• 한국지능시스템학회논문지
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• 제13권6호
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• pp.722-728
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• 2003

In this paper, we propose a fuzzy traffic controller of Sugeno`s fuzzy model so as to model the nonlinear characteristics of controlling the traffic light. It use a degree of the traffic congestion of the preceding roads as an input so that it can cope with traffic congestion appropriately, which causes the loss of fuel and our discomfort. First, in order to construct fuzzy traffic controller of Sugeno`s fuzzy model, we model the control process of the traffic light by using Mamdani`s fuzzy model, which has the uniform membership functions of the same size and shape. Second, we make Mamdani`s fuzzy model with the non-uniform membership functions so that it can exactly reflect the knowledge of experts and operators. Last, we construct the fuzzy traffic controller of Sugeno`s fuzzy model by learning from the input/output data, which is retrieved from Mamdani`s fuzzy model with the non-uniform membership functions. We compared and analyzed the fixed traffic light controller, the fuzzy traffic controller of Mamdani`s fuzzy model and the fuzzy traffic controller of Sugeno`s fuzzy model by using the delay time and the proportion of the entered vehicles to the occurred vehicles. As a result of comparison, the fuzzy traffic controller of Sugeno`s fuzzy model showed the best performance.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제1권1호
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• pp.1-5
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• 2001

In this paper, we propose a fuzzy traffic controller that is able to cope with traffic congestion appropriately. In order to consider such situation as loss of green time caused by spillback of upper crossroad, it imports a degree of traffic congestion of upper roads which vehicles on a crossroad are to proceed to. We constructed the equal-partitioned fuzzy traffic controller that uses the membership functions of the same size and shape, and modified the size and shape, and modified the size and shape of its membership functions by the membership function modification algorithm. In experiment, we compared and analyzed the fixed signal controller, the fuzzy traffic controller with the membership of the same size and shape, and the modified fuzzy traffic controller by using the delay time, the proportion of entered vehicles to occurred vehicles and the proportion of passed vehicles to entered vehicles. As a result of experiment, the modified fuzzy controller showed more enhanced performance than others.

• 대한교통학회지
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• 제14권2호
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• pp.89-118
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• 1996

The development and implementation of a real-time, traffic adaptive control scheme based on fuzzy logic through Video Image Detector systems (VIDs) is presented. Through VIDs based image processing, fuzzy logic can be used for a real-time traffic adaptive signal control scheme. Fuzzy control logic allows linguistic and inexact traffic data to be manipulated as a useful tool in designing signal timing plans. The fuzzy logic has the ability to comprehend linguistic instructions and to generate control strategy based on a priori verbal communication. The implementation of fuzzy logic controller for a traffic network is introduced. Comparisons are made between implementations of the fuzzy logic controller and the actuated controller in an isolated intersection. The results obtained from the application of the fuzzy logic controller are also compared with those corresponding to a pretimed controller for the coordinated intersections. Simulation results from the comparisons indicate the performance of the system is between under the fuzzy logic controller. Integration of the aforementioned schemes into and ATMS framework will lead to real-time adjustment of the traffic control signals, resulting in significant reduction in traffic congestion.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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• pp.664-667
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• 2003

We propose a frizzy traffic controller of Sugeno's fuzzy model so as to model the nonlinear characteristics of controlling the traffic light. It uses a degree of the traffic congestion of the preceding roads as an input so that it can cope with traffic congestion appropriately, which causes the loss of fuel and our discomfort. In order to construct fuzzy traffic controller of Sugeno's fuzzy model we first model the control process of the traffic light by using Mamdani's fuzzy model, which has the uniform membership functions of the same size and shape. Next we make Mamdani's fuzzy model with the non-uniform membership functions so that it can exactly reflect the knowledge of experts and operators. Lastly, we construct the fuzzy traffic controller of Sugeno's fuzzy model by learning from the input/output data, which is retrieved from Mamdani's fuzzy model with the non-uniform membership functions. We compared and analyzed the service level of the traffic light controllers by using the delay time. As a result of comparison, the fuzzy traffic controller of Sugeno's fuzzy model shows the best service level of them.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1997년도 하계학술대회 논문집 B
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• pp.735-738
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• 1997

The traffic congestion caused by the exploding increase of vehicles became one of the severest social problems. Among the various approaches to solve this problem, controlling the length of traffic signals appropriately according to the individual traffic situation would be the most plausible and cost-effective method. To design a traffic signal controller which has such a property as adaptive decision-making process, we adopt fuzzy logic control method(fuzzy traffic signal controller), Moreover, using genetic algorithms we obtain an optimized fuzzy traffic signal controller (GA-fuzzy traffic signal controller). To evaluate and validate the proposed fuzzy and GA-fuzzy traffic signal controller, simulation results are presented.

