A macroscopic approach for calibration and validation of a modified social force model for bidirectional pedestrian streams

References

• Appert-Rolland, C., P. Degond, and S. Motsch. 2014. “A Macroscopic Model for Bidirectional Pedestrian Flow.” In Pedestrian and Evacuation Dynamics, edited by U. Weidmann, U. Kirsch, and M. Schreckenberg, 575–583. Cham: Springer.
   Google Scholar
• Benner, H., T. Kretz, H. Lohmiller, and P. Sukennik. 2017. “Is Calibration a Straight-forward Task If Detailed Trajectory Data is Available?” In the Proceedings of the Transportation Research Board, 96th Annual Meeting, 8th–12th Jan 2017.
   Google Scholar
• Blue, V., and J. Adler. 1999. “Cellular Authomata Microsimulation of Bidirectional Pedestrian Flows.” Transportation Research Record: Journal of the Transportation Research Board 1678: 135–141. doi: 10.3141/1678-17
   Google Scholar
• Blue, V., and J. Adler. 2000. “Modeling Four-Directional Pedestrian Flows.” Transportation Research Record: Journal of the Transportation Research Board 1710: 20–27. doi: 10.3141/1710-03
   Google Scholar
• Campanella, M., S. Hoogendoorn, and W. Daamen. 2014. “Quantitative and Qualitative Validation Procedure for General Use of Pedestrian Models.” In Proceedings of the Conference on Pedestrian and Evacuation Dynamics 2012 (PED2012), edited by U. Weidmann, U. Kirsch, and M. Schreckenberg, 891–905. Cham: Springer.
   Google Scholar
• Daamen, W., M. Campanella, and S. P. Hoogendoorn. 2013. “Calibration of Nomad Parameters Using Empirical Data.” In Traffic and Granular Flow ‘11, edited by V. Kozlov, A. Buslaev, A. Bugaev, M. Yashina, A. Schadschneider, and M. Schreckenberg, 109–120. Berlin, Heidelberg: Springer.
   Google Scholar
• Daamen, W., and S. P. Hoogendoorn. 2012. “Calibration of Pedestrian Simulation Model for Emergency Doors by Pedestrian Type.” Transportation Research Record: Journal of the Transportation Research Board 2316: 69–75. doi: 10.3141/2316-08
   Web of Science ®Google Scholar
• 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
   Web of Science ®Google Scholar
• 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
   Web of Science ®Google Scholar
• Duives, D., W. Daamen, and S. Hoogendoorn. 2013. “State-of-the-art Crowd Motion Simulation Models.” Transportation Research Part C 37: 193–209. doi: 10.1016/j.trc.2013.02.005
   Web of Science ®Google Scholar
• 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: Statistical Mechanics and its Applications 447: 36–48. doi: 10.1016/j.physa.2015.11.025
   Web of Science ®Google Scholar
• Flötteröd, G., and G. Lämmel. 2015. “Bidirectional Pedestrian Fundamental Diagram.” Transportation Research Part B 71: 194–212. doi: 10.1016/j.trb.2014.11.001
   Google Scholar
• Geroliminis, N., and C. F. Daganzo. 2008. “Existence of Urban-Scale Macroscopic Fundamental Diagrams: Some Experimental Findings.” Transportation Research Part B 9: 759–770. doi: 10.1016/j.trb.2008.02.002
   Google Scholar
• Gloor, C. D. 2005. “Distributed Intelligence in Real World Mobility Simulations.” PhD diss., Swiss Federal Institute of Technology Zurich.
   Google Scholar
• Gloor, C. 2016. “PEDSIM – Pedestrian Crowd Simulation.” http://pedsim.silmaril.org/.
