• Proceedings of the IEEK Conference
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• 2002.06c
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• pp.143-146
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• 2002

The aim of this work is the real-time road edge detection using the fast processing of Cellular Analogic Parallel Processing Networks(CAPPN). The CAPPN is composed of 2D analog cell way. If the dynamic programming is implemented with the CAPPN, the optimal path can be detected in parallel manner Provided that fragments of road edge are utilized as the cost inverse(benefit) in the CAPPN-based optimal path algorithm, the CAPPN determines the most plausible path as the road edge line. Benefits of the proposed algorithm are the fast processing and the utilization of optimal technique to determine the road edge lines.

• Transactions of the Korean Society of Automotive Engineers
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• v.10 no.5
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• pp.147-159
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• 2002

This paper proposes a method to recognize the noisiness of road images connected with the extraction of lane-related information in order to prevent the usage of erroneous information. The proposed method uses a fuzzy neural network(FNN) with the back-Propagation loaming algorithm. The U decides road images good or bad with respect to visibility of lane marks on road images. Most input parameters to the FNN are extracted from an edge distribution function(EDF), a function of edge histogram constructed by edge phase and norm. The shape of the EDF is deeply correlated to the visibility of lane marks of road image. Experimental results obtained by simulations with real images taken by various lighting and weather conditions show that the proposed method was quite successful, providing decision-making of noisiness with about 99%.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.802-804
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• 2014

Edge detection of image for performing the road lane recognition is an essential preprocessing. Various studies are being performed in order to detect such edge and there are conventional edge detection methods such as Sobel, Prewitt and Roberts. Such methods regardless of pixel distribution are processed by applying the same weighted value to the entire pixels and show a somewhat insufficient edge detection results. Therefore, this paper has proposed an algorithm that detects the edge using the suitable weighted value for the road lane recognition considering the pixel distribution shape of the image.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.334-335
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• 2021

In this paper, the distance traveled by a vehicle in an area where a part of the road is cut is measured using the motion of a parabola. Here, when a car running at a constant speed passes over the edge of a broken road, how far it goes from the edge of the road to fall was calculated.

• International Journal of Highway Engineering
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• v.17 no.6
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• pp.37-45
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• 2015

PURPOSES : The purpose of this study is to validate the design criteria of the concrete modular road system, which is a new semi-bridge-type concept road, through a comparison of numerical analysis results and actual loading test results under static axial loads. METHODS : To design the semi-bridge-type modular road, both the bridge design code and the concrete structural design code were adopted. The standard truck load (KL-510) was applied as the major traffic vehicle for the design loading condition. The dimension of the modular slab was designed in consideration of self-weight, axial load, environmental load, and combined loads, with ultimate limit state coefficients. The ANSYS APDL (2010) program was used for case studies of center and edge loading, and the analysis results were compared with the actual mock-up test results. RESULTS : A full-scale mock-up test was successfully conducted. The maximum longitudinal steel strains were measured as about 35 and 83.5 micro-strain (within elastic range) at center and edge loading locations, respectively, under a 100 kN dual-wheel loading condition by accelerating pavement tester. CONCLUSIONS : Based on the results of the comparison between the numerical analysis and the full-scale test, the maximum converted stress range at the edge location is 32~51% of the required standard flexural strength under the two times over-weight loading condition. In the case of edge loading, the maximum converted stresses from the Westergaard equation, the ANSYS APDL analysis, and the mock-up test are 1.95, 1.7, and 2.3 times of that of the center loading case, respectively. The primary reason for this difference is related to the assumption of the boundary conditions of the vertical connection between the slab module and the crossbeam module. Even though more research is required to fully define the boundary conditions, the proposed design criteria for the concrete modular road finally seems to be reasonable.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.4
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• pp.86-97
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• 2011

This paper presents a novel algorithm to detect more accurate road lane with image sensor-based color classification and directional edge clustering. With treatment of road region and lane as a recognizable color object, the classification of color cues is processed by an iterative optimization of statistical parameters to each color object. These clustered color objects are taken into considerations as initial kernel information for color object detection and recognition. In order to improve the limitation of object classification using the color cues, the directional edge cures within the estimated region of interest in the lane boundary (ROI-LB) are clustered and combined. The results of color classification and directional edge clustering are optimally integrated to obtain the best detection of road lane. The characteristic of the proposed system is to obtain robust result to all real road environments because of using non-parametric approach based only on information of color and edge clustering without a particular mathematical road and lane model. The experimental results to the various real road environments and imaging conditions are presented to evaluate the effectiveness of the proposed method.

• International Journal of Automotive Technology
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• v.6 no.2
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• pp.171-181
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• 2005

The purpose of this paper is two-fold: 1) A novel algorithm in order to extract lane-related information from road images is presented; 2) Design specifications of an image processing onboard unit capable of extracting lane­related information in real-time is also presented. Obtaining precise information from road images requires many features due to the effects of noise that eventually leads to long processing time. By exploiting a FPGA and DSP, we solve the problem of real-time processing. Due to the fact that image processing of road images relies largely on edge features, the FPGA is adopted in the hardware design. The schematic configuration of the FPGA is optimized in order to perform 3 $\times$ 3 Sobel edge extraction. The DSP carries out high-level image processing of recognition, decision, estimation, etc. The proposed algorithm uses edge features to define an Edge Distribution Function (EDF), which is a histogram of edge magnitude with respect to the edge orientation angle. The EDF enables the edge-related information and lane-related to be connected. The performance of the proposed system is verified through the extraction of lane-related information. The experimental results show the robustness of the proposed algorithm and a processing speed of more than 25 frames per second, which is considered quite successful.

• Journal of information and communication convergence engineering
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• v.20 no.4
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• pp.273-279
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• 2022

Owing to the need to establish a cooperative-intelligent transport system (C-ITS) environment in the transportation sector locally and abroad, various research and development efforts such as high-tech road infrastructure, connection technology between road components, and traffic information systems are currently underway. However, the current central control center-oriented information collection and provision service structure and the insufficient road infrastructure limit the realization of the C-ITS, which requires a diversity of traffic information, real-time data, advanced traffic safety management, and transportation convenience services. In this study, a network construction method based on the existing received signal strength indicator (RSSI) selected as a comparison target, and the experimental target and the proposed intelligent edge network compared and analyzed. The result of the analysis showed that the data transmission rate in the intelligent edge network was 97.48%, the data transmission time was 215 ms, and the recovery time of network failure was 49,983 ms.

• 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 KIEE
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• v.11 no.1
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• pp.69-77
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• 2001

This paper describes an image processing algorithm capable of recognizing road lanes by using a CDF(cumulative distribution function). The CDF is designed for the model function of road lanes. Based on the assumptions that there are no abrupt changes in the direction and location of road lanes and that the intensity of lane boundaries differs from that of the background, we formulated the CDF, which accumulates the edge magnitude for edge directions. The CDF has distinctive peak points at the vicinity of lane directions due to the directional and the positional continuities of a lane. To obtain lane-related information a scatter diagram was constructed by collecting edge pixels, of which the direction corresponds to the peak point of the CDF, then the principal axis-based line fitting was performed for the scatter diagram. Noises can cause many similar features to appear and to disappear in an image. Therefore, to reduce the noise effect a recursive estimator of the CDF was introduced, and also to prevent false alarms or miss detection a scene understanding index (DUI) was formulated by the statistical parameters of the CDF. The proposed algorithm has been implemented in real time on video data obtained from a test vehicle driven on a typical highway.