• 전자공학회논문지B
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• 제30B권6호
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• pp.100-108
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• 1993

In this paper, noticing the point of human's ability which appropriately cope with vague conditions, we design fuzzy traffic signal light controller similar to human's distinction ability and decide the optimum cycle most suited to any traffic junction using fuzzy identification algorithm. In this study, for the control output decision process we design fuzzy controller better than electronic vehicle actuated controller in performance. We propose the cycle decision method which is not limited by the variance of traffic junction vehicle number through overcoming the limit of Webster's method which is adopted by the fixed cycle controller. Simulated experimental results show that fuzzy controller and fuzzy identification algorithm are better than the existing electronic vehicle actuated controller and fixed cycle controller in delay time per vehicle.

• 한국산학기술학회논문지
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• 제9권6호
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• pp.1592-1598
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• 2008

기존의 교통신호기의 방법은 고정신호제어기이다. 즉, 교통대안을 한 가지씩 채택하여 24시간 내내 이미 결정한 교통신호대안에 의존하여 주기 싸이클을 결정하는 방법이다. 교통신호 운영자가 교통대안을 잘못 입력하여 설정하게 되면 교차로내에서 잘못된 교통대안으로 인해 교통지체가 빈번하게 일어남을 알 수 있다. 교통대안은 눈으로 보아 설정하는 것이 아니고 유력한 교통대안을 서로 비교하여 가장 영향력 있는 교통대안을 설정하는 것이 교통신호제어에 유효하다. 본 논문에서는 고정신호제어기를 사용하여 제어기에 맞는 교통대안을 찾는 방법을 퍼지계층분석방법을 이용하여 찾는 방법을 모색하고 기존제어기와 비교 검토한다.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1993년도 Fifth International Fuzzy Systems Association World Congress 93
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• pp.907-910
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• 1993

This paper describes the use of fuzzy control and decision making to simulate the control of traffic flow at an intersection. To show the value of fuzzy logic as an alternative method for control of traffic environments. A traffic environment includes the lanes to and from an intersection, the intersection, vehicle traffic, and signal lights in the intersection. To test the fuzzy logic controller, a computer simulation was constructed to model a traffic environment. A typical cross intersection was chosen for the traffic environment, and the performance of the fuzzy logic controller was compared with the performance of two different types of conventional control. In the hardware verifications, fuzzy logic was used to control acceleration of a model train on a circular path. For the software experiment, the fuzzy logic controller proved better than conventional control methods, especially in the case of highly uneven traffic flow between different directions. On the hardware si e of the research, the fuzzy acceleration control system showed a marked improvement in smoothness of ride over crisp control.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.364-364
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• 2000

Timed Petri Net(TPN) is one of methods to model and to analyze Discrete Event Dynamic Systems(DEDSs) with real time values. It has two time values, earliest firing time ($\alpha$$_{i}$) and latest firing time ($\beta$$_{I}$) for the each transition. A transition of TPN is fired at arbitrary time of time interval ($\alpha$$_{I}$, $\beta$$_{i}$). Uncertainty of firing time gives difficulty to analyze and estimate a modeled system. In this paper, we proposed the Fuzzy Transition Timed Petri Net(FTTPN) with fuzzy theory to determine the optimal transition time (${\gamma}$$_{i}$). The transition firing time (${\gamma}$$_{i}$) of FTTPN is determined from fuzzy controller which is modeled with information of state transition. Each of the traffic signal controllers are modeled using the proposed method and timed petri net. And its Performance is evaluated by simulation of traffic signal controller. controller.

• 대한교통학회지
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• 제14권1호
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• pp.117-133
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• 1996

본 논문에서는 모호한 상황에서도 적절하게 대처하는 인간의 판단능력과 유사한 퍼지논리를 이용, 교차로 교통신호등의 최적현시를 결정하는 제어기를 구현하여 기존의 차량감응식 제어기(Vehicle Actuated Controller)와 고정주기식 제어기(Fixed Cycle Time) 및 그외의 구현 가능성 있는 제어기와 비교하여 성능이 우수한 알고리즘을 제시한다. 각 현시단계의 주기시간을 결정함에 있어 기존의 방식인 웹스터(Webster)식을 이용하는 방법보다는 상황에 맞는 현시순서를 퍼지 논리 알고리즘을 통해 선정하고, 불확실한 교통량변화에 적절하게 대응하는 퍼지최적주기시간을 결정하여 구성한 퍼지 최적현시제어기가 비교제어기에 비해 교통소통에 우수함을 보여주었다.