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Indoor evacuation model based on visual-guidance artificial bee colony algorithm

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  • Advances in Modeling and Simulation Tools
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Abstract

Research on evacuation simulation and modeling is an important and urgent issue for emergency management. This paper presents an evacuation model based on cellular automata and social force to simulate the evacuation dynamics. Attractive force of target position, repulsive forces of individuals and obstacles, as well as congestion are considered in order to simulate the interaction among evacuees and the changing environment. A visual-guidance-based artificial bee colony algorithm is proposed to optimize the evacuation process. Each evacuee moves toward exits with the guidance of leading bee in his/her visual field. And leading bee is selected according to comprehensive factors including distance from the current individual, the number of obstacles and congestion, which avoids the randomness of roulette mechanism used by basic artificial bee colony algorithm. The experimental results indicate that the proposed model and algorithm can achieve effective performances for indoor evacuation problems with a large number of evacuees and obstacles, which accords with the actual evacuation situation.

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References

  • Alam MJ, Habib MA (2020). Modeling traffic disruptions during mass evacuation. Procedia Computer Science, 170: 506–513.

    Article  Google Scholar 

  • Banos A, Corson N, Lang C, et al. (2017). 2-Multiscale modeling: Application to traffic flow. Agent-based Spatial Simulation with NetLogo, 2: 37–62.

    Article  Google Scholar 

  • Basak B, Gupta S (2017). Developing an agent-based model for pilgrim evacuation using visual intelligence: A case study of Ratha Yatra at Puri. Computers, Environment and Urban Systems, 64: 118–131.

    Article  Google Scholar 

  • Chen X, Tianfield H, Li K (2019). Self-adaptive differential artificial bee colony algorithm for global optimization problems. Swarm and Evolutionary Computation, 45: 70–91.

    Article  Google Scholar 

  • Chen Y, Wang C, Li H, et al. (2020). Cellular automaton model for social forces interaction in building evacuation for sustainable society. Sustainable Cities and Society, 53: 101913.

    Article  Google Scholar 

  • Cristiani E, Peri D (2017). Handling obstacles in pedestrian simulations: Models and optimization. Applied Mathematical Modelling, 45: 285–302.

    Article  MathSciNet  Google Scholar 

  • Delcea C, Cotfas LA, Craciun L, et al. (2020). An agent-based modeling approach to collaborative classrooms evacuation process. Safety Science, 121: 414–429.

    Article  Google Scholar 

  • Fang W, Yang L, Fan W (2003). Simulation of bi-direction pedestrian movement using a cellular automata model. Physica A: Statistical Mechanics and Its Applications, 321: 633–640.

    Article  Google Scholar 

  • Fu L, Fang J, Cao S, et al. (2018). A cellular automaton model for exit selection behavior simulation during evacuation processes. Procedia Engineering, 211: 169–175.

    Article  Google Scholar 

  • Gao Y, Luh PB, Zhang H, et al. (2013). A modified social force model considering relative velocity of pedestrians. In: Proceedings of the IEEE International Conference on Automation Science and Engineering, Madison, WI, USA.

  • Gao H, Medjdoub B, Luo H, et al. (2020). Building evacuation time optimization using constraint-based design approach. Sustainable Cities and Society, 52: 101839.

    Article  Google Scholar 

  • Haghani M (2020). Optimising crowd evacuations: Mathematical, architectural and behavioural approaches. Safety Science, 128: 104745.

    Article  Google Scholar 

  • Helbing D, Molnar P (1995). Social force model for pedestrian dynamics. Physical Review E, 51: 4282.

    Article  Google Scholar 

  • Jiang Y, Chen B, Li X, et al. (2020). Dynamic navigation field in the social force model for pedestrian evacuation. Applied Mathematical Modelling, 80: 815–826.

    Article  MathSciNet  Google Scholar 

  • Jumadi, Carver S, Quincey D (2016). A conceptual framework of volcanic evacuation simulation of merapi using agent-based model and GIS. Procedia - Social and Behavioral Sciences, 227: 402–409.

    Article  Google Scholar 

  • Kang Z, Zhang L, Li K (2019). An improved social force model for pedestrian dynamics in shipwrecks. Applied Mathematics and Computation, 348: 355–362.

    Article  MathSciNet  Google Scholar 

  • Khamis N, Selamat H, Ismail FS, et al. (2020). Optimized exit door locations for a safer emergency evacuation using crowd evacuation model and artificial bee colony optimization. Chaos, Solitons & Fractals, 131: 109505.

    Article  MathSciNet  Google Scholar 

  • Kinateder M, Comunale B, Warren WH (2018). Exit choice in an emergency evacuation scenario is influenced by exit familiarity and neighbor behavior. Safety Science, 106: 170–175.

    Article  Google Scholar 

  • Kiran MS (2021). A binary artificial bee colony algorithm and its performance assessment. Expert Systems with Applications, 175: 114817.