   Google Scholar
• Handel, O., and A. Borrmann. 2017. “Service Bottlenecks in Pedestrian Dynamics.” Transportmetrica A: Transport Science 14 (5–6): 392–405. doi: 10.1080/23249935.2017.1280712
   Web of Science ®Google Scholar
• Hanseler, F., M. Bierlaire, B. Farooq, and T. Muhlematter. 2014. “A Macroscopic Loading Model for Time-Varying Pedestrian Flows in Public Walking Areas.” Transportation Research Part B 69: 60–80. doi: 10.1016/j.trb.2014.08.003
   Google Scholar
• Hanseler, F., W. H. K. Lam, M. Bierlaire, G. Lederrey, and M. Nikolic. 2017b. “A Dynamic Network Loading Model for Anisotropic and Congested Pedestrian Flows.” Transportation Research Part B 95: 149–168. doi: 10.1016/j.trb.2016.10.017
   Google Scholar
• Hanseler, F., N. Molyneaux, and M. Bierlaire. 2017a. “Estimation of Pedestrian Origin-Destination Demand in Train Stations.” Transportation Science 51 (3): 981–997. doi: 10.1287/trsc.2016.0723
   Web of Science ®Google Scholar
• Helbing, D., and P. Molnar. 1995. “Social Force Model for Pedestrian Dynamics.” Physical Review E 51 (5): 4282–4286. doi: 10.1103/PhysRevE.51.4282
   PubMed Web of Science ®Google Scholar
• Hoogendoorn, S. P., M. C. Campanella, and W. Daamen. 2010. “Macroscopic Fundamental Diagrams for Pedestrian Networks.” Presented at 89th Annual Meeting of the Transportation Research Board, Washington, DC.
   Google Scholar
• Hoogendoorn, S. P., and W. Daamen. 2006. “Microscopic Parameter Identification of Pedestrian Models and Implications for Pedestrian Flow Modeling.” Transportation Research Record: Journal of the Transportation Research Board 1982: 57–64. doi: 10.1177/0361198106198200108
   Google Scholar
• Hoogendoorn, S. P., W. Daamen, V. Knoop, J. Steenbakkers, and M. Sarvi. 2017 “Macroscopic Fundamental Diagram for Pedestrian Networks: Theory and Application.” Transportation Research Part C. doi:10.1016/j.trc.2017.09.003
   Google Scholar
• Hoogendoorn, S., W. Daamen, and R. Landman. 2007. “Microscopic Calibration and Validation of Pedestrian Models Cross-Comparison of Models Using Experimental Data.” In Pedestrian and Evacuation Dynamics 2005 (PED2005), edited by N. Waldau, P. Gattermann, H. Knoflacher, and M. Schreckenberg, 253–265. Berlin, Heidelberg: Springer.
   Google Scholar
• Hussein, M., and T. Sayed. 2017. “A bi-Directional Agent-Based Pedestrian Microscopic Model.” Transportmetrica A: Transport Science 13 (4): 326–355. doi: 10.1080/23249935.2016.1266531
   Web of Science ®Google Scholar
• Johansson, A., D. Helbing, and P. Shukla. 2007. “Specification of the Social Force Pedestrian Model by Evolutionary Adjustment to Video Tracking Data.” Advances in Complex Systems 10: 271–288. doi: 10.1142/S0219525907001355
   Google Scholar
• Knoop, V. L., H. van Lint, and S. P. Hoogendoorn. (2015). “Traffic Dynamics: Its Impact on the Macroscopic Fundamental Diagram.” Physcia A: Stat. Mech. Appl 438: 236–250. doi: 10.1016/j.physa.2015.06.016
   Web of Science ®Google Scholar
• Ko, M., T. Kim, and K. Sohn. 2013. “Calibrating a Social-Force-Based Pedestrian Walking Model Basedon Maximum Likelihood Estimation.” Transportation 40: 91–107. doi: 10.1007/s11116-012-9411-z
   Web of Science ®Google Scholar
• Kretz, T., J. Lohmiller, and P. Sukennik. 2018. “Some Indications on How to Calibrate the Social Force Model of Pedestrian Dynamics.” In the Proceedings of the Transportation Research Board, 97th Annual Meeting, 7th–11th Jan 2018.
   Google Scholar
• Lakoba, Y., D. J. Kaup, and N. M. Finkelstein. 2005. “Modifications of the Helbing-Monar-Farkas-Vicsek Social Force Model for Pedestrian Evolution.” Simulation 81 (5): 339–352. doi: 10.1177/0037549705052772
   Google Scholar
• Lovreglio, R., C. Dias, X. Song, and L. Ballerini. 2017. “Towards Microscopic Calibration of Pedestrian Simulation Models using Open Trajectory Data-Sets: The Case Study of the Edinburgh Informatics Forum.” In the Proceedings of the Conference on Traffic and Granular Flow (TGF), July 2017.
