• Korean Journal of Culture and Social Issue
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• v.22 no.1
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• pp.19-39
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• 2016

Though research has shown that public transportation drivers experience greater burnout than other drivers, the sources of their burnout and possible mediators remain largely unknown. In response, in this study we investigate the relationships among sensation seeking, Type A driving behavior, and meaning of work to elucidate the burnout experienced by bus drivers in Gyeonggi-do, South Korea. To collect data regarding these relationships, 188 bus drivers answered a questionnaire involving the sensation seeking scale, burnout scale, and meaning of work scale. Results showed that Type A driving behavior mediated the relationship between sensation seeking and burnout, while meaning of work moderated the mediated model. These findings demonstrate that sensation-seeking bus drivers tend to experience greater burnout given their tendency to exhibit Type A driving behavior, and this relationship depends on perceived meaning of work. This study therefore contributes meaningful information and outlines significant implications in understanding drivers' burnout.

• Proceedings of the Korean Society for Cognitive Science Conference
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• 2002.05a
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• pp.241-250
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• 2002

본 연구의 목적은 최근 운전자 행동에 대한 연구 방법으로 매우 중요하게 대두되고 있는 운전 시뮬레이션 방법을 이용하여 운전자들이 보이는 기본적인 운전 수행 능력 및 이러한 운전 수행 능력과 관련이 가장 깊은 것으로 기존의 연구들이 밝혀왔던 기본적인 지각적/인지적/운동적 수행 능력을 측정하여 운전자 수행을 평가하는 것을 목적으로 한다. 특히 운전자의 운전 수행 및 운전과 관련된 기본적인 정신/운동 수행 능력은 정보 처리적 관점에서 측정되고 분석되었으며, 이를 통해 운전자들이 보이는 기본적인 정보처리 능력의 패턴에 대한 전반적 이해를 시도하였다. 본 연구에서는 기본적인 운전 수행 능력을 평가하는데 사용되는 차량의 속도 유지와 차선 유지에 대한 측정치와 더불어 운전과 관련한 인간 수행 중에서 단순 반응 능력, 선택 반응 능력, 속도 추정 능력, 청각적 주의나 시각적 주의의 분산 능력 등이 운전 시뮬레이션을 통하여 운전 중에 실시간으로 측정되었다. 본 연구에서 수집된 자료는 운전자들의 실제 운전 수행 및 이와 관련된 정보 처리 활동에 대한 표준화된 준거를 제시하는데 기초적 자료로 사용될 수 있으리라 생각된다.

• Journal of Korean Society of Transportation
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• v.36 no.1
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• pp.51-65
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• 2018

Intentional aggressive driving (IAD) is defined as a hazardous driving event that the aggressive driver intentionally threatens neighbor drivers with abrupt longitudinal and lateral maneuvering. This study developed a methodology for detecting IAD events based on the analysis of interactions between aggressive driver and normal driver. Three major aggressive events including rear-close following, side-close driving, and sudden deceleration were analyzed to develop the algorithm. Then, driving simulation experiments were conducted using a multi-agent driving simulator to obtain data to be used for the development of the detection algorithm. In order to detect the driver's intention to attack, a relative evaluation index (Erratic Driving Index, EDI) reflecting the driving pattern was derived. The derived IAD event detection algorithm utilizes both the existing absolute detection method and the relative detection method. It is expected that the proposed methodology can be effectively used for detecting IAD events in support of in-vehicle data recorder technology in practice.

• Proceedings of the KSR Conference
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• 2001.10a
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• pp.350-357
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• 2001

본 논문은 고정폐색구간에서 차량운전 특성과 속도패턴이 다양한 다종의 열차들이 동일선로에서 복합되어 고밀도 운행을 위한 방법으로, 신호현시에 대한 제반정보를 차상으로 전송 받아 기관실 신호표시반에 신호를 현시 하는 차상신호방식(Cab Signalling System)중에서, 선행열차의 위치, 선로조건 등 지상의 상태정보를 후속열차가 수신하여 열차 자신의 제동특성 등 차량정보와 비교 분석하여 제동거리를 계산하는 distance to go 방식으로 열차운전속도를 제어하는 ATP (Automatic Train Protection) 시스템을 제안하였다. 폐색구간별 고정된 신호속도단계가 부여되는 ATC(Automatic Train Control) 시스템에서는 운행패턴이 같은 단일차종의 열차만 운행하는 구간에서는 일정속도에 의한 폐색구간 분할로 구간내 distance to go 신호체계가 이루어지지만, 차종과 속도패턴이 서로 상이한 복합열차들의 운행구간에서는 안전거리 확보를 위하여 저속열차의 제동거리를 기준으로 폐색구간 분할 및 속도결정이 이루어지므로 ATP 방식보다 운행효율이 다소 떨어짐을 알 수 있었다. 이를 차량특성과 속도패턴이 다른 3개의 열차를 모델로 하여 열차별 감속도에 의한 제동특성을 ATC와 ATP 신호제어체계에 접목시켜 시뮬레이션을 하였다.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.2
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• pp.98-112
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• 2018

