• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.2
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• pp.135-148
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• 2020

The ongoing development of autonomous driving-related technology may cause different kinds of accidents while testing new changes. As a result, more information on ODD suitable for the domestic road environment will be necessary to prevent safety accidents. Besides, implementation of the Autonomous Vehicle Act will increase autonomous driving demonstrations on roads currently in use. This study describes an ODD for demonstrating an autonomous driving shuttle in downtown areas. It addresses a possible scenario of autonomous driving around a downtown road in Anyang. Geometric, operational, and environmental factors are considered while maintaining a domestic road environment and safety. Autonomous driving shuttles are demonstrated in 30 nodes, each identified by node type and signal-communication. Link criteria are an autonomous driving restriction in 42 morning peak (8-9am) hours, 39 non-peak (12-13pm) hours, and 40 afternoon peak (18-19pm) hours. In the future, conclusions may be considered for preliminary safety assessments of roads where autonomous driving tests are performed.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.5
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• pp.287-300
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• 2022

The introduction of Connected and Automated(CAD) technology has a growing interests especially in areas with low demand for transport, where often the local transport services do not connect to peripheral areas for more efficient and convenient mobility services. However, there are few researches on CAD-based mobility services in areas with low demand for transport. Because current researches are mainly focuses on introduction of CAD-based mobility services in area with high demand for transport such as urban and highway. These two areas have different road environments and these differences require different driving technology especially related to Operational Design Domain(ODD). ODD is important factors for introduction of CAD-based mobility services. Therefore, we compare the road environments of areas with low demand for transport and areas with high demand for transport in terms of ODD. In addition, this paper proposes suggest guidance for the introduction of CAD-based mobility services in areas with low demand for transport such as rural and suburban areas.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.2
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• pp.195-211
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• 2023

For the commercialization For the commercialization of autonomous vehicles (AV), the operational design domain (ODD) of automated driving systems (ADS) is to be clearly defined. A common language and consistent format must be prepared so that AV-related stakeholders can understand ODD at the same level. Therefore, overseas countries are presenting a standardized ODD framework and developing scenarios that can evaluate ADS-specific functions based on ODD. However, ODD includes conditions reflecting the characteristics of each country, such as road environment, weather environment, and traffic environment. Thus, it is necessary to clearly understand the meaning of the items defined overseas and to harmonize them to reflect the specific domestic conditions. Therefore, in this study, domestic optimization of the ODD classification system was performed by analyzing the domestic driving environment based on international standards. The driving environment of currently operating self-driving car test districts (Sangam, Seoul, and Gwangju) was investigated using the developed domestic ODD items. Then, based on the results obtained, the ranges of the ODDs in each test district were determined and compared.

• 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.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.1
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• pp.192-207
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• 2023

Commercialization of level-4 (Lv.4) autonomous driving applications requires the definition of a safe road environment under which autonomous vehicles can operate safely. Thus, a risk assessment model is required to determine whether the operation of autonomous vehicles can provide safety to is sufficiently prepared for future real-life traffic problems. Although the risk factors of autonomous vehicles were selected and graded, the decision-making method was applied as qualitative data using a survey of experts in the field of autonomous driving due to the cause of the accident and difficulty in obtaining autonomous driving data. The fuzzy linguistic representation of decision-makers and the fuzzy analytic hierarchy process (AHP), which converts uncertainty into quantitative figures, were implemented to compensate for the AHP shortcomings of the multi-standard decision-making technique. Through the process of deriving the weights of the upper and lower attributes, the road alignment, which is a physical infrastructure, was analyzed as the most important risk factor in the operation risk of autonomous vehicles. In addition, the operation risk of autonomous vehicles was derived through the example of the risk of operating autonomous vehicles for the 5 areas to be evaluated.

