Fangkai Yang
Christopher Peters
ABSTRACT
Agent-based crowd simulation in virtual environments is of great utility in a variety of domains, from the entertainment industry to serious applications including mobile robots and swarms. Many studies of crowd behavior simulations do not consider the fact that people tend to congregate in smaller social gatherings, such as friends, or families, rather than walking alone. Based on a real-time crowd simulator which has been implemented as a unilateral incompressible fluid and augmented with group behaviors, a perceptual study was conducted to determine the impact of groups on the perception of the crowds at various densities from different camera views. If it is not possible to see groups under certain circumstances, then it may not be necessary to simulate them, to reduce the amount of calculations, an important issue in real-time simulations. This study provides researchers with a proper reference to design better algorithms to simulate realistic behaviors.
- Adrian F Aveni. 1977. The not-so-lonely crowd: Friendship groups in collective behavior. Sociometry (1977), 96--99.Google Scholar
- James S Coleman and John James. 1961. The equilibrium size distribution of freely-forming groups. Sociometry 24, 1 (1961), 36--45.Google ScholarCross Ref
- Cathy Ennis and Carol O'Sullivan. 2012. Perceptually plausible formations for virtual conversers. Computer Animation and Virtual Worlds 23, 3-4 (2012), 321--329. Google ScholarDigital Library
- Cathy Ennis, Christopher Peters, and Carol O'Sullivan. 2011. Perceptual effects of scene context and viewpoint for virtual pedestrian crowds. ACM Transactions on Applied Perception (TAP) 8, 2 (2011), 10. Google ScholarDigital Library
- Mizar Luca Federici, Andrea Gorrini, Lorenza Manenti, and Giuseppe Vizzari. 2012. Data collection for modeling and simulation: case study at the university of milan-bicocca. In International Conference on Cellular Automata. Springer, 699--708.Google ScholarCross Ref
- JJ Fruin. 1970. Designing for Pedestrians. A Level of Service Concept. Polytechnical Institute of Brooklyn. Ph.D. Dissertation. Ph. D.Google Scholar
- Weina Ge, Robert T Collins, and Barry Ruback. 2009. Automatically detecting the small group structure of a crowd. In Applications of computer vision (wacv), 2009 workshop on. IEEE, 1--8.Google Scholar
- Weina Ge, Robert T Collins, and R Barry Ruback. 2012. Vision-based analysis of small groups in pedestrian crowds. IEEE transactions on pattern analysis and machine intelligence 34, 5 (2012), 1003--1016. Google ScholarDigital Library
- Edward Twitchell Hall. 1966. The hidden dimension. (1966).Google Scholar
- A Paul Hare. 1976. Handbook of small group research. (1976).Google Scholar
- Dirk Helbing, Anders Johansson, and Habib Zein Al-Abideen. 2007. Dynamics of crowd disasters: An empirical study. Physical review E 75, 4 (2007), 046109.Google Scholar
- Rafael Hocevar, Fernando Marson, Vinícius Cassol, Henry Braun, Rafael Bidarra, and Soraia R. Musse. 2012. From their environment to their behavior: Aprocedural approach to model groups of virtual agents. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 7502 LNAI (2012), 370--376. Google ScholarDigital Library
- Roger L Hughes. 2002. A continuum theory for the flow of pedestrians. Transportation Research Part B: Methodological 36, 6 (2002), 507--535.Google ScholarCross Ref
- John James. 1953. The distribution of free-forming small group size. American Sociological Review (1953).Google Scholar
- Tobias Kretz, Anna Grünebohm, Maike Kaufman, Florian Mazur, and Michael Schreckenberg. 2006. Experimental study of pedestrian counterflow in a corridor. Journal of Statistical Mechanics: Theory and Experiment 2006, 10 (2006), P10001.Google ScholarCross Ref
- Tobias Kretz, Anna Grünebohm, and Michael Schreckenberg. 2006. Experimental study of pedestrian flow through a bottleneck. Journal of Statistical Mechanics: Theory and Experiment 2006, 10 (2006), P10014.Google ScholarCross Ref
- Francisco Martinez-Gil, Miguel Lozano, Ignacio García-Fernández, and Fernando Fernández. 2017. Modeling, Evaluation, and Scale on Artificial Pedestrians: A Literature Review. ACM Computing Surveys (CSUR) 50, 5 (2017), 72. Google ScholarDigital Library
- Mehdi Moussaïd, Niriaska Perozo, Simon Garnier, Dirk Helbing, and Guy Theraulaz. 2010. The Walking Behaviour of Pedestrian Social Groups and Its Impact on Crowd Dynamics. PLOS ONE 5, 4 (04 2010), 1--7.Google Scholar
- Rahul Narain, Abhinav Golas, Sean Curtis, and Ming C. Lin. 2009. Aggregate Dynamics for Dense Crowd Simulation. In ACM SIGGRAPH Asia 2009 Papers (SIGGRAPH Asia '09). ACM, New York, NY, USA, Article 122, 8 pages. Google ScholarDigital Library
- Xiaoshan Pan, Charles S Han, and Kincho H Law. 2005. A multiagent based simulation framework for the study of human and social behavior in egress analysis. In Computing in Civil Engineering (2005). 1--12.Google Scholar
- Christopher Peters and Cathy Ennis. 2009. Modeling groups of plausible virtual pedestrians. IEEE Computer Graphics and Applications 29, 4 (2009).Google Scholar
- Francisco Arturo Rojas, Hyun Seung Yang, and Fernando M Tarnogol. 2014. Safe Navigation of Pedestrians in Social Groups in a Virtual Urban Environment. In Cyberworlds (CW), 2014 International Conference on. IEEE, 31--38. Google ScholarDigital Library
- Kenneth H. Rosen. 2002. Discrete Mathematics and Its Applications (5th ed.). McGraw-Hill Higher Education. Google ScholarDigital Library
- Harmeet Singh, Robyn Arter, Louise Dodd, Paul Langston, Edward Lester, and John Drury. 2009. Modelling subgroup behaviour in crowd dynamics DEM simulation. Applied Mathematical Modelling 33, 12 (2009), 4408--4423.Google ScholarCross Ref
- G Keith Still. 2000. Crowd dynamics. Ph.D. Dissertation. University of Warwick.Google Scholar
- Jur Van Den Berg, Sachin Patil, Jason Sewall, Dinesh Manocha, and Ming Lin. 2008. Interactive navigation of multiple agents in crowded environments. In Proceedings of the 2008 symposium on Interactive 3D graphics and games. ACM, 139--147. Google ScholarDigital Library
- Xiaoge Wei, Wei Lv, Weiguo Song, and Xiaolian Li. 2015. Survey study and experimental investigation on the local behavior of pedestrian groups. Complexity 20, 6 (2015), 87--97. Google ScholarDigital Library
- Steven A Wilmarth, Nancy M Amato, and Peter F Stiller. 1999. MAPRM: A probabilistic roadmap planner with sampling on the medial axis of the free space. In Robotics and Automation, 1999. Proceedings. 1999 IEEE International Conference on, Vol. 2. IEEE, 1024--1031.Google ScholarCross Ref
- Michael Wooldridge and Nicholas R Jennings. 1995. Intelligent agents: Theory and practice. The knowledge engineering review 10, 2 (1995), 115--152.Google Scholar
- Wenjian Yu and Anders Johansson. 2007. Modeling crowd turbulence by many-particle simulations. Physical review E 76, 4 (2007), 046105.Google Scholar
Index Terms
- Do you see groups?: The impact of crowd density and viewpoint on the perception of groups
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