• 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.

• 디지털산업정보학회논문지
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• 제5권4호
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• pp.69-76
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• 2009

High-speed services and bulk transmission were available by the development of the network and communication technologies. Moreover various next-generation converged services are undergoing a change by various services. This paper presents improved real-time simulated traffic generation and verification schemes based on the actual traffic pattern analysis. For this, we analyzed traffic patterns of actual application system and generated simulated traffics. We also suggested scheme that verify similarity of simulated traffic and actual traffic.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제5권4호
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• pp.360-366
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• 2005

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. Now days, with increasing many vehicles on restricted roads, the conventional traffic light creates 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 we 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 doesn't consider vehicle length.

• 한국지능시스템학회논문지
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• 제10권6호
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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.

• 한국안전학회지
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• 제27권3호
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• pp.147-152
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• 2012

Traffic Accident Merging Index (TAMI) is developed for TMACS (Traffic Safety Information Management Complex System). TAMI is calculated by combining 'Severity Index' and 'Frequency'. The existing indexes are Traffic deaths per 100,000 population, Traffic deaths per 100,000 inhabitants/per billion veh-km, etc. However, there is no consistency in using them among local governments, so it can create confusion. Moreover, the index level is too complicated to understand. Therefore, this study suggests new traffic safety index, TAMI. It will work to improve the weaknesses and present accurate status of traffic safety in local governments.

• 한국산학기술학회논문지
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• 제6권5호
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• pp.378-383
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• 2005

트래픽 엔지니어링(Traffic Engineering)은 트래픽을 네트워크 전체에 가능한 균등히 분배하여 사용자들이 원하는 서비스 품질을 보장해주면서 동시에 네트워크 자원의 활용도를 극대화시키는 기술이다. 트래픽 엔지니어링의 주요 목적은 트래픽 레벨과 자원 레벨에서 네트워크의 성능을 향상시키는 것인데, 이것은 네트워크 자원을 경제적으로 그리고 신뢰성 있게 이용하면서 트래픽에 관련된 성능 요구사항을 만족해야 한다. 본 논문에서는 IP/WDM 트래픽 엔지니어링을 구현하기 위한 두 가지 모델에 대해서 비교 분석하고 마지막으로 IP/WDM 트래픽 엔지니어링의 기능 구조에 대해서 설명한다.

• 한국멀티미디어학회논문지
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• 제21권11호
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• pp.1244-1253
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• 2018

The color of traffic light is sensitive to various illumination conditions. Especially it loses the hue information when oversaturation happens on the lighting area. This paper proposes a traffic light recognition method robust to these illumination variations. The method consists of two steps of traffic light detection and recognition. It just uses the intensity and saturation in the first step of traffic light detection. It delays the use of hue information until it reaches to the second step of recognizing the signal of traffic light. We utilized a deep learning technique in the second step. We designed a deep convolutional neural network(DCNN) which is composed of three convolutional networks and two fully connected networks. 12 video clips were used to evaluate the performance of the proposed method. Experimental results show the performance of traffic light detection reporting the precision of 93.9%, the recall of 91.6%, and the recognition accuracy of 89.4%. Considering that the maximum distance between the camera and traffic lights is 70m, the results shows that the proposed method is effective.

• 반도체디스플레이기술학회지
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• 제23권1호
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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.

• Journal of information and communication convergence engineering
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• 제5권2호
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• pp.171-176
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• 2007

To give a guarantee a consistently high level of quality and reliability of Telematics traffic service, traffic flow forecasting is very important issue. In this paper, we proposed an adaptable integrated prediction model to predict the traffic flow in the future. Our model combines two methods, short-term prediction model and long-term prediction model with different combining coefficients to reflect current traffic condition. Short-term model uses the Kalman filtering technique to predict the future traffic conditions. And long-term model processes accumulated speed patterns which means the analysis results for all past speeds of each road by classifying the same day and the same time interval. Combining two models makes it possible to predict future traffic flow with higher accuracy over a longer time range. Many experiments showed our algorithm gives a better precise prediction than only an accumulated speed pattern that is used commonly. The result can be applied to the car navigation to support a dynamic shortest path. In addition, it can give users the travel information to avoid the traffic congestion areas.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제3권6호
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• pp.575-596
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• 2009

Facing limited network resources such as bandwidth and processing capability, the Internet will have congestion from time to time. In this paper, we propose a scheme to maximize the total utility offered by the network to the end user during congested times. We believe the only way to achieve our goal is to make the scheme application-aware, that is, to take advantage of the characteristics of the application. To make our scheme scalable, it is designed to be class-based. Traffic from applications with similar characteristics is classified into the same class. We adopted the RED queue management mechanism to adaptively control the traffic belonging to the same class. To achieve the optimal utility, the traffic belonging to different classes should be controlled differently. By adjusting link bandwidth assignments of different classes, the scheme can achieve the goal and adapt to the changes of dynamical incoming traffic. We use the control theoretical approach to analyze our scheme. In this paper, we focus on optimizing the control on two types of traffic flows: TCP and Simple UDP (SUDP, modeling audio or video applications based on UDP). We derive the differential equations to model the dynamics of SUDP traffic flows and drive stability conditions for the system with both SUDP and TCP traffic flows. In our study, we also find analytical results on the TCP traffic stable point are not accurate, so we derived new formulas on the TCP traffic stable point. We verified the proposed scheme with extensive NS2 simulations.