• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.3
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• pp.160-174
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• 2023

LiDAR plays a key role in autonomous vehicles, and to improve its visibility, it is necessary to improve its performance and the detection objects. Accordingly, this study proposes a shape for traffic safety signs that is advantageous for self-driving vehicles to recognize. Improvement plans are also proposed using a shape-recognition algorithm based on point cloud data collected through LiDAR sensors. For the experiment, a DBSCAN-based road-sign recognition and classification algorithm, which is commonly used in point cloud research, was developed, and a 32ch LiDAR was used in an actual road environment to conduct recognition performance tests for 5 types of road signs. As a result of the study, it was possible to detect a smaller number of point clouds with a regular triangle or rectangular shape that has vertical asymmetry than a square or circle. The results showed a high classification accuracy of 83% or more. In addition, when the size of the square mark was enlarged by 1.5 times, it was possible to classify it as a square despite an increase in the measurement distance. These results are expected to be used to improve dedicated roads and traffic safety facilities for sensors in the future autonomous driving era and to develop new facilities.

• Journal of Aerospace System Engineering
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• v.14 no.3
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• pp.32-41
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• 2020

The International Civil Aviation Organization (ICAO) in 2015 proposed a road-map for the global recognition system of the Approved Maintenance Organization (AMO) fto mitigate the redundant work and regulatory burdens of the aviation industry and authorities on the certification and oversight activities of the State of Registry. Since then, the ICAO standards and guidelines have been revised accordingly with the goal of implementing the system in 2024. Korea should actively prepare for this AMO global recognition system to cope with the ICAO road-map appropriately as well as to develop the Maintenance Repair Overhaul (MRO) industry. Thus, this paper focused on the ratings and limitations system, a key element of the AMO, and proposes the improvement of domestic regulatory/administrative rules necessary for the global recognition system, through the review of newly established ICAO standards/guidelines and the comparative analysis of leading aviation countries' and Korean system/requirements.

• Journal of KIISE:Software and Applications
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• v.31 no.11
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• pp.1496-1504
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• 2004

In this paper, we propose an algorithm for initializing a target vehicle detection, tracking the vehicle and estimating the distance from it on the stereo images acquired from a forward-looking stereo camera mounted on a road driving vehicle. The process of vehicle detection extracts road region using lane recognition and searches vehicle feature from road region. The distance of tracking vehicle is estimated by TSS correlogram matching from stereo Images. Through the simulation, this paper shows that the proposed method segments, matches and tracks vehicles robustly from image sequences obtained by moving stereo camera.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.3
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• pp.563-570
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• 2024

This paper proposes a method to recognize and track drivable lane areas to assist the driver. The main topic is designing a deep-based network that predicts drivable road areas using computer vision and deep learning technology based on images acquired in real time through a camera installed in the center of the windshield inside the vehicle. This study aims to develop a new model trained with data directly obtained from cameras using the YOLO algorithm. It is expected to play a role in assisting the driver's driving by visualizing the exact location of the vehicle on the actual road consistent with the actual image and displaying and tracking the drivable lane area. As a result of the experiment, it was possible to track the drivable road area in most cases, but in bad weather such as heavy rain at night, there were cases where lanes were not accurately recognized, so improvement in model performance is needed to solve this problem.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.141-144
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• 1996

This study deals with the problem of the recognition of the preceding vehicles by image processing. The purpose of this study is the development of the equipment to prevent a collision with preceding vehicles during driving the vehicle. In order to decrease the processing time and increase reliability, at first, the traffic lane is extracted. It is determined by detecting road edges and calculating their tangent. After the traffic lane is gotten, the position of the vehicle is searched inside the lane. The features used to detect the vehicles in the algorithm are shadow of the vehicle, vertical edges, horizontal edges, and symmetrical segment. The preceding vehicles are extracted successfully by this method.

