• Wind and Structures
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• v.16 no.3
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• pp.225-240
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• 2013

The wind-induced vibrations of the mast arm of cantilever traffic signal structures can lead to the fatigue failure of these structures. Wind tunnel tests were conducted on an aeroelastic model of this type of structure. Results of these experiments indicated that when the signals have backplates, vortex shedding causes large-amplitude vibrations that could lead to fatigue failure. Vibrations caused by galloping were only observed for one particular angle of attack with the signals having backplates. No evidence for galloping, previously thought to be the dominant cause of fatigue failures in these structures, was observed.

• 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 Semiconductor & Display Technology
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• v.23 no.1
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• pp.61-64
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• 2024

As research on autonomous driving technology becomes more active, various studies on signal recognition of traffic lights are also being conducted. When recognizing traffic lights with different purposes and shapes, such as pedestrian traffic lights, vehicle-only traffic lights, and right-turn traffic lights, existing classification methods may cause misrecognition problems. Therefore, in this study, we studied a model that allows accurate signal recognition by subdividing the classification of signals according to the purpose and type of traffic lights. A signal recognition model was created by classifying traffic lights according to their shape and purpose into horizontal, vertical, right turn, etc., and by comparing them with the existing signal recognition model based on YOLOv5, it was confirmed that more correct and accurate recognition was possible.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.3D
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• pp.343-353
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• 2011

The unsignalized intersections in a community road in the city of Seoul have 3,753 traffic accidents(9%) of total 41,702 cases in 2008, not high in the occurrence rate of traffic accidents, but seem to have a quite high potential of accidents due to the unreasonable and insufficient operation of systems and facilities in the part of traffic foundations. In particular, the un-signalized intersections in a community road have an insufficient measure for safety as compared to the crossroads with signals, and there are few analysis of traffic accidents and domestic researches on the model of affecting factors. Our country also has no concept of passing priority in operating a crossroad without signals, differently from foreign countries, so the researches and safety measures for improving the safety of a crossroad without signals in a community road are urgent. Therefore, This study set out to analyze the road conditions, traffic conditions, and traffic environment conditions on unsignalized intersection, to identify the elements that would impose obstructions in safety, and develop a traffic accident prediction model to evaluate the safety of an unsignalized intersection using the correlation between the elements and an accident. In addition, the focus was made on suggesting appropriate traffic safety policies by dealing with the danger elements in advance and on enhancing the safety on intersection in developing a traffic accident prediction model for an unsignalized intersection.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.2
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• pp.647-669
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• 2016

Multiple attribute for decision making including user preference will increase the complexity of route selection process. Various approaches have been proposed to solve the optimal route selection problem. In this paper, multi attribute decision making (MADM) algorithms such as Simple Additive Weighting (SAW), Weighted Product Method (WPM), Analytic Hierarchy Process (AHP) method and Total Order Preference by Similarity to the Ideal Solution (TOPSIS) methods have been proposed for acoustic signature based optimal route selection to facilitate user with better quality of service. The traffic density state conditions (very low, low, below medium, medium, above medium, high and very high) on the road segment is the occurrence and mixture weightings of traffic noise signals (Tyre, Engine, Air Turbulence, Exhaust, and Honks etc) is considered as one of the attribute in decision making process. The short-term spectral envelope features of the cumulative acoustic signals are extracted using Mel-Frequency Cepstral Coefficients (MFCC) and Adaptive Neuro-Fuzzy Classifier (ANFC) is used to model seven traffic density states. Simple point method and AHP has been used for calculation of weights of decision parameters. Numerical results show that WPM, AHP and TOPSIS provide similar performance.

• Journal of IKEEE
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• v.22 no.1
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• pp.46-52
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• 2018

The problem of traffic light detection and recognition has recently become one of the most important topics in various researches on autonomous driving. Most algorithms are based on colors to detect and recognize traffic light signals. These methods have disadvantage in that the recognition rate is lowered due to the change of the color of the traffic light, the influence of the angle, distance, and surrounding illumination environment of the image. In this paper, we propose machine learning based detection and recognition algorithm using shape information to solve these problems. Unlike the existing algorithms, the proposed algorithm detects and recognizes the traffic signals based on the morphological characteristics of the traffic lights, which is advantageous in that it is robust against the influence from the surrounding environments. Experimental results show that the recognition rate of the signal is higher than those of other color-based algorithms.

• Journal of the Korea Convergence Society
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• v.10 no.9
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• pp.111-117
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• 2019

Green light flashing signals of pedestrian lights can cause lots of confusion for pedestrians, resulting in serious road traffic problems. In this study, a new signalling lamp was proposed using the Lenticular technique to make the signals of pedestrians entering and not entering crosswalks look different. In order to review the possibility of introducing this signal, we conducted a cognitive test on the signal of the Lenticular. As a result of the experiment, the subjects were able to distinguish red and green flashing signals according to the distance. Based on this, we found the possibility of introducing lenticular signals that could prevent pedestrian accidents and prevent excessive crossings. In the future, we will manufacture and experiment with real traffic lights and actively examine the introduction plan.

• Journal of Korean Society of Transportation
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• v.4 no.2
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• pp.75-92
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• 1986

The paper contains the data collection methods and procedures employed in the study to evaluate the operational effects of stop sign and signal control at diamond interchanges. An assessment of traffic control alternatives is described in terms of operational effects of queues and travel speed. Guidelines for installing signal control at diamond interchanges are provided in terms of internal volume, left turn proportion within internal volume, and the sum of internal and external volume. The specific traffic volume guidelines were developed based on a combination of these variables affecting operational performance.

• Journal of Korean Society of Transportation
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• v.14 no.2
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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.

• Journal of Korean Society for Atmospheric Environment
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• v.9 no.E
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• pp.364-372
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• 1993

The purpose of this study is to analyze traffic patterns by use of TRANSYT-7F Model, and to choose the optimum traffic-light cycle length and cycle splite to improve traffic flow and air quality at Samsung Intersection in Seoul. Emission rates of air pollutants are calculated for three time segments 0700-0900, 0900-1800 and 1800-2000. The traffic volume correlated reasonably well with air pollutants emitted ; however, the phasing and timing of traffic signals was found to equally be important. The results of performance with optimal setting indicate that the best cycle length were 80sec(0700-0900), 95sec(0900-1800) and 90sec(1800-2000), res-pectively. As expected the highest emissions of air pollutants were observed during the evening rush hours (1800-2000). A properly designed signalized intersection can help reduce traffic delay, driver discomfort, fuel consumption, and air pollution by efficiently the capacity of existing intersection.