• 한국철도학회:학술대회논문집
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• 한국철도학회 2007년도 춘계학술대회 논문집
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• pp.1931-1936
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• 2007

Demand forecasting for railroad traffic is fairly important to establish future policy and plan. The future demand of railroad traffic can be predicted by analyzing the demand of air, marine and bus traffic which influence the demand of railroad traffic. In this study, forecasting the demand of railroad traffic is implemented through neural network using the demand of air, marine and bus traffic. Estimate accuracy of the demand of railroad traffic was shown about 84% through neural net model proposed.

• 정보과학회 컴퓨팅의 실제 논문지
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• 제22권2호
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• pp.113-118
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• 2016

현재 교통약자(장애인, 고령자, 어린이 등)의 보행 속도는 일반인 보다 느려, 기존 신호등의 제한된 시간 동안 안전하게 횡단이 불가능하다. 단지 기존의 보행신호등의 시간을 늘려 해결할 수 있지만 교통약자의 구분 없이 신호 대기 시간만 늘리면 신호등의 효율성이 떨어진다. 본 논문은 스마트 보행신호 등과 보행자의 스마트기기 연동 메커니즘을 제안하고, 이를 통해 교통약자와 일반인을 구분하여 교통약자에게 추가 보행 시간을 제공으로 교통체증을 최소화 하고자 한다. 스마트 보행신호등은 사물인터넷(IOT) 기술을 활용하여 교통약자를 식별하는 교통약자 중심의 보행신호등 메커니즘이다. 또한 시뮬레이션 기법을 통한 효율적 스마트 보행신호등 메커니즘 구축에 필요한 Data를 추출하고 스마트 보행신호등의 효율성 확인을 위해 가상의 시뮬레이션 환경에서 여러 종류의 신호등을 구축하여 인원 증가에 따른 신호대기시간 비교 분석 통해 효율적 시간을 검증한다.

• 대한교통학회지
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• 제27권2호
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• pp.57-71
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• 2009

교통정보제공을 통한 교통량 분산효과에 대한 관심이 높아짐에 따라, 효율적인 교통정보제공을 위한 기초 연구로써 운전자의 반응행태 및 우회효과에 대한 연구가 지속되고 있다. 본 연구는 실제 조사를 통해 추정된 우회율과 소통상황과의 상관분석을 통해, 우회가 어떻게 결정되며, 그 효과가 어떤지를 알아보고자 하였다. 속도-교통량 분석결과, 고속도로의 속도가 떨어짐에 따라 우회교통량이 증가하고, 우회교통량의 증가로 고속도로 교통량이 줄어 소통상황이 원활해지면서 다시 우회교통량이 줄어드는, 우회 메커니즘을 확인하였다. 또한 상관분석을 통해 우회율과 통행속도는 음(-)의 관계를, 통행시간과는 양(+)의 관계를 갖는다는 것을 밝혀냈으며, 혼잡상황별로, 통행방향별로 우회율과 소통상황과의 관계가 다양함을 밝혀냈다. 마지막으로 본선교통량과 통행속도, 통행시간을 변수로 하는 우회율 회귀식을 제시하였으며, 이 때 결정계수는 38.5%로 나타났다. 이 값은 고속도로 소통상황이 운전자의 우회결정시 영향을 미치는 다양한 변수 중에서 약 40%를 차지한다는 것을 의미한다.

• 환경영향평가
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• 제10권4호
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• pp.297-304
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• 2001

Recently the road traffic noise has appeared as a significant environmental issue because of dramatic increase of vehicles and expansion of newly constructed road. Therefore, this study proposes the method that improves prediction factors and models through analysis of the existing road traffic noise prediction model. Prediction factors can be improved by establishing guideline for diffraction attenuation and applying daily traffic discharge, peak traffic discharge, and average traveling speed through an analysis of level service. Prediction must be made by periods of one or five years during 20 years. Prediction models also can be improved to include better prediction model through setting the database, establishing functional relation between physical properties and noise levels by acoustic analysis, and developing models for road traffic noise prediction in residential areas.

• 대한교통학회지
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• 제14권2호
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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.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제3권1호
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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.

