An Open Framework for Developing, Evaluating, and Sharing Steering Algorithms

  • Shawn Singh
  • Mubbasir Kapadia
  • Petros Faloutsos
  • Glenn Reinman
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5884)


There are very few software frameworks for steering behaviors that are publicly available for developing, evaluating, and sharing steering algorithms. Furthermore, there is no widely accepted methodology for how to evaluate results of agent steering simulations. This situation makes it difficult to identify the real underlying challenges in agent simulations and future research directions to advance the state of the art. With the hope of encouraging community participation to address these issues, we have released SteerSuite, a flexible but easy-to-use set of tools, libraries, and test cases for steering behaviors. The software includes enhanced test cases, an improved version of SteerBench, a modular simulation engine, a novel steering algorithm, and more. Care has been taken to make SteerSuite practical and easy-to-use, yet flexible and forward-looking, to challenge researchers and developers to advance the state of the art in steering.


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  1. 1.
    Singh, S., Kapadia, M., Naik, M., Reinman, G., Faloutsos, P.: SteerBench: A Steering Framework for Evaluating Steering Behaviors. Computer Animation and Virtual Worlds (2009)Google Scholar
  2. 2.
    Kapadia, M., Singh, S., Allen, B., Reinman, G., Faloutsos, P.: SteerBug: An Interactive Framework for Specifying and Detecting Steering Behaviors. In: ACM Siggraph/Eurographics Symposium on Computer Animation, SCA (2009)Google Scholar
  3. 3.
    Kapadia, M., Singh, S., Hewlett, W., Faloutsos, P.: Egocentric affordance fields in pedestrian steering. In: I3D 2009: Proceedings of the 2009 symposium on Interactive 3D graphics and games 2009, pp. 215–223 (2009)Google Scholar
  4. 4.
    Singh, S., Kapadia, M., Reinman, G., Faloutsos, P.: Steersuite,
  5. 5.
  6. 6.
    Hart, P.E., Nilsson, N.J., Raphael, B.: A formal basis for the heuristic determination of minimum cost paths. IEEE Transactions on Systems Science and Cybernetics 4(2), 100–107 (1968)CrossRefGoogle Scholar
  7. 7.
    Paris, S., Pettre, J., Donikian, S.: Pedestrian reactive navigation for crowd simulation: a predictive approach. In: EUROGRAPHICS 2007, pp. 665–674 (2007)Google Scholar
  8. 8.
    Shao, W., Terzopoulos, D.: Autonomous pedestrians. In: SCA 2005: Proc. of the 2005 ACM SIGGRAPH/Eurographics symp. on Computer animation, pp. 19–28 (2005)Google Scholar
  9. 9.
    Brogan, D.C., Hodgins, J.K.: Group behaviors for systems with significant dynamics. Auton. Robots 4(1), 137–153 (1997)CrossRefGoogle Scholar
  10. 10.
    Goldenstein, S., et al.: Scalable nonlinear dynamical systems for agent steering and crowd simulation. Computers and Graphics 25(6), 983–998 (2001)CrossRefGoogle Scholar
  11. 11.
    Treuille, A., Cooper, S., Popović, Z.: Continuum crowds. In: SIGGRAPH 2006: ACM SIGGRAPH 2006 Papers, pp. 1160–1168 (2006)Google Scholar
  12. 12.
    Helbing, D., Farkas, I., Vicsek, T.: Simulating dynamical features of escape panic. Nature 407, 487 (2000)CrossRefGoogle Scholar
  13. 13.
    Lamarche, F., Donikian, S.: Crowd of virtual humans: a new approach for real time navigation in complex and structured environments. Computer Graphics Forum 23, 509–518 (2004)CrossRefGoogle Scholar
  14. 14.
    Loscos, C., Marchal, D., Meyer, A.: Intuitive crowd behaviour in dense urban environments using local laws. In: TPCG 2003: Proceedings of the Theory and Practice of Computer Graphics 2003, p. 122. IEEE Computer Society, Los Alamitos (2003)CrossRefGoogle Scholar
  15. 15.
    Reynolds, C.: Steering behaviors for autonomous characters. In: Game Developers Conference (1999)Google Scholar
  16. 16.
    Rudomín, I., Millán, E., Hernández, B.: Fragment shaders for agent animation using finite state machines. Simulation Modelling Practice and Theory 13(8), 741–751 (2005)CrossRefGoogle Scholar
  17. 17.
    Pelechano, N., Allbeck, J.M., Badler, N.I.: Controlling individual agents in high-density crowd simulation. In: SCA 2007: Proceedings of the 2007 ACM SIGGRAPH/Eurographics symposium on Computer animation, pp. 99–108 (2007)Google Scholar
  18. 18.
    Boulic, R.: Relaxed steering towards oriented region goals. In: Egges, A., Kamphuis, A., Overmars, M. (eds.) MIG 2008. LNCS, vol. 5277, pp. 176–187. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  19. 19.
    Metoyer, R.A., Hodgins, J.K.: Reactive pedestrian path following from examples. The Visual Computer 20(10), 635–649 (2004)CrossRefGoogle Scholar
  20. 20.
    Sud, A., Gayle, R., Andersen, E., Guy, S., Lin, M., Manocha, D.: Real-time navigation of independent agents using adaptive roadmaps. In: VRST 2007: Proceedings of the 2007 ACM symposium on Virtual reality software and technology, pp. 99–106. ACM, New York (2007)CrossRefGoogle Scholar
  21. 21.
    van den Berg, J., Patil, S., Sewall, J., Manocha, D., Lin, M.: Interactive navigation of multiple agents in crowded environments. In: SI3D 2008: Proceedings of the 2008 symposium on Interactive 3D graphics and games, pp. 139–147 (2008)Google Scholar
  22. 22.
    Lee, K.H., Choi, M.G., Hong, Q., Lee, J.: Group behavior from video: a data-driven approach to crowd simulation. In: SCA 2007: Proceedings of the 2007 ACM SIGGRAPH/Eurographics symposium on Computer animation, pp. 109–118 (2007)Google Scholar
  23. 23.
    Lerner, A., Chrysanthou, Y., Lischinski, D.: Crowds by example. Computer Graphics Forum 26(3), 655–664 (2007)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Shawn Singh
    • 1
  • Mubbasir Kapadia
    • 1
  • Petros Faloutsos
    • 1
  • Glenn Reinman
    • 1
  1. 1.University of CaliforniaLos Angeles

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