Self-organizing control of urban traffic signal network

Sekiyama, Kosuke; Nakanishi, Jun; Takagawa, I.; Higashi, Takanobu; Fukuda, Toshio

doi:10.1109/icsmc.2001.972930

Cited by 31 publications

(20 citation statements)

References 5 publications

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“…Third, we develop traffic signal control system by adopting decentralized control strategy of the cycle time and the split setting of the signals. So the desired offset patterns are self-organized through mutual entrainment based on local traffic demand to achieve efficient traffic flow reducing the cost of the "stop-and-go" at signals [7]. Finally, visualization of simulation demonstrates the effectiveness proposed method under unstructured condition like in Indonesia.…”

Section: Introductionmentioning

confidence: 91%

Self-Organizing Urban Traffic Control Architecture With Swarm-Self Organizing Map in Jakarta: Signal Control System and Simulator

Jatmiko

Azurat

Herry

et al. 2010

International Journal on Smart Sensing and Intelligent Systems

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Abstract-Urban traffic control is the main factor that contributes to traffic jam. Approach in distributed Urban traffic control has been developed in several research, but the coordinating controller factor is basically a quite complicated task to tackle, because between intersection have dependency, so required a method of distributed control system capable for synchronizing between intersections. In this paper we present architecture of decentralized self-organizing traffic control with swarm-self organizing map in real situation even on non-structure intersections like in Jakarta (Indonesia). Based on the proposed architecture we have been implemented Traffic Signal Control System for controlling traffic lights in which the coordination between the intersections is implemented using distributed swarm self-organizing map. Traffic Signal Control System were tested in a simulated real-road scenario of Jakarta. By means of the computer simulation, the application of distributed swarm signal self-organizing control is proved effective in urban traffic.

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Section: Introductionmentioning

confidence: 91%

Self-Organizing Urban Traffic Control Architecture With Swarm-Self Organizing Map in Jakarta: Signal Control System and Simulator

Jatmiko

Azurat

Herry

et al. 2010

International Journal on Smart Sensing and Intelligent Systems

Self Cite

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“…In addition, some researchers were interested in forecasting the urban traffic using a wide range of methods, such as ARIMA [12], generalized linear models, and neural networks [13]. Interestingly, Smith et al [14] in a resemblance of historical norm, nonparametric regression, time series, and neural network models discover that the nonparametric regression model meaningfully exceed in performance comparing to the other models [15].…”

Section: Literature Reviewmentioning

confidence: 99%

Modeling and Simulation of Urban Traffic Signals

Salimifard¹,

Ansari²

2013

IJMO

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Abstract-Traffic signals play a vital role in effective traffic management. In this paper we apply Arena simulation tool box for modeling and simulation of urban traffic signal system. It has been shown that Arena could be used in simulation of traffic signals system, despite the fact that Arena is not designed for modeling urban traffic signal control. We presented a non-trivial case study to illustrate how Arena is capable of modeling traffic systems.

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“…This form of coupling appears in various studies of coupled oscillators and their application, e.g., [5], [10], [11], [12], [13], [14]. Specifically, we employ the formulation in [10] to coordinate the desired phase relationship.…”

Section: ) Inter-and Intra-limb Phase Coordinationmentioning

confidence: 99%

An empirical exploration of phase resetting for robust biped locomotion with dynamical movement primitives

Nakanishi¹,

Morimoto²,

Endo³

et al.

2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (IEEE Cat. No.04CH37566)

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Abstract-We propose a framework for learning biped locomotion using dynamical movement primitives based on nonlinear oscillators. In our previous work, we suggested dynamical movement primitives as a central pattern generator (CPG) to learn biped locomotion from demonstration. We introduced an adaptation algorithm for the frequency of the oscillators based on phase resetting at the instance of heel strike and entrainment between the phase oscillator and mechanical system using feedback from the environment.In this paper, we empirically explore the role of phase resetting in the proposed algorithm for robust biped locomotion. We demonstrate that phase resetting contributes to robustness against external perturbations and environmental changes by numerical simulations and experiments with a physical biped robot.

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Self-organizing control of urban traffic signal network

Cited by 31 publications

References 5 publications

Self-Organizing Urban Traffic Control Architecture With Swarm-Self Organizing Map in Jakarta: Signal Control System and Simulator

Self-Organizing Urban Traffic Control Architecture With Swarm-Self Organizing Map in Jakarta: Signal Control System and Simulator

Modeling and Simulation of Urban Traffic Signals

An empirical exploration of phase resetting for robust biped locomotion with dynamical movement primitives

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