• Proceedings of the ESK Conference
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• 1995.10a
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• pp.208-213
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• 1995

The vehicle navigation system is developed for helping driver to retrieve driving information more easily and lastly. Navigation System informs driver many pieces of driving information - roadway structure and system, on-line traffic condition, the position of vehicle, route guidance, destination and other infor- mation service. As the style of information is diverse and the amount of information is large, driver may have mental and visual overload. The display of information can disturb the driver's attention and this can cause accidents. This state is caused by the defect of human-machine interactions. When the navigation system is designed, human factors - cognitive, judgment, operating -must be considered. The display style must be designed simply and easily, not to be obstacle of human - machine interface. In this study, outside- in view display style and inside-out view display style are compared each other. Tow factors are measured. One is cognitive factor-time of cognition on information that is displayed by screen display, cognition error rate. The other is image of screen display - subject's feeling about several styles of display, degree of subject's preference. The prototype of roadway is four kinds -Cross, T-cross and O-cross. Roadway display for test is taken from paper maps. Traffic condition display style, vehicle position display style and route guidance display style are taken from current display style. Traffic condition display style is symbol. vehicle position display style and route guidance display style are described as color and symbol. The test on screen display is implemented doing given tasks. Then the test is analyzed statistically. The result of test analysis gives the guideline to the designer for the map display of the vehicle navigation system.

• Journal of Korean Society for Atmospheric Environment
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• v.28 no.1
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• pp.94-104
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• 2012

The purpose of this research is to quantify the compliance of on-road emission from a light duty diesel vehicle, based on a comparison to emission regulation standard. $NO_x$, CO and THC emissions were measured using a portable device on a selected real-world driving route with a length of approximately 22 km. On-road measurements were repeated by 10 times on a same route to reflect variability in traffic conditions. A test route was divided into 22 road links with length of 1 km to analyze emission results with higher spatial resolution. The average emissions of $NO_x$, CO and THC over total travel distance, which is approximately 220 km, were quantified to be in compliance with emission regulation standards. Under higher spatial resolution, $NO_x$ concentration exceeded a standard in 92 links out of 220 links. The extended time in stop period and the stop-and-go driving cycle were identified as two important reasons for increased $NO_x$ emissions in observed cases. Heavy traffics showed higher $NO_x$ emissions than free flow. These results indicate that the real-world vehicle emissions might exceed the compliance level associate with traffic conditions. Another interesting observation of this research is that the on-road emission characteristics can be independent to the average speed of road links with higher spatial resolution. Variability in on-road emission might not be fully described by solely relying on an average speed, because variability in traffic conditions and road conditions can influence on real-world vehicle emissions.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.18 no.36
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• pp.49-59
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• 1995

The vehicle navigation system is developed for helping driver to retrieve driving information more easily and fastly. Navigation System informs driver many pieces of driving information - roadway structure and system, on-line traffic condition, the position of vehicle, route guidance, destination and other information service. As the style of information is diverse and the amount of information is large, driver may have mental and visual overload. The display of information can disturb the driver's attention and this can cause accidents. This state is caused by the defect of human-machine interactions. When the navigation system is designed, human factors - cognitive, judgment, operating - must be considered. The display style must be designed simply and easily, not to be obstacle of human -machine interface. In this study, outside-in view display style and inside-out view display style are compared each other. Two factors are measured. One is cognitive factor-time of cognition on information that is displayed by screen display, cognition error rate. The other is image of screen display - subject's feeling about several styles of display, degree of subject's preference. The prototype of roadway is four kinds - Cross, T-cross, Y-cross and O-cross. Roadway display for test is taken from paper maps. Traffic condition display style, vehicle position display style and route guidance display style are taken from current display style. Traffic condition display style is symbol. Vehicle position display style and route guidance display style are described as color and symbol. The test on screen display is implemented doing given tasks. Then the test is analyzed statistically, The result of test analysis gives the guideline to the designer for the map display of the vehicle navigation system.

• The Journal of Information Systems
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• v.31 no.3
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• pp.47-65
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• 2022

Purpose With the recent development of Big Data and Artificial Intelligence technology, self-driving technology has developed into three stages (partial self-driving) or four stages (conditional self-driving), it is expected to bring a new paradigm to transportation in the city. Although many researchers are researching related technologies, there is no research on self-driving for disabled persons. In this study, the basic research was conducted based on the assumption that the shared self-driving car used by the disabled person is similar to the special transportation currently driving. Design In this study, data analysis and machine learning techniques were utilized to analyze the mobility patterns of disabled persons by type and to search for leading factors affecting the traffic volume of special transportation. Findings The study found that external physical disorders and developmental disorders often visit general welfare centers, internal organ disorders often visit general hospitals, and the elderly and mental disorders have various destinations. In addition, machine learning analysis showed that the main transportation routes for the disabled person use arterial roads and auxiliary arterial roads and that the ratio of building usage-related variables affecting the use of special transportation for a disabled person is high. In addition, the distance to the subway and bus stops was also mentioned as a meaningful variable. Based on these analysis results, it is expected that the necessary infrastructure for shared self-driving cars for disability person traffic will be used as meaningful research data in the future.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.57 no.1
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• pp.34-44
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• 2021

