• 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 Korea Institute of Intelligent Transport Systems
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• v.13 no.2
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• pp.27-33
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• 2014

This paper proposes a gradation image processing method for the development of a Road Sign Recognition Platform (RReP), which aims to facilitate the rapid and accurate management and surveying of approximately 160,000 road signs installed along the highways, national roadways, and local roads in the cities, districts (gun), and provinces (do) of Korea. RReP is based on GPS(Global Positioning System), IMU(Inertial Measurement Unit), INS(Inertial Navigation System), DMI(Distance Measurement Instrument), and lasers, and uses an imagery information collection/classification module to allow the automatic recognition of signs, the collection of shapes, pole locations, and sign-type data, and the creation of road sign registers, by extracting basic data related to the shape and sign content, and automated database design. Image division and merging, which were applied in this study, produce superior results compared with local binarization method in terms of speed. At the results, larger texts area were found in images, the accuracy of text recognition was improved when images had been gradated. Multi-threshold values of natural scene images are used to improve the extraction rate of texts and figures based on pattern recognition.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.5
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• pp.126-134
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• 2009

This paper describes the vision-based system to track road signs from within a moving vehicle. The proposed system has the standard architecture with particle filter due to its robust tracking performance in complex environment. In the case of tracking road signs in real environment, it has a great difficulty in predicting time series data by reason of an occlusion due to an obstacle and the rapid change of objects on roads. To overcome this problem and improve the tracking performance, this paper proposes the algorithm using an autoregressive model as an state transition model which has affine parameters as states and using robust statistics for determining occlusion due to obstacles. The experiments of this paper show that the proposed method is efficient for real time tracking of road signs and performs well in road signs under occlusion due to obstacles.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.4
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• pp.190-211
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• 2022

This study investigated the effect of the shape and height of road signs on detection performance when detecting road signs with LiDAR, which is recognized as an essential sensor for autonomous vehicles. For the study, four types of road signs with the same area and material and different shapes were produced, and a road driving test was performed by installing a 32Ch rotating LiDAR on the upper part of the vehicle. As a result of comparing the shape of the point cloud and the NPC according to the shape of the road sign, It is expected that a distance of less than 40m is required to recognize the overall shape of a road sign using 32Ch LiDAR, and shapes such as triangles and rectangles are more advantageous than squares in securing the maximum point cloud from a long distance. As a result of the study according to the height of the road sign, At short distances (within 20m), if the height of the sign is raised to more than 2m, it deviates from the vertical viewing angle of the LiDAR and cannot express the complete point cloud shape. However, it showed a negligible effect compared to the near-field height change. These research results are expected to be utilized in the development of road facilities dedicated to LiDAR for the commercialization of autonomous cooperative driving technology.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.11
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• pp.1088-1095
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• 2009

In this paper, we describe the reorientation method of distorted road sign by using projection transformation for improving recognition rate of road sign. RSR (Road Sign Recognition) is one of the most important topics for implementing driver assistance in intelligent transportation systems using pattern recognition and vision technology. The RS (Road Sign) includes direction of road or place name, and intersection for obtaining the road information. We acquire input images from mounted camera on vehicle. However, the road signs are often appeared with rotation, skew, and distortion by perspective camera. In order to obtain the correct road sign overcoming these problems, projection transformation is used to transform from 4 points of image coordinate to 4 points of world coordinate. The 4 vertices points are obtained using the trajectory as the distance from the mass center to the boundary of the object. Then, the candidate areas of road sign are transformed from distorted image by using homography transformation matrix. Internal information of reoriented road signs is segmented with arrow and the corresponding indicated place name. Arrow area is the largest labeled one. Also, the number of group of place names equals to that of arrow heads. Characters of the road sign are segmented by using vertical and horizontal histograms, and each character is recognized by using SAD (Sum of Absolute Difference). From the experiments, the proposed method has shown the higher recognition results than the image without reorientation.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.3
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• pp.119-127
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• 2019

In this study, we investigated the application of deep learning to the manufacturing process of traffic and road signs which are constituting the road layer in map production with 1 / 1,000 digital topographic map. Automated classification of road traffic sign images was carried out through construction of training data for images acquired by using transfer learning which is used in image classification of deep learning. As a result of the analysis, the signs of attention, regulation, direction and assistance were irregular due to various factors such as the quality of the photographed images and sign shape, but in the case of the guide sign, the accuracy was higher than 97%. In the digital mapping, it is expected that the automatic image classification method using transfer learning will increase the utilization in data acquisition and classification of various layers including traffic safety signs.

