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Transportation Letters
The International Journal of Transportation Research
Volume 16, 2024 - Issue 4
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Research Article

Crowd model calibration at strategic, tactical, and operational levels: Full-spectrum sensitivity analyses show bottleneck parameters are most critical, followed by exit-choice-changing parameters

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Pages 354-381 | Received 11 May 2022, Accepted 22 Mar 2023, Published online: 28 Mar 2023

References

  • Abdelghany, A., K. Abdelghany, H. Mahmassani, and W. Alhalabi. 2014. “Modeling Framework for Optimal Evacuation of Large-Scale Crowded Pedestrian Facilities.” European Journal of Operational Research 237 (3): 1105–1118. doi:10.1016/j.ejor.2014.02.054.
  • Antonini, G., M. Bierlaire, and M. Weber. 2006. “Discrete Choice Models of Pedestrian Walking Behavior.” Transportation Research Part B: Methodological 40 (8): 40. doi:10.1016/j.trb.2005.09.006.
  • Asano, M., T. Iryo, and M. Kuwahara. 2010. “Microscopic Pedestrian Simulation Model Combined with a Tactical Model for Route Choice Behaviour.” Transportation Research Part C: Emerging Technologies 18 (6): 842–855. doi:10.1016/j.trc.2010.01.005.
  • Bandini, S., F. Rubagotti, G. Vizzari, and K. Shimura. 2011. “A Cellular Automata Based Model for Pedestrian and Group Dynamics: Motivations and First Experiments.” In Parallel Computing Technologies, edited by V. Malyshkin, 125–139. Berlin Heidelberg: Springer.
  • Berrou, J. L., J. Beecham, P. Quaglia, M. A. Kagarlis, and A. Gerodimos. 2007. “Calibration and validation of the Legion simulation model using empirical data.” In Pedestrian and evacuation dynamics 2005, 167–181. Berlin Heidelberg: Springer.
  • Bode, N. W. F., and E. A. Codling. 2013. “Human Exit Route Choice in Virtual Crowd Evacuations.” Animal Behaviour 86 (2): 347–358. doi:10.1016/j.anbehav.2013.05.025.
  • Boltes, M., and A. Seyfried. 2013. “Collecting Pedestrian Trajectories.” Neurocomputing 100: 127–133. doi:10.1016/j.neucom.2012.01.036.
  • 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): 507–525. doi:10.1016/S0378-4371(01)00141-8.
  • Cepolina, E. M. 2009. “Phased Evacuation: An Optimisation Model Which Takes into Account the Capacity Drop Phenomenon in Pedestrian Flows.” Fire Safety Journal 44 (4): 532–544. doi:10.1016/j.firesaf.2008.11.002.
  • Cepolina, E. M., and A. Farina (2010). A Pedestrian Movement Model That Takes into Account the Capacity Drop Phenomenon in the Motion of Crowd. In Cellular Automata: 9th International Conference on Cellular Automata for Research and Industry, ACRI 2010, Ascoli Piceno, Italy September 21-24. Cellular Automata: 9th International Conference on Cellular Automata for Research and Industry, ACRI 2010 (pp. 446–454). Springer Ascoli Piceno, Italy.
  • Chraibi, M., M. Freialdenhoven, A. Schadschneider, and A. Seyfried. 2013. “Modeling the Desired Direction in a Force-Based Model for Pedestrian Dynamics.” In Traffic and Granular Flow ’11, edited by V. V. Kozlov, A. P. Buslaev, A. S. Bugaev, M. V. Yashina, A. Schadschneider, and M. Schreckenberg, 263–275. Berlin Heidelberg: Springer.
  • Chraibi, M., U. Kemloh, A. Schadschneider, and A. Seyfried. 2011. “Force-Based Models of Pedestrian Dynamics.” Networks & Heterogeneous Media 6 (3): 425. doi:10.3934/nhm.2011.6.425.
  • Chraibi, M., A. Seyfried, and A. Schadschneider. 2010. “Generalized Centrifugal Force Model for Pedestrian Dynamics.” Physical Review E 82 (4). doi:10.1103/PhysRevE.82.046111.
