• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.4
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• pp.243-251
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• 2019

The road sign location information installed on national roads is continuously updated using MMS (Mobile Mapping System) technology. It is possible to map accurate road facilities by MMS, but the equipment is very expensive and requires specialized technology. Also, the accuracy of the position of the object greatly depends on the GPS (Global Positioning System) accuracy. In the case of road facility mapping, the advantage of drone is more remarkable than that of field survey or conventional aerial photogrammetry. In particular, it is more efficient than field surveying and it is possible to acquire high resolution images with low budget compared to conventional aerial photogrammetry. In this study, the accuracy of the location information measured by the existing MMS is compared with the GPS survey result and the accuracy analysis is performed by the drone aerial photogrammetry. In order to confirm the space accuracy that can be obtained when conducting drone aerial photogrammetry, the accuracy of the change in the number of ground control points and the degree of overlap was evaluated. As a result of the experiment, it was possible to obtain sufficient accuracy with two ground control points distributed at both ends of the road and 60% overlap.

• International Journal of Computer Science & Network Security
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• v.24 no.8
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• pp.14-20
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• 2024

Traffic sign recognition is an essential feature of intelligent transportation systems and Advanced Driver Assistance Systems (ADAS), which are necessary for improving road safety and advancing the development of autonomous cars. This research investigates the incorporation of the YOLOv9 model into traffic sign recognition systems, utilizing its sophisticated functionalities such as Programmable Gradient Information (PGI) and Generalized Efficient Layer Aggregation Network (GELAN) to tackle enduring difficulties in object detection. We employed a publically accessible dataset obtained from Roboflow, which consisted of 3130 images classified into five distinct categories: speed_40, speed_60, stop, green, and red. The dataset was separated into training (68%), validation (21%), and testing (12%) subsets in a methodical manner to ensure a thorough examination. Our comprehensive trials have shown that YOLOv9 obtains a mean Average Precision (mAP@0.5) of 0.959, suggesting exceptional precision and recall for the majority of traffic sign classes. However, there is still potential for improvement specifically in the red traffic sign class. An analysis was conducted on the distribution of instances among different traffic sign categories and the differences in size within the dataset. This analysis aimed to guarantee that the model would perform well in real-world circumstances. The findings validate that YOLOv9 substantially improves the precision and dependability of traffic sign identification, establishing it as a dependable option for implementation in intelligent transportation systems and ADAS. The incorporation of YOLOv9 in real-world traffic sign recognition and classification tasks demonstrates its promise in making roadways safer and more efficient.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.1
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• pp.70-79
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• 2017

This study proposes a method to quickly and accurately acquire distance information on direction signs. The proposed method is composed of the recognition of the sign, pre-processing to facilitate the acquisition of the road sign distance, and the acquisition of the distance data. The road sign recognition uses color detection including gamma correction in order to mitigate various noise issues. In order to facilitate the acquisition of distance data, this study applied tilt correction using linear factors, and resolution correction using Fourier transform. To acquire the distance data, morphological operation was used to highlight the area, along with labeling and template matching. By acquiring the distance information on the direction sign through such a processes, the proposed system can be output the distance remaining to the next junction. As a result, when the proposed method is applied to system it can process the data in real-time using the fast calculation speed, average speed was shown to be 0.46 second per frame, with accuracy of 0.65 in similarity value.

• International Journal of Highway Engineering
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• v.18 no.1
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• pp.131-141
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• 2016

PURPOSES : While road networks are becoming increasingly complex, traffic signs are being indiscriminately installed and operated, which makes drivers who depend on traffic signs to reach their destination confused and unable to understand road information efficiently. In order to promptly and exactly guide road users to their destinations, traffic signs should be able to satisfy the functions of connectivity, visibility, and location suitability. However, the results of a site survey shows that most of the traffic signs currently installed in the Jeollanam-do Province do not satisfy these functions. METHODS : This study analyzed the problems of traffic signs after an actual site survey and focused on a total on 9,353 traffic signs and 70 road routes in Jeollanam-do Province. RESULTS : This study analyzed the problems of traffic signs based on their required functions (connectivity, visibility, suitability) and suggested improvements by establishing a guide system that considered the problems found in the study. CONCLUSIONS : The guide system can be utilized as a basic material that provides efficient road information for future installation and maintenance of traffic signs in Jeollanam-do Province.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.46 no.5
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• pp.29-37
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• 2009

