JACIII Vol.15 No.2 pp. 233-239
doi: 10.20965/jaciii.2011.p0233


Massive Multiagent-Based Urban Traffic Simulation with Fine-Grained Behavior Models

Hiromitsu Hattori, Yuu Nakajima, and Shohei Yamane

Graduate School of Informatics, Kyoto University, Yoshida-Honmachi, Sakyo-ku, Kyoto 606-8021, Japan

August 9, 2010
December 31, 2010
March 20, 2011
multiagent-based simulation, traffic simulation, human behavior modeling

As it is getting easier to obtain reams of data on human behavior via ubiquitous devices, it is becoming obvious that we must work on two conflicting research directions for realizing multiagent-based social simulations; creating large-scale simulations and elaborating fine-scale human behavior models. The challenge in this paper is to achievemassively urban traffic simulations with fine-grained levels of driving behavior. Toward our objective, we show the design and implementation of a multiagent-based simulation platform, that enables us to execute massive but sophisticated multiagent traffic simulations. We show the capability of the developed platform to reproduce the urban traffic with a social experiment scenario. We investigate its potential to analyze the traffic from both macroscopic and microscopic viewpoints.

Cite this article as:
H. Hattori, Y. Nakajima, and S. Yamane, “Massive Multiagent-Based Urban Traffic Simulation with Fine-Grained Behavior Models,” J. Adv. Comput. Intell. Intell. Inform., Vol.15, No.2, pp. 233-239, 2011.
Data files:
  1. [1] J. Epsterin and R. Axtell, “Growing Artificial Societies: Social Science from the Bottom Up,” MIT Press, 1996.
  2. [2] D. Scerri, S. Hickmotthas, A. Drogoul, and L. Padgham, “An Architecture for Modular Distributed Simulation with Agent-Based Models,” Proc. of AAMAS-2010, pp. 541-548, 2010.
  3. [3] G. Yamamoto, H. Tai, and H. Mizuta, “A Platform for Massive Agent-based Simulation and its Evaluation,” Lecture Notes in Computer Science, Vol.5043, pp. 1-12, Springer, 2008.
  4. [4] Y. Murakami, Y. Sugimoto, and T. Ishida, “Modeling Human Behavior for Virtual Training Systems,” Proc. of AAAI-2005, pp. 127-132, 2005.
  5. [5] J. Illenberger, G. Flotterod, and K. Nagel, “Enhancing MATSim with Capabilities of Within-Day Re-Planning,” Proc. of the IEEE Intelligent Transportation Systems Conference, pp. 94-99, 2007.
  6. [6] J. Bhattacharya and R. Horiguchi, “Implementation of Transportation Management Strategies using AVENUE for developing countries,” Proc. of 7th Asia-Pacific ITS Folum, 2005.
  7. [7] N. Geroliminis and C. Daganzo, “Existence of Urban-scale Macroscopic Fundamental Diagrams: Some Experimental Findings,” J. of Transportation Research Part B: Methodological, Vol.42, No.9, pp. 759-770, 2008.
  8. [8] B. Raney and K. Nagel, “Iterative Route Planning for Large-scale Modular Transportation Simulations,” Future Generation Computer Systems, Vol.20, No.7, pp. 1101-1118, 2004.
  9. [9] H. Hattori, Y. Nakajima, and T. Ishida, “Learning from Humans: Agent Modeling with Individual Human Behaviors,” IEEE Trans. on Systems, Man, and Cybernetics-Part A: Systems and Humans, 2010.

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome, Firefox, Safari, Edge, IE9,10,11, Opera.

Last updated on Feb. 14, 2019