  • Corbetta, A., A. Muntean, and K. Vafayi. 2015. “Parameter Estimation of Social Forces in Pedestrian Dynamics Models via a Probabilistic Method.” Mathematical Biosciences and engineering 12 (2): 337–356. doi:10.3934/mbe.2015.12.337.
  • Crociani, L., Y. Zeng, G. Vizzari, and S. Bandini. 2018. “Shape Matters: Modelling, Calibrating and Validating Pedestrian Movement Considering Groups.” Simulation Modelling Practice and Theory 87: 73–91. doi:10.1016/j.simpat.2018.06.001.
  • Cui, X., and H. Shi. 2011. “A*-Based Pathfinding in Modern Computer Games.” International Journal of Computer Science and Network Security 11: 125–130.
  • Daamen, W., and S. Hoogendoorn. 2012a. “Calibration of Pedestrian Simulation Model for Emergency Doors by Pedestrian Type.” Transportation Research Record: Journal of the Transportation Research Board 2316 (1): 69–75. doi:10.3141/2316-08.
  • Daamen, W., and S. Hoogendoorn. 2012b. “Emergency Door Capacity: Influence of Door Width, Population Composition and Stress Level.” Fire Technology 48 (1): 55–71. doi:10.1007/s10694-010-0202-9.
  • Dias, C., M. Iryo-Asano, H. Nishiuchi, and T. Todoroki. 2018. “Calibrating a Social Force Based Model for Simulating Personal Mobility Vehicles and Pedestrian Mixed Traffic.” Simulation Modelling Practice and Theory 87: 395–411. doi:10.1016/j.simpat.2018.08.002.
  • Dias, C., and R. Lovreglio. 2018. “Calibrating Cellular Automaton Models for Pedestrians Walking Through Corners.” Physics Letters A 382 (19): 1255–1261. doi:10.1016/j.physleta.2018.03.022.
  • Dirk, H. 2010. “Adaptive Pedestrian Dynamics Based on Geodesics.” New Journal of Physics 12 (4): 043032. doi:10.1088/1367-2630/12/4/043032.
  • Ezaki, T., D. Yanagisawa, and K. Nishinari. 2012. “Pedestrian Flow Through Multiple Bottlenecks.” Physical Review E - Statistical, Nonlinear, and Soft Matter Physics 86 (2). doi:10.1103/PhysRevE.86.026118.
  • Gao, S., E. Frejinger, and M. Ben-Akiva. 2010. “Adaptive Route Choices in Risky Traffic Networks: A Prospect Theory Approach.” Transportation Research Part C: Emerging Technologies 18 (5): 727–740. doi:10.1016/j.trc.2009.08.001.
  • Geoerg, P., J. Schumann, M. Boltes, and M. Kinateder. 2022. “How People with Disabilities Influence Crowd Dynamics of Pedestrian Movement Through Bottlenecks.” Scientific Reports 12 (1): 1–16. doi:10.1038/s41598-022-18142-7.
  • Geoerg, P., J. Schumann, S. Holl, M. Boltes, and A. Hofmann. 2020. “The Influence of Individual Impairments in Crowd Dynamics.” Fire and Materials 45 (4): 529–542. n/a. doi:10.1002/fam.2789.
  • Geoerg, P., J. Schumann, S. Holl, and A. Hofmann. 2019. “The Influence of Wheelchair Users on Movement in a Bottleneck and a Corridor.” Journal of Advanced Transportation 2019: 1–17. doi:10.1155/2019/9717208.
  • Gödel, M., R. Fischer, and G. Köster. 2020. “Sensitivity Analysis for Microscopic Crowd Simulation.” Algorithms 13 (7): 162. doi:10.3390/a13070162.
  • Greene, W. 2007. NLOGIT: Version 4.0, User Manual. Econometric Software. New York. Inc.
  • Guan, J., K. Wang, and F. Chen. 2016. “A Cellular Automaton Model for Evacuation Flow Using Game Theory.” Physica A: Statistical Mechanics and Its Applications 461: 655–661. doi:10.1016/j.physa.2016.05.062.
