Abstract
Human behavior in a crisis situation can be very different from what is expected. Although intrinsically related to the personality of individuals and several other educational and innate parameters, in response to crisis situations, several emotional characters, and spontaneous behaviors can be triggered in search of outcomes. These psychological expressions are multiple and can be followed by variable decision-making inadequacy with the situation. This paper presents the impact of fuzzy behavior in the decision-making process in a crisis. The objective is to control the flow in public closed spaces while avoiding crowd formation to prevent contamination of the COVID’19 virus. We evaluate our model by simulating passenger behaviors in a closed public area during the post-pandemic COVID’19 context. In the experiments, we show the impact of the combination of rationality and emotional characters on the traffic flow and the risk of the pandemic spread.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Blackwood, J.C., Childs, L.M.: An introduction to compartmental modeling for the budding infectious disease modeler (2018)
Del Sent, A., Roisenberg, M., de Freitas Filho, P.J.: Simulation of crowd behavior using fuzzy social force model. In: 2015 Winter Simulation Conference (WSC), pp. 3901–3912. IEEE (2015)
Dell’Orco, M., Marinelli, M., Ottomanelli, M.: Simulation of crowd dynamics in panic situations using a fuzzy logic-based behavioural model. In: Computer-Based Modelling and Optimization in Transportation, pp. 237–250. Springer (2014)
Mao, Y., Fan, X., Fan, Z., He, W.: Modeling group structures with emotion in crowd evacuation. IEEE Access 7, 140010–140021 (2019)
Ronchi, E., Scozzari, R., Fronterrè, M.: A risk analysis methodology for the use of crowd models during the covid-19 pandemic (2020)
Sakour, I., Hu, H.: Robot-assisted crowd evacuation under emergency situations: a survey. Robotics 6(2), 8 (2017)
Sharma, S., Ogunlana, K., Scribner, D., Grynovicki, J.: Modeling human behavior during emergency evacuation using intelligent agents: a multi-agent simulation approach. Inf. Syst. Front. 20(4), 741–757 (2018)
Sharma, S., Singh, H., Prakash, A.: Multi-agent modeling and simulation of human behavior in aircraft evacuations. IEEE Trans. Aerosp. Electron. Syst. 44(4), 1477–1488 (2008)
Şuvar, M.C., Păsculescu, V.M., Irimia, A., Păsculescu, D.: Aspects regarding numerical models for safe evacuation of people, in the current pandemic context. In: MATEC Web of Conferences, vol. 342. EDP Sciences (2021)
Xue, Z., Dong, Q., Fan, X., Jin, Q., Jian, H., Liu, J.: Fuzzy logic-based model that incorporates personality traits for heterogeneous pedestrians. Symmetry 9(10), 239 (2017)
Zakaria, W., Yusof, U.K., Naim, S.: Modelling and simulation of crowd evacuation with cognitive behaviour using fuzzy logic. Int. J. Adv. Soft Comput. Appl. 11(2) (2019)
Zhu, B., Liu, T., Tang, Y.: Research on pedestrian evacuation simulation based on fuzzy logic. In: 2008 9th International Conference on Computer-Aided Industrial Design and Conceptual Design, pp. 1024–1029. IEEE (2008)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Abdallah, W., Abdallah, O., Kanzari, D., Madani, K. (2022). Fuzzy Decision-Making in Crisis Situation: Crowd Flow Control in Closed Public Spaces in COVID’19. In: Czarnowski, I., Howlett, R.J., Jain, L.C. (eds) Intelligent Decision Technologies. Smart Innovation, Systems and Technologies, vol 309. Springer, Singapore. https://doi.org/10.1007/978-981-19-3444-5_42
Download citation
DOI: https://doi.org/10.1007/978-981-19-3444-5_42
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-19-3443-8
Online ISBN: 978-981-19-3444-5
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)