Artificial Societies and GPU-Based Cloud Computing for Intelligent Transportation Management

The article focuses on the C part of the ACP approach. The ACP approach comprises of artificial societies, computational experiments, and parallel execution of real and artificial systems. It explains the advantages of cloud computing and GPUs and presents the architectures of GPU-based cloud computing for transportation systems.

[1]  Javier J. Sanchez-Medina,et al.  Traffic Signal Optimization in “La Almozara” District in Saragossa Under Congestion Conditions, Using Genetic Algorithms, Traffic Microsimulation, and Cluster Computing , 2010, IEEE Transactions on Intelligent Transportation Systems.

[2]  Bo Chen,et al.  A Review of the Applications of Agent Technology in Traffic and Transportation Systems , 2010, IEEE Transactions on Intelligent Transportation Systems.

[3]  Kai Nagel,et al.  Using common graphics hardware for multi-agent traffic simulation with CUDA , 2009, SimuTools.

[4]  N. Gilbert,et al.  Artificial Societies: The Computer Simulation of Social Life , 1995 .

[5]  Wang Feiyue,et al.  From Artificial Life to Artificial Societies——New Methods for Studies of Complex Social Systems , 2004 .

[6]  Fei-Yue Wang,et al.  Parallel Control and Management for Intelligent Transportation Systems: Concepts, Architectures, and Applications , 2010, IEEE Transactions on Intelligent Transportation Systems.

[7]  Yong Yuan,et al.  Artificial Societies, Computational Experiments, and Parallel Systems: An Investigation on a Computational Theory for Complex Socioeconomic Systems , 2013, IEEE Transactions on Services Computing.

[8]  Moshe Sipper.  Studying artificial life using a simple, general cellular model , 1995 .

[9]  Kai Wang,et al.  Cloud Computing for Agent-Based Urban Transportation Systems , 2011, IEEE Intelligent Systems.

[10]  Javier J. Sánchez Medina,et al.  Traffic Signal Optimization in "La Almozara" District in Saragossa Under Congestion Conditions, Using Genetic Algorithms, Traffic Microsimulation, and Cluster Computing , 2010, IEEE Trans. Intell. Transp. Syst..

[11]  Wang Feiyue,et al.  Parallel system methods for management and control of complex systems , 2004 .