References
- Burstedde, C., A. Kirchner, K. Klauck, A. Schadschneider, and J. Zittartz. 2002. Cellular automaton approach to pedestrian dynamics - applications. In Pedestrian and Evacuation Dynamics, ed. M. Schreckenberg and S. D. Sharma, 87–98. Berlin: Springer.
- Burstedde, C., K. Klauck, A. Schadschneider, and J. Zittartz. 2001. Simulation of pedestrian dynamics using a two-dimensional cellular automaton. Physica A: Statistical Mechanics and Its Applications 295 (3–4):507–25. doi:https://doi.org/10.1016/S0378-4371(01)00141-8.
- Chen, X., M. Treiber, V. Kanagaraj, and H. Li. 2018. Social force models for pedestrian traffic - state of the art. Transport Reviews 38 (5):625–53. doi:https://doi.org/10.1080/01441647.2017.1396265.
- Chiang, C. H., P. J. Chiang, J. Fei, and J. S. Liu. 2007. “A comparative study of implementing Fast Marching Method and A* SEARCH for mobile robot path planning in grid environment: Effect of map resolution.” In IEEE Workshop on Advanced Robotics and Its Social Impacts (ARSO 2007), 1–6, Hsinchu, Taiwan.
- Corrêa, B. A., A. L. Bicho, and D. F. Adamatti. 2019. Multiagent systems and potential fields to smoke dispersion applied to evacuation simulations: The case of Kiss nightclub. Applied Artificial Intelligence 33 (11):1008–21. doi:https://doi.org/10.1080/08839514.2019.1661577.
- Dias, C., and R. Lovreglio. 2018. Calibrating cellular automaton models for pedestrians walking through corners. Physics Letters. A 382 (19):1255–61. doi:https://doi.org/10.1016/j.physleta.2018.03.022.
- Duives, D. C., W. Daamen, and S. P. Hoogendoorn. 2013. State-of-the-art crowd motion simulation models. Transportation Research Part C 37:193–209. doi:https://doi.org/10.1016/j.trc.2013.02.005.
- Duives, D. C., W. Daamen, and S. P. Hoogendoorn. 2016. Continuum modelling of pedestrian flows - Part 2: Sensitivity analysis featuring crowd movement phenomena. Physica A 447:36–48. doi:https://doi.org/10.1016/j.physa.2015.11.025.
- Fukui, M., and Y. Ishibashi. 1996. Traffic flow in 1D cellular automaton model including cars moving with high speed. Journal of the Physical Society of Japan 65 (6):1868–70. doi:https://doi.org/10.1143/JPSJ.65.1868.
- Fukui, M., and Y. Ishibashi. 1999a. “Jamming transition in cellular automaton models for pedestrians on passageway.” Journal of the Physical Society of Japan 68 (11):3738–39. doi:https://doi.org/10.1143/JPSJ.68.3738.
- Fukui, M., and Y. Ishibashi. 1999b. “Self-organized phase transitions in cellular automaton models for pedestrians.” Journal of the Physical Society of Japan 68 (8):2861–63. doi:https://doi.org/10.1143/JPSJ.68.2861.
- Galán, S. F. 2019. Fast Evacuation Method: Using an effective dynamic floor field based on efficient pedestrian assignment. Safety Science 120:79–88. doi:https://doi.org/10.1016/j.ssci.2019.06.042.
- Galán, S. F. 2020. Message Passing Cellular Automata. Marcombo: Marcombo.
- Hassan, Y., and E. Tazaki. 2010. Adaptive behavior in cellular automata using rough set theory. Applied Artificial Intelligence 17 (2):155–75. doi:https://doi.org/10.1080/713827104.
- Helbing, D. 2001. Traffic and related self-driven many-particle systems. Reviews of Modern Physics 73 (4):1067–141.
- Helbing, D., I. Farkas, and T. Vicsek. 2000. Simulating dynamical features of escape panic. Nature 407 (6803):487–90. doi:https://doi.org/10.1038/35035023.
- Helbing, D., L. Buzna, A. Johansson, and T. Werner. 2005. Self-organized pedestrian crowd dynamics: Experiments, simulations, and design solutions. Transportation Science 39 (1):1–24. doi:https://doi.org/10.1287/trsc.1040.0108.
- Helbing, D., M. Isobe, T. Nagatani, and K. Takimoto. 2003. Lattice gas simulation of experimentally studied evacuation dynamics. Physical Review E 67 (6):067101. doi:https://doi.org/10.1103/PhysRevE.67.067101.
- Helbing, D., and P. Molnár. 1995. Social force model for pedestrian dynamics. Physical Review E 51 (5):4282–86. doi:https://doi.org/10.1103/PhysRevE.51.4282.
- Ioannidis, K., G. C. Sirakoulis, and I. Andreadis. 2011. A path planning method based on cellular automata for cooperative robots. Applied Artificial Intelligence 25 (8):721–45. doi:https://doi.org/10.1080/08839514.2011.606767.
- Isobe, M., D. Helbing, and T. Nagatani. 2004. Experiment, theory, and simulation of the evacuation of a room without visibility. Physical Review E 69 (6):066132. doi:https://doi.org/10.1103/PhysRevE.69.066132.
- Kirchner, A., and A. Schadschneider. 2002. Simulation of evacuation processes using a bionics-inspired cellular automaton model for pedestrian dynamics. Physica A: Statistical Mechanics and Its Applications 312 (1–2):260–76. doi:https://doi.org/10.1016/S0378-4371(02)00857-9.
