• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.4
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• pp.1-17
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• 2022

As pedestrian deaths account for a high proportion of traffic accident deaths in Korea, interest in pedestrian safety is growing. In particular, it is necessary to develop various pedestrian-centered traffic signal operation techniques to improve the pedestrian environment at signal intersections. Therefore, in this study, a method for time-of-day operating a pedestrian signal based on residual pedestrians was studied. To this end, the pedestrian signal operation technique in response to the pedestrian demand, which is operated by extending the pedestrian signal time only during the time when the pedestrian demand and the number of remaining pedestrians increase, was applied to the field. The difference in safety according to the application of the new pedestrian signal operation technique was statistically analyzed. As a result of the analysis, the residual pedestrian rate decreased by 20% (3.3 people) before application and 8% (1.4 people) after application, and the residual pedestrian rate in the crosswalk at the time of red signal decreased by 12% (1.9 people), And it was analyzed that the position of the residual pedestrian decreased by 3.3m from 5.2m before application to 1.9m after application.

• Journal of the Ergonomics Society of Korea
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• v.22 no.2
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• pp.15-28
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• 2003

The one of the most important factors is the platoon design on developing AH3(Advanced Highway System), as it is related to traffic efficiency and drivers' safety. This study was evaluated that how much speed is comfortable for drivers and how long distance is appropriate for vehicular gap of platoon by measuring drivers' physiology signal and sensibility. A fixed-based AHS simulator was developed by using a real vehicle cockpit and the restructured part of Korean highway for human factors evaluation. The EEG(electroencephalogram), ECG (electrocardiogram) and GSR(Galvanic Skin Response) were measured for obtaining drivers' physiology signal according to the change of speed and gap. The brain wave(${\alpha},\;{\beta},\;{\delta},\;{\theta}$) by EEG, the response of the autonomic nervous system. the sympathetic and parasympathetic nervous system, by ECG, and relax-arousal situation by GSR were analyzed. The SD(Semantic Differential) method was also applied to evaluate drivers' sensibility by 5-grade evaluation scale with 96 adjectives. SSQ(Simulator Sickness Questionnaire) was used to measure the simulator sickness of pre and post driving, two times. As the results, drivers were comfortable with 120km/h speed of platoon and lam to 15m vehicular distance. The results of this study may differ from the adaption of the reality because of many parameters. However, the purpose of this study is show to significant results of the drivers' safety and the acceptability of human factors evaluation.

• Journal of Platform Technology
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• v.9 no.3
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• pp.44-51
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• 2021

In general, golden time refers to the most important time in the initial response to accidents such as saving lives or extinguishing fires. The golden time varies from disaster to disaster, but is aimed at five minutes in terms of fire and first aid. However, for the actual site, the average dispatch time for ambulances is 9 minutes and the average transfer time is 17.6 minutes, which is quite large compared to the golden time. There are various causes for this delay, but the main cause is traffic jams. In order to solve the problem, the government has established emergency car concession obligations and secured golden time to prioritize ambulances in places with the highest accident rate, but it is not a solution in rush hour when traffic is increasing rapidly. Therefore, this paper proposed a deep learning-based emergency vehicle priority signal system using collected sound data by installing sound sensors on traffic lights and conducted an experiment to classify frequency signals that differ depending on the distance of the emergency vehicle.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.13 no.1
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• pp.1-14
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• 2014

The expansion of the physical road in response to changes in social conditions and policy of the country has reached the limit. In order to alleviate congestion on the existing road to reconsider the effectiveness of this method should be asking. Currently, how to collect traffic information for management of the intersection is limited to point detection systems. Intelligent Transport Systems (ITS) was the traffic information collection system of point detection method such as through video and loop detector in the past. However, intelligent transportation systems of the next generation(C-ITS) has evolved rapidly in real time interval detection system of collecting various systems between the pedestrian, road, and car. Therefore, this study is designed to evaluate the development of an algorithm for queue length based real-time traffic signal control methodology. Four coordinates estimate on time-space diagram using the travel time each individual vehicle collected via the interval detector. Using the coordinate value estimated during the cycle for estimating the velocity of the shock wave the queue is created. Using the queue length is estimated, and determine the signal timing the total queue length is minimized at intersection. Therefore, in this study, it was confirmed that the calculation of the signal timing of the intersection queue is minimized.