• 한국지반공학회:학술대회논문집
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• 한국지반공학회 2010년도 추계 학술발표회
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• pp.1328-1332
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• 2010

The enlargement of existing tunnels is required to cope with problems related to traffic congestion. Sometimes, the tunnel traffic must be maintained through existing tunnels during their reconstruction due to non-availability of detours. And excavation by drill and blasting is desired for widening a hard rock tunnel. In this case, the road must be closed for some period for blasting through analyzing of traffic volume. In this paper, a case study on some traffic countermeasures for tunnel enlargement by blasting was performed. And the traffic flow characteristics of some tunnels in domestic main city were analyzed.

• 대한교통학회지
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• 제34권5호
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• pp.449-464
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• 2016

본 연구의 목적은 혼잡 교차로에 직결형 회전교차로의 적용 가능성을 평가하고 적용 가능한 교통량 범위를 산정하여 도입기준을 마련하는데 있다. 이를 위해 진입 교통량 및 주 부도로 교통량 비율, 좌회전 교통량 비율에 따라 다양한 시나리오를 작성하고 직결형 회전교차로와 회전교차로, 신호교차로에 대한 시뮬레이션을 수행하여 지체시간을 비교 분석하였다. 분석 결과 주 부도로 교통량 비율이 6:4인 경우의 차로당 교통량이 400대/시에서는 좌회전 비율 30%까지, 500대/시에서는 20%까지, 600대/시에서는 10%까지 직결형 회전교차로의 지체시간이 가장 작게 나타났다. 주 부도로 비율이 7:3인 경우에는 차로당 교통량이 400-600대/시에는 6:4와 동일하게 나타났으나 300대/시의 좌회전 비율 30%, 700대/시인 경우의 10%에서 직결형 회전교차로가 가장 작게 나타났다. 주 부도로 비율 8:2인 경우에는 차로당 교통량이 400-500대/시, 700대/시인 경우에는 7:3과 동일하게 나타났으나 300대/시의 10-30%, 600대/시에는 좌회전 비율이 20% 인 경우에도 가장 작게 나타났다. 종합해보면 주 부도로의 교통량 비율 차이가 커질수록 좌회전 교통량 비율과 교통량이 적을수록 직결형 회전교차로의 교통 처리 능력이 높게 나타났다. 따라서 주 부도로 교통량 차이가 크고 주도로 직진교통량 비율이 큰 혼잡교차로에 직결형 회전교차로의 도입 시 효과가 클 것으로 기대된다.

• 한국도로학회논문집
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• 제18권3호
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• pp.109-114
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• 2016

PURPOSES : The demand for extending national highways is increasing, but traffic monitoring is hindered because of resource limitations. Hence, this study classified highway segments into 5 types to improve the efficiency of short-term traffic count planning. METHODS : The traffic volume trends of 880 highway segments were classified through R-squared and linear regression analyses; the steadiness of traffic volume trends was evaluated through coefficient of variance (COV), and the normality of the data were determined through the Shapiro-Wilk W-test. RESULTS : Of the 880 segments, 574 segments had relatively low COV and were classified as type 1 segments, and 123 and 64 segments with increasing and decreasing traffic volume trends were classified as type 2 and type 3 segments, respectively; 80 segments that failed the normality test were classified as type 4, and the remaining 39 were classified as type 5 segments. CONCLUSIONS : A theoretical basis for biennial count planning was established. Biennial count is recommended for types 1~4 because their mean absolute percentage errors (MAPEs) are approximately 10%. For type 5 (MAPE =19.26%), the conventional annual count can be continued. The results of this analysis can reduce the traffic monitoring budget.

• 제어로봇시스템학회논문지
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• 제22권2호
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• pp.110-116
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• 2016

Autonomous vehicles must obey the traffic laws in order to drive actual roads. Traffic signs erected at the side of roads explain the road traffic information or regulations. Therefore, traffic sign recognition is necessary for the autonomous vehicles. In this paper, color characteristics are first considered to detect traffic sign candidates. Subsequently, we establish HOG (Histogram of Oriented Gradients) features from the detected candidate and recognize the traffic sign through a SVM (Support Vector Machine). However, owing to various circumstances, such as changes in weather and lighting, it is difficult to recognize the traffic signs robustly using only SVM. In order to solve this problem, we propose a tracking algorithm with RANSAC-based motion estimation. Using two-point motion estimation, inlier feature points within the traffic sign are selected and then the optimal motion is calculated with the inliers through a bundle adjustment. This approach greatly enhances the traffic sign recognition performance.