• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.8 no.6
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• pp.127-132
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• 2008

Traffic intersection control is implemented by the data which is acquired to vechile loop detector. Traffic intersection control equation is Webster equation. which use passig and delayed vechile number. But webster equation is applied to the spot traffic intersection, it is not used to related traffic intersection network system. There is not the approprate remote traffic intersection control, even if there is, it is high cost local network system. Therefore low cost and expert traffic intersection control is realized by internet referencing next and distant intersection traffic information.

• Proceedings of the KAIS Fall Conference
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• 2008.05a
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• pp.245-247
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• 2008

Traffic intersection conrol is implemented by the data which is acquired to vechile Loop detector. Traffic intersection control equation is Webster equation, which use passing and delayed vechile number. But webster equation is applied to the spot traffic intersection, it is not used to related traffic intersection network system. There is not the approprate remote traffic intersection control, even if there is, it is high cost local network system. Therefore low cost and expert traffic intersection control is realized by internet referencing next and distant intersection traffic information.

• 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 Institute of Intelligent Systems Conference
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• 1993.06a
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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.

• International Journal of Control, Automation, and Systems
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• v.5 no.2
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• pp.200-207
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• 2007

The passive direction finding cross localization method is widely adopted in passive tracking, therefore there will exist masses of false intersection points. Eliminating these false intersection points correctly and quickly is a key technique in passive localization. A new method is proposed for passive locating and tracking multi-jammer target in this paper. It not only solves the difficulty of determining the number of targets when masses of false intersection points existing, but also solves the initialization problem of elastic network. Thus this method solves the problem of multi-jammer target correlation and the elimination of static false intersection points. The method which dynamically establishes multiple hypothesis trajectory trees solves the problem of eliminating the remaining false intersection points. Simulation results show that computational burden of the method is lower, the elastic network can more quickly find all or most of the targets and have a more probability of locking the real targets. This method can eliminate more false intersection points.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.1
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• pp.83-93
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• 2020

The time delay is used as a major indicator of the level of traffic congestion on traffic crossroads. For this purpose, the Daechi Station intersection where traffic congestion occurs and the Yeongdong 5 Bridge intersection where the traffic condition is relatively good, and the average lag time based on the field survey with the lag time calculated various simulation programs. comparison of the average control delay of the field survey data the signal intersection analysis model the KHCS Dechi intersection 7.7 second / vehicle Young dong 5 bridge intersection 7.9 second / vehiclehe VISSIM showed a difference Dechi intersection 21.1 second / vehicle and Young dong 5 bridge intersection 8.1 second / vehiclehe T7F showed a difference Dechi intersection 3.3 second / vehicle and Young dong 5 bridge intersection 9.3 second / vehicle. Analyzing the same intersection proved that the results differed from one simulation model to another.

• Journal of Korean Society of Transportation
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• v.14 no.3
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• pp.127-141
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• 1996

This paper presents a unique approach to urban traffic network signal control. This paper begins with an introduction to traffic control in general, and then goes on to describe the approach of fuzzy control, where the signal timing parameters at a given intersection are adjusted as functions of the local traffic network condition and adjacent intersection. The signal timing parameters evolve dynamically using only local information to improve traffic signal flow. The signal timing at an intersection is defined by three parameters : cycle time, phase split, off set. Fuzzy decision rules are used to adjust three parameters based only on local information. The amount of change in the timing parameters during each cycle is limited to a small fraction of the current parameters to ensure smooth transition. In this paper the effectiveness of this method is showed through simulation of the traffic signal flow in a network of controlled intersection.

• International Journal of Highway Engineering
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• v.17 no.1
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• pp.91-98
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• 2015

PURPOSES : Although signalized intersections have been considered the best way to control traffic volume in urban areas for several decades, roundabouts are currently being discussed as an alternative way to control traffic volume, especially when traffic is light. Because a roundabout's efficiency depends on the load geometry as well as the traffic volume, design guidelines for roundabouts are recommended only if the incoming traffic volume is very low. It is rare to substitute a roundabout for an existing signalized intersection in urban areas. This study aims to estimate the benefits from the transformation of an existing signalized intersection into a roundabout in an urban area. When there is a more moderate volume of traffic, roundabouts can be effectively used by optimizing signals located at an approaching roadway. METHODS : The methodologies of this paper are as follows: First, a signalized intersection was analyzed to determine the traffic characteristics. Second, the signalized intersection was transformed into a roundabout using VISSIM microscopic traffic simulation. Then, we estimated and analyzed the effects and the performance of the roundabout. In addition, we adjusted a method to improve the benefits of the transformation via the optimization of signals located at an approaching road to control the incoming traffic volume. RESULTS : The results of this research are as follows: The signal-optimized roundabout improved delays compared with the signalized intersection during the morning peak hour, non-peak hour, and evening peak hour by 1.78%, 12.45%, and 12.72%, respectively. CONCLUSIONS : According to the simulation results of each scenarios, the signal-optimized roundabout had less delay time than the signalized intersection. If optimized signal control algorithms are installed in roundabouts in the future, this will lead to more efficient traffic management.

• Journal of Korean Society of Transportation
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• v.6 no.2
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• pp.49-56
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• 1988

Alternate use of lane at a signalized intersection is a quite different control of the operation of an intersection. This control introduces a new stop line and signal before the original stop line. All of the lanes between the two stop lines are used for left turn traffic or through traffic at a time. The purpose of the control is increasing the capacity of a n intersection without widening the approach width. this paper contains a study on the condition of a application, the proper distances between the two stop lines, the reasonable offsets(rear) to guarantee clearing the vehicles of previous phase, the comparison of approach capacity between the existing control and this control. The study results reveals that the offsets(rear) are rather stable showing the range(maximum value minus minimum value) of it's value does not exceed 3.6 seconds according to the field data. The approach capacity will be increased by 27%, 43%, 59%, 84% when the distances between the stop lines are 30.0m respectively. The control might have theoretical limitation to operate in practice. So an experimental application of the control at some suitable intersections prior to expanding it.

• Journal of IKEEE
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• v.23 no.4
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• pp.1381-1386
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• 2019

As traffic congestion in cities becomes more serious, intelligent traffic control is actively being researched. Reinforcement learning is the most actively used algorithm for traffic signal control, and recently Deep reinforcement learning has attracted attention of researchers. Extended versions of deep reinforcement learning have been emerged as deep reinforcement learning algorithm showed high performance in various fields. However, most of the existing traffic signal control were studied in a single intersection environment, and there is a limitation that the method at a single intersection does not consider the traffic conditions of the entire city. In this paper, we propose a cooperative traffic control at multi-intersection environment. The traffic signal control algorithm is based on a combination of extended versions of deep reinforcement learning and we considers traffic conditions of adjacent intersections. In the experiment, we compare the proposed algorithm with the existing deep reinforcement learning algorithm, and further demonstrate the high performance of our model with and without cooperative method.