• Journal of The Korean Society of Agricultural Engineers
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• v.57 no.4
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• pp.39-49
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• 2015

Since most medical facilities and medical personnel are concentrated in urban areas in South Korea, an imbalance of access to medical facilities causes a gap in medical resource availability between urban and rural areas. Accessibility to medical facilities is a means of assessment that evaluates a measure of inequality in utilization of medical resources. The evaluation of accessibility uses Euclidean distance, in general; however, this method has its limits in that Euclidean distance cannot reflect actual distance. This study aims to estimate real road distance from village halls to medical facilities in rural areas using Open Application Programming Interface (Open API) of an internet portal site. Using real road distance, we evaluated medical accessibility and compared it with Euclidean distance. The accessibility to primary medical institutions was valued relatively well, but secondary and tertiary medical institutions were vulnerable in Pyeonchang-gun. Comparing Euclidean distance with real road distance from village halls to medical facilities, real road distance appeared to be approximately 1.4 times that of Euclidean distance. This calculation is similar to the circuity factor of Gangwon-do in Korea that estimated to fix the limits of Euclidean distance and assumed real road distance.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.4D
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• pp.291-303
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• 2012

In order to lead safe driving, it is better to provide dynamic and detailed information on how the driver using the relevant road should behave as concerning movements of individual car rather than providing monotone and static information of reducing of speed to unspecified drivers. Assuming road and communication of highway where real-time collection and transfer of information on vehicles and road traffic status is possible, the purpose of this study was to provide real-time safe distance by considering road traffic condition such as road condition and driving condition, travel speed and distance between preceding/following vehicles. We intended to provide basic information about dangerous situation by defining different values of condition based column ($C_{condition}$) in accordance with the road surface condition, based on which Real-time Safety Distance Index(RSDI) is to be calculated comprehensively reflecting speed of preceding and following vehicles, distance between vehicles, vertical alignment and road surface condition on the scope of expression column ($C_n$). We intended to enable the driver to secure safety by providing the calculated Real-time Safety Distance Index (RSDI) so that the driver can intuitively sense and sufficiently cope with a dangerous situation where collision of vehicles may occur. The calculated RSDI value is comprised of 30 unit columns and will be provided to the driver being divided into risk evaluation grades of 3 predetermined steps, 'warning', 'dangerous' and 'normal'.

• Journal of the Korean Society of Safety
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• v.28 no.5
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• pp.71-77
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• 2013

This Study aims at investigating actual condition on attending school road of children and analyzing empirically the characteristics of cognition and the influence of safety on school road. This study findings are as follows : 1) Walking alone to go to school is the highest rates among Commuting Mode, and Commuting distance to school is nearly doubles than range of school zone(300 m). 2) Among characteristics of urban spatial structure affecting on influence classify safety of school road, 'Commuting Distance' has been drawn to most influential variable. Especially, there are 4 types classified by commuting distance and it became obvious that the longer the distance, the lower the safety score(under 127 m=76.9 points, Over 451 m=58.3 points). 3) As a result of investigating the influence of Safety on attending school road, Vehicle commuting speed urder 127 m as internal of school zone, and Walking and crossing convenience over 451 m as external of school zone have a lot of influence on safety cognition on school road. Therefore Safety on school road should be considering the commuting distance to school among surrounding characteristics, needed for improvement plan and program based on real safety cognition of children.

• Journal of Korea Multimedia Society
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• v.20 no.4
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• pp.649-659
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• 2017

Typically, a smart car is equipped with access to the Internet and a wireless local area network. Moreover, a smart car is equipped with a global positioning system (GPS) based navigation system that presents a map to a user for recommending the shortest path to a desired destination. This paper presents the design and implementation of a real-time shortest path search system for directed and dynamic roads. Herein, we attempt to simulate real-world road environments, while considering changes in the ratio of directed roads and in road conditions, such as traffic accidents and congestions. Further, we analyze the effect of the ratio of directed roads and road conditions on the communication cost between the server and vehicles and the arrival times of vehicles. In this study, we compare and analyze distance-based shortest path algorithms and driving time-based shortest path algorithms while varying the number of vehicles to search for the shortest path, road conditions, and ratio of directed roads.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.12
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• pp.2665-2674
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• 2012

This paper propose the method to recognize the lanes and distance between cars in real-time which detects dangerous situations and helps safe driving in the actual road environment. First of all, it extracts the area of interest corresponding to roads and cars from the road image photographed by using the forward-looking camera. Through the hough transform for the area of interest, this study detects linear components and also selects the lane and conducts filtering by calculating probability. And through the shadow threshold analysis of the cars in front within the area of interest, it extracts the objects of cars in front and calculates the distance from cars in front. According to the result of applying the suggested technology to recognize the lane and distance between cars to the road situation for testing, it showed over 95% recognition rate; thus, it has been proved that it can respond to safe driving.