• Journal of the Korean Society for Railway
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• v.5 no.3
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• pp.22-28
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• 2002

한국철도는 100여년의 역사를 지내오면서 설계, 건설, 운영에 이르기까지 괄목할만한 성장을 하였으며 기술산업의 측면에서도 고부가가치를 창출해 낼 수 있는 공학분야의 전문화된 기술이라는 인식이 사회전반에 확산되고 있다. 특히, 90년대 초에 시작된 고속철도 건설사업을 계기로 철도산업은 그 동안의 낙후된 이미지를 벗어나 고속열차 운행에 따른 여행시간의 단축과 효율성의 극대화 그리고 쾌적한 환경을 창출하고자 하는 강한 사회적인 욕구에 부응할 수 있는 새로운 산업영역으로 각광을 받고 있다. (중략)

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.4
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• pp.107-118
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• 2022

As connected and automated driving(CAD) technology is entering its commercialization stage, service platforms providing CAD-based mobility services have increased these days. However, CAD-baded mobility services with these platforms need more consideration for the demand for mobility services when determining target areas for CAD-based mobility services because current CAB-based mobility design focus on driving performance and driving stability. For a more efficient design of CAD-based mobility services, we analyzed the applicability for the introduction of CAD-based mobility services in terms of driving difficulty of CAD and demand patterns of current non-CAD based-mobility services, e.g., taxi, demand-responsive transit(DRT), and special transportation systems(STS). In addition, for the spatial analysis of the applicability of the CAD-based mobility service, we propose the Index for Autonomous Driving Applicability (IADA) and analyze the characteristics of the spatial distribution of IADA from the network perspective. The analysis results show that the applicability of CAD-based mobility services depends more on the demand patterns than the driving difficulty of CAV. In particular, the results show that the concentration pattern of demand in a specific road link is more important than the size of demand. As a result, STS service shows higher applicability compared to other mobility services, even though the size of demand for this mobility service is relatively small.

• Proceedings of the KSRS Conference
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• 2009.03a
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• pp.78-81
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• 2009

레일형 GB-SAR의 단점을 극복하고자 차량에 원형레일을 탑재하여 신속한 기동을 확보하고 합성구경의 길이를 늘리며 영상영역을 확장한 ArcSAR를 세계 최초로 설계하고 시작품을 제작하였다. ArcSAR의 핵심기술이라고 할 수 있는 원형레일은 알루미늄 프로파일로 제작한 회전디스크, 곡선가이드, 리니어 가이드로 구성되며, 서보모터를 이용하여 구동된다. 회전디스크의 지름은 2.1 m 이며, 회전 디스크 위에 장착된 곡선 가이드를 따라 안테나가 탑재된 리니어 가이드가 이동하며 정밀한 원형 운행을 하게 된다. 리니어 가이드는 슬라이드식으로 제작되어 최대 3 m 까지 확장이 가능하여 스폿 모드 측정시 6 m 길이의 레일에서의 자료 획득과 유사한 결과를 얻게 된다. SAR 측정 장비는 회전디스크 위에 장착되어 전원을 제외한 별도의 슬립링을 사용을 자제하였다. 레일의 구동과 자료의 획득은 LabVIEW 기반의 통합 제어측정 소프트웨어를 통해 구현하였으며, 실내 실험 및 현장적용 실험을 통해 가능성을 확인하였다.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.36 no.11
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• pp.1311-1318
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• 2012

Vehicle systems are frequently exposed to parameter uncertainties such as vehicle speed and height of center of gravity. If a controller is designed to be robust against these parameter uncertainties, the rollover prevention capability can be considerably enhanced. In this study, robust controllers $H_2$ and $H_{\infty}$ are designed by using LMI for vehicle rollover prevention control in the discrete time domain. Some simulations using CarSim, a reliable simulation tool, are performed to validate the proposed controllers.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.8
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• pp.1693-1700
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• 2012

Recently, the warning system to aid drivers for safe driving is being developed. The system estimates the distance between the driver's car and the car before it and informs him of safety distance. In this paper, we designed and implemented the collision warning system which detects the car in front on the actual road situation and measures the distance between the cars in order to detect the risk situation for collision and inform the driver of the risk of collision. First of all, using the forward-looking camera, it extracts the interest area corresponding to the road and the cars from the image photographed from the road. From the interest area, it extracts the object of the car in front through the analysis on the critical value of the shadow of the car in front and then alerts the driver about the risk of collision by calculating the distance from the car in front. Based on the results of detecting driving cars and measuring the distance between cars, the collision warning system was designed and realized. According to the result of applying it in the actual road situation and testing it, it showed very high accuracy; thus, it has been verified that it can cope with safe driving.