• Journal of Platform Technology
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• v.9 no.2
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• pp.46-54
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• 2021

Recently, interest in the safety of Self-driving has been increasing. Self-driving have been studied and developed by many universities, research centers, car companies, and companies of other industries around the world since the middle 1980s. In this study, we propose the automatic extraction method of the threatening obstacle on the Road for the Self-driving. A threatening obstacle is defined in this study as a comparatively large object at center of the image. First of all, an input image and its decreased resolution images are segmented. Segmented areas are classified as the outer or the inner area. The outer area is adjacent to boundaries of the image and the other is not. Each area is merged with its neighbors when adjacent areas are included by a same area in the decreased resolution image. The Obstacle area and Non Obstacle area are selected from the inner area and outer area respectively. Obstacle areas are the representative areas for the obstacle and are selected by using the information about the area size and location. The Obstacle area and Non Obstacle area consist of the threatening obstacle on the road. Through experiments, we expect that the proposed method will be able to reduce accidents and casualties in Self-driving.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.07a
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• pp.287-289
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• 2023

본 논문에서는 무인주행로봇에 적용할 수 있는 장애물 탐지 및 주행지역 이탈을 관리하는 시스템을 제안한다. 제안 시스템은 웹캠과 같은 일반적인 카메라를 활용하여 촬영되는 공간에서 무인주행로봇을 운용할 영역을 선정하고 운용영역내의 장애물 발생 여부를 판단한다. 제안 시스템은 카메라 위치 기준으로 촬영되는 버드뷰에서 무인주행로봇의 운용영역을 설정하고 탐지된 장애물의 정보를 제공하여 무인주행로봇의 주행에 있어 안전하고 효율적인 주행 기능을 제공할 수 있을 것으로 기대한다.

• 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.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.36 no.6
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• pp.623-628
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• 2012

Conventional path planning methods have focused on the generation of an optimal shortest path to the goal. However, this optimal path cannot guarantee safe navigation, because it can often lead to a narrow area. Therefore, we propose a Coulomb's law-based safe path planning method that uses an information grid map. The information grid map includes four types of information: occupied, empty, guide, and dangerous areas. A safe path can be generated away from the dangerous area and close to the guide area by repulsive and attractive forces, respectively. Experiments and simulations show that the proposed method can generate paths inside the safe region and is useful for safe navigation.

• Journal of Auto-vehicle Safety Association
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• v.11 no.2
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• pp.17-22
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• 2019

This paper describes the tracking algorithm performance evaluation for autonomous vehicle using a safety envelope based path. As the level of autonomous vehicle technologies evolves along with the development of relevant supporting modules including sensors, more advanced methodologies for path generation and tracking are needed. A safety envelope zone, designated as the obstacle free regions between the roadway edges, would be introduced and refined for further application with more detailed specifications. In this paper, the performance of the path tracking algorithm based on the generated path would be evaluated under safety envelop environment. In this process, static obstacle map for safety envelope was created using Lidar based vehicle information such as current vehicle location, speed and yaw rate that were collected under various driving setups at Seoul National University roadways. A level of safety was evaluated through CarSim simulation based on paths generated with two different references: a safety envelope based path and a GPS data based one. A better performance was observed for tracking with the safety envelop based path than that with the GPS based one.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2011.04a
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• pp.485-488
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• 2011

본 연구에서는 경부고속철도의 콘크리트궤도에서 열차주행안전측면에서 관리해야할 레일패드강성의 상한값을 차량 및 궤도의 동특성과 운영환경을 고려하여 결정하는 방법을 제시하였다. 차량과궤도의 상호작용의 해석의 중요 입력파라메타인 궤도틀림과 관련하여 프랑스 및 독일에서 제시한 궤도틀림 PSD(Power Spectral Density)와 경부 1단계구간 콘크리트궤도에서 계측한 궤도틀림 자료를 통하여 얻은 PSD를 기초로 하여 넓은 범위의 주파수영역에서 적용할 수 있는 콘크리트궤도의 궤도틀림 PSD를 제시하였다. 제시된 PSD 기준모델을 사용하여 시간영역에서의 궤도틀림 입력을 Random Generation을 통하여 구한 후 개발된 차량-궤도 상호작용해석 기법을 사용하여 레일패드에 따른 윤중감소율을 산정하였다. 산정된 윤중감소율에 대하여 국내 철도차량 안전기준에 관한 규칙의 탈선계수 규정을 적용하여 주행안전측면에서 허용할 수 있는 레일패드강성의 상한값을 제시하였다.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.7
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• pp.575-583
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• 2017