• Journal of Korean Society of Transportation
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• v.29 no.1
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• pp.47-55
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• 2011

The purpose of this study was to determine the legibility distance for traffic road sign and traffic sign, fixation duration and number of fixation during the time of recognition of traffic road signs under different vision conditions. This experiment was conducted on a closed-road circuit which has realistic driving road and environment Each participant drove the real vehicle for the experiment and specially built traffic road sign for the experiment and traffic road signs on the side of closed-road circuit were used. Different vision conditions were simulated using spectacle lenses to reach visual acuity 1.0 and 0.8 and it was 1.2 without spectacles and each participant tested under 3 vision conditions.. The result of this study demonstrated that there was a significant difference on legibility distance between visual acuity of 1.2 and 0.8 and there were also significant difference on fixation duration and number of fixations with smaller traffic signs. This study demonstrated the importance of vision correction for driving at night-time, also showed there would be difference on legibility distance and efficiency of eye movement such as fixation duration and number of fixation despite of satisfied visual acuity for driver's license requirement.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.4
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• pp.131-140
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• 2012

The shortest path search algorithm of navigation is generally based on Dijkstra algorithm and considers only the distance using the weight. Dijkstra algorithm based on the distance mainly ought to perform the 'number of nodes 1' and requires a lot of memory, for it is to start from the starting node and to decide the shortest path for all the nodes. Also, it searches only the same identical path in case of any bottleneck due to an accident nearby, since it is based only on the distance, and hence does not have a system that searches the detour road. In order to solve this problem, this paper considers only the travelling time per road (travelling speed * distance), without applying speed criteria (smoothness, slow speed, stagnation and accident control) or road class (express road, national road and provincial road). This provides an advantage of searching the detour, considering the reality that there are differences in time take for the car to travel on different roads with same distance, due to any accident, stagnation, or repair construction. The suggested algorithm proves that it can help us to reach the destination within the shortest time, making a detour from any congested road (outbreak) on providing an information on traveling time continuously(real-time) even though there is an accident in a particular road.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.97-100
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• 1996

In this paper, we describe an algorithm which estimate road following direction using the vanishing point property and obstacle detection. This method of detecting the lane markers in a set of continuous lane highway images using linear approximation is presented. This algorithm is designed for accurate and robust extraction of this data as well as high processing speed. Also, this algorithm reckon distance and chase about an obstacle. It include four algorithms which are lane prediction, lane extraction, road following parameter estimation and obstacle detection algorithm. High accuracy was proven by quantitative evaluation using simulated images. Both robustness and the practicality of real time video rate processing were then confirmed through experiment using VTR real road images.

• Journal of Korea Spatial Information System Society
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• v.9 no.1
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• pp.59-77
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• 2007

Advances in mobile techknowledges and supporting techniques require an effective representation and analysis of moving objects. Similarity search of moving object trajectories is an active research area in data mining. In this paper, we propose a trajectory search algorithm for spatio-temporal similarity of moving objects on road network. For this, we define spatio-temporal distance between two trajectories of moving objects on road networks, and propose a new method to measure spatio-temporal similarity based on the real road network distance. In addition, we propose a similar trajectory search algorithm that retrieves spatio-temporal similar trajectories in the road network. The algorithm uses a signature file in order to retrieve candidate trajectories efficiently. Finally, we provide performance analysis to show the efficiency of the proposed algorithm.

• Journal of Auto-vehicle Safety Association
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• v.14 no.2
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• pp.57-69
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• 2022

Recently, as interest in self-driving cars has increased worldwide, research and development on the Advanced Driver Assist System is actively underway. Among them, the purpose of Adaptive Cruise Control (ACC) is to minimize the driver's driving fatigue through the control of the vehicle's longitudinal speed and relative distance. In this study, for the research of the ACC test in the real environment, the real-road test was conducted based on domestic-road test scenario proposed in preceding study, considering ISO 15622 test method. In this case, the distance measurement method using the dual camera was verified by comparing and analyzing the result of using the dual camera and the result of using the measurement equipment. As a result of the comparison, two results could be derived. First, the relative distance after stabilizing the ACC was compared. As a result of the comparison, it was found that the minimum error rate was 0.251% in the first test of scenario 8 and the maximum error rate was 4.202% in the third test of scenario 9. Second, the result of the same time was compared. As a result of the comparison, it was found that the minimum error rate was 0.000% in the second test of scenario 10 and the maximum error rate was 9.945% in the second test of scenario 1. However, the average error rate for all scenarios was within 3%. It was determined that the representative cause of the maximum error occurred in the dual camera installed in the test vehicle. There were problems such as shaking caused by road surface vibration and air resistance during driving, changes in ambient brightness, and the process of focusing the video. Accordingly, it was determined that the result of calculating the distance to the preceding vehicle in the image where the problem occurred was incorrect. In the development stage of ADAS such as ACC, it is judged that only dual cameras can reduce the cost burden according to the above derivation of test results.