   Google Scholar
• Moussaïd, M., D. Helbing, S. Garnier, A. Johansson, M. Combe, and G. Theraulaz. 2009. “Experimental Study of the Behavioural Mechanisms Underlying Self-Organization in Human Crowds.” Proceedings of the Royal Society B 276: 2755–2762. doi: 10.1098/rspb.2009.0405
   PubMed Web of Science ®Google Scholar
• Moussaïd, M., D. Helbing, and G. Theraulaz. 2011. “How Simple Rules Determine Pedestrian Behavior and Crowd Disasters.” Proceedings of the National Academy of Sciences of the United States of America 108 (17): 6884–6888. doi: 10.1073/pnas.1016507108
   PubMed Web of Science ®Google Scholar
• Nikolic, M., and M. Bierlaire. 2017. “Data-driven Spatio-temporal Discretization for Pedestrian Flow Characterization.” Transportation Research Part C. doi:10.1016/j.trc.2017.08.026
   Google Scholar
• Parisi, D., M. Gilman, and H. Moldovan. 2009. “A Modification of the Social Force Model can Reproduce Experimental Data of Pedestrian Flows in Normal Conditions.” Physica A: Statistical Mechanics and its Applications 388 (17): 3600–3608. doi: 10.1016/j.physa.2009.05.027
   Web of Science ®Google Scholar
• Payet, G. 2016. “Developing a massive real-time crowd simulation framework on the GPU.” Department of Computer Science and Software Engineering University of Canterbury, Christchurch, New Zealand.
   Google Scholar
• Porter, E., S. Hamdar, and W. Daamen. 2018. “Pedestrian Dynamics at Transit Stations: An Integrated Pedestrian Flow Modeling Approach.” Transportmetrica A: Transport Science 14 (5–6): 468–483. doi: 10.1080/23249935.2017.1378280
   Web of Science ®Google Scholar
• Ramezani, M., J. Haddad, and N. Geroliminis. 2015. “Dynamics of Heterogeneity in Urban Networks: Aggregated Traffic Modeling and Hierarchical Control.” Transportation Research Part B 74: 1–19. doi: 10.1016/j.trb.2014.12.010
   Google Scholar
• Saberi, M., K. Aghabayk, and A. Sobhani. 2015. “Spatial Fluctuations of Pedestrian Velocities in Bidirectional Streams: Exploring the Effects of Self-Organization.” Physica A: Statistical Mechanics and its Application 434: 120–128. doi: 10.1016/j.physa.2015.04.008
   Web of Science ®Google Scholar
• Saberi, M., and H. S. Mahmassani. 2012. “Exploring the Properties of Network-Wide Flow-Density Relations in Freeway Networks.” Transportation Research Record: Journal of the Transportation Research Board 2315: 153–163. doi: 10.3141/2315-16
   Web of Science ®Google Scholar
• Saberi, M., and H. Mahmassani. 2014. “Exploring Areawide Dynamics of Pedestrian Crowds: Three-Dimensional Approach.” Transportation Research Record Journal of the Transportation Research Board 2421: 31–40. doi: 10.3141/2421-04
   Web of Science ®Google Scholar
• Seer, S., C. Rudloff, T. Matyus, and N. Brandle. 2014. “Validating Social Force Based Models with Comprehensive Real World Motion Data.” Transpotation Research Procedia 2: 724–732. doi: 10.1016/j.trpro.2014.09.080
   Google Scholar
• Seyfried, A., B. Steffen, W. Klingsch, and M. Boltes. 2005. “The Fundamental Diagram of Pedestrian Movement Revisited.” Journal of Statistical Mechanics: Theory and Experiment 2005 (10): P10002. doi: 10.1088/1742-5468/2005/10/P10002
   Web of Science ®Google Scholar
• Seyfried, A., B. Steffen, and T. Lippert. 2006. “Basics of Modeling the Pedestrian Flow.” Physica A: Statistical Mechanics and its Applications 368 (1): 232–238. doi: 10.1016/j.physa.2005.11.052
   Web of Science ®Google Scholar
• Shahhosseini, Z., M. Sarvi, and M. Saberi. 2017. “Pedestrian Crowd Dynamics Observed at Merging Sections: The Impact of Different Designs on Movement Efficiency.” Transportation Research Record: Journal of the Transportation Research Board 2622: 48–57. doi: 10.3141/2622-05
   Web of Science ®Google Scholar
• Shahhosseini, Z., M. Sarvi, and M. Saberi. 2018. “Pedestrian Crowd Dynamics in Merging Sections: Revisiting the “Faster-is-Slower” Phenomenon.” Physica A: Statistical Mechanics and Its Applications 491: 101–111. doi: 10.1016/j.physa.2017.09.003
   Web of Science ®Google Scholar
• Steffen, B. 2010. “A Modification of the Social Force Model by Foresight.” In Pedestrian and Evacuation Dynamics 2008, edited by W. Klingsch, C. Rogsch, A. Schadschneider, and M. Schreckenberg, 1902–1910. Berlin, Heidelberg: Springer.