- Kirchner, A., H. Klüpfel, K. Nishinari, A. Schadschneider, and M. Schreckenberg. 2003. Simulation of competitive egress behavior: Comparison with aircraft evacuation data. Physica A: Statistical Mechanics and Its Applications 324 (3–4):689–97. doi:https://doi.org/10.1016/S0378-4371(03)00076-1.
- Kretz, T. 2009a. “Pedestrian traffic: On the quickest path.” Journal of Statistical Mechanics: Theory and Experiment 3:P03012.
- Kretz, T. 2009b. “The use of dynamic distance potential fields for pedestrian flow around corners.” In Proceedings of the 1st International Conference on Evacuation Modeling and Management (ICEM 2009), The Hague.
- Kretz, T., A. Große, S. Hengst, L. Kautzsch, A. Pohlmann, and P. Vortisch. 2011. Quickest paths in simulations of pedestrians. Advances in Complex Systems 14 (5):733–59. doi:https://doi.org/10.1142/S0219525911003281.
- Kretz, T., C. Bönisch, and P. Vortisch. 2010. “Comparison of various methods for the calculation of the distance potential field.” In Proceedings of the 9th International Conference on Pedestrian and Evacuation Dynamics (PED 2008), 335–46, Lund, Sweden.
- Lovreglio, R., C. Dias, X. Song, and L. Ballerini. 2017. “Towards microscopic calibration of pedestrian simulation models using open trajectory datasets: The case study of the Edinburgh Informatics Forum.” In Proceedings of the Conference on Traffic and Granular Flow (TGF 2017),Washington DC.
- Lovreglio, R., C. Dias, X. Song, and L. Ballerini. 2018. Investigating pedestrian navigation in indoor open space environments using big data. Applied Mathematical Modelling 62:499–509. doi:https://doi.org/10.1016/j.apm.2018.06.014.
- Martínez-Gil, F., M. Lozano, I. García-Fernández, and F. Fernández. 2017. Modeling, evaluation and scale on artificial pedestrians: A literature review. ACM Computing Surveys 50 (5): Article No. 72. doi:https://doi.org/10.1145/3117808.
- Schadschneider, A. 2002. Cellular automaton approach to pedestrian dynamics - theory. In Pedestrian and Evacuation Dynamics, ed. M. Schreckenberg and S. D. Sharma, 75–86. Berlin: Springer.
- Schadschneider, A., D. Chowdhury, and K. Nishinari. 2011. Pedestrian dynamics. In Stochastic Transport in Complex Systems: From Molecules to Vehicles. Chap, 407–60. Amsterdam: Elsevier.
- Sethian, J. A. 1999. Level Set Methods and Fast Marching Methods. Cambridge, UK: Cambridge University Press.
- Shi, X., Z. Ye, N. Shiwakoti, and O. Grembek. 2018. “A state-of-the-art review on empirical data collection for external governed pedestrians complex movement.”Journal of Advanced Transportation 42. Article ID 1063043.
- Shiwakoti, N., M. Sarvi, and G. Rose. 2008. “Modelling pedestrian behaviour under emergency conditions - State-of-the-art and future directions.” In Proceedings of the 31st Australasian Transport Research Forum (ATRF 2008), 457–73, Gold Coast, Australia.
- Shiwakoti, N., X. Shi, and Z. Ye. 2019. A review on the performance of an obstacle near an exit on pedestrian crowd evacuation. Safety Science 113:54–67. doi:https://doi.org/10.1016/j.ssci.2018.11.016.
- Tajima, Y., K. Takimoto, and T. Nagatani. 2001. Scaling of pedestrian channel flow with a bottleneck. Physica A: Statistical Mechanics and Its Applications 294 (1–2):257–68. doi:https://doi.org/10.1016/S0378-4371(01)00109-1.
- Tajima, Y., and T. Nagatani. 2001. Scaling behavior of crowd flow outside a hall. Physica A: Statistical Mechanics and Its Applications 292 (1–4):545–54. doi:https://doi.org/10.1016/S0378-4371(00)00630-0.
- Toffoli, T., and N. Margolus. 1987. Cellular Automata Machines: A New Environment for Modeling. Cambridge, MA (USA): MIT Press.
- Varas, A., M. D. Cornejo, D. Mainemer, B. Toledo, J. Rogan, V. Muñoz, and J. A. Valdivia. 2007. Cellular automaton model for evacuation process with obstacles. Physica A: Statistical Mechanics and Its Applications 382 (2):631–42. doi:https://doi.org/10.1016/j.physa.2007.04.006.
- von Neumann, J. 1966. Theory of Self-Reproducing Automata. Champaign, IL (USA): University of Illinois Press. Edited and completed by A. W. Burks.
- Wijermans, N., C. Conrado, M. Van Steen, C. Martella, and J. Li. 2016. A landscape of crowd-management support: An integrative approach. Safety Science 86:142–64. doi:https://doi.org/10.1016/j.ssci.2016.02.027.
- Wilensky, U. 1999. NetLogo. Evanston, IL: Northwestern University. http://ccl.northwestern.edu/netlogo/.CenterforConnectedLearningandComputerScience.
- Wolfram, S. 2002. A New Kind of Science. Champaign, IL (USA): Wolfram Media Inc.