• Journal of Korean Society of Transportation
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• v.14 no.2
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• pp.45-58
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• 1996

In a large signal intersection, it is the most important to set phase sequences and phase intervals of traffic signal in order to improve the efficiency of the capacity as well as safety. These setting allows to select the best sequence of signal phase among several alternatives, and thus to rearrange the starting and ending points of the individual phase using an effective interphase periods (EIP). The EIP is a gap between previous and current traffic movements at a potential collision point in an intersection. Each of traffic movements has an equality for safety and efficiency at the balanced condition of EIP. This paper presents how to set optimally the phase sequences and intervals of traffic signal in an intersection using phase based approach. And in the second part, we applied the theory developed in the first part. In particular, a numerical example of phase base signal setting is presented using a matrix computation method in order to select the best sequence among several alternatives, and thus to rearrange the starting and ending points of the individual phase using the EIP. This method also allows to apply to optimum signal setting even in five-lag or staggered-type intersection.

• 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.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.1
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• pp.81-92
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• 2023

Traffic state classification is crucial for time-of-day (TOD) traffic signal control. This paper proposed a traffic state classification technique applying Deep-Embedded Clustering (DEC) method that uses a high dimensional traffic data observed at all signalized intersections in a traffic signal control sub area (SA). So far, signal timing plan has been determined based on the traffic data observed at the critical intersection in SA. The current method has a limitation that it cannot consider a comprehensive traffic situation in SA. The proposed method alleviates the curse of dimensionality and turns out to overcome the shortcomings of the current signal timing plan.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.11
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• pp.5334-5337
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• 2013

In this paper, the structure of traffic lights removed the wire for the completion of urban aesthetics is analyzed. The finite element model consists of shell elements from three-dimensional CAD model of actual traffic signal. Traffic light pole, horizontal stand shape, thickness, stiffeners, etc. are considered in this study. Analysis of stress and deformation is performed by applying wind load. When the wind load is applied, the result on traffic signal is analyzed. This study is to perform the basic tasks for improving the design.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.66-66
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• 2000

In this parer, we introduce an algorithm to control flows of the traffic in multi-intersections. It is pointed out that the main problem in traffic control is how to resolve the congested situations for the particular time-durations and directions. The heavy load to a certain direction usually leads the intersection to congested situations, and the adjacent intersections are affected. We control and analyze the traffic flow of multi-intersections consisting of five intersections, in which four intersections are linked to the four directions of the central one. The entrance of vehicles of each direction is described using the concept of probability. We compare the performance of the pretimed signal controls to the traffic adaptive signal controller using a Petri Net simulation tool, Exspect.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.2
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• pp.45-52
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• 2009

The off-state impedance of LED signal head is greater than that of a traditional bulb signal head, and the traffic controller has inherent off-state output leakage current. These two characteristics make the field trouble and reduce signal safety when the LED signal head is installed with traffic controller. In this Paper, a complement method of the LED signal head and traffic controller local standard (220vac line voltage) for improving signal safety is suggested. The point of designed complement method is to reduce the output leakage current of the traffic controller under 3mA, to increase the voltage feedback threshold to $70{\pm}5V$, and to make LED signal head maintain off-state in 0-95vac with 10Kohm maximum impedance.

• Journal of the Korea Computer Industry Society
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• v.5 no.9
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• pp.1005-1016
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• 2004

The conventional traffic light loses the function of optimal traffic signal cycle. And so, 30-45% of conventional traffic signal cycle is not matched to the present traffic signal cycle. In this paper proposes electro sensitive traffic light using fuzzy rules which will reduce the average vehicle waiting time and improve average vehicle speed. This paper is researching the storing method of 40 different kinds of sensor input conditions. Such as, car speed, delay· in starting time and the volume of cars in the real traffic situation. It will estimate the optimal green time in the 10 different intersections using Intelligent fuzzy method. Computer simulation results prove that reducing the average vehicle waiting time and offset better than fixed signal method which doesn't consider vehicle length.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.5 no.1 s.9
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• pp.31-43
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• 2006

As of March 2005, the standard of traffic signal controllers became effective. The standard presents specifications and functions of a traffic signal controller which collects traffic information, sends it to the traffic control center, and controls traffic signal with adequate traffic signal timing provided by the traffic control center. Since the controllers by the previous standard lack parts compatibility and have different control functions and communication protocol, the maintenance cost has been increased. Also, some important functions like conflict detection have not worked out perfectly. To overcome these disadvantages, first of all, this standard secures hardware compatibility. Conflict detection method has been enhanced. Communication protocol to the traffic control center was included in the standard. With this standard, independent maintenance system and prompt treatment of hardware malfunctions becomes possible. Also, the unified intersection traffic control method will increase traffic safety.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.6
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• pp.697-702
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• 2018

Recently, the number of private cars has increased sharply due to the increase in national income. The sudden increase in the number of vehicles in limited territory has caused serious traffic congestion and the traffic congestion cost wasted on the road due to such traffic congestion is increasing every year. To solve this problem, we propose a traffic signal control system using image processing. In this paper, we use the camera installed at the intersection to measure the amount of traffic flowing in and out of each road simultaneously. We propose a traffic signal control system that can prevent traffic congestion before it happens. In the case of applying the traffic signal control system proposed in this paper to the daytime, the traffic volume could be measured accurately. However, the result of the experiment with the night-time general camera and the headlight with the infrared camera at the night-time of 72.8% was 86.6%.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.6
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• pp.1-10
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• 2019

Traffic Signal Evaluation HILS is a system designed to evaluate a traffic signal system, and has a function of driving that simulates a real environment using a simulator that simulates a real traffic signal environment and an LCS that simulates a traffic signal controller. This study simulates the function of the traffic signal controller and is designed for design the LCS which is connected to the center system and the traffic simulator (VISSIM). The design of the LCS program uses a portable python language, and the code is designed in two versions running on Windows in the PC environment and unning on embedded environment, with a slight modification of the code. In this study, we analyzed the limitations of using LCS on Windows in PC environment and confirmed the ease of simulation Linux in embedded environment at large capacity.