In order to collect basic information of response behavior of red seabream (Pagrus major) during pilling, works for constructing wind power station in Byeonsan Peninsular, Korea were investigated. Four cultured red seabream CRB1 to CRB4 [total length (TL): 27.1 ± 1.0 cm; body weight: 359 ± 30 g] were tagged with an acoustic tag and used in experiment. CRB1 and CRB2 to CBR4 were released on the sea surface at same time around the constructing site of the wind power plant on September 22, 2017 and July 18, 2018, respectively. The tracking of the CRB1 to CRB2 and CRB3 to CRB4 were conducted for two hours, approximately, using VR100 receiver including a directional hydrophone and VR2W receivers array consisted of 19 presence/absence receivers (VR2W receivers), respectively. The underwater noise level before (no pile driving works) and during pile driving works was measured 116.0-118.0 dB (re 1��Pa) and a maximum of 160 dB (re 1��Pa), respectively. CRB1 moved about 6.0 km with average swimming speed of 80.2 ± 20.5 cm/s for 2.1 hours without pile driving work. The average water depth of the sea bed on the route of CRB1 was 9.1 ± 0.4 m. CRB2 moved about 7.3 km with the average swimming speed of 96.8 ± 27.1 cm/s for 2.1 hours with pile driving work. The water depth of the sea bed on the route of CRB2 was 11.9 ± 0.6 m. At results of the Rayleigh's z-test two fishes CRB1 and CRB2 showed significant directionality in the movement (p < 0.01). Movement mean angles of CRB1 and CRB2 were 92.7 and 251.8°, respectively. CRB2, CRB3 and CRB4 exhibited the escaping behavioral response from the noise of source during the pile driving work. The swimming speed of the CRB2 exposed on the heavy underwater noise stimuli due to the pile driving work was 1.21 times faster than that of the CRB1 exposed on the ambient underwater noise in the study site.

• 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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.4
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• pp.549-557
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• 2021

In this research, we will use the existing OID sensor environment for smart robots, which are a type of educational robot, but we would like to propose that the problem of running be handled by a program. Maybe you have driving information We are building a driving test environment focusing on environment, position recognition, route planning, obstacle avoidance and path reset, and it is not the average final error rate, but the time when the error increases The experiment was conducted by a household that catches the moment of recalibration. Through the process, stable running results were obtained compared to the previous experiment. In this research, I think that it will be a development method that can improve the running performance of educational robots equipped with low-cost sensors currently on the market.

• Safety and Health at Work
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• v.13 no.2
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• pp.148-154
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• 2022

Background: Bus driving is a mentally demanding activity that requires prolonged attention to ensure safety. The aim of the study was to assess mental fatigue caused by driving a public bus and to find a profile of workers at higher risk. Methods: We evaluated changes of critical flicker fusion (CFF) (index of central arousal) and heart rate variability (HRV) (index of autonomic balance) in a 6-hour driving shift on a real route, in 31 professional bus drivers, and we tested the influence of personal factors such as sleep quality, BMI, and age. Paired t-test was used to test differences of CFF and HRV between both initial and final phase of driving, while multiple linear regression tested the influence of personal variables on the indexes of mental fatigue. Results: Results showed that CFF significantly decreased after 6 hours of bus driving (41.91 Hz, sd 3.31 vs. 41.15 Hz, sd 3.15; p = 0.041), and heart rate significantly decreased in the final phase of driving, with respect to the initial phase (85 vs. 78 bpm, p = 0.027). Increasing age (beta = -0.729, p = 0.022), risk of obstructive sleep apnea syndrome (beta = -0.530, p = 0.04), and diurnal sleepiness (beta = -0.406, p = 0.017) showed a significant effect on influencing mental fatigue. Conclusion: Elderly drivers at higher risk of sleep disorders are more prone to mental fatigue, when exposed to driving activity. Monitoring indexes of central arousal and autonomic balance, coupled with the use of structured questionnaires can represent a useful strategy to detect profile of workers at higher risk of mental fatigue in such duty.

• Journal of Korean Society for Geospatial Information Science
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• v.13 no.4 s.34
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• pp.39-46
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• 2005

This paper use virtual running after possible traffic capacity application for optimal route location. General road is designed the design after we examine an alternate adequacy investigation and an execution design sufficiently. Various road user's requirement must be reflected from the beginning. But it is difficult to contain the various suitable design criteria because we consider the existing 2-dimension element. First of all, this study chose optimal route, used traffic assignment and 3D simulation. Then selected optimal route through the consistent road construction by analyzing road driving simulation of 3-dimension data and the urban landscape. possible traffic capacity and virtual running will be able to do the urban landscape analysis harmonizing with the environment; equally, it could be objectively solve the problem of a civil appeal.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.1
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• pp.265-275
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• 2023

The purpose of this paper is to devise an optimal route allocation algorithm for automated vehicle(AV) in monitoring quality of road infrastructure to support the road safety. The tasks of an AV in this paper include visiting node-links at least once during its operation and checking status of road infrastructure, and coming back to its depot.. In selecting optimal route, its priority goal is visiting the node-links with higher risks while reducing costs caused by operation. To deal with the problem, authors devised reward maximizing algorithm for AVs. To check its validity, the authors developed simple toy network that mimic node-link networks and assigned costs and rewards for each node-link. With the toy network, the reward maximizing algorithm worked well as it visited the node-link with higher risks earlier then chinese postman route algorithm (Eiselt, Gendreau, Laporte, 1995). For further research, the reward maximizing algorithm should be tested its validity in a more complex network that mimic the real-life.