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Original Articles

A unified pedestrian routing model for graph-based wayfinding built on cognitive principles

, , &
Pages 406-432 | Received 25 Apr 2016, Accepted 18 Mar 2017, Published online: 09 Apr 2017

References

  • Anderson, J. R. 2010. Cognitive Psychology and its Implications. 7th ed. New York: Worth Publishing.
  • Andresen, E., D. Haensel, M. Chraibi, and A. Seyfried. 2016. “Wayfinding and Cognitive Maps for Pedestrian Models.” In Proceedings of the 11th Conference on Traffic and Granular Flow, 249–256. Netherland: Springer International Publishing.
  • Angus, D., T. Hendtlass, and M. Ali. 2002. “Ant Colony Optimisation Applied to a Dynamically Changing Problem.” In Developments in applied artificial intelligence: 15th international conference on industrial and engineering applications of artificial intelligence and expert systems (IEA/AIE 2002), Cairns, Australia, 618–627.
  • Biedermann, D. H., F. Dietrich, O. Handel, P. M. Kielar, and M. Seitz. 2015. Using Raspberry Pi for scientific video observation of pedestrians during a music festival. Germany: Technische Universität München.
  • Biedermann, D. H., P. M. Kielar, and A. Borrmann. 2015. “Oppilatio - The Forecast of Crowd Congestions on Street Networks During Public Events.” Proceedings of the 11th conference on traffic and granular flow, Nootdorp, the Netherland.
  • Bierlaire, M., and T. Robin. 2009. “Pedestrians Choices.” In Pedestrian Behavior. Models, Data Collection and Applications, edited by Harry Timmermans, 1–26. Bingley, UK: Emerald Group Publishing Limited.
  • 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
  • Conroy, R. 2001. “Spatial Navigation in Immersive Virtual Environments.” Ph.D. thesis. University College London.
  • Dalton, R. C. 2003. “The Secret is to Follow Your Nose Route Path Selection and Angularity.” Environment and Behavior 35 (1): 107–131. doi: 10.1177/0013916502238867
  • Danalet, A., and M. Bierlaire. 2015. “Importance Sampling for Activity Path Choice.” Swiss Transport Research Conference (STRC), Ascona, Switzerland.
  • Dijkstra, E. W. 1959. “A Note on Two Problems in Connexion with Graphs.” Numerische Mathematik 1 (1): 269–271. doi: 10.1007/BF01386390
  • Dijkstra, J., and A. J. Jessurun. 2014. “Agent-Based Pedestrian Activity Simulation in Shopping Environments using a Choice Network Approach.” In Cellular Automata: 11th International Conference on Cellular Automata for Research and Industry, 680–687. Krakow, Poland: Springer International Publishing.
  • Dyer, J. R. G., A. Johansson, D. Helbing, I. D. Couzin, and J. Krause. 2009. “Leadership, Consensus Decision Making and Collective Behaviour in Humans.” Philosophical Transactions of the Royal Society of London B: Biological Sciences 364 (1518): 781–789. doi: 10.1098/rstb.2008.0233
  • Frith, C. D., and U. Frith. 2012. “Mechanisms of Social Cognition.” Annual Review of Psychology 63, 287–313. doi: 10.1146/annurev-psych-120710-100449
  • Gaisbauer, C., and A. U. Frank. 2008. “Wayfinding Model for Pedestrian Navigation.” AGILE 2008 Conference-Taking geo-information science one step further, University of Girona, Spain, 9.
  • Geraerts, R., and M. H. Overmars. 2006. “Creating High-Quality Roadmaps for Motion Planning in Virtual Environments.” 2006 IEEE/RSJ international conference on intelligent robots and systems, Beijing, China, 4355–4361.
  • Geraerts, R., and M. H. Overmars. 2007. “The Corridor Map Method: A General Framework for Real-Time High-Quality Path Planning.” Computer Animation and Virtual Worlds 18 (2): 107–119. doi: 10.1002/cav.166
