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Issue No.04 - July/August (2011 vol.26)
pp: 22-28
Kai Wang , National University of Defense Technology and Chinese Academy of Sciences
Zhen Shen , Chinese Academy of Sciences
<p>It is challenging to establish accurate mathematical models for complex systems, and experiments on them are generally costly or even impossible, making it difficult to analyze, control, and manage them. The ACP approach provides a way to attack this difficulty. However, with the agent technologies for the A (artificial societies) part, the burdens from computing agent behaviors and the algorithms' evaluating process are usually very heavy. Fortunately, computing hardware is going through a revolution with the development of graphics processing units (GPUs). A single GPU can provide numerous threads running together and is suitable for parallel computing. This article focuses on the C (computational experiments) part of the ACP approach. It explains the advantages of cloud computing and GPUs and presents the architectures of the GPU-based cloud computing for the transportation systems.</p>
Intelligent transportation systems, intelligent systems, GPU, NVIDIA, artificial societies, artificial transportation systems
Kai Wang, Zhen Shen, "Artificial Societies and GPU-Based Cloud Computing for Intelligent Transportation Management", IEEE Intelligent Systems, vol.26, no. 4, pp. 22-28, July/August 2011, doi:10.1109/MIS.2011.65
1. F.-Y. Wang, "Parallel Control and Management for Intelligent Transpor-tation Systems: Concepts, Architectures, and Applications," IEEE Trans. Intelligent Transportation Systems, vol. 11, no. 3, 2010, pp. 630–638.
2. F.-Y. Wang, "Artificial Societies, Computational Experiments, and Parallel Systems: An Investigation on Computational Theory of Complex Social Economic Systems," Complex Systems and Complexity Science, vol. 1, no. 4, 2004, pp. 25–35.
3. F.-Y. Wang, "Parallel System Methods for Management and Control of Complex Systems," Control and Decision, vol. 19, no. 5, 2004, pp. 485–489.
4. F.-Y. Wang and J.S. Lansing, "From Artificial Life to Artificial Societies—New Methods for Studies of Complex Social Systems," Complex Systems and Complexity Science, vol. 1, no. 1, 2004, pp. 33–41.
5. N. Gilbert and R. Conte, Artificial Societies: The Computer Simulation of Social Life, UCL Press, 1995.
6. M. Sipper, "Studying Artificial Life Using a Simple, General Cellular Model," Artificial Life, vol. 2, no. 1, 1994, pp. 1–35.
7. B. Chen and H.H. Chen, "A Review of the Applications of Agent Technologies in Traffic and Transportation Systems," IEEE Trans. Intelligent Transportation Systems, vol. 11, no. 2, 2010, pp. 485–497.
8. Z.-J. Li, C. Chen, and K. Wang, "Cloud Computing for Agent-Based Urban Transportation Systems," IEEE Intelligent Systems, vol. 26, no. 1, 2011, pp. 73–79.
9. J.J. Sánchez-Medina, M.J. Galán-Moreno, and E. Rubio-Royo, "Traffic Signal Optimization in 'La Almozara' District in Saragossa under Congestion Conditions, Using Genetic Algorithms, Traffic Microsimulation, and Cluster Computing," IEEE Trans. Intelligent Transpor-tation Systems, vol. 11, no. 1, 2010, pp. 132–141.
10. D. Strippgen and K. Nagel, "Using Common Graphics Hardware for Multi-agent Traffic Simulation with CUDA," Proc. 2nd Int'l Conf. Simulation Tools and Techniques, Brussels, 2009, pp. 1–8.
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