• Journal of the Korean Institute of Rural Architecture
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• v.8 no.1
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• pp.80-89
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• 2006

This study is derived from relation between the natural landscape and architectural landscape. The type of landscape in Donghae seaside consist of three; Road, Mountain, Seaside. And we selected three landscapes about individual housing; Western, Traditional, Modern. This paper is analyzed 18-simulation scenes, which evaluated with semantic differential method in using 12-bipolar adjectives. The results of this study are as follows(ref: table 6). 1)The housing of western style do not correspond with landscape of Road, but landscape of mountain and seaside were suitable to the western style. 2)Mountain in Donghae seaside harmonizes with housing of traditional style. 3)Even though the housing of modern style were marked low assessment in three landscape, we found out relation, modern housing was well-matched with load landscape.

• IEMEK Journal of Embedded Systems and Applications
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• v.3 no.3
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• pp.143-150
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• 2008

In this paper, we investigate a real-time environment recognition system based on stereo vision for moving object. This system consists of stereo matching, obstacle detection and distance estimation. In stereo matching part, depth maps can be obtained real road images captured adjustable baseline stereo vision system using belief propagation(BP) algorithm. In detection part, various obstacles are detected using only depth map in case of both v-disparity and column detection method under the real road environment. Finally in estimation part, asymmetric parabola fitting with NCC method improves estimation of obstacle detection. This stereo vision system can be applied to many applications such as unmanned vehicle and robot.

• Transactions of the Korean Society of Automotive Engineers
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• v.19 no.3
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• pp.16-22
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• 2011

This paper presents the potential of in-vehicle data recorder system for monitoring aggressive driving patterns and providing feedback to drivers on their on road behaviour. This system can detect 10 risky types of drivers' driving patterns such as aggressive lane change, sudden brakes and turns with acceleration etc. Vehicle dynamics simulation and vehicle road test have been performed in order to develop driving pattern recognition algorithms. Recorder systems are installed to 50 buses in a single company. Drivers' driving behaviour are monitored for 1 month. The drivers' risky driving data collected by the system are analyzed. Aggressive lane change in 50km/h below is a cause in overwhelming majority of risky driving pattern.

• Journal of the Korea institute for structural maintenance and inspection
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• v.28 no.1
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• pp.82-89
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• 2024

Black ice is very difficult to recognize and reduces the friction of the road surface, causing automobile accidents. Since black ice is difficult to detect, there is a need for a system that identifies black ice in real time and warns the driver. Various studies have been conducted to prevent black ice on road surfaces, but there is a lack of research on systems that identify black ice in real time and warn drivers. In this paper, an real-time image-based analysis system was developed to identify the condition of asphalt road surface, which is widely used in Korea. For this purpose, a dataset was built for each asphalt road surface image, and then the road surface condition was identified as dry, wet, black ice, and snow using deep learning. In addition, temperature and humidity data measured on the actual road surface were used to finalize the road surface condition. When the road surface was determined to be black ice, the salt spray equipment installed on the road was automatically activated. The surface condition recognition system for the asphalt concrete pavement and black ice automatic prevention system developed in this study are expected to ensure safe driving and reduce the incidence of traffic accidents.

• Spatial Information Research
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• v.15 no.3
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• pp.335-346
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• 2007

Road sign is one of the road attached facilities to provide conveniences to motor drivers. The setup of location information according to the related regulation and the inclusion of various attributes such as place names, route numbers, symbols, bearings, distances to the place of interest distinguish the road sign from other facilities. These features give advantages to the informationization of road sign. Presently there established about 130,000 road signs on each class of roads, and about 280 road management offices have controlled these road signs independently, but there are plethora of ineffectiveness such as the lack of consistency, recognition, connectivity, and location suitability etc. These are the major factor of confusions rather than providing conveniences, and arisen a lot of public grievances. Accordingly, in this research the road signs throughout the nation were databased and the web-GIS based road sign management system was established to ameliorate the problems reveled. Since the road sign management system we developed reflected the demands of the persons in charge and users, the management effectiveness might be enhanced and the public inconveniences will be reduced.