Scholar] [CrossRef]
 Su, B.; Andelfinger, P.; Kwak, J.; Eckhoff, D.; Cornet, H.; Marinkovic, G.; Cai, W.; Knoll, A. A passenger model for simulating boarding and alighting in spatially confined transportation scenarios. J. Comput. Sci. 2020, 45, 101173. [Google Scholar] [CrossRef]
 Ronayne, D.; Sgroi, D.; Tuckwell, A. Evaluating the sunk cost effect. J. Econ. Behav. Organ. 2021, 186, 318–327. [Google Scholar] [CrossRef]
 Ohlert, C.R.; Weißenberger, B.E. Debiasing escalation of commitment: The effectiveness of decision aids to enhance deescalation. J. Manag. Control 2020, 30, 405–438. [Google Scholar] [CrossRef]
 Lu, L.; Ji, J.; Zhai, C.; Wang, S.; Zhang, Z.; Yang, T. Research on the Influence of Narrow and Long Obstacles with Regular Configuration on Crowd Evacuation Efficiency Based on Tri14 Model with an Example of Supermarket. Fire 2022, 5, 164. [Google Scholar] [CrossRef]
 Chinese Ministry of Housing and UrbanRural Development. Code for Fire Protection in Building Design, GB 550372022; China Planning Press: Beijing, China, 2022; pp. 33–34.
 Lin, P.; Gao, D.L.; Wang, G.Y.; Wu, F.Y.; Ma, J.; Si, Y.L.; Ran, T. The Impact of an Obstacle on Competitive Evacuation Through a Bottleneck. Fire Technol. 2019, 55, 1967–1981. [Google Scholar] [CrossRef]
 Li, J.; Wang, J.; Xu, S.; Feng, J.; Li, J.; Wang, Z.; Wang, Y. The effect of geometric layout of exit on escape mechanism of crowd. Build. Simul. 2022, 15, 659–668. [Google Scholar] [CrossRef]
 Jia, X.L.; Murakami, H.; Feliciani, C.; Yanagisawa, D.; Nishinari, K. Pedestrian lane formation and its influence on egress efficiency in the presence of an obstacle. Saf. Sci. 2021, 144, 105455. [Google Scholar] [CrossRef]
 Yu, W.; Johansson, A. Modeling crowd turbulence by manyparticle simulations. Phys. Rev. E—Stat. Nonlinear Soft Matter Phys. 2007, 76, 046105. [Google Scholar] [CrossRef]
 Helbing, D.; Farkas, I.J.; Vicsek, T. Freezing by heating in a driven mesoscopic system. Phys. Rev. Lett. 2000, 84, 1240. [Google Scholar] [CrossRef]
 Yuen, J.; Lee, E. The effect of overtaking behavior on unidirectional pedestrian flow. Saf. Sci. 2012, 50, 1704–1714. [Google Scholar] [CrossRef]
 Helbing, D.; Molnar, P. Social force model for pedestrian dynamics. Phys. Rev. E 1995, 51, 4282. [Google Scholar] [CrossRef]
 AndrésThió, N.; Ras, C.; Bolger, M.; Lemiale, V. A study of the role of forceful behaviour in evacuations via microscopic modelling of evacuation drills. Saf. Sci. 2021, 134, 105018. [Google Scholar] [CrossRef]
 Haghani, M.; Sarvi, M.; Shahhoseini, Z. When ‘push’does not come to ‘shove’: Revisiting ‘faster is slower’in collective egress of human crowds. Transp. Res. Part A Policy Pract. 2019, 122, 51–69. [Google Scholar] [CrossRef]
 Zhang, W.; Zhang, Z.; Ma, Y.; Lee, E.W.M.; Shi, M. Psychological impatience in pedestrian evacuation: Modelling, simulations and experiments. Phys. A Stat. Mech. Its Appl. 2024, 635, 129472. [Google Scholar] [CrossRef]
 You, L.; Wu, Q.; Wei, J.; Hu, J.; Wang, J.; Liang, Y. A study of pedestrian evacuation model of impatient queueing with cellular automata. Phys. Scr. 2020, 95, 095211. [Google Scholar] [CrossRef]
 Corbetta, A.; Toschi, F. Physics of human crowds. Annu. Rev. Condens. Matter Phys. 2023, 14, 311–333. [Google Scholar] [CrossRef]
 Crowds in Front of Bottlenecks from the Perspective of Physics and Social Psychology. Available online: http://ped.fzjuelich.de/da/2018crowdqueue (accessed on 3 January 2018).
 Cornes, F.E.; Frank, G.A.; Dorso, C.O. Microscopic dynamics of the evacuation phenomena in the context of the Social Force Model. Phys. AStat. Mech. Its Appl. 2021, 568, 125744. [Google Scholar] [CrossRef]
Parameters  Value 

${m}_{i}$  80 kg 
${v}_{i}^{0}\left(t\right)$  3 m/s 
${\tau}_{i}$  0.5 s 
${A}_{i}$  2000 
${B}_{i}$  0.08 
$k$  1.2 × 10^{5} 
$\kappa $  2.4 × 10^{5} 
${\overrightarrow{v}}_{i}^{\mathrm{max}}$  5 m/s 
${r}_{i}$  0.25 m 
${a}_{i}$  0.25 m 
${b}_{i}$  0.2 m 
${\rho}_{\mathrm{max}}$  9 ped/m^{2} [45] 
Search Radius  $3{\mathbf{a}}_{\mathbf{i}}$  $4{\mathbf{a}}_{\mathbf{i}}$  $5{\mathbf{a}}_{\mathbf{i}}$ 

Standard deviation  2.01  4.03  5.92 
$\mathit{\beta}$  0.25  0.5  0.75  1 

Mean absolute error  0.007479  0.007464  0.007421  0.007621 
$\mathit{\alpha}$  0.6  0.7  0.8  0.9 

Mean absolute error  1.5  2.4  3  1.8 
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. 
© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Liu, S.; Li, X.; Peng, B.; Li, C. The Impact of Pedestrian Lane Formation by Obstacles on Fire Evacuation Efficiency in the Presence of Unfair Competition. Fire 2024, 7, 242. https://doi.org/10.3390/fire7070242
Liu S, Li X, Peng B, Li C. The Impact of Pedestrian Lane Formation by Obstacles on Fire Evacuation Efficiency in the Presence of Unfair Competition. Fire. 2024; 7(7):242. https://doi.org/10.3390/fire7070242
Chicago/Turabian StyleLiu, Shanwei, Xiao Li, Bozhezi Peng, and Chaoyang Li. 2024. "The Impact of Pedestrian Lane Formation by Obstacles on Fire Evacuation Efficiency in the Presence of Unfair Competition" Fire 7, no. 7: 242. https://doi.org/10.3390/fire7070242