  • Gwynne, S., E. Galea, P. Lawrence, M. Owen, and L. Filippidis. 2000. “Adaptive Decision-Making in Building EXODUS in Response to Exit Congestion.” Fire Safety Science 6: 1041–1052. doi:10.3801/IAFSS.FSS.6-1041.
  • Gwynne, S., E. R. Galea, M. Owen, P. J. Lawrence, and L. Filippidis. 2005. “A Systematic Comparison of buildingExodus Predictions with Experimental Data from the Stapelfeldt Trials and the Milburn House Evacuation.” Applied Mathematical Modelling 29 (9): 818–851. doi:10.1016/j.apm.2004.11.005.
  • Gwynne, S. M. V., and A. L. E. Hunt. 2018. “Why Model Evacuee Decision-Making?” Safety Science 110: 457–466. doi:10.1016/j.ssci.2018.02.016.
  • Gwynne, S. M. V., E. D. Kuligowski, J. Kratchman, and J. A. Milke. 2009. “Questioning the Linear Relationship Between Doorway Width and Achievable Flow Rate.” Fire Safety Journal 44 (1): 80–87. doi:10.1016/j.firesaf.2008.03.010.
  • Haghani, M. 2020a. “Empirical Methods in Pedestrian, Crowd and Evacuation Dynamics: Part I. Experimental Methods and Emerging Topics.” Safety Science 129: 104743. doi:10.1016/j.ssci.2020.104743.
  • Haghani, M. 2020b. “Empirical Methods in Pedestrian, Crowd and Evacuation Dynamics: Part II. Field Methods and Controversial Topics.” Safety Science 129: 104760. doi:10.1016/j.ssci.2020.104760.
  • Haghani, M. 2020c. “Optimising Crowd Evacuations: Mathematical, Architectural and Behavioural Approaches.” Safety Science 128: 104745. doi:10.1016/j.ssci.2020.104745.
  • Haghani, M. 2021. “The Notion of Validity in Experimental Crowd Dynamics.” SSRN Electronic Journal arXiv preprint arXiv:2112.10673. doi:10.2139/ssrn.3974364.
  • Haghani, M., and M. Sarvi. 2016a. “Human Exit Choice in Crowded Built Environments: Investigating Underlying Behavioural Differences Between Normal Egress and Emergency Evacuations.” Fire Safety Journal 85: 1–9. doi:10.1016/j.firesaf.2016.07.003.
  • Haghani, M., and M. Sarvi. 2016b. “Pedestrian Crowd Tactical-Level Decision Making During Emergency Evacuations.” Journal of Advanced Transportation 50 (8): 1870–1895. n/a-n/a. doi:10.1002/atr.1434.
  • Haghani, M., and M. Sarvi. 2017. “Stated and Revealed Exit Choices of Pedestrian Crowd Evacuees.” Transportation Research Part B: Methodological 95: 238–259. doi:10.1016/j.trb.2016.10.019.
  • Haghani, M., and M. Sarvi. 2018a. “Crowd Behaviour and Motion: Empirical Methods.” Transportation Research Part B: Methodological 107: 253–294. doi:10.1016/j.trb.2017.06.017.
  • Haghani, M., and M. Sarvi. 2018b. “Hypothetical Bias and Decision-Rule Effect in Modelling Discrete Directional Choices.” Transportation Research Part A: Policy and Practice 116: 361–388. doi:10.1016/j.tra.2018.06.012.
  • Haghani, M., and M. Sarvi. 2019a. “Herding’ in Direction Choice-Making During Collective Escape of Crowds: How Likely is It and What Moderates It?” Safety Science 115: 362–375. doi:10.1016/j.ssci.2019.02.034.
  • Haghani, M., and M. Sarvi. 2019b. “Laboratory Experimentation and Simulation of Discrete Direction Choices: Investigating Hypothetical Bias, Decision-Rule Effect and External Validity Based on Aggregate Prediction Measures.” Transportation Research Part A: Policy and Practice 130: 134–157. doi:10.1016/j.tra.2019.09.040.