   Google Scholar
• Steffen, B., and A. Seyfried. 2010. “Methods for Measuring Pedestrian Density, Flow, Speed and Direction with Minimal Scatter.” Physica A: Statistical Mechanics and its Applications 389 (9): 1902–1910. doi: 10.1016/j.physa.2009.12.015
   Web of Science ®Google Scholar
• Tak, S., S. Kim, and H. Yeo. 2018. “Agent-based Pedestrian Cell Transmission Model for Evacuation.” Transportmetrica A: Transport Science 14 (5–6): 484–502. doi: 10.1080/23249935.2017.1280559
   Web of Science ®Google Scholar
• Tian, H., H. He, Y. Wei, X. Yu, and W. Lu. 2009. “Lattice Hydrodynamic Model with Bidirectional Pedestrian Flow.” Physica A: Statistical Mechanics and its Applications 388 (14): 2895–2902. doi: 10.1016/j.physa.2009.02.047
   Web of Science ®Google Scholar
• van Wageningen-Kessels, F. L. M., S. P. Hoogendoorn, and W. Daamen. (2014). “ Extension of Edie’s Definitions for Pedestrian Dynamics.” Transportation Research Procedia 2: 507–512. doi: 10.1016/j.trpro.2014.09.067
   Google Scholar
• Weifeng, F., Y. Lizhong, and F. Weicheng. 2003. “Simulation of bi-Direction Pedestrian Movement Using a Cellular Automata Model.” Physica A: Statistical Mechanics and its Applications 321 (3–4): 633–640. doi: 10.1016/S0378-4371(02)01732-6
   Web of Science ®Google Scholar
• Wong, S. C., W. L. Leung, S. H. Chan, and W. H. K. Lam. 2010. “Bidirectional Pedestrian Stream Model with Oblique Intersecting Angle.” Journal of Transportation Engineering 136 (3): 234–242. doi: 10.1061/(ASCE)TE.1943-5436.0000086
   Web of Science ®Google Scholar
• Xie, S., and S. C. Wong. 2015. “A Bayesian Inference Approach to the Development of a Multidirectional Pedestrian Stream Model.” Transportmetrica A: Transport Science 11 (1): 61–73. doi: 10.1080/23249935.2014.924165
   Web of Science ®Google Scholar
• Xue, Y., J. J. Tian, H. D. He, W. Z. Lu, and Y. F. Wei. 2009. “Exploring Jamming Transitions and Density Waves in Bidirectional Pedestrian Traffic.” The European Physical Journal B 69 (2): 289–295. doi: 10.1140/epjb/e2009-00149-8
   Web of Science ®Google Scholar
• Yang, X., W. Daamen, S. P. Hoogendoorn, Y. Chen, and H. Dong. 2014. “Breakdown Phenomenon Study in the Bidirectional Pedestrian Flow.” Transportation Research Procedia 2: 456–461. doi: 10.1016/j.trpro.2014.09.060
   Google Scholar
• 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 40: 143–159. doi: 10.1016/j.trc.2014.01.007
   Web of Science ®Google Scholar
• 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 80: 37–70. doi: 10.1016/j.trc.2017.04.009
   Web of Science ®Google Scholar
• Zeng, W., H. Nakamura, and P. Chen. 2014. “A Modified Social Force Model for Pedestrian Behavior Simulation at Signalized Crowsswalks.” Procedia Social and Behavioral Sciences 138: 521–530. doi: 10.1016/j.sbspro.2014.07.233
   Google Scholar
• Zhang, J., W. Klingsch, A. Schadschneider, and A. Seyfried. 2012. “Ordering in Bidirectional Pedestrian Flows and its Influence on the Fundamental Diagram.” Journal of Statistical Mechanics: Theory and Experiment 2012: P02002.
   Web of Science ®Google Scholar
• Zhang, J., and A. Seyfried. 2013. “Empirical Characteristics of Different Types of Pedestrian Streams.” Procedia Engineering 62: 655–662. doi: 10.1016/j.proeng.2013.08.111
   Google Scholar