• International Journal of Highway Engineering
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• v.8 no.4 s.30
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• pp.37-47
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• 2006

The road sign is one of street furnitures functioning to guide directions for drivers. The road sign should be employed and designed to help drivers find their destinations easily and accurately. It is obvious that the road sign is one of the main components that enhance efficiency and safety of driving environments. The current way of guiding strategy at road signs in Korea is a system for mainly guiding 'points' although a new system guiding 'road names' and 'street numbers' with the introduction of new address system is now being introduced on urban areas. When the regional territory management offices and local governments try to employ current road sign systems, they are supposed to follow the sign regulations which contains standard project processes, selection methods of guiding points, character size and design, and location selection for each road sign. However, the current road sign regulations are very complex to understand and unclear for a person in charge to do tasks described above. Especially, selection process and criteria of guiding points are cumbersome and controversial. Furthermore, non sufficient ways of selecting guiding points considering road functions and geographic characteristics decrease the connectivity of guiding points. This study develops enhanced ways of increasing connectivity of successive guiding points through three case studies. Developed ways will help highway agencies and officials understand how to improve the connectivity of road signs.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.6
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• pp.1-9
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• 2016

Place names of road sign mean various place names being used on road signs for path guidance of drivers such as administrative district, facility, road, etc. It is very important that not only the choice method of place names for connectivity of road signs but standard establishment of spatial impact zone according to place names. However this standard are not established currently, so it is difficult to fix the spatial range for changing place names around the main facility according to the new construction or relocation of main facility in urban region. Considering the use of big data, one of the Government 3.0, we need to utilize actively the road sign management system database. This paper suggested a methodology for standard establishment of spatial impact zone according to place names of road sign in urban regions based on the road sign management system database. To perform a case study, we selected a major facility ("City Hall") which is the most frequently used the place name of road signs and presented standard of spatial impact zone by urban size in 84 cities.

• Journal of the Korean Society of Safety
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• v.31 no.5
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• pp.158-170
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• 2016

It has been applied several ways in order to prevent traffic accidents and speed management on the road which is one of very important factors to prevent accidents. In this study, it is analyzed whether the facility such as the flashing and crosswalk, speed cameras and intermittent warning signs affect on a driving deceleration or not. It has been shown that the flashing and crosswalk and speed cameras except intermittent warning signs play a role of reducing the driving speed. The result showed that these traffic safety facilities help to improve the average speed as well as velocity distribution which was derived by the speed deviation even if there were the difference between facilities. Speed limit display does not affect the deceleration of the driver. Therefore, it was founded in this research that there were the driving speed reduction effect due to the facilities on the road. In order to control the driving speed on the road, it is necessary to install facilities with appropriate location and spacing on the road. In addition, place that turns out suppressed speeding through speed management also are required adequate facilities such as speed cameras.

• Journal of Korean Society of Forest Science
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• v.94 no.2 s.159
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• pp.112-116
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• 2005

This study was conducted to obtain the information of distribution, protection and management for mammal species in fragmented forest areas around the road from June 2002 to May 2003 in 9 study sites of Baekdugdaegan mountains, Korea. Field signs of twelve mammals, moles Molera robusta, Korean hares Lepus coreanus, Manchurian chipmunk Tamias sibiricus, red squirrels Sciurus vulgaris, Korean racoon dogs Nyctereutes procyonoides, Siberian weasels Mustela sibirica, badgers Meles meles, otters Lutra lutra, Bengal cats Felis bengalensis, wild boars Sus scrofa, water deer Hydropotes inermis and roe deer Capreolus pygargus were recorded in this study. There were no differences in total number of species between 50 m areas and 50-100 m areas from road in snow and non-snow season. Number of mammals' field signs were different in non-snow season between both areas. Red squirrels and Siberian weasels were more abundant in 50 m areas, and Korean hares and Manchurian chipmunks were in 50-100 m areas. Habitat using pattern of mammal species may be affected by the road. Reasonable road construction and maintenance would be needed for protection and management of wildlife and their habitats.