• Journal of the Korean Institute of Intelligent Systems
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• v.8 no.6
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• pp.78-84
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• 1998

In this paper, a fuzzy traffic controller using genetic algorithms is presented. Conventional fuzzy traffic controllers use membership functions generated by humans. However, this approach does not guarantee the optimal solution to design the fuzzy controller. Genetic algorithm is a good problem solving method requiring domain-specific knowledge that is often heuristic. To find fuzzy membership functions showing good performance, a fitness function must be defined. However it's not easy in traffic control to define such a function as a numeric expression. Thus, we use simulation approach, namely, the fitness value of a solution is determined by use of a performance measure that is obtained by traffic simulator. The proposed method outperforms the conventional fuzzy controllers.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1996.10a
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• pp.180-183
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• 1996

This work discusses simulation results for the fuzzy logic controller tested the project“Fuzzy Ramp Metering Algorithm Implementation.”The performance objectives were, in order of priority, to maximize total vehicle-miles, maximize mainline speeds, and minimize delay per vehicle while maintaining an acceptable ramp queue. In the fuzzy logic controller, the sensors from the on-ramps were helpful in maintaining reasonable ramp queue and mainline congestion because it considered these factors simultaneously. Each metered ramp had a parameter input file, which allowed the controller to be modified without recompiling the software. Consequently, maintenance costs should be minimal.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.04a
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• pp.421-428
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• 2007

This paper discusses a fitness of the control on intersection network using fuzzy analytic hierachy process. The validity of control of traffic signal on intersection is phase, cycle of intersection. But the aigent of traffic intersection network is relative of intersection article. Therefor the aigent of traffic network intersection is before intersection passing vechile number, delayed vechile number. Fuzzy analytic hierachy process clears the grade of validity of the fixed cycle time controller and adaptive fixed cycle time and fuzzy traffic controller and proposes a new control type a traffic signal by this fuzzy analytic hierachy process.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.578-581
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• 2001

In this paper, the development of a new group controller for high-speed elevator is carried out utilizing approach of an adaptive dual fuzzy logic. A goals of control are the minimization of waiting time, mean-waiting time and long-waiting time in a building. when a new hall call is generated, adaptive dual fuzzy controller evaluate traffic pattern and change appropriately the membership function of fuzzy rule base. Control for co-operation among elevators in group control algorithm are essential, and the most critical control function in group controller is a effective and proper hall call assignment of elevators. Thy group elevator system utilizing adaptive dual fuzzy control reveals a great deal of improvement on its performance.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.11a
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• pp.157-160
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• 2000

In this paper, the development of a new group controller for high-speed elevator is carried out utilizing approach of an adaptive dual fuzzy logic. A goals of control are the minimization of waiting time, mean-waiting time and long-waiting time in a high building, when a new hall call is generated, adaptive dual fuzzy controller evaluate traffic pattern and change appropriately the membership function of fuzzy rule, base. Control for co-operation among elevators in group control algorithm are essential , and the most critical control function in group controller is a effective and proper hall call assignment of elevators. The group elevator system utilizing adaptive dual fuzzy control reveals a great deal of improvement on its performance.

• Journal of the Korean Society for Precision Engineering
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• v.18 no.4
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• pp.112-120
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• 2001

In this paper, the development of a new group controller for high-speed elevator is carried out utilizing the approach of an adaptive dual fuzzy logic. Some goals of control are the minimization of waiting time, mean-waiting time and long-waiting time in a high building, when a new hall call is generated, adaptive dual fuzzy controller evaluate traffic pattern and change appropriately the membership function of a fuzzy rule base. Controls for co-operation among elevators in a group control algorithm arte essential, and the most critical control function in the group controller is an effective and proper hall call assignment of elevators. The group elevator system utilizing adaptive dual fuzzy control reveals a great deal of improvement on its performance.

• Journal of Mechanical Science and Technology
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• v.15 no.12
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• pp.1664-1675
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• 2001

In this paper, the development of a new group controller for high-speed elevators is described utilizing the approach of adaptive dual fuzzy logic. Some goals of the control are to minimize the waiting time, mean-waiting time and long-waiting time in a building. When a new hall call is generated, all adaptive dual fuzzy controller evaluates the traffic patterns and changes the membership function of a fuzzy rule base appropriately. A control algorithm is essential to control the cooperation of multiple elevators in a group and the most critical control function in the group controller is an effective and proper hall call assignment of the elevators. The group elevator system utilizing adaptive dual fuzzy control clearly performs more effectively than previous group controllers.

• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.6
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• pp.584-590
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• 2000

Urban traffic situations are extremely complex and highly interactive. The multi-agent systems approach can provide a new desirable solution. Currently, a traffic simulator is needed to understand and explore the difficulties in an agent-oriented traffic control. This paper presents an agent-oriented fuzzy logic controller for multiple crossroads simulation. A fuzzy logic control simulation with variables of arrival, queue, and traffic volume could alleviate traffic congestion. We developed an agent-oriented simulator suitable for traffic junctions with η$\times$η intersections in Visual C++. The proposed method adaptively controls the cycle of traffic signals even though the traffic volume varies. The effectiveness of this method was shown through simulation of multiple intersections.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.3
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• pp.193-201
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• 2002

For measuring a traffic symbolic confusion Quantity and symbolic air pleasantness, we use fuzzy sensor algorithm maded by symbolic information Quantity. Hut for implementation of fuzzy sensor, we use some symbolic information item, this method cannot produce precise output because we use vague fuzzy rule method and we cannot abundance fuzzy for precision of fuzzy rule method. For this reason, this paper introduce new fuzzy sensor algorithm composed of not fuzzy rule method but using Analytic Hierachy Process. To prove that new method is good, two type of fuzzy sensor applied to traffic signal controller and through much passing vehicle, two fuzzy sensor compared each other.

• Journal of Korean Society of Transportation
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• v.29 no.6
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• pp.129-136
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• 2011

Variable Message Signs have been used for providing information on the current traffic conditions. However, it is considered more important to achieve optimal traffic allocation among the alternative routes by strategic VMS information provision. Fuzzy control is very effective and efficient to deal with such systems that are too complex and uncertain to build mathematical models. In this paper, a fuzzy feedback controller for VMS is proposed, whose goal is to achieve the travel time equilibrium between the two alternative routes. The performance of the suggested controller is implemented and examined using MATLAB/Simulink. More robust controller applicable to a real highway network is suggested for the further research.