This paper describes a vision-based and real-time system for detecting road signs from within a moving vehicle. The proposed system has the standard architecture with adaboost algorithm to detect road signs in real time. And it uses the value of vortical plane in the process of extracting candidate areas in view of fact that there are vertically most of signs on roads. Although being useful for detecting objects in real time, the conventional adaboost algorithm deteriorates the performance of detection rate in complex circumstance by reason of using only integral images as features. To overcome this problem, this paper proposes the method that improves the reliability of candidates as using the value of vertical plane for extracting candidate area and improves the performance of the detection rate as using integral images to which we add the kind of feature prototype. The experiments of this paper show that the detection rate of the proposed method has higher than that of the conventional adaboost algorithm under the real complex circumstance of roads.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.7 no.2
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• pp.100-109
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• 2008

Traffic accidents at night occur more than any other time because of improper road light facility and delineators. Therefore, cost-effective criteria of installing delineators are needed instead of expensive road light facility, especially, on rural road including light volume of traffic. This paper presents the criteria of installing 'Chevron Alignment Sign' considering driver's visual behavior characteristics and 'Raised Pavement Marker' considering critical encroachment angie of both straight section and curve one in order to reduce both the number of accidents on curve sections and the number of road encroachment accidents, respectively. The characteristics of visual behaviors can be expressed by visual angle involving curve radius and intersection angle. The estimated installing angles are $1^{\circ}{\sim}2.5^{\circ}$ by radii, which is based on changes in sensitivity across visual field by exogenous attention. Also, the raised pavement marker is installed every 2m, 3m, and 4m considering critical encroachment angles by radii.

• Journal of the Korean Institute of Rural Architecture
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• v.18 no.3
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• pp.25-34
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• 2016

The purpose of this study is to investigate installation status of information facilities and condition of walking road influencing to psychological safety of walking tourists. For this purpose, four roads for walking tour are selected; the course no. 16 of Jeju Olle Trail, Sarabong Byeoldobong walkway in Jeju and the course no. 8 of Bougil, Gyeongpo Lake walkway in Gangneung. Facilities installed on roads for walking tour are classified into four facilities; safety facility, information facility, amenity facility, local cultural facility. In order to consider installation status of information facilities and condition of walking road influencing to psychological safety of walking tourist, a field experiment was conduced focusing on the course no. 16 of Jeju Olle Trail. Thirteen cases were happened as confusing situation while walking tour. Of the 13 cases, the situation of being lost and wandering on the trail accounted for six cases. In contrast to the expectation that the situation of being lost and wandering would occur only at a crossroads, it is not that such situation took place at specific places like a crossroads or where direction signs were inaccurate. Walking tourists of this field experiment also confronted situations of having lost confidence about continuing the ongoing direction, of having anxiety over walking a walking trail, of feeling discomfort caused by walking and of being offended by uncomfortable or messy areas of walking trial. These confusing situations are happened inappropriate installation of direction sign, so direction sign is needed to install more carefully and detailed.

• 한국도로학회:학술대회논문집
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• 2010.09a
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• pp.489-492
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• 2010

• Journal of Korea Multimedia Society
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• v.16 no.4
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• pp.430-443
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• 2013

The recognition of current position and road surrounding of car is very important to driver for safe driving. This paper presents the recognition technique of the road traveling environment using position information hiding and viewpoint transform that monitors the information of road furniture and signature and notifies them to driver. The proposed scheme generates the road images into which the position information are hided, from car camera and GPS module and provides the road information to driver through the viewpoint transformation and the road signature detection. The driving tests with camera and GPS module verified that the position information hiding takes about 66.5ms per frame, the detection rate of road signature is about 95.83%, and the road signature detection takes about 227.45ms per frame. Therefore, we know that the proposed scheme can recognize the road traveling environment on the road video with 15 frame rate.

• Journal of the Korean Society of Safety
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• v.32 no.3
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• pp.123-129
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• 2017

This study deals with the traffic accident of truck at circular intersection. The purpose of this study is to develop the truck accident models based on type of accident and conflict. In pursuing the above, the study gives particular attentions to selecting the appropriate models among Poisson and Negative binomial models using statistical program LIMDEP 8.0. The traffic accident data from 2007 to 2014 are collected from TAAS data set of Road Traffic Authority. Such the dependent variable as number of truck accidents and the 24 independent variables as geometry, traffic volume and others are used. The main results are as follows. First, 5 Poisson models (${\rho}^2$ of 0.164~0.351) which are all statistically significant are selected. Second, the common variable based on type of accident and conflict is analyzed to be truck apron width. The specific variables are, however, evaluated to splitter island, area of splitter island, speed limit sign, truck apron, number approach road, circular intersection sign, speed hump and traffic volume. Finally, widening the truck apron width and improving the above specific variables are analyzed to be important for truck accident reduction at circular intersections.