Abstract
Pedestrian simulation has many applications in computer games, military simulations, and animation systems. A realistic pedestrian simulation requires a realistic pedestrian behavioral model that takes into account the various behavioral aspects of a real pedestrian. In this article, we describe our work on such a model, which aims to generate human-like pedestrian behaviors. To this end, various important factors in a real-pedestrian's decision-making process are considered in our model. These factors include a pedestrian's sensory attention, memory, and navigational behaviors. In particular, a two-level navigation model is proposed to generate realistic navigational behavior. As a result, our pedestrian model is able to generate various realistic behaviors such as overtaking, waiting, side-stepping and lane-forming in a crowded area. The simulated pedestrians are also able to navigate through complex environment, given an abstract map of the environment.
- Baddeley, A. 1997. Human Memory: Theory and Practice. Psychology Press.Google Scholar
- Blue, V. J. and Adler, J. L. 2001. Cellular automata microsimulation for modeling bi-directional pedestrian walkways. Transport. Res. Part B 35, 293--312.Google ScholarCross Ref
- Bohannon, R. 1997. Comfortable and maximum walking speed of adults aged 20--79 years: Reference values and determinants. Age and Ageing 26, 1, 15--19.Google ScholarCross Ref
- Braun, A., Musse, S., de Oliverira, L., and Bodmann, B. 2003. Modelling individual behaviours in crowd simulation. In Proceedings of the 16th International Conference on Computer Animation and Social Agents (CASA'03). 143--148. Google ScholarDigital Library
- Burstedde, C., Klauck, K., Schadschneider, A., and Zittartz, J. 2001. Simulation of pedestrian dynamics using a two-dimensional cellular automaton. Physica A: Stat. Mechanics Appl. 295, 507--525.Google ScholarCross Ref
- Feurtey, F. 2000. Simulating the collision avoidance behaviour of pedestrains. M.S. thesis, School of Engineering, University of Tokyo.Google Scholar
- Gwynne, S. et al. 1999. Escape as a Social Response. Society of Fire Protection Engineers, Boston, MA.Google Scholar
- Hart, P. E., Nilsson, N. J., and Raphael, B. 1968. A formal basis for the heuristic determination of minimum cost paths. IEEE Trans. Syst. Sci. Cybern. 2, 100--107.Google ScholarCross Ref
- Helbing, D. et al. 2005. Self-organized pedestrian crowd dynamics: Experiments, simulations, and design solutions. Transport. Sci. 39, 1--24. Google ScholarDigital Library
- Helbing, D. and Molnar, P. 1995. Social force model for pedestrian dynamics. Physical Rev. 51, 4282--4286.Google Scholar
- Hoogendoorn, S. P. and Bovy, P. H. L. 2001. Generic gas-kinetic traffic systems modeling with applications to vehicular traffic flow Transport. Res. Part B 35, 317--336.Google ScholarCross Ref
- Hughes, R. L. 2002. A continuum theory for the flow of pedestrians. Transport. Res. Part B 36, 507--535.Google ScholarCross Ref
- Johnstone, M. and Wilson, P. 1999. The memory fragmentation problem: Solved? ACM SIGPLAN Not. 34, 26--36. Google ScholarDigital Library
- Kirchner, A. 2002. Simulation of evacuation processes using a bionics-inspired cellular automaton model for pedestrian dynamics. Physica A: Stat. Mechanics Appl. 312, 260--276.Google ScholarCross Ref
- Lamarche, F. and Donikian, S. 2004. Crowd of virtual humans: A new approach for real-time navigation in complex and structured environments. Comput. Graph. Forum 23, 3, 509--518.Google ScholarCross Ref
- Le, D. D., Boulic, R., and Thalmann, D. 2003. Integrating age attributes to virtual human locomotion. In International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. XXXIV.Google Scholar
- Millington, I. 2006. Artificial Intelligence for Games. Morgan Kaufmann. Google ScholarDigital Library
- Musse, S. and Thalmann, D. 2001. Hierarchical model for real time simulation of virtual human crowds. IEEE Trans. Visualiz. Comput. Graph. 7. 152--164. Google ScholarDigital Library
- Pan, X., Han, C. S., Dauber, K., and Law, K. H. 2005. A multi-agent based simulation framework for the study of human and social behavior in egress analysis. Comput. Civil Eng. 179, 92--92.Google Scholar
- Pelechano, N., Allbeck, J., and Badler, N. 2007. Controlling individual agents in high-density crowd simulation. In Proceedings of the ACM SIGGRAPH/Eurographics Symposium on Computer Animation (SCA'07). ACM, New York. Google ScholarDigital Library
- Posner, M. I. and Petersen, S. E. 1990. The attention system of the human brain. Ann. Rev. Neuroscience 13, 25--42.Google ScholarCross Ref
- Rao, A. S. and Georegff, M. P. 1999. Modeling rational agents within a BDI architecture. In Proceedings of the 2nd International Conference on Principles of Knowledge Representation and Reasoning. 473--484.Google Scholar
- Reynolds, C. W. 1999. Steering behaviours for autonomous characters. In Proceedings of the Game Developer Conference. 763--782.Google Scholar
- Sakuma, T., Mukai, T., and Kuriyama, S. 2005. Psychological model for animating crowded pedestrians. Comput. Animation Virtual Worlds 16, 343--351. Google ScholarDigital Library
- Schadschneider, A., Kirchner, A., and Nishinari, K. 2002. CA approach to collective phenomena in pedestrian dynamics. In Proceedings of 5th International Conference on Cellular Automata for Research and Industry. 239--248. Google ScholarDigital Library
- Shao, W. and Terzopoulos, D. 2005. Autonomous pedestrians. In Proceedings of the 2005 ACM SIGGRAPH/Eurographics Symposium on Computer Animation. ACM, New York, 19--28. Google ScholarDigital Library
- Still, G. 2000. Use of crowd dynamics around the world. Ph.D. dissertation, Robert Gordon Institute of Technology.Google Scholar
- Teknomo, K. 2006. Applications of microscopic pedestrian simulation model. Transport. Res. Part F: Traffic Psychol. Behaviour 9, 15--27.Google ScholarCross Ref
- Thalmann, D. et al. 1999. Virtual human behaviour: Individuals, groups and crowds. In Proceedings of Digital Media Futures.Google ScholarCross Ref
- Treuille, A., Cooper, S., and Popovic, Z. 2006. Continuum crowds. In Proceedings of SIGGRAPH'06. ACM, New York, 1160--1168. Google ScholarDigital Library
- Ulicny, B. and Thalmann, D. 2002. Towards interactive real-time crowd behaviour. Comput. Graph. Forum 21, 767--775.Google ScholarCross Ref
Index Terms
- Modeling and simulation of pedestrian behaviors in crowded places
Recommendations
Simulating operational behaviors of pedestrian navigation
Navigation is an innate ability for humans, but simulating this capability in a virtual environment is no easy task and has been of interest to researchers for over a decade. This paper describes the development of ISAPT, an individual-based Intermodal ...
Spatial-temporal patterns and pedestrian simulation
CASA' 2010 Special IssueIn this paper, we propose a framework for modeling lower-level pedestrian navigational behaviors. We aim not only to generate realistic simulation results but also to make our framework flexible and extendible, and easy to use for model developers. A ...
Modelling and Simulation of Pedestrian Behaviours
PADS '08: Proceedings of the 22nd Workshop on Principles of Advanced and Distributed SimulationThe modelling and simulation of autonomous pedestrians has important applications in real-time crowd and crisis simulations. With the increase in processing powers and dedicated graphics cards, more processing powers can now be allocated for the ...
Comments