In previous work, virtual force has been used to simulate the motions of virtual creatures, such as birds or fish, in a crowd. However, how to set up the virtual forces to achieve desired effects remains empirical. In this work, we propose to use a genetic algorithm to generate an optimal set of weighting parameters for composing virtual forces according to the given environment and desired movement behaviour. A list of measures for composing the fitness function is proposed.We have conducted experiments in simulation for several environments and behaviours, and the results show that compelling examples can be generated with the parameters found automatically in this approach.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
T. Balch and R.C. Arkin, “Behaviour-based formation control for multirobot teams,” IEEE Trans. on Robotics and Automation, 14(6), pp 926-939 (1998).
E. Bouvier, E. Cohen and L. Najman, “From crowd simulation to airbag deployment: particle systems, a new paradigm of simulation,” J. of Electronic Imaging, 6 (1), pp 94-107 (1997).
D.C. Brogan and J. Hodgins, “Group behaviors for systems with significant dynamics,” Autonomous Robots, 4, pp 137-153 (1997).
J. Funge, X. Tu and D. Terzopoulos, “Cognitive model: knowledge, reasoning, and planning for intelligent characters,” Proc. of ACM SIGGRAPH, pp 29-38, Los Angels (1999).
T.Y. Li, Y.J. Jeng and S.I. Chang, “Simulating virtual human crowds with a leader-follower model,” Proc. of 2001 Computer Animation Conf., Seoul, Korea (2001).
C.C. Wang, T.Y. Li. “Evolving Crowd Motion Simulation with Genetic Algorithm,” Proc. 3rd Intl. Conf. on Autonomous Robots and Agents ICARA’2006, Palmerston North, New Zealand, pp 443-448 (2006).
G. Mitsuo and C. Runwei, Genetic Algorithms & Engineering Design, John Wiley & Sons. Inc., New York (1997).
G.A. Miller. “The magical number seven, plus or minus two: Some limits on our capacity for processing information,” Psychological Review, 63, pp 81-97 (1956).
S.R. Musse and D. Thalmann, “Hierarchical model for real time simulation of virtual human crowds,” IEEE Trans. on Visualization and Computer Graphics, 7 (2), pp 152-164 (2001).
C.W. Reynolds, “Flocks, herds, and schools: A distributed behavioural model,” Computer Graphics, pp 25-34 (1987).
C.W. Reynolds, “Steering behaviours for autonomous characters,” Proc. of Game Developers Conf., San Jose (1999).
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2007 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Li, TY., Wang, CC. (2007). An Evolutionary Approach to Crowd Simulation. In: Mukhopadhyay, S.C., Gupta, G.S. (eds) Autonomous Robots and Agents. Studies in Computational Intelligence, vol 76. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73424-6_14
Download citation
DOI: https://doi.org/10.1007/978-3-540-73424-6_14
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-73423-9
Online ISBN: 978-3-540-73424-6
eBook Packages: EngineeringEngineering (R0)