  • Golledge, R. G. 1995. “Path Selection and Route Preference in Human Navigation: A Progress Report.” In Spatial Information Theory a Theoretical Basis for GIS: International Conference COSIT '95, 207–222. Austria: Springer.
  • Golledge, R. G. 1999. “Human Wayfinding and Cognitive Maps.” Wayfinding behavior: Cognitive mapping and other spatial processes, 5–45.
  • Gross, J. L., and J. Yellen. 2005. Graph Theory and its Applications. Boca Raton: CRC Press.
  • Guo, R-Y., H-J. Huang, and S. C. Wong. 2013. “A Potential Field Approach to the Modeling of Route Choice in Pedestrian Evacuation.” Journal of Statistical Mechanics: Theory and Experiment 2013 (2): P02010. doi: 10.1088/1742-5468/2013/02/P02010
  • Hart, P. E., N. J. Nilsson, and B. Raphael. 1968. “A Formal Basis for the Heuristic Determination of Minimum Cost Paths.” IEEE Transactions on Systems Science and Cybernetics 4 (2): 100–107. doi: 10.1109/TSSC.1968.300136
  • Hartmann, D. 2010. “Adaptive Pedestrian Dynamics Based on Geodesics.” New Journal of Physics 12 (4): 043032. doi: 10.1088/1367-2630/12/4/043032
  • 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: 10.1287/trsc.1040.0108
  • Höcker, M., V. Berkhahn, A. Kneidl, A. Borrmann, and W. Klein. 2010. “Graph-Based Approaches for Simulating Pedestrian Dynamics in Building Models.” eWork and eBusiness in Architecture, Engineering and Construction, Republic of Ireland, 389–394. doi: 10.1201/b10527-65
  • Hölscher, C., T. Tenbrink, and J. M. Wiener. 2011. “Would You Follow Your Own Route Description? Cognitive Strategies in Urban Route Planning.” Cognition 121 (2): 228–247. doi: 10.1016/j.cognition.2011.06.005
  • Hoogendoorn, S. P., P. H. L. Bovy, and W. Daamen. 2002. “Microscopic Pedestrian Wayfinding and Dynamics Modelling.” In Pedestrian and Evacuation Dynamics, 124–154. Berlin: Springer-Verlag.
  • Kasemsuppakorn, P., and H. A. Karimi. 2013. “A Pedestrian Network Construction Algorithm Based on Multiple GPS Traces.” Transportation Research Part C: Emerging Technologies 26, 285–300. doi: 10.1016/j.trc.2012.09.007
  • Kemloh, W., U. Armel, A. Seyfried, and S. Holl. 2012. “Modeling the Dynamic Route Choice of Pedestrians to Assess the Criticality of Building Evacuation.” Advances in Complex Systems 15 (07): 1250029.
  • Kielar, P. M., D. H. Biedermann, and B. André. 2016. MomenTUMv2: a modular, extensible, and generic agent-based pedestrian behavior simulation framework. Technical Report TUM-I1643. Müchen, Germany: Technische Universität Müchen.
  • Kielar, P. M., D. H. Biedermann, A. Kneidl, and A. Borrmann. 2015. “A Unified Pedestrian Routing Model Combining Multiple Graph-Based Navigation Methods.” Proceedings of the 11th conference on traffic and granular flow, Nootdorp, the Netherland.
  • Kneidl, A. 2013. “Methoden zur Abbildung menschlichen Navigationsverhaltens bei der Modellierung von Fußgängerströmen.” Ph.D. thesis. Technical University Munich.
  • Kneidl, A. 2015. “How do People Queue – a Study of Different Queuing Models.” Proceedings of the 11th conference on traffic and granular flow, Nootdorp, Netherland.
  • Kneidl, A., and A. Borrmann. 2011. “How do Pedestrians Find their Way? Results of an Experimental Study with Students Compared to Simulation Results.” Emergency Evacuation of People from Buildings.
  • Kneidl, A., A. Borrmann, and D. Hartmann. 2012. “Generation and Use of Sparse Navigation Graphs for Microscopic Pedestrian Simulation Models.” Advanced Engineering Informatics 26 (4): 669–680. doi: 10.1016/j.aei.2012.03.006
  • Moussaïd, M., D. Helbing, and G. Theraulaz. 2011. “How Simple Rules Determine Pedestrian Behavior and Crowd Disasters.” Proceedings of the National Academy of Sciences 108 (17): 6884–6888. doi: 10.1073/pnas.1016507108
