• International Journal of Fuzzy Logic and Intelligent Systems
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• v.1 no.1
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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.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.41 no.10
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• pp.69-77
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• 2004

In this thesis, we created a Fuzzy rule in a Fuzzy logic that are fuzzy logic which is composed of linguistic rules and Fuzzy inference engine for effective traffic control in ATM networks. The parameters of the Fuzzy rules are adapted to minimize the given performance index in both cases. In other words, the difuzzification value controls the service rate in the server to total traffic arrival ratio and buffer occupancy ratio using fuzzy set theory for traffic connected after reasoning. Also, show experiment result about rule by MATLAB6.5 and on-line bulid-up to verify validity of created Fuzzy rule. As a result, we can verify that service ratio in server is efficiently controlled by the total traffic arrival ratio and buffer occupancy ratio.

• Journal of the Korea Computer Industry Society
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• v.3 no.1
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• pp.95-104
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• 2002

This paper presents some studies on the Internet TCP/IP(Transmission Control Protocol-Internet Protocol) traffic over ATM(Asynchronous Transfer Mode) UBR(Unspecified Bit Rate) and ABR(Available Bit Rate) classes of service. Fuzzy logic prediction has been used to improve the efficiency and fairness of traffic throughput. For TCP/IP over UBR, a novel fuzzy logic based cell dropping scheme is presented. This is referred to as fuzzy logic selective cell drop (FSCD). A key feature of the scheme is its ability to accept or drop a new incoming packet dynamically based on the predicted future buffer condition in the switch. This is achieved by using fuzzy logic prediction for the production of a drop factor. Packet dropping decision is then based on this drop factor and a predefined threshold value. Simulation results show that the proposed scheme significantly improves TCP/IP efficiency and fairness. To study TCP/IP over ABR, we applied the fuzzy logic ABR service buffer management scheme from our previous work to both approximate and exact fair rate computation ER(Explicit cell Rate) switch algorithms. We then compared the performance of the fuzzy logic control with conventional schemes. Simulation results show that on zero TCP packet loss, the fuzzy logic control scheme achieves maximum efficiency and perfect fairness with a smaller buffer size. When mixed with VBR traffic, the fuzzy logic control scheme achieves higher efficiency with lower cell loss.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.8C
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• pp.1149-1158
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• 2004

In this thesis, we created a Fuzzy rule in a Fuzzy logic that are Fuzzy logic which is composed of linguistic rules and Fuzzy inference engine for effective traffic control in ATM networks. The parameters of the Fuzzy rules are adapted to minimize the given performance index in both cases. In other words, the difuzzification value controls the threshold in the buffer to arrival ratio to traffic priority (low or high) using fuzzy set theory for traffic connected after reasoning. Also, show experiment result about rule by MATLAB6.5 and on-line bulid-up to verify validity of created Fuzzy rule. As a result, we can verify that threshold value in buffer is efficiently controlled by the traffic arrival ratio.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.5
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• pp.679-684
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• 2008

The slow port scan attack detection is the one of the important topics in the network security. We suggest an abnormal traffic control framework to detect slow port scan attacks using fuzzy rules. The abnormal traffic control framework acts as an intrusion prevention system to suspicious network traffic. It manages traffic with a stepwise policy: first decreasing network bandwidth and then discarding traffic. In this paper, we show that our abnormal traffic control framework effectively detects slow port scan attacks traffic using fuzzy rules and a stepwise policy.

• Proceedings of the KIEE Conference
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• 1997.07b
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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.

• The Transactions of the Korea Information Processing Society
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• v.6 no.4
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• pp.977-987
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• 1999

The current traffic signal control systems are operated depending on the pre-planned control scheme or the selected control scheme according to a period of time. The problem with these types of traffic control systems is that they can not cope with variant traffic flows appropriately. Such a problem can be difficult to solve by using binary logic. Therefore, in this 0paper, we propose a traffic signal control system which can deal wit various traffic flows quickly and effectively. The proposed controller is operated under uncertainty and in a fuzzy environment. It show the congestion of road traffic by using fuzzy logic, and it determines the length of green signal by means of a fuzzy inference engine. It modeled using petri-net to verify its validation.

• The Transactions of the Korea Information Processing Society
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• v.4 no.1
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• pp.167-176
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• 1997

Due to continuous change in traffic and increase in traffic volumes at the intersection, efficient traffic control system is required to manage road situations flexibly in accordance with the change occurring every hour. In this paper, we study the control systems which will help us to determine the interva ls of intersection following the autonomous analysis of complexity of the road. Fuzzy logic control concept was applied to the fuzzy logic controller(FLC) for controlling traffic signal. Furthermore the fuzzy signal systems were compare with the regular signal systems to prove higher performance of the FLC presente d in the paper. By means of simulation, the validity of FLC was proven. About 6% increase in the efficiency of traffic control based on the proposed algorithm in this paper was when we use the simulation.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.3 no.1
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• pp.66-71
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• 2003

In the past, when there were few vehicles on the road, the T.O.D.(Time of Day) traffic signal worked very well. The T.O.D. signal operates on a preset signal cycling which cycles on the basis of the average number of average passenger cars in the memory device of an electric signal unit. Today, with increasing traffic and congested roads, the conventional traffic light creates startup-delay time and end lag time so that thirty to forty-five percent efficiency in traffic handling is lost, as well as adding to fuel costs. To solve this problem, this paper proposes a new concept of optimal green time algorithm, which reduces average vehicle waiting time while improving average vehicle speed using fuzzy rules and neural networks. Through computer simulation, this method has been proven to be much more efficient than fixed time interval signals. Fuzzy Neural Network will consistanly improve average waiting time, vehicle speed, and fuel consumption.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.3 no.1
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• pp.105-111
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• 2003

This paper is researching the storing of 40 different kinds of conditions. Such as, car speed, delay in starting time and the volume of cars in traffic. Through the use of a central nervous networking system or AI, using 10 different intersecting roads. We will improve the green traffic light. And allow more cars to easily flow through the intersections. Now days, with increasing many vehicles on restricted roads, the conventional traffic light creates prove startup-delay time and end-lag-time. The conventional traffic light loses the function of optimal cycle. And so, 30-45% of conventional traffic cycle is not matched to the present traffic cycle. In this paper proposes electro sensitive traffic light using fuzzy look up table method which will reduce the average vehicle waiting time and improve average vehicle speed. Computer simulation results prove that reducing the average vehicle waiting time which proposed considering passing vehicle length for optimal traffic cycle is better than fixed signal method which dosen't consider vehicle length.