JACIII Vol.15 No.2 pp. 220-225
doi: 10.20965/jaciii.2011.p0220


Risk Evaluation by Human Trajectory Simulation Based on Real Data

Kiyoshi Izumi*, Yoshifumi Nishida**, and Yoichi Motomura**

*School of Engineering, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan, PRESTO, JST, Japan

**Digital Human Research Center, National Institute of Advanced Industrial Science and Technology, 2-3-26 Aomi, Koto-ku, Tokyo 135-0064, Japan, CREST, JST, Japan

August 3, 2010
December 31, 2010
March 20, 2011
agent-based simulation, moving data analysis, sensing, movement model, accident prevention
This paper proposes a new approach integrating the modeling of moving persons from sensor data and agent-based simulation for indoor layout design viewed from preventing children’s accidents. Our model focuses on interaction between indoor objects and children to estimate the risk of indoor accidents. We discuss the agent-based simulation of multiple persons moving in public spaces and its application to evaluating information presentation for guidance.
Cite this article as:
K. Izumi, Y. Nishida, and Y. Motomura, “Risk Evaluation by Human Trajectory Simulation Based on Real Data,” J. Adv. Comput. Intell. Intell. Inform., Vol.15 No.2, pp. 220-225, 2011.
Data files:
  1. [1] The Ministry of Health, Labour and Welfare, “Population Survey Report 2005,” The Ministry of Health, Labour and Welfare, 2006.
  2. [2] Akita Prefecture, “Field survey of children’s accidents,” 2009. (in Japanese)
  3. [3] D. Helbing, I. Farkas, and T. Vicsek, “Simulating dynamical features of escape panic,” Nature, Vol.407, pp. 487-490, 2000.
  4. [4] T. Yoshida and T. Kaneda, “A Simulation Analysis of Shop-around Behavior in a Commercial District as an Intelligent Agent Approach,” In Agent-based Approaches in Economic and Social Complex Systems V, pp. 131-142, Springer, 2009.
  5. [5] D. Helbing and P. Molnar, “Social force model for pedestrian dynamics,” Phys. Rev. E, Vol.51, No.5, pp. 4282-4286, 1995.
  6. [6] Y. Susumu, “Jinko Shakai Kouchiku Shinan,” Shoseki Koubou Hayama, 2007. (in Japanese)
  7. [7] Y. Nishida, H. Aizawa, T. Hori, N. Hoffman, T. Kanade, and M. Kakikura, “3D Ultrasonic Tagging System for Observing Human Activity,” In Proc. of IEEE Int. Conf. on Intelligent Robots and Systems (IROS2003), pp. 785-791, 2003.
  8. [8] Y. Nishida, K. Kitamura, Y. Motomura, A. Simo, and T. Yamanaka, “Infant Behavior Simulation: Computational Approach to Infant Safety,” In Proc. of the 4th IARP/IEEE-RAS/EURON Workshop on Technical Challenges for Dependable Robots in Human Environments, T16-01, 2005.
  9. [9] M. Vlachos, D. Gunopoulos, and G. Kollios, “Discovering Similar Multidimensional Trajectories,” In Proc. of the 18th Int. Conf. on Data Engineering, ICDE ’02, pp. 673-684, IEEE Computer Society, 2002.
  10. [10] R. Shoda, T. Matsuda, T. Yoshida, H. Motoda, and T. Washio, “Graph Clustering with Structure Similarity,” In Proc. of the 17th Annual Conf. of the Japanese Society for Artificial Intelligence, 2003. (in Japanese)
  11. [11] Y. Nishida and Y. Motomura, “Ningen no Keisann ron ni motodsuku digital human contents,” In Proc. of the 1st digital contents symposium, S2-5(1)-(6), 2005. (in Japanese)
  12. [12] K. Kitamura, Y. Nishida, M. Matsumoto, Y. Motomura, T. Yamanaka, and H. Mizoguchi, “Development of Infant Behavior Simulator: Modeling Grasping Achievement Behavior Based on Developmental Behavior Model and Environmental Interest Induction Model,” J. of Robotics and Mechatronics, Vol.17, No.6, pp. 705-716, 2005.

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Last updated on Jun. 18, 2024