• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.19 no.6
• /
• pp.37-48
• /
• 2020

Eight colors prescribed by the Enforcement Rules of the Road Traffic Act and the group standard were tested to secure the minimum recursive reflectance performance standards when drying and wetting. The results were calculated to be 260.8 (mcd/㎡·lux) when drying white and 154.6 (mcd/㎡·lux) when wet. Yellow was 67% compared to the white reflective performance when drying. Wet poetry was 79 % and 59 %, respectively. In the case of blue, it was 64% in the case of white versus 72% in the case of white. Wet poetry was 63 % and 72 %, respectively. The range of changes in reflective performance during wetting was higher than when drying, and the absence of glass grains was similar to the previous results. The new colors also have a standard value of more than 50% compared to the white color in red, orange, pink, light green, and green. Based on this, it was estimated that the minimum reflective performance criteria according to the color of the road markings would form the basis for the enforcement rules of the Road Traffic Act.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2015.10a
• /
• pp.1411-1412
• /
• 2015

Detection of road lanes is an important technology, which is being used in autonomous vehicles from last few years. This method is very helpful and supportive for the drivers to provide them safety and to avoid road accidents. Alot of methods are being used to detect road lane markings. We can categorize them into three major categories: sensor-based, feature-based, and model-based methods. And in this study we give the comprehensive survey on lane marking techniques.

• Journal of Institute of Control, Robotics and Systems
• /
• v.22 no.10
• /
• pp.803-810
• /
• 2016

This paper presents a study of localization methods based on particle filter using 2D laser sensor measurements and road feature map information, for autonomous vehicles. In order to navigate in an urban environment, an autonomous vehicle should be able to estimate the location of the ego-vehicle with reasonable accuracy. In this study, road features such as curbs and road markings are detected to construct a grid-based feature map using 2D laser range finder measurements. Then, we describe a particle filter-based method for accurate positional estimation of the autonomous vehicle in real-time. Finally, the performance of the proposed method is verified through real road driving experiments, in comparison with accurate DGPS data as a reference.

• Journal of Korea Spatial Information System Society
• /
• v.11 no.1
• /
• pp.137-144
• /
• 2009

Understanding lane markings in a live video captured from a moving vehicle is essential to build services for intelligent vehicles such as LDWS(Lane Departure Warning Systems), unmanned vehicles, video-based car navigation systems. In this paper, we present a novel approach to recognize the color of lane markings and the lane number that he/she is driving on. More specifically, we present a background-color removal approach to understand the color of lane markings for various illumination conditions, such as backlight, sunset, and so on. In addition, we present a probabilistic network approach to decide the lane number. According to our experimental results, the proposed idea shows promising results to detect lane number in a various illumination conditions and road environments.

• International Journal of Highway Engineering
• /
• v.12 no.3
• /
• pp.9-16
• /
• 2010

The purpose of this study is to establish how drivers react on different pavement markings in a driving simulator for speed reduction. For this, forty one people between the ages of twenty and seventy took part in this experiment. A study analyzed which patterns are effective to reduce a speeding. As a results, 'Peripheral Transverse Lines II' were the most effective treatment for reducing driving speeds in the driving simulator. This study carries an important meaning when presenting the effectiveness of speed reduction for perceptual countermeasure based on the human factors. Further research will be required to determine the long term effectiveness of these countermeasures due to concerns over drivers becoming too accustomed to implemented markings. Also, the color contrasts (for example, dark asphalt with white markings) can be considered.

• The Journal of Korea Robotics Society
• /
• v.16 no.2
• /
• pp.112-121
• /
• 2021

Unlike a typical small-sized robot navigating in a free space, an autonomous vehicle has to travel in a designated road which has lanes to follow and traffic rules to obey. High-Definition (HD) maps, which include road markings, traffic signs, and traffic lights with high location accuracy, can help an autonomous vehicle avoid the need to detect such challenging road surroundings. With space constraints and a pre-built HD map, a new type of path planning algorithm can be conceived as a substitute for conventional grid-based path planning algorithms, which require substantial planning time to cover large-scale free space. In this paper, we propose an obstacle-avoiding, cost-based planning algorithm in a continuous space that aims to pursue a globally-planned path with the help of HD map information. Experimentally, the proposed algorithm is shown to outperform other state-of-the-art path planning algorithms in terms of computation complexity in a typical urban road setting, thereby achieving real-time performance and safe avoidance of obstacles.

