• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.9
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• pp.1088-1095
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• 2019

The information and communication technology that is being developed recently has been greatly influencing the automobile market. In recent years, devices equipped with IT technology have been installed for the safety and convenience of the driver. However, it has the advantage of increased convenience as well as the disadvantage of increasing traffic accidents due to driver's distraction. In order to prevent such accidents, it is necessary to develop safety systems of various types and ways. In this paper implements a platform that can recognize LDWS and FCWS and PDWS by using a single camera without using radar sensor and camera fusion and stereo camera method using two or more sensors, and proposes to study multi-function driving safety platform using a single camera by analyzing recognition rate evaluation and validity on a vehicle.

• Science of Emotion and Sensibility
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• v.16 no.2
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• pp.195-206
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• 2013

The main causes of traffic accidents while driving a car is of the driver's visual distraction. In this study, the color sensitivity of the information projected on the windshield were evaluated for HUD (Head Up Display) system which helps the driver's eyes on the road while driving. The driving Information were projected $9^{\circ}$ downward from front sight $0^{\circ}$ under lab's fluorescent lights, LED floorlights and the TV had having 25 [lux] illumination when driving at night environment and 100,000 [lux] of daylight environment. Munsell color hue of the basic five colors (R, Y, G, B, P) and the color of traffic lights YR, W were the color of the seven characters, each character were outlined by White, Gray except for W. Total of 19 experimental stimuli was shown in the environment of day and night driving for asking visibility information of color, fatigue, preferences, and evaluate the degree of interference. The results came out that the bright Y and G color is visibility significantly for daylight. Second, with the outline of the text, the color of the outline works as a background for luminance contrast effects and affects visibility. Third, without the outline, the glass in front of the vehicle acts as the background and the luminance contrast of characters achieve greater brightness and visibility. The luminance contrast between the stimuli and background should be considered for increasing color visibility for driving information which is an important factor for HUD commercialization.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39B no.8
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• pp.544-554
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• 2014

In this paper, we introduce a cyber-physical intersection systems (CPIS) which intimately interconnects roadside units (RSU) located at intersection, on-board units (OBU) of moving vehicles, and smartphone apps. Based on the architecture of CPIS, we also present a green light optimal speed advisory based on the reference mobility models (GLOSA-RMM) to reduce intersection stopping time (IST) and fuel consumption. Based on several reference mobility models, the GLOSA-RMM determines the appropriate speed advisory by taking into account the current mobility and the intersection traffic light status, and then provides screen/voice GLOSA instructions to minimize the driver's distraction. We show that the GLOSA-RMM can reduce both the IST and the fuel consumption through the numerical results obtained from the prototype of the CPIS consisting of the OBU, the RSU and the smartphone app.

• Korean Journal of Culture and Social Issue
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• v.17 no.2
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• pp.175-197
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• 2011

This study aimed to expand and reconstruct the Driving Behavior Determinants' factors in order to confirm the relationship between Driving Behavior Determinants(DBD) and drivers' reckless driving behavior level. To expand the structure of DBD, drivers anger, introversion and type A characteristics were added, which were never considered as related factors in existing DBD studies before. The correlations between the new factors of DBD and reckless driving behavior(includes driver's personal records of driving experiences for the last three years) were verified. A factor analysis result showed us that new DBD questionnaire consists of five factors such as, 'Problem Evading', 'Benefits/Sensation Seeking', 'Anti-personal Anxiety', 'Anti-personal Anger', and 'Aggression'. Also, reckless driving behavior consists of 'Speeding', 'Inexperienced Coping', 'Wild Driving', 'Drunken Driving', and 'Distraction'. The result of correlation between the DBD and reckless driving behavior indicates that inappropriate level of DBD is highly correlated with dangerous driving behavior and strong possibilities of traffic accidents. Based on these results, we might be able to discriminate drivers according to DBD level and predict their reckless driving behavior through a standardization procedure. Futhermore, this will make us to provide drivers differentiated safety education service.