  • Haghani, M., and M. Sarvi. 2019c. “Simulating Dynamics of Adaptive Exit-Choice Changing in Crowd Evacuations: Model Implementation and Behavioural Interpretations.” Transportation Research Part C: Emerging Technologies 103: 56–82. doi:10.1016/j.trc.2019.04.009.
  • Haghani, M., and M. Sarvi. 2019d. “Simulating Pedestrian Flow Through Narrow Exits.” Physics Letters A 383 (2–3): 110–120. doi:10.1016/j.physleta.2018.10.029.
  • Haghani, M., M. Sarvi, and A. Rajabifard. 2018. “Simulating Indoor Evacuation of Pedestrians: The Sensitivity of Predictions to Directional-Choice Calibration Parameters.” Transportation Research Record 2672 (1): 171–182. doi:10.1177/0361198118796351.
  • Haghani, M., M. Sarvi, and Z. Shahhoseini. 2015. “Accommodating Taste Heterogeneity and Desired Substitution Pattern in Exit Choices of Pedestrian Crowd Evacuees Using a Mixed Nested Logit Model.” Journal of Choice Modelling 16: 58–68. doi:10.1016/j.jocm.2015.09.006.
  • Haghani, M., M. Sarvi, and Z. Shahhoseini. 2019. “When ‘Push’ Does Not Come to ‘Shove’: Revisiting ‘Faster is slower’ in Collective Egress of Human Crowds.” Transportation Research Part A: Policy and Practice 122: 51–69. doi:10.1016/j.tra.2019.02.007.
  • Haghani, M., M. Sarvi, and Z. Shahhoseini. 2020. “Evacuation Behaviour of Crowds Under High and Low Levels of Urgency: Experiments of Reaction Time, Exit Choice and Exit-Choice Adaptation.” Safety Science 126: 104679. doi:10.1016/j.ssci.2020.104679.
  • Haghani, M., M. Sarvi, Z. Shahhoseini, M. Boltes, and J. Jing. 2016. “How Simple Hypothetical-Choice Experiments Can Be Utilized to Learn Humans’ Navigational Escape Decisions in Emergencies.” Plos One 11 (11): e0166908. doi:10.1371/journal.pone.0166908.
  • Helbing, D., I. Farkas, and T. Vicsek. 2000. “Simulating Dynamical Features of Escape Panic.” Nature 407 (6803): 487–490. doi:10.1038/35035023.
  • Hollander, Y., and R. Liu. 2008. “The Principles of Calibrating Traffic Microsimulation Models.” Transportation 35 (3): 347–362. doi:10.1007/s11116-007-9156-2.
  • Hoogendoorn, S. P., and W. Daamen. 2005. “Pedestrian Behavior at Bottlenecks.” Transportation Science 39 (2): 147–159. doi:10.1287/trsc.1040.0102.
  • Hoogendoorn, S. P., F. L. M. van Wageningen-Kessels, W. Daamen, and D. C. Duives. 2014. “Continuum Modelling of Pedestrian Flows: From Microscopic Principles to Self-Organised Macroscopic Phenomena.” Physica A: Statistical Mechanics and Its Applications 416: 684–694. doi:10.1016/j.physa.2014.07.050.
  • Ibrahim, A. M., I. Venkat, and P. De Wilde. 2019. “The Impact of Potential Crowd Behaviours on Emergency Evacuation: An Evolutionary Game Theoretic Approach.” Journal of Artificial Societies and Social Simulation 22 (1). doi:10.18564/jasss.3837.
  • Kinateder, M., B. Comunale, and W. H. Warren. 2018. “Exit Choice in an Emergency Evacuation Scenario is Influenced by Exit Familiarity and Neighbor Behavior.” Safety Science 106: 170–175. doi:10.1016/j.ssci.2018.03.015.
  • Kinateder, M., M. Müller, M. Jost, A. Mühlberger, and P. Pauli. 2014. “Social Influence in a Virtual Tunnel Fire – Influence of Conflicting Information on Evacuation Behavior.” Applied Ergonomics 45 (6): 1649–1659. doi:10.1016/j.apergo.2014.05.014.
