A Memory-Based Evacuation Navigation Model in Complex High-Rise Buildings
Keywords:pedestrian and evacuation dynamics, modeling, high-rise building, cognition, memory
AbstractIn contemporary society, safety issues are the main focus in the field of pedestrian and evacuation dynamics. As for complex high-rise buildings, the navigation strategies of evacuees still need to be further studied. Previous types of research has contributed to the construction of evacuation navigation model in complex high-rise buildings, where pedestrians are regarded as having an omniscient view in most of these models. In reality, evacuees’ perception is always limited, especially when the scenario is complex. In this contribution, pedestrians’ perception procedure is considered by computing the visible space so that the occlusion of the visual field can be estimated. In addition, human memory progress is modeled. Not all parts of environmental information would be remembered. Driven by evacuees’ memory data, a proposed dynamical shortest path algorithm will be periodically implemented or suddenly triggered by incidents during the simulation. For the pedestrians who have no enough knowledge about the evacuation scenario, a communication system is utilized so that information can be obtained from well-knowledged pedestrian, and an autonomous way-finding system will be executed when useful information cannot be acquired through near evacuees. For the microscopic perspective, human following and avoidance behavior is modeled. Simulations in two different types of scenarios are conducted. The knowledge level of simulated agents is gradually evolved by in-room free exploration. Results in different conditions show that the proposed memory-based model can reproduce pedestrians’ observation, turn-back, communication, and searching behavior. The intense conflict caused by the bidirectional crowd is observed and analyzed. In addition, the effects of knowledge level are investigated. The presented model in this contribution can be promising and useful in safety engineering.
Helbing, D., Farkas, I., Vicsek, T.: Simulating dynamical features of escape panic. Nature 407(6803), 487-490 (2000). doi:10.1038/35035023
Helbing, D., Molnar, P.: Social force model for pedestrian dynamics. Physical review E 51(5), 4282 (1995). doi:10.1103/PhysRevE.51.4282
Yu, W.J., Chen, R., Dong, L.Y., Dai, S.Q.: Centrifugal force model for pedestrian dynamics. Physical Review E 72(2 Pt 2), 026112 (2005). doi:10.1103/PhysRevE.72.026112
Chraibi, M., Seyfried, A., Schadschneider, A.: Generalized centrifugal-force model for pedestrian dynamics. Physical Review E 82(4), 046111 (2010). doi:10.1103/PhysRevE.82.046111
Burstedde, C., Klauck, K., Schadschneider, A., Zittartz, J.: Simulation of pedestrian dynamics using a two-dimensional cellular automaton. Physica A: Statal Mechanics and its Applications 295(3–4), 507-525 (2001). doi:10.1016/S0378-4371(01)00141-8
Song, W., Xuan, X., Wang, B.H., Ni, S.: Simulation of evacuation processes using a multi-grid model for pedestrian dynamics. Physica A Statistical Mechanics & Its Applications 363(2), 492-500 (2006). doi:10.1016/j.physa.2005.08.036
Zanlungo, F., Ikeda, T., Kanda, T.: Social force model with explicit collision prediction. EPL (Europhysics Letters) 93(6), 68005 (2011). doi:10.1209/0295-5075/93/68005
Hasegawa, Y., Dias, C., Iryo-Asano, M., Nishiuchi, H.: Modeling pedestrians’ subjective danger perception toward personal mobility vehicles. Transportation research part F: traffic psychology and behaviour 56, 256-267 (2018). doi:10.1016/j.trf.2018.04.016
Xue, S., Jia, B., Jiang, R., Shan, J.: Pedestrian evacuation in view and hearing limited condition: The impact of communication and memory. Physics Letters A 380(38), 3029-3035 (2016). doi:10.1016/j.physleta.2016.07.030
Xia, Y., Wong, S., Shu, C.W.: Dynamic continuum pedestrian flow model with memory effect. Physical Review E 79(6), 066113 (2009). doi:10.1103/PhysRevE.79.066113
Kneidl, A., Borrmann, A.: How do pedestrians find their way? results of an experimental study with students compared to simulation results. Emergency Evacuation of people from Buildings (2011)
Kneidl, A., Borrmann, A., Hartmann, D.: Generation and use of sparse navigation graphs for microscopic pedestrian simulation models. Advanced Engineering Informatics 26(4), 669-680 (2012). doi:10.1016/j.aei.2012.03.006
Kielar, P.M., Biedermann, D.H., Kneidl, A., Borrmann, A.: A unified pedestrian routing model for graph-based wayfinding built on cognitive principles. Transportmetrica A: transport science 14(5-6), 406-432 (2018). doi:10.1080/23249935.2017.1309472
Kielar, P.M., Borrmann, A.: Spice: a cognitive agent framework for computational crowd simulations in complex environments. Autonomous Agents and Multi-Agent Systems 32(3), 387-416 (2018). doi:10.1007/s10458-018-9383-2
How to Cite
Copyright (c) 2021 Long Xia, Weiguo Song
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors contributing to Collective Dynamics agree to publish their articles under the Creative Commons Attribution 4.0 license.
This license allows:
Share — copy and redistribute the material in any medium or format
Adapt — remix, transform, and build upon the material
for any purpose, even commercially.
The licensor cannot revoke these freedoms as long as you follow the license terms.
Authors retain copyright of their work. They are permitted and encouraged to post items submitted to Collective Dynamics on personal or institutional websites and repositories, prior to and after publication (while providing the bibliographic details of that publication).