  • Neis, P., and D. Zielstra. 2014. “Generation of a Tailored Routing Network for Disabled People Based on Collaboratively Collected Geodata.” Applied Geography 47, 70–77. doi: 10.1016/j.apgeog.2013.12.004
  • Pan, X., C. S. Han, K. Dauber, and K. H. Law. 2007. “A Multi-Agent Based Framework for the Simulation of Human and Social Behaviors During Emergency Evacuations.” Ai & Society 22 (2): 113–132. doi: 10.1007/s00146-007-0126-1
  • Peters, C., and C. Ennis. 2009. “Modeling Groups of Plausible Virtual Pedestrians.” IEEE Computer Graphics and Applications 29 (4): 54–63. doi: 10.1109/MCG.2009.69
  • Raafat, R. M., N. Chater, and C. Frith. 2009. “Herding in Humans.” Trends in Cognitive Sciences 13 (10): 420–428. doi: 10.1016/j.tics.2009.08.002
  • Raubal, M. 2001. “Ontology and Epistemology for Agent-Based Wayfinding Simulation.” International Journal of Geographical Information Science 15 (7): 653–665. doi: 10.1080/13658810110061171
  • Schadschneider, A., A. Kirchner, and K. Nishinari. 2003. “From Ant Trails to Pedestrian Dynamics.” Applied Bionics and Biomechanics 1 (1): 11–19. doi: 10.1155/2003/292871
  • Seitz, M., G. Köster, and A. Pfaffinger. 2014. “Pedestrian Group Behavior in a Cellular Automaton.” In Pedestrian and Evacuation Dynamics 2012, edited by W. Ulrich, K. Uwe, S. Michael, 807–814. Switzerland: Springer International Publishing.
  • Sud, A., E. Andersen, S. Curtis, M. Lin, and D. Manocha. 2008. “Real-Time Path Planning for Virtual Agents in Dynamic Environments.” In ACM SIGGRAPH 2008 classes, 1–55. Los Angeles, CA: ACM.
  • Tan, L., L. Wu, and H. Lin. 2015. “An Individual Cognitive Evacuation Behaviour Model for Agent-Based Simulation: A Case Study of a Large Outdoor Event.” International Journal of Geographical Information Science 29 (9): 1–17. doi: 10.1080/13658816.2015.1030751
  • Tani, J. 1996. “Model-Based Learning for Mobile Robot Navigation from the Dynamical Systems Perspective.” IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 26 (3): 421–436. doi: 10.1109/3477.499793
  • Thill, J-C., T. H. D. Dao, and Y. Zhou. 2011. “Traveling in the Three-Dimensional City: Applications in Route Planning, Accessibility Assessment, Location Analysis and Beyond.” Journal of Transport Geography 19 (3): 405–421. doi: 10.1016/j.jtrangeo.2010.11.007
  • Turau, V., and C. Weyer. 2015. Algorithmische Graphentheorie. Berlin, Germany: Walter de Gruyter GmbH & Co KG.
  • von Sivers, I., A. Templeton, G. Köster, J. Drury, and A. Philippides. 2014. “Humans do not Always Act Selfishly: Social Identity and Helping in Emergency Evacuation Simulation.” Transportation Research Procedia 2, 585–593. doi: 10.1016/j.trpro.2014.09.099
  • Wen, W., T. Ishikawa, and T. Sato. 2013. “Individual Differences in the Encoding Processes of Egocentric and Allocentric Survey Knowledge.” Cognitive Science 37 (1): 176–192. doi: 10.1111/cogs.12005
  • Wiener, J. M., S. J. Büchner, and C. Hölscher. 2009. “Taxonomy of Human Wayfinding Tasks: A Knowledge-Based Approach.” Spatial Cognition & Computation 9 (2): 152–165. doi: 10.1080/13875860902906496
  • Wolbers, T., and M. Hegarty. 2010. “What Determines Our Navigational Abilities?.” Trends in Cognitive Sciences 14 (3): 138–146. doi: 10.1016/j.tics.2010.01.001
  • Wooldridge, M. 2009. An Introduction to Multiagent Systems. 2nd ed. Chichester, UK: John Wiley & Sons.
  • Yen, J. Y. 1971. “Finding the k Shortest Loopless Paths in a Network.” Management Science 17 (11): 712–716. doi: 10.1287/mnsc.17.11.712

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