• Journal of the Institute of Convergence Signal Processing
• /
• v.7 no.3
• /
• pp.108-115
• /
• 2006

In this paper, a recognition algorithm of the straight line components of lane markings and an obstacle in the travelling lane region is proposed. This algorithm also involve the pitching error correction algorithm due to traveling vehicle's fluctuation. In order to reduce their error a practical road image modelling algorithm using V.F. model and camera calibration procedure are suggested to adapt the geometric variations. It is obtained the 3D world coordinate data by the 2D road images. In experimental test, we showed that this algorithm is available to recognize lane markings and an obstacle in the traveling lane.

• Current Optics and Photonics
• /
• v.3 no.5
• /
• pp.423-428
• /
• 2019

Visibility of road-surface markings is one of the critical issues that should be secured for self-driving cars as well as human drivers. Glass beads are taking on the role of retroreflectors, and therefore are considered a necessity in modern pavements. In this context, retroreflectance is sensitively dependent not only on the refractive index of glass beads but also on that of the surrounding medium. This implies that the optimum refractive index of glass beads immersed in water, i.e. under wet conditions, is different from that of glass beads surrounded by air, i.e. under dry conditions. A refractive index of approximately 1.9, which is known to maximize retroreflectance under dry conditions, actually exhibits much poorer retroreflectance under wet conditions. This suggests that glass beads with optimal refractive index for wet conditions need to be installed together with those for dry conditions. We propose a facile but practical model capable of calculating retroreflectance of glass beads surrounded by an arbitrary medium, here water in particular, and experimentally verify its capability of assessing the refractive index of commercial glass beads. Changes in retroreflectance according to the mixing ratio of glass beads with different refractive indices are also discussed, in an effort to propose the proper use of glass beads produced for dry and wet conditions.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.21 no.6
• /
• pp.97-114
• /
• 2022

Unlike ground roads, the on-ramp merging section of underground roads cannot be seen by drivers of main road due to tunnels. In this study, a driving simulator was used for analysis, and virtual driving experiments were carried out to assess the driver's visibility for different design factors. The driver's driving behavior was analyzed by setting scenarios considering the length of chevron markings and the approach speed from the main road. The results of the analysis were used to determine the design factors for ensuring visibility when constructing the virtual driving environment for each scenario. These factors, including speed, lane change points, and driver's gaze ratios, were reviewed for significance using a statistical approach. As a result, in scenarios with a higher approach speed from the main road, it was discovered that there was a difference in driver's behavior between specific scenarios depending on the length of the section with chevron markings. Based on these findings, this study suggests implications and feasible solutions to improve driver safety on the on-ramp merging section of underground roads.

• International Journal of Highway Engineering
• /
• v.7 no.4 s.26
• /
• pp.163-171
• /
• 2005

Current roads were designed and constructed based on the design criteria and thus those were overly simplified drivers' needs. The road criteria do not suggest the desirable range of the design values but suggest the minimum requirements for the road design. Therefore, a completed road design based on the design criteria does not always guarantee the best design in terms of safety and it sometimes violates drivers' expectation. Therefore, the ROSSAV(ROad Safety Survey and Analysis Vehicle) is being developed by the KICT to evaluate road safety and increase driving safety. In this paper, the image capture system was described in detail. The image capture system is consisted of two front view cameras, two side down-looking cameras and a synchronization device. Two front view cameras were used to take a picture of road and road facilities at the driver's viewpoint. Also, two side down-looking cameras were used to capture road surface image to extract lane markings. A synchronization device were used to generate image capturing signal at the fixed distance spacing huck as every 10m. The front view images could be used to calculate and measure highway geometry such as shoulder width because every image is saved with it's locational information. And also the side down looking images could be used to extract median lane mark which representing road alignement efficiently.