• Journal of Korean Society of Transportation
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• v.26 no.4
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• pp.173-184
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• 2008

Development of an accident estimation model based on accident data can be made after accident occurrences. However, the taking of historical accident data is not easy, and there have been differences between real accident data and police-reported accident data. Also, another difficult shortcoming is that historical traffic accident data better consider driver behavior or intersection characteristics. A new method needs to be developed that can predict accident occurrences for traffic safety improvement in black spots. Traffic conflict decision techniques can acquire and analyze data in time and space, requiring less data collection through investigation. However, there are shortcomings: as existing traffic conflict techniques do not operate automatically, the analyst's opinion could easily affect the study results. Also, existing methods do not consider the severity of traffic conflicts. In this study, the authors presented traffic conflict decision criteria which consider conflict severity, including opposing left turn traffic conflict and cross traffic conflict decision criteria. In order to test these criteria, the authors acquired three signalized intersection images (two intersections in Sungnam city and one intersection in Paju) and analyzed the acquired images using image processing techniques based on individual vehicle tracking technology. Within the analyzed images, level 1 conflicts occurred 343 times over three intersections. Some of these traffic conflicts resulted in level 3 conflict situations. Level 3 traffic conflicts occurred 25 times. From the study results, the authors found that traffic conflict decision techniques can be an alternative to evaluate traffic safety in black spots.

• International Journal of Highway Engineering
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• v.9 no.4
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• pp.83-92
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• 2007

In 2004, the number of traffic crashes and deaths in Korea are 220,755 and 6,563, respectively. Korea Road Traffic Safety Authority reported that the number of traffic accidents occupies over 25% out of total accidents, and found that traffic crash probability is extremely high at intersections since intersections have various traffic conflict points. A Safety study using Traffic Conflict Technique is much more useful than a study using reported traffic accident data. Existing traffic conflict research hardly considered conflict severity occurring at intersections. So, the study developed new criteria considering conflict severity. Analytic methods precisely detecting crashing points using field surveying data, and applied an application of our new criteria. Opposing left-turn conflict criteria was devided by three groups(high severe conflict, middle severe conflict, and less severe conflict) based on conflict boundary by means of a standard vehicle length. After analyzing field surveying data(3hours), we found totally 41 opposing left-turn conflicts. 3 cases are high severe conflict, and another 10 cases are middle severe conflicts, and the other cases are less severe. Studies related in conflict severity are considerably important to evaluate intersection's detailed safety index, and existing studies(purely conflict counting does not consider severity) have a limitation to clearly determine the level of safety of intersections for an application.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.7 no.5
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• pp.64-76
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• 2008

To increase road safety at blackspots, it is needed to develop a new method that can process before accident occurrence. Accident situation could result from traffic conflict. Traffic conflict decision technique has an advantage that can acquire and analyze data in time and confined space that is less through investigation. Therefore, traffic conflict technique is highly expected to be used in many application of road safety. This study developed traffic conflict decision program that can analyze and process from signalized intersection image. Program consists of the following functional modules: an image input module that acquires images from the CCTV camera, a Save-to-Buffer module which stores the entered images by differentiating them into background images, current images, difference images, segmentation images, and a conflict detection module which displays the processed results. The program was developed using LabVIEW 8.5 (a graphic language) and the VISION module library.

• Journal of Communications and Networks
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• v.15 no.3
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• pp.321-328
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• 2013

In this paper, we present a technique for obtaining conflict-free schedules for real-time automation protocol for industrial Ethernet (RAPIEnet) switches. Mathematical model of the switch is obtained using graph theory. Initially network traffic entry and exit parts in a single RAPIEnet switch are identified, so that a bipartite conflict graph can be constructed. The obtained conflict graph is transformed to three kinds of matrices to be used as inputs for our simulation model, and selection of any of the matrix forms is application-specific. A greedy edge-coloring algorithm is used to schedule the network traffic and to solve the minimum coloring problem. After scheduling, empty slots are identified for forwarding the non real-time traffic of asynchronous devices. Finally, an algorithm for synchronizing the schedules of adjacent switches is proposed using edge-contraction and minors. All simulations were carried out using Matlab.

• Journal of the Korean Society for Railway
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• v.7 no.2
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• pp.71-76
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• 2004

In this paper, we propose a pilot study to deploy the Railway Conflict Detection and Resolution System(RCDRS) in the context of Korean Railway(KORAIL). KORAIL plans to deploy in near future RCDRS, which is a decision support module placed on the top level of the Railway Traffic Management System(RTMS). This study entails the review of the state-of-art researches and projects in the field of the railway traffic management, as well as the analysis of the traffic characteristics of the major railroad lines in KORAIL. The analysis provides a basis to choose a solution approach for the railway conflict detection and resolution problem that each individual line faces. This study plays a role as a pilot study for a full systematic approach, in which interactions between lines require further advanced analysis to take the entire KORAIL lines into consideration rather than a myopic approach.