  • Kinateder, M., E. Ronchi, D. Gromer, M. Müller, M. Jost, M. Nehfischer, A. Mühlberger, and P. Pauli. 2014. “Social Influence on Route Choice in a Virtual Reality Tunnel Fire.” Transportation Research Part F, Traffic Psychology and Behaviour 26: 116–125. Part A. doi:10.1016/j.trf.2014.06.003.
  • Ko, M., T. Kim, and K. Sohn. 2013. “Calibrating a Social-Force-Based Pedestrian Walking Model Based on Maximum Likelihood Estimation.” Transportation 40 (1): 91–107. doi:10.1007/s11116-012-9411-z.
  • Köster, G., and M. Gödel. 2015. “Implementation Issues of Force Based Pedestrian Motion Models.” In Traffic and Granular Flow ’13, edited by M. Chraibi, M. Boltes, A. Schadschneider, and A. Seyfried, 63–71, Springer International Publishing.
  • Kretz, T., K. Lehmann, and I. Hofsäß. 2014. “User Equilibrium Route Assignment for Microscopic Pedestrian Simulation.” Advances in Complex Systems 17 (02): 17. doi:10.1142/S0219525914500106.
  • Kretz, T., J. Lohmiller, and P. Sukennik. 2018. “Some Indications on How to Calibrate the Social Force Model of Pedestrian Dynamics.” Transportation Research Record 2672 (20): 228–238. doi:10.1177/0361198118786641.
  • Liao, W., A. Seyfried, J. Zhang, M. Boltes, X. Zheng, and Y. Zhao. 2014. “Experimental Study on Pedestrian Flow Through Wide Bottleneck.” Transportation Research Procedia 2: 26–33. doi:10.1016/j.trpro.2014.09.005.
  • Liao, W., A. U. K. Wagoum, and N. W. Bode. 2017. “Route Choice in Pedestrians: Determinants for Initial Choices and Revising Decisions.” Journal of the Royal Society Interface 14 (127): 20160684. doi:10.1098/rsif.2016.0684.
  • Li, M., Y. Zhao, L. He, W. Chen, and X. Xu. 2015. “The Parameter Calibration and Optimization of Social Force Model for the Real-Life 2013 Ya’an Earthquake Evacuation in China.” Safety Science 79: 243–253. doi:10.1016/j.ssci.2015.06.018.
  • Lopez-Carmona, M. A. 2022. “System Identification for the Design of Behavioral Controllers in Crowd Evacuations.” Transportation Research Part C: Emerging Technologies 144: 103913. doi:10.1016/j.trc.2022.103913.
  • Lopez-Carmona, M. A., and A. P. Garcia. 2021. “CellEvac: An Adaptive Guidance System for Crowd Evacuation Through Behavioral Optimization.” Safety Science 139: 105215. doi:10.1016/j.ssci.2021.105215.
  • Lovreglio, R., D. Borri, L. Dell’olio, and A. Ibeas. 2014. “A Discrete Choice Model Based on Random Utilities for Exit Choice in Emergency Evacuations.” Safety Science 62: 418–426. doi:10.1016/j.ssci.2013.10.004.
  • Lovreglio, R., E. Ronchi, and D. Borri. 2014. “The Validation of Evacuation Simulation Models Through the Analysis of Behavioural Uncertainty.” Reliability Engineering & System Safety 131: 166–174. doi:10.1016/j.ress.2014.07.007.
  • Lovreglio, R., E. Ronchi, and D. Nilsson. 2015. “Calibrating Floor Field Cellular Automaton Models for Pedestrian Dynamics by Using Likelihood Function Optimization.” Physica A: Statistical Mechanics and Its Applications 438: 308–320. doi:10.1016/j.physa.2015.06.040.
  • Mohd Ibrahim, A., I. Venkat, and P. D. Wilde. 2017. “Uncertainty in a Spatial Evacuation Model.” Physica A: Statistical Mechanics and Its Applications 479: 485–497. doi:10.1016/j.physa.2017.03.024.
