• Journal of Digital Convergence
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• v.9 no.3
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• pp.59-67
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• 2011

The World aerospace industry grows consistently with the development digital technology. We study the activation of the digital aerospace industry based on avionics system, with respect to demand, system and industrial structure in the gimpo area. The strategy is made for aerospace industry to be a growth driver and then we suggest some projects to carry out it. Those are lasting creation of aerospace demand, possession of core part material and competitive digital technology, construction infrastructure for activation of system operation, improvement of administrative assistance system and finally strengthening policy modulation between civil, company, army, academy, and government. Therefore, it is possible to develop into it focusing the MRO and the Helicopter, if we complement systems related in the field of administration and Industry.

• Journal of Digital Convergence
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• v.14 no.7
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• pp.175-184
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• 2016

The purpose of the study focuses on increasing dangers of using smartphones while driving recently, and then is to come up with measures to reduce traffic accidents caused by using devices like a smartphone. This study conducted a survey of drivers using their smartphones while driving to understand risks caused by using a smartphones while operating vehicles. Results showed that a lot of activities may lead to distracted driving, such as texting, making phone calls, using GPS or road maps, game, etc. In this paper, we presented that functions of smartphone should be controlled partially while driving for safe driving performance. These results suggest that using IoT-based smart devices like a beacon and a smartphone application implemented, tentatively called "Safe driving solution", while driving can reduce traffic accidents. Thus, in order to effectively prevent dangerous driving due to the use of smartphones, a "Safe driving solution" which restricts all functions except for calls and driver assistance functions is suggested.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.10
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• pp.1443-1449
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• 2013

Automatic detection of vehicles in front is an integral component of many advanced driver-assistance system, such as collision mitigation, automatic cruise control, and automatic head-lamp dimming. Regardless day and night, tail-lights play an important role in vehicle detecting and status recognizing of driving in front. However, some drivers do not know the status of the tail-lights of vehicles. Thus, it is required for drivers to inform status of tail-lights automatically. In this paper, a recognition method of status of tail-lights based on video processing and recognition technology is proposed. Background estimation, optical flow and Euclidean distance is used to detect vehicles entering tollgate. Then saliency map is used to detect tail-lights and recognize their status in the Lab color coordinates. As results of experiments of using tollgate videos, it is shown that the proposed method can be used to inform status of tail-lights.

• Smart Media Journal
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• v.6 no.3
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• pp.15-20
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• 2017

Recently, the automotive industry has been studied about driver assistance systems for helping drivers to drive their cars easily by integrating them with the IT technology. This study suggests a method of detecting lanes, robust to road condition changes and applicable to lane departure warning and autonomous vehicles mode. The proposed method uses the method of detecting candidate areas by using the Gaussian filter and by determining the Otsu threshold value and edge. Moreover, the proposed method uses lane gradient and width information through the Hough transform to detect lanes. The method uses road lane information detected before to detect dashed lines as well as solid lines, calculates routes in which the lanes will be located in the next frame to draw virtual lanes. The proposed algorithm was identified to be able to detect lanes in both dashed- and solid-line situations, and implement real-time processing where applied to Raspberry Pi 2 which is open source hardware.

• Journal of the Optical Society of Korea
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• v.17 no.4
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• pp.336-343
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• 2013

Recently various types of driver assistance systems have been used for automobiles. In 2008, the U.S Congress passed a law which required that most cars be equipped with devices to warn objects behind the vehicle. Because of that, market of rear view cameras is expected to rise dramatically. Therefore many suppliers try to provide a wide angle camera for car makers. But a high distortion is caused by the wide angle might result in lower image quality. In order to improve the image quality, normally we use an algorithm to correct a distortion. Though we can improve the distorted image by correction algorithm, we must pay more cost to use it. In this paper, we propose a new optical system reducing a distortion in contrast to a conventional lens without cost. In other words, we can see only an area of interest. That is similar to reducing a field of view. Using a new optical system, we can get a less distorted image. In order to view an area of interest, we introduce an off axis optical system having refractive surfaces and reflective surfaces. In this paper, we describe the results of design and, evaluation of an off axis wide angle compact imaging system. In comparison to conventional wide angle lens, we can get the improvement of MTF, distortion, and lateral color aberrations. And we also can reduce a total cost because we don't need the outer apparatus or bracket to mount on the car.