• Smart Structures and Systems
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• v.24 no.5
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• pp.617-630
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• 2019

Currently most of the vision-based structural identification research focus either on structural input (vehicle location) estimation or on structural output (structural displacement and strain responses) estimation. The structural condition assessment at global level just with the vision-based structural output cannot give a normalized response irrespective of the type and/or load configurations of the vehicles. Combining the vision-based structural input and the structural output from non-contact sensors overcomes the disadvantage given above, while reducing cost, time, labor force including cable wiring work. In conventional traffic monitoring, sometimes traffic closure is essential for bridge structures, which may cause other severe problems such as traffic jams and accidents. In this study, a completely non-contact structural identification system is proposed, and the system mainly targets the identification of bridge unit influence line (UIL) under operational traffic. Both the structural input (vehicle location information) and output (displacement responses) are obtained by only using cameras and computer vision techniques. Multiple cameras are synchronized by audio signal pattern recognition. The proposed system is verified with a laboratory experiment on a scaled bridge model under a small moving truck load and a field application on a footbridge on campus under a moving golf cart load. The UILs are successfully identified in both bridge cases. The pedestrian loads are also estimated with the extracted UIL and the predicted weights of pedestrians are observed to be in acceptable ranges.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.3
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• pp.677-684
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• 2018

Recently, negative emotional responses by drivers are a growing problem, which leads to not only a traffic accident but a crime so called 'road rage' in countries with heavy traffics including South Korea. Under such a circumstance, measuring stress- and fatigue-induced emotional responses by means of wireless communication and a wearable system would be useful. The purpose of this study is to implement a system that measures various signals from a driver, derives and monitors his emotional responses from the measurements and verify its derivations with reliability. This paper, as a first part of the research, describes how the system has been implemented with experimental methods.

• Smart Media Journal
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• v.5 no.3
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• pp.81-87
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• 2016

In line with the sharp increase of container traffic from globalization, ships have become larger with an aim of improving the maritime transport capacity in addition to the growing interest in monitoring danger areas on ships considering the quantity increase of ships, along with the tightening of international standard for ship safety by IMO(international Maritime Organization). Korea established a location based ship accident forecasting and preventing system in 2012 by Korea Coast Guard, however its poor response in ship accidents has been pointed out in the wake of the recent disaster of Sewol ferry. To resolve this problem, this study attempts to design a wearable type, instant emergency response system that has DGPS to issue an alert on danger areas and automatically send ship's location and operation information in emergency situation.

• Journal of Korean Society of Transportation
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• v.22 no.2 s.73
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• pp.95-102
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• 2004

The COSMOS is an adaptive traffic control systems that can adjust signal timing parameters in response to various traffic conditions. To evaluate the performance of the COSMOS systems, the field study is only practical option because any evaluation tools are not available. To overcome this limitation, a newly integrated interfacing simulator between a microscopic simulation program and COSMOS was developed. In this paper, a detector module and a signal timing module as well as general feature of the simulator were described. A validation test was performed to verify the accuracy of the data flow within the simulator. It was shown that the accuracy level of information from the simulator was high enough for real application. Several practical comments on further studies were also included to enhance the functional specifications of the simulator.

• Industrial Engineering and Management Systems
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• v.4 no.2
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• pp.176-183
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• 2005

The theory of signal detection has been applied to a wide range of practical situation for a long time, including sonar detection, air traffic control and so on. In general, in this theory, sensitivity parametric index d' and bias parametric index $\beta$ are used to evaluated the performance of vigilance. These indices use observer's response "hit" and "false alarm" to explain and evaluate vigilance, but not considering reaction time. However, the reaction time of detecting should be considered in measuring vigilance in some supervisory tasks such as unlimited monitoring tasks (e.g., supervisors in nuclear plant). There are some researchers have used the segments of reaction time to generate a pair of probabilities of hit and false alarm probabilities and plot the receiver operating characteristic curve. The purpose of this study was to develop a quantitative vigilance-measuring model by fuzzy sets, which combined the concepts of hit, false alarm and reaction time. The model extends two-values logic to multi-values logic by membership functions of fuzzy sets. A simulated experiment of monitoring task in nuclear plant was carried out. Results indicated that the new vigilance-measuring model is more efficient than traditional indices; the characteristics of vigilance would be realized more clearly in unlimited monitoring task.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.4B
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• pp.566-575
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• 2010

In recent, artificial immune system has become an important research direction in the anomaly detection of networks. The conventional artificial immune systems are usually based on the negative selection that is one of the computational models of self/nonself discrimination. A main problem with self and non-self discrimination is the determination of the frontier between self and non-self. It causes false positive and false negative which are wrong detections. Therefore, additional functions are needed in order to detect potential anomaly while identifying abnormal behavior from analogous symptoms. In this paper, we design novel network attack detection and response schemes based on artificial immune system, and evaluate the performance of the proposed schemes. We firstly generate detector set and design detection and response modules through adopting the interaction between dendritic cells and T-cells. With the sequence of buffer occupancy, a set of detectors is generated by negative selection. The detection module detects the network anomaly with a set of detectors and generates alarm signal to the response module. In order to reduce wrong detections, we also utilize the fuzzy number theory that infers the degree of threat. The degree of threat is calculated by monitoring the number of alarm signals and the intensity of alarm occurrence. The response module sends the control signal to attackers to limit the attack traffic.