  • Moussaïd, M., M. Kapadia, T. Thrash, R. W. Sumner, M. Gross, D. Helbing, and C. Hölscher. 2016. “Crowd Behaviour During High-Stress Evacuations in an Immersive Virtual Environment.” Journal of the Royal Society Interface 13 (122): 20160414. doi:10.1098/rsif.2016.0414.
  • Muir, H. C., D. M. Bottomley, and C. Marrison. 1996. “Effects of Motivation and Cabin Configuration on Emergency Aircraft Evacuation Behavior and Rates of Egress.” The International Journal of Aviation Psychology 6 (1): 57–77. doi:10.1207/s15327108ijap0601_4.
  • Nicolas, A., S. Bouzat, and M. N. Kuperman. 2017. “Pedestrian Flows Through a Narrow Doorway: Effect of Individual Behaviours on the Global Flow and Microscopic Dynamics.” Transportation Research Part B: Methodological 99: 30–43. doi:10.1016/j.trb.2017.01.008.
  • Park, B., and J. Schneeberger. 2003. “Microscopic Simulation Model Calibration and Validation: Case Study of VISSIM Simulation Model for a Coordinated Actuated Signal System.” Transportation Research Record: Journal of the Transportation Research Board 1856 (1): 185–192. doi:10.3141/1856-20.
  • Rahn, S., M. Gödel, R. Fischer, and G. Köster. 2021. “Dynamics of a Simulated Demonstration March: An Efficient Sensitivity Analysis.” Sustainability 13 (6): 3455. doi:10.3390/su13063455.
  • Robin, T., G. Antonini, M. Bierlaire, and J. Cruz. 2009. “Specification, Estimation and Validation of a Pedestrian Walking Behavior Model.” Transportation Research Part B: Methodological 43 (1): 36–56. doi:10.1016/j.trb.2008.06.010.
  • Seyfried, A., M. Boltes, J. Kähler, W. Klingsch, A. Portz, T. Rupprecht, A. Schadschneider, B. Steffen, and A. Winkens. 2010. “Enhanced Empirical Data for the Fundamental Diagram and the Flow Through Bottlenecks.” In Pedestrian and Evacuation Dynamics 2008, edited by W. W. F. Klingsch, C. Rogsch, A. Schadschneider, and M. Schreckenberg, 145–156. Berlin Heidelberg: Springer.
  • Seyfried, A., O. Passon, B. Steffen, M. Boltes, T. Rupprecht, and W. Klingsch. 2009. “New Insights into Pedestrian Flow Through Bottlenecks.” Transportation Science 43 (3): 395–406. doi:10.1287/trsc.1090.0263.
  • Shipman, A., and A. Majumdar. 2018. “Fear in Humans: A Glimpse into the Crowd-Modeling Perspective.” Transportation Research Record 2672 (1): 0361198118787343. doi:10.1177/0361198118787343.
  • Teknomo, K. 2006. “Application of Microscopic Pedestrian Simulation Model.” Transportation Research Part F, Traffic Psychology and Behaviour 9 (1): 15–27. doi:10.1016/j.trf.2005.08.006.
  • Tian, W., W. Song, J. Ma, Z. Fang, A. Seyfried, and J. Liddle. 2012. “Experimental Study of Pedestrian Behaviors in a Corridor Based on Digital Image Processing.” Fire Safety Journal 47: 8–15. doi:10.1016/j.firesaf.2011.09.005.
  • Tobias, K., G. Anna, and S. Michael. 2006. “Experimental Study of Pedestrian Flow Through a Bottleneck.” Journal of Statistical Mechanics: Theory and Experiment 2006 (10): 10014. doi:10.1088/1742-5468/2006/10/P10014.
  • Wang, K., Z. Fu, Y. Li, and S. Qian. 2020. “Influence of Human-Obstacle Interaction on Evacuation from Classrooms.” Automation in Construction 116: 103234. doi:10.1016/j.autcon.2020.103234.