    Article  Google Scholar 

  • Li X, Guo F, Kuang H, et al. (2019). An extended cost potential field cellular automaton model for pedestrian evacuation considering the restriction of visual field. Physica A: Statistical Mechanics and Its Applications, 515: 47–56.

    Article  Google Scholar 

  • Li B, Li T, Jiang Q, et al. (2020a). A knowledge-based system for disaster emergency relief. International Journal of Pattern Recognition and Artificial Intelligence, 34: 2059038.

    Article  Google Scholar 

  • Li C, Bi C, Li Z (2020b). Crowd evacuation model based on improved PSO algorithm. Journal of System Simulation, 32: 1000–1008.

    Google Scholar 

  • Li L, Liu H, Han Y (2020c). An approach to congestion analysis in crowd dynamics models. Mathematical Models and Methods in Applied Sciences, 30: 867–890.

    Article  MathSciNet  Google Scholar 

  • Liu H, Xu B, Lu D, et al. (2018). A path planning approach for crowd evacuation in buildings based on improved artificial bee colony algorithm. Applied Soft Computing, 68: 360–376.

    Article  Google Scholar 

  • Ma J, Smith BL, Zhou X (2016). Personalized real-time traffic information provision: Agent-based optimization model and solution framework. Transportation Research Part C: Emerging Technologies, 64: 164–182.

    Article  Google Scholar 

  • Tehzeeb-Ul-hassan, Alquthami T, Butt SE, et al. (2020). Short-term optimal scheduling of hydro-thermal power plants using artificial bee colony algorithm. Energy Reports, 6: 984–992.

    Article  Google Scholar 

  • Tian X, Cui H, Zhu M (2020). Improved social force model for rescue action during evacuation. Modern Physics Letters B, 34: 2050273.

    Article  MathSciNet  Google Scholar 

  • Vermuyten H, Beliën J, de Boeck L, et al. (2016). A review of optimisation models for pedestrian evacuation and design problems. Safety Science, 87: 167–178.

    Article  Google Scholar 

  • Wang Y, Chu X, Zhou C, et al. (2018). Wave dynamics in an extended macroscopic traffic flow model with periodic boundaries. Modern Physics Letters B, 32: 1850168.

    Article  MathSciNet  Google Scholar 

  • Xu Y, Wang X (2021). An artificial bee colony algorithm for scheduling call centres with weekend-off fairness. Applied Soft Computing, 109: 107542.

    Article  Google Scholar 

  • Zhao R, Zhai Y, Qu L, et al. (2021). A continuous floor field cellular automata model with interaction area for crowd evacuation. Physica A: Statistical Mechanics and Its Applications, 575: 126049.

    Article  Google Scholar 

  • Zheng X, Zhong T, Liu M (2009). Modeling crowd evacuation of a building based on seven methodological approaches. Building and Environment, 44: 437–445.

    Article  Google Scholar 

  • Zheng Y, Li X, Jia B, et al. (2019). Simulation of pedestrians’ evacuation dynamics with underground flood spreading based on cellular automaton. Simulation Modelling Practice and Theory, 94: 149–161.

    Article  Google Scholar 

  • Zong X, Xiong S, Fang Z (2014). A conflict-congestion model for pedestrian-vehicle mixed evacuation based on discrete particle swarm optimization algorithm. Computers & Operations Research, 44: 1–12.

    Article  Google Scholar 

  • Zong X, Wang C, Du J, et al. (2019a). Tree hierarchical directed evacuation network model based on artificial fish swarm algorithm. International Journal of Modern Physics C, 30: 1950097.

    Article  Google Scholar 

  • Zong XL, Du JY, Liu W, et al. (2019b). Indoor emergency evacuation model based on artificial bee colony algorithm. In: Proceedings of the 10th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications, Metz, France.

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Acknowledgements

This work was supported by the National Natural Science Foundation of China (No. 61772180), the Key R & D Plan of Hubei Province (No. 2020BHB004 and No. 2020BAB012), and the Natural Science Foundation of Hubei Province (No. 2020CFB798). The authors would also like to thank the anonymous reviewers for their valuable comments and suggestions.

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Authors and Affiliations

  1. College of Computer Science and Technology, Hubei University of Technology, No. 28, Nanli Road, Hong-shan District, Wuchang, Wuhan, Hubei Province, China

    Xinlu Zong, Aiping Liu, Chunzhi Wang, Zhiwei Ye & Jiayuan Du

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  1. Xinlu Zong
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  2. Aiping Liu
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  3. Chunzhi Wang
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  4. Zhiwei Ye
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  5. Jiayuan Du
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Correspondence to Xinlu Zong.

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Zong, X., Liu, A., Wang, C. et al. Indoor evacuation model based on visual-guidance artificial bee colony algorithm. Build. Simul. 15, 645–658 (2022). https://doi.org/10.1007/s12273-021-0838-z

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  • DOI: https://doi.org/10.1007/s12273-021-0838-z

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