• Proceedings of the Korean Information Science Society Conference
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• 2011.06a
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• pp.491-493
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• 2011

Traffic sign detection is the domain of automatic driver assistant systems. There are literatures for traffic sign detection using color information, however, color-based method contains ill-posed condition and to extract the region of interest is difficult. In our work, we propose a method for traffic sign detection using k-means clustering method, back-propagation neural network, and projection histogram features that yields the robustness for ill-posed condition. Using the color information of traffic signs enables k-means algorithm to cluster the region of interest for the detection efficiently. In each step of clustering, a cluster is verified by the neural network so that the cluster exactly represents the location of a traffic sign. Proposed method is practical, and yields robustness for the unexpected region of interest or for multiple detections.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.3
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• pp.59-72
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• 2017

As the part of study which handles the measure to use the individual vehicle information of taxi GPS data on signal controls in order to overcome the limitation of Loop detector-based collecting methods of real-time signal control system, this paper conducted series of evaluations and improvements on link travel time, queue vehicle time estimates and traffic condition decision algorithm from the research introduced in 2016. considering the control group and the other, the link travel time has enhanced the travel time and the length of queue vehicle has enhanced the estimated model taking account of the traffic situation. It is analyzed that the accuracy of the average link travel time and the length of queue vehicle are respectably both approximately 95 % and 85%. The traffic condition decision algorithm reflected the improved travel speed and vehicle length. Smoothing was performed to determine the trend of the traffic situation and reduce the fluctuation of the data, and the algorithms have refined so as to reflect the pass period on overflow judgment criterion.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.8 no.1
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• pp.23-27
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• 2015

Nowdays, in order to reduce recent traffic accident the traffic accident research which uses IT techniques is plentifully advanced. But, when running away traffic accident occurs, the assault vehicle the searching is difficult very from site. Respected a traffic accident investigation scientification RFID techniques and type expense to use an ubiquitous theory constructs the traffic accident preventive system which is efficient the algorithm which proposed. Especially in this paper, It simulated that every hour changes road follows produces the optimum traffic safety speed which in situation and weather condition.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.11a
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• pp.782-785
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• 2004

In the Well-being age, many people use a city park for rest deeply think and constitutional walk. The city park is located at near side by traffic road in urban. Citizens are not satisfied with it's fuction as a haven of peace due to road traffic noise. Thus, this study is for a research on the actual noise condition of a city park in Nowon go. This study uses a prediction method called ASJ-model in order to calculate PWLs of road traffic noise. Using calculated PWLs, noise levels in a park are predicted and compared with measured values.

• Journal of Navigation and Port Research
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• v.32 no.2
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• pp.127-132
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• 2008

The safety degree of navigation for collision avoidance is closely related with the combination between mariner's behavior and navigational environment. The condition of navigational environment is mainly decided by navigable waters, ship traffic, rule of road, sea state, weather and so on. Especially, the condition of navigable waters and ship traffic in navigational environment are ones of the important factors to attain safe navigation when mariners are underway and crossing, head on or overtaking situation. Thus this paper is to analyze the characteristics of mariner's behavior for collision avoidance caused by ship traffic and navigable waters by analyzing the contents of questionnaire and the results of international collaborative research. As a result, it can be concluded that the density of ship traffic and the area of navigable waters affect mariner's ship handling for collision avoidance.

• International Journal of Highway Engineering
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• v.14 no.5
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• pp.11-19
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• 2012

PURPOSES: The new methodology is proposed for estimation of long-term performance and pavement life based on the national highway database in Daejeon area. Furthermore, this study tried to verify the applicability of performance estimation using NHPCI (National Highway Pavement Condition Index) on tendency of pavement deterioration as time goes by under Korean road environments. METHODS: Reliability theories are applied to estimate the mean life and to determine the appropriate distribution using 3 levels of traffic loads (high, medium, low) based on maintenance and rehabilitation history data for 15 years. RESULTS: As a result, Lognormal distribution is suitable for explanation of pavement lifetime in Daejeon area regardless of traffic loads. In addition, we found that the results of mean life and maintenance timing based on NHPCI for the pavement sections of 3 levels of traffic loads are available. CONCLUSIONS: Based on this study, it was found that mean life of high, medium and low levels of traffic loads are about 8.1 years, 12.2 years and 12.7 years, respectively. Higher level of traffic loads shorten the pavement mean life.