  • Wang, K., X. Shi, A. P. Xuan Goh, and S. Qian. 2019. “A Machine Learning Based Study on Pedestrian Movement Dynamics Under Emergency Evacuation.” Fire Safety Journal 106: 163–176. doi:10.1016/j.firesaf.2019.04.008.
  • Werberich, B. R., C. O. Pretto, and H. B. B. Cybis. 2015a. “Calibration of a Pedestrian Route Choice Model with a Basis in Friction Forces.” Transportation Research Record 2519 (1): 137–145. doi:10.3141/2519-15.
  • Werberich, B. R., C. O. Pretto, and H. B. B. Cybis. 2015b. “Calibration of a Pedestrian Route Choice Model with a Basis in Friction Forces.” Transportation Research Record: Journal of the Transportation Research Board 2519 (1): 137–145. doi:10.3141/2519-15.
  • Wolinski, D., J. G. S, A. H. Olivier, M. Lin, D. Manocha, and J. Pettré. 2014. “Parameter Estimation and Comparative Evaluation of Crowd Simulations.” Computer Graphics Forum 33 (2): 303–312. doi:10.1111/cgf.12328.
  • Xu, Q., M. Chraibi, and A. Seyfried. 2021. “Prolonged Clogs in Bottleneck Simulations for Pedestrian Dynamics.” Physica A: Statistical Mechanics and Its Applications 573: 125934. doi:10.1016/j.physa.2021.125934.
  • Yanagisawa, D., A. Kimura, R. Nishi, A. Tomoeda, and K. Nishinari. 2009. Theoretical and Empirical Study of Pedestrian Outflow Through an Exit, Distributed Autonomous Robotic Systems 8, 227–238. Springer.
  • Yanagisawa, D., and K. Nishinari. 2007. “Mean-Field Theory for Pedestrian Outflow Through an Exit.” Physical Review E 76 (6): 061117. doi:10.1103/PhysRevE.76.061117.
  • Zeng, W., P. Chen, H. Nakamura, and M. Iryo-Asano. 2014. “Application of Social Force Model to Pedestrian Behavior Analysis at Signalized Crosswalk.” Transportation Research Part C: Emerging Technologies 40: 143–159. doi:10.1016/j.trc.2014.01.007.
  • Zeng, W., P. Chen, G. Yu, and Y. Wang. 2017. “Specification and Calibration of a Microscopic Model for Pedestrian Dynamic Simulation at Signalized Intersections: A Hybrid Approach.” Transportation Research Part C: Emerging Technologies 80: 37–70. doi:10.1016/j.trc.2017.04.009.
  • Zhang, D., H. Zhu, L. Du, and S. Hostikka. 2018. “An Optimization-Based Overtaking Model for Unidirectional Pedestrian Flow.” Physics Letters A 382 (44): 3172–3180. doi:10.1016/j.physleta.2018.08.024.
  • Zhang, D., H. Zhu, S. Hostikka, and S. Qiu. 2019. “Pedestrian Dynamics in a Heterogeneous Bidirectional Flow: Overtaking Behaviour and Lane Formation.” Physica A: Statistical Mechanics and Its Applications 525: 72–84. doi:10.1016/j.physa.2019.03.032.
  • Zhong, J., and W. Cai. 2015. “Differential Evolution with Sensitivity Analysis and the Powell’s Method for Crowd Model Calibration.” Journal of Computational Science 9: 26–32. doi:10.1016/j.jocs.2015.04.013.
  • Zhou, Z. -X., W. Nakanishi, and Y. Asakura. 2021a. “Data-Driven Framework for the Adaptive Exit Selection Problem in Pedestrian Flow: Visual Information Based Heuristics Approach.” Physica A: Statistical Mechanics and Its Applications 583: 126289. doi:10.1016/j.physa.2021.126289.
  • Zhou, Z. -X., W. Nakanishi, and Y. Asakura. 2021b. “Route Choice in the Pedestrian Evacuation: Microscopic Formulation Based on Visual Information.” Physica A: Statistical Mechanics and Its Applications 562: 125313. doi:10.1016/j.physa.2020.125313.