• Journal of Korean Society of Transportation
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• v.20 no.1
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• pp.55-63
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• 2002

It has been known well that Traffic Conflict Technique(TCT) used to evaluate the safety of intersections in the case of shortage of traffic accidents data and surveying time. Because data for using in traffic conflict technique that is collected by trained surveyors, it is rely on the knowledge, experience and the characteristics of them. The data of surveying generate varying result. So, its variance must minimize and then it is considered of calculating in traffic conflict technique however obviously technique to minimize has not developed until now. So, this paper has a focus on the technical method to minimize the variance. For this, it applied the fuzzy reasoning theory to the existed traffic conflict technique that is the most comprehensive method in the country and then developed the new traffic conflict technique model. Fuzzy reasoning theory is a very appropriate method for minimizing the variance among surveyors because it can systematically calculate the uncertainty of surveyors by approximation reasoning structure. The result of analysis from pilot study, the new Procedure in this Paper minimized the variance by 53 Percentiles and it increased the value of conversion factor two times than the exited traffic conflict technique. The method proposed in this paper, it can be used for evaluating the safety of intersection, and before and after analysis of improving Project of black spots.

• Journal of the Korean Society of Safety
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• v.32 no.3
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• pp.123-129
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• 2017

This study deals with the traffic accident of truck at circular intersection. The purpose of this study is to develop the truck accident models based on type of accident and conflict. In pursuing the above, the study gives particular attentions to selecting the appropriate models among Poisson and Negative binomial models using statistical program LIMDEP 8.0. The traffic accident data from 2007 to 2014 are collected from TAAS data set of Road Traffic Authority. Such the dependent variable as number of truck accidents and the 24 independent variables as geometry, traffic volume and others are used. The main results are as follows. First, 5 Poisson models (${\rho}^2$ of 0.164~0.351) which are all statistically significant are selected. Second, the common variable based on type of accident and conflict is analyzed to be truck apron width. The specific variables are, however, evaluated to splitter island, area of splitter island, speed limit sign, truck apron, number approach road, circular intersection sign, speed hump and traffic volume. Finally, widening the truck apron width and improving the above specific variables are analyzed to be important for truck accident reduction at circular intersections.

• International Journal of Aeronautical and Space Sciences
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• v.13 no.3
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• pp.377-385
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• 2012

The Automatic Dependent Surveillance Broadcast (ADS-B) system is a key component of CNS/ATM recommended by the International Civil Aviation Organization (ICAO) as the next generation air traffic control system. ADS-B broadcasts identification, positional data, and operation information of an aircraft to other aircraft, ground vehicles and ground stations in the nearby region. This paper explores the ADS-B based trajectory prediction and the conflict detection algorithm. The multiple-model based trajectory prediction algorithm leads accurate predicted conflict probability at a future forecast time. We propose an efficient and accurate algorithm to calculate conflict probability based on approximation of the conflict zone by a set of blocks. The performance of proposed algorithms is demonstrated by a numerical simulation of two aircraft encounter scenarios.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.18 no.3
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• pp.27-33
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• 2010

The goal for the CD&R system is to predict that a conflict is going to occur in the future, communicate the detected conflict to a human operator, and, in some cases, assist in the resolution of the conflict situation. To provide insight into different methods of conflict detection and resolution, a literature review of previous research models and current developmental and operational systems was performed. This paper focuses only on the specific attributes of each model, not on the depth to which a model has been analyzed, validated, or accepted. Thus, care should be taken to remember that a model that seems to be simple according to our categorization scheme may be significantly more viable than an apparently sophisticated model.

• Journal of Advanced Navigation Technology
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• v.28 no.4
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• pp.450-458
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• 2024

Urban air mobility (UAM) shows great promise for commercialization, yet the technical foundations for ensuring safety in large-scale operations remain a challenge. The purpose of this paper was to analyze current air traffic conflict management techniques in order to develop strategies for implementing strategic conflict management within UAM traffic management systems. We found that UAM conflict management can benefit from demand and capacity balancing techniques, and a system-wide approach is essential. Specifically, the use of data sharing and probabilistic methods is essential for addressing flight time uncertainty and large-scale UAM operations effectively.