• International Journal of Highway Engineering
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• v.11 no.1
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• pp.25-36
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• 2009

Everyday congestion length (distance) and duration (time) data are collected and recorded in Expressway Traffic Information Center. These records are based on the information that the operators watch CCTV and decide traffic condition in order to present information about congestion on VMS. Using VMS message has some merits like that it doesn't need a great lot of cost to construct hardware such like FTMS because operators can check traffic condition by watching CCTV only. Of cause in the aspect of accuracy, using VMS message has the limitation that it is based on subject decision compared with FTMS. However, it can be said that the value of using VMS message is very large. The object of this study is to use the VMS information record (log file) usefully to provide information of traffic condition on expressway for users (drivers) without keeping the VMS information record in dead storage. To do so, in this research, congestion calculation method able to understand traffic congestion condition on expressway was developed.

• Journal of the Ergonomics Society of Korea
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• v.35 no.3
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• pp.135-142
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• 2016

Objective: Objective of this study is to provide characteristics of injury frequency and severity by driving condition in large truck-related traffic collisions. Background: Traffic accidents involving large trucks draw a lot of attention in accident prevention and management policies since they bring about severe human and financial damages. Method: In order to identify the major risk factors of accidents by driving condition, 255 recognized traffic accidents by large truck drivers were analyzed in terms of time of the day, road type, and shape of the road. Results: The driving conditions in the results are represented by the following form of combination, "Road Type (Non-expressway or Express) - Shape of Roads (Straight, Curved, Downhill, or Intersection) - Time of Accidents (Day or Night)". In the analysis of injury frequency, Non-expressway-Straight-Day condition was the most frequent one. Meanwhile, Expressway-Curved-Day, Non-expressway-Curved-Night and Non-expressway-Intersection-Night were evaluated as high level in view of injury severity. Also, Expressway-Straight-Night is the driving condition that is the highest in risk among the conditions that have to be managed as grade "High". Non-expressway-Straight-Night, Non-expressway-Downhill-Day, and Non-expressway-Curved-Day are also categorized as grade "High". Conclusion and Application: Safety managers in the fields require basic information on accident prevention that can be easily understood. The research findings will serve as a practical guideline for establishing preventive measures for traffic accidents.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1996.10a
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• pp.131-137
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• 1996

To perform condition monitoring of P.C. Box girder bridge under ambient traffic, dynamic characteristics were identified using the results of load test an analysis. It was found that natural frequencies obtained from the measured acceleration data for the forced vibration part and free vibration part were nearly identical. Thus it can be concluded that dynamic parameters are properly determined under ambient traffic condition. Finite element model for analysis was calibrated using measured frequencies. Change of dynamic characteristics were predicted through analysis of the established finite element model with anticipated change.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.1
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• pp.41-60
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• 2018

Recently, road traffic congestion is becoming a serious urban phenomenon, leading to massive adverse impacts on the ecology and economy. Therefore, solving this problem has drawn public attention throughout the world. One new promising solution is to take full advantage of vehicular ad hoc networks (VANETs). In this study, we propose a new traffic congestion detection and quantification method based on vehicle clustering and fuzzy assessment in VANET environment. To enhance real-time performance, this method collects traffic information by vehicle clustering. The average speed, road density, and average stop delay are selected as the characteristic parameters for traffic state identification. We use a comprehensive fuzzy assessment based on the three indicators to determine the road congestion condition. Simulation results show that the proposed method can precisely reflect the road condition and is more accurate and stable compared to existing algorithms.