• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.2
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• pp.471-476
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• 2004

This paper presents an active vision system for on-line traffic sign recognition. The system is composed of two cameras, one is equipped with a wide-angle lens and the other with a telephoto lends, and a PC with an image processing board. The system first detects candidates for traffic signs in the wide-angle image using color, intensity, and shape information. For each candidate, the telephoto-camera is directed to its predicted position to capture the candidate in a large size in the image. The recognition algorithm is designed by intensively using built in functions of an off-the-shelf image processing board to realize both easy implementation and fast recognition. The results of on-road experiments show the feasibility of the system.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.3
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• pp.416-421
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• 2008

This paper realizes a system that recognizes traffic safety signs by applying the principle used for game in reverse. The game used for this paper is one that expresses the shape of temporary objects intended by the maker when the maker sees the numerical image provided on (x, y) coordinates and then expresses it on the mesh. After separating the traffic safety sign image from the input image, the system is realized by outputting the content of the sign into letters by recognizing the forms and colors constituting the sign using the puzzle game above. Our system has fast process time and better rate of recognition than the existing system with black-and-white image processing and recognition without any penciling progress.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.115.3-115
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• 2001

In this paper, discrete-time cellular neural networks are designed in order to function as associative memories by using Hebbian learning rule and non-cloning template. The proposed method has a very simple structure to design and to learn. Weights are updated by the connection between the neuron and its neighborhood. In the simulation, the proposed method is applied to the classification of a traffic sign pattern.

• 한국방재학회:학술대회논문집
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• 2008.02a
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• pp.485-488
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• 2008

The structure supporting road sign is a road information facility for ensuring the safe transportation and smooth traffic. But, lots of road information facilities were damaged by the typhoon "Maemi" in 2003. Such damaged facilities should be rehabilitated and could increase economic loss by causing traffic accident. Therefore, in this study, behavior that reduce wind load and improve wind resistance of the structure supporting road sign are studied about wind load beyond design specification by abnormal climate as below. The first is wind load reducing technique such that shear key resist wind load that is not greater than design wind speed but in case that it is over the design wind limit, column member is rotated on the inner steel pipe axis by the brittle failure of shear key. The second is the technique such that fail-safe the overturning of road sign panel by equipment installation in the vertical member. The third is the technique of installing stiffening plate inside the vertical member to relieve stress concentration.

• Journal of KIISE
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• v.42 no.2
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• pp.203-212
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• 2015

This paper proposes a traffic sign recognition method in real road environments. The video stream in driving environments has two different characteristics compared to a general object video stream. First, the number of traffic sign types is limited and their shapes are mostly simple. Second, the camera cannot take clear pictures in the road scenes since there are many illumination changes and weather conditions are continuously changing. In this paper, we improve a modified census transform(MCT) to extract features effectively from the road scenes that have many illumination changes. The extracted features are collected by histograms and are transformed by the dense descriptors into very high dimensional vectors. Then, the high dimensional descriptors are encoded into a low dimensional feature vector by Fisher-vector coding and Gaussian Mixture Model. The proposed method shows illumination invariant detection and recognition, and the performance is sufficient to detect and recognize traffic signs in real-time with high accuracy.

• Journal of Korea Spatial Information System Society
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• v.10 no.2
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• pp.13-24
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• 2008

A next generation video based car navigation is researched to supplement the drawbacks of existed 2D based navigation and to provide the various services for safety driving. The components of this navigation system could be a load object database, identification module for load lines, and crossroad identification module, etc. In this paper, we proposed the traffic lights and road sign recognition method which can be effectively exploited for crossroad recognition in video-based car navigation systems. The method uses object color information and other spatial features in the video image. The results show average 90% recognition rate from 30m to 60m distance for traffic lights and 97% at 40-90m distance for load sign. The algorithm also achieves 46msec/frame processing time which also indicates the appropriateness of the algorithm in real-time processing.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.2D
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• pp.193-201
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• 2011

The provision of traffic information plays an important role in increasing social benefit not only by saving travel time for individuals but also by improving the efficiency of road operation. VMS(Variable Message Sign) helps on-wheel drivers easily understand the road situation, and also provides real-time traffic information to people on the streets. However, it has not been sufficiently studied on how traffic information based on VMS influences on the drivers' selection of route. This study investigated how drivers use VMS traffic information and how they are satisfied with it. Then, the model of drivers' route selection was specified with the types of traffic information and the expected travel time to examine the influence on the selection of drivers' route. The model was estimated and analyzed in three types according to the condition of detour roads, and the rate of route change and the degree of sensitivity was calculated from the estimation. The results of analysis are as follows. the $1^{st}$ type model showed the 10% of route change for the travel time saving of 5minutes, and the 81.6% of route change for the travel time saving of 20minutes. The $2^{nd}$ type led to the range of route change from 14.2% to 92.7% over the 5 through 20 minutes of travel time saving. The $3^{rd}$ model resulted in the 99.1% of route change. The sensitivity of route change showed the highest for the travel time saving of 11 minutes with the $1^{st}$ type model, 9 minutes with the $2^{nd}$ type model, and 5 minutes with the $3^{rd}$ type model respectively.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.7 no.4
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• pp.25-35
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• 2008

Variable Message Sign(VMS) is one of the subsystem of Intelligent Transportation Systems (ITS), which is useful for providing real-time information on weather, traffic and highway conditions. However, there are various situations such as incidents/accidents, constructions, special events, etc., which would be occurred on segments, it is unable to control traffic with only the VMS. Thus, it is essential to use of PVMS(Portable Variable Message Signs), which can move to the location needed traffic control and provide more active traffic information than VMS. This study developed a legibility distance model for PVMS messages using in-vehicle Differential Global Positioning Data(DGPS). Traffic conditions, drivers' characteristics, weather conditions and characteristics of PVMS message were investigated for establishing the legibility model based on multiple linear regression analysis. The factors such as height of PVMS characters, spot speed, age, gender and day and night were identified as dominants affecting the variation of legibility distances. It is expected that the proposed model would play a significant role in designing PVMS messages for providing more effective real-time traffic information.

• Structural Engineering and Mechanics
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• v.55 no.2
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• pp.365-377
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• 2015

Large-amplitude vibration of overhead sign structures can cause unfavorable psychological responses in motorists, interfere with readability of the signs, and lead to fatigue cracking in the sign structures. Field experience in Texas suggests that an overhead sign structure can vibrate excessively when supported within the span of a highway bridge instead of at a bent. This study used finite element modeling to analyze the dynamic displacement response of three hypothetical sign structures subjected to truck-passage-induced vertical oscillations recorded for the girders from four actual bridges. The modeled sign bridge structures included several span lengths based on standard design practices in Texas and were mounted on precast concrete I-girder bridges. Results revealed that resonance with bridge girder vertical vibrations can amplify the dynamic displacement of sign structures, and a specific range of frequency ratios subject to undesirable amplification was identified. Based on these findings, it is suggested that this type of sign structure be located at a bridge bent if its vertical motion frequency is within the identified range of bridge structure excitation frequencies. Several alternatives are investigated for cases where this is not possible, including increasing sign structure stiffness, reducing sign mass, and installing mechanical dampers.

• 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.