This paper describes the design and evaluation of a driving mode decision algorithm for automated driving for merge situations on highways. For the development of a highly automated driving control algorithm for merge situations, the driving mode decision is crucial for merging appropriately. There are two driving modes: lane keeping and lane changing (merging). The merge mode decision is determined based on the state of the surrounding vehicles and the remaining length of the merge lane. In the merge mode decision algorithm, merge possibility and the desired merge position are decided to change the lane safely and quickly. A safety driving envelope is defined based on the desired driving mode using the information on the surrounding vehicles' behaviors. To obtain the desired steering angle and longitudinal acceleration for maintaining the subject vehicle in the safe driving envelope, a motion planning controller is designed using model predictive control (MPC), with constraints that are decided considering the vehicle dynamics, safe driving envelope, and actuator limit. The proposed control algorithm has been evaluated via computer simulation studies.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.1
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• pp.51-58
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• 2022

Drivable area detection, one of the main functions of advanced driver assistance systems, means detecting an area where a vehicle can safely drive. The drivable area detection is closely related to the safety of the driver and it requires high accuracy with real-time operation. To satisfy these conditions, V-disparity-based method is widely used to detect a drivable area by calculating the road disparity value in each row of an image. However, the V-disparity-based method can falsely detect a non-road area as a road when the disparity value is not accurate or the disparity value of the object is equal to the disparity value of the road. In a road environment including vegetation, such as a highway and a country road, the vegetation area may be falsely detected as the drivable area because the disparity characteristics of the vegetation are similar to those of the road. Therefore, this paper proposes a drivable area detection method and hardware architecture with a high accuracy in road environments including vegetation areas by reducing the number of false detections caused by V-disparity characteristic. When 289 images provided by KITTI road dataset are used to evaluate the road detection performance of the proposed method, it shows an accuracy of 90.12% and a recall of 97.96%. In addition, when the proposed hardware architecture is implemented on the FPGA platform, it uses 8925 slice registers and 7066 slice LUTs.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.04a
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• pp.348-351
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• 2010

본 논문에서는 단일 카메라로부터 주어진 영상을 실시간으로 장애물과 비장애물 영역으로 분류한 후 VFH 를 이용하여 안전한 경로를 선정하는 실시간 주행 시스템을 개발한다. 제안된 시스템은 점유 그리드맵 생성기와 VFH 기반의 선정기로 구성된다. 점유 그리드맵 생성기는 입력된 $320{\times}240$ 영상의 색조와 명도 정보를 이용하여 실시간으로 배경과 장애물 영역을 분류하고, 이를 바탕으로 위험도에 따라 10 개의 그레이 레벨을 가지는 $32{\times}24$ 의 점유 그리드맵을 생성한다. VFH를 이용하여 폴라 히스토그램을 작성한 후 밀도가 낮은 곳으로 주행 경로를 결정 한다. 제안된 기술의 효율성을 증명하기 위하여 다양한 형태의 장애물을 포함하는 실내 및 실외 환경에서 평가하였으며 센서 기반의 그 결과는 기존의 센서기반의 주행시스템과 비교 되었다. 그 결과 제안된 시스템은 88%의 정확도를 보였으며, 기존의 시스템보다 실시간으로 빠르고 안전한 주행을 수행할 수 있음이 증명되었다.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.6
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• pp.299-312
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• 2021

Autonomous vehicles using V2X can drive safely information on areas outside the sensor coverage of autonomous vehicles conventional autonomous vehicles. As V2X technology has emerged as a key component of autonomous vehicles, research on V2X security is actively underway research on risk analysis due to failure of V2X communication is insufficient. In this paper, the service scenario and function of autonomous driving system V2X were derived by presenting the intersection scenario of the autonomous vehicle, the malfunction was defined by analyzing the hazard of V2X. he ISO26262 Part3 process was used to analyze the risk of malfunction