• Journal of IKEEE
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• v.22 no.4
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• pp.970-977
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• 2018

The autonomous vehicle is based on an advanced driver assistance system (ADAS) consisting of a sensor that collects information about the surrounding environment and a control module that determines the measured data. As interest in autonomous navigation technology grows recently, an easy development framework for ADAS beginners and learners is needed. However, existing development and verification methods are based on high performance vehicle simulator, which has drawbacks such as complexity of verification method and high cost. Also, most of the schemes do not provide the sensing data required by the ADAS directly from the simulator, which limits verification reliability. In this paper, we present an interactive ADAS development and verification framework using a 3D vehicle simulator that overcomes the problems of existing methods. ADAS with image recognition based artificial intelligence was implemented as a virtual sensor in a 3D car simulator, and autonomous driving verification was performed in real scenarios.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.7
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• pp.849-856
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• 2020

Recently, as the number of high-height vehicles such as double-decker buses has increased, collision accidents have occurred in bridges and tunnels due to the deviation from the designated routes and driver's carelessness. In the case of the existing front collision warning system, it is limited to vehicles and pedestrians, so it is difficult to use it as a pass height warning system for the high height vehicles. In this paper, we propose a system that generates a warning by determining the correlation and time series characteristics of data for each segment using multiple lidar sensors and then determining the possibility of collision in the upper part of the vehicle. Also, the proposed system confirmed the proper operation through a real-time driving test and a system performance evaluation by the Korea Automobile Testing & Research Institute.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.3
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• pp.219-230
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• 2023

With the development of autonomous driving technology, as the use of software in vehicles increases, the complexity of the system increases and the difficulty of development increases. Developments that meet ISO 26262 must be carried out to reduce the malfunctions that may occur in vehicles where the system is becoming more complex. ISO 26262 for the functional safety of the vehicle industry proposes to consider functional safety from the design stage to all stages of development. Specifically at the software level, the requirements to be complied with during development and the requirements to be complied with during verification are defined. However, it is not clearly expressed about specific design methods or development methods, and it is necessary to supplement development guidelines. The importance of analysis and verification of requirements is increasing due to the development of technology and the increase of system complexity. The vehicle industry must carry out developments that meet functional safety requirements while carrying out various development activities. We propose a process that reflects the perspective of system engineering to meet the smooth application and developmentrequirements of ISO 26262. In addition, the safety analysis/verification FMEA processforthe safety of the proposed ISO 26262 function was conducted based on the FCAS (Forward Collision Avoidance Assist System) function applied to autonomous vehicles and the results were confirmed. In addition, the safety analysis/verification FMEA process for the safety of the proposed ISO 26262 function was conducted based on the FCAS (Forward Collision Avoidance Assist System) function applied to the advanced driver assistance system and the results were confirmed.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.388-390
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• 2021

This paper introduces a system that can help visually impaired people to board a bus using an embedded board with keypad, dot matrix, lidar sensor, NFC reader, a public data portal Open API system, and deep learning algorithm (YOLOv5). The user inputs the desired bus number through the NFC reader and keypad, and then obtains the location and expected arrival time information of the bus through the Open API real-time data through the voice output entered into the system. In addition, by displaying the bus number as the dot matrix, it can help the bus driver to wait for the visually impaired, and at the same time, a deep learning algorithm (YOLOv5) recognizes the bus number that stops in real time and detects the distance to the bus with a distance detection sensor such as lidar sensor.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.6
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• pp.907-917
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• 2023

Recently, a self-driving car have applied deep learning technology to advanced driver assistance system can provide convenience to drivers, but it is shown deep that learning technology is vulnerable to adversarial evasion attacks. In this paper, we performed five adversarial evasion attacks, including MI-FGSM(Momentum Iterative-Fast Gradient Sign Method), targeting the object detection algorithm YOLOv5 (You Only Look Once), and measured the object detection performance in terms of mAP(mean Average Precision). In particular, we present a method applying morphology operations for YOLO to detect objects normally by removing noise and extracting boundary. As a result of analyzing its performance through experiments, when an adversarial attack was performed, YOLO's mAP dropped by at least 7.9%. The YOLO applied our proposed method can detect objects up to 87.3% of mAP performance.