Intentional aggressive driving (IAD) is a very dangerous driving behavior that threatens to attack the adjacent vehicles. Most existing studies have focused on the independent driving characteristics of attack drivers. However, the identification of interactions between the offender and the victim is necessary for the traffic safety analysis. This study established multi-agent driving simulation environments to systematically analyze vehicle interactions in terms of traffic safety. Time-to-collision (TTC) was adopted to quantify vehicle interactions in terms of traffic safety. In addition, a exponential decay function was further applied to compare the overall pattern of change in crash potentials when IAD events occurred. The outcome of this study would be useful in developing policy-making activities to enhance traffic safety by reducing dangerous driving events including intentional aggressive driving.

• Proceedings of the Korean Society of Computer Information Conference
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• 2011.01a
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• pp.107-108
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• 2011

Since the development of railway technology, the current urban Railway the first train line in the country for safe operation control automatic/unattended operation, automatic train operation equipment available (ATO) on time and reliable operation has introduced. ATO Automatic operation controlled by the value (Target velocity) and the feedback value (Actual velocity) by the error between the backing and braking of the train by repeated low energy efficiency. In this paper, given a fixed distance stations between time operation with minimal energy in the driving characteristics and driving trains are modeled. Therefore, in line 5 real route time sectional drive straight sections for experimental data analysis / draft Section / curved and section of the train on that line is selected according to the changing driving patterns to minimize the energy optimal driving patterns were presented.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.6
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• pp.1-12
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• 2009

Recently, as the importance of Economical Driving has been gradually growing up, the needs for research on automatic analysis of driving patterns that will ultimately provide drivers the methods for Economical Driving have been increasingly risen. Based on this purpose, we have executed two things in this paper. First, we have collected overall driving information such as date, distance, driving time, speed, idle time, sudden acceleration/deceleration count, and the amount of fuel consumption. Second, we have analyzed the influences of driving patterns on economical driving by employing the data mining techniques. These results can be applied in preventing bad driving patterns which will have consequently bad effects on Economical Driving in two aspects: by presenting some information on the terminal of the vehicles such as idle time, over-speed time, sudden acceleration/deceleration count continuously and by providing the drivers with alert information when the idle time ratio and the over-speed time ratio are excessive.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.947-950
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• 2015

In the cause of car accidents in Korea, drowsy driving has shown that it is larger fctors than drunk driving. Therefore, in order to prevent drowsy driving accidents, drowsiness detection and warning system for drivers has recently become a very important issue. Furthermore, Many researches have been published that measuring alpha wave of EEG signals is the effective way in order to be aware of drowsiness of drivers. In this study, we have developed EEG measuring device that applies a signal processing algorithm using the LabView program for detecting drowsiness. According to results of drowsiness inducement experiments for small test subjects, it was able to detect the pattern of EEG, which means drowsy state based on the changing of power spectrum, counterpart of alpha wave. After all, Comparing to the results of drowsiness pattern between commercial equipments and developed device, we could confirm acquiring similar pattern to drowsiness pattern. With this results, the driver's drowsiness prevention system expect that it will be able to contribute to lowering the death rate caused by drowsy driving accidents.

• Science of Emotion and Sensibility
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• v.13 no.1
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• pp.61-68
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• 2010

The objective of this study was to test the estimation possibility of driver's stress degrees with the HRV analysis. For this, first, HRV analysis was applied to the 5 driver's ECG signals which were acquired in 7 different stress situations. From this, the facts that HRV trend was different from that in long-distance driving and 6 parameters - meanRR, sdRR, HF, LF/HF, LFnorm, HFnorm were useful for the stress estimation in stress varying driving situation. Next, we designed 5 personalized linear regression models in which 6 HRV parameters were input and the outcomes were 7 different stress degrees. Finally, we tested each model for 5min-long 16 segments individually. Consequently, the models could not hit the stress degrees exactly in some segments but the correlation coefficients between original stress pattern and estimated stress pattern during entire driving showed reasonably high.

• Proceedings of the KIEE Conference
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• 2006.07e
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• pp.53-54
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• 2006

본 논문에서는 유도전동기의 고정자권선 고장진단을 목적으로 이상적인 전동기의 전류신호와 실시간으로 운전하고 있는 전동기 전류신호를 Park's Vector에 각각 적용시켜 Park's Vector 패턴을 만들고 패턴 피크값의 기준치와 측정치의 편차를 이용하여 오차치를 벗어날 때 고장으로 진단하는 Park's Vector 패턴의 피크값을 이용한 고정자권선의 고장진단을 시도하였다. 숙달된 작업자가 Park's Vector패턴을 보고 고장을 분석해야 했던 방법과는 달리 패턴을 비교하지 않고도 자동으로 고장을 진단하고 경보해주는 진단 방법을 제시하였다. 실제 전류분석 및 진단을 위해 상용 프로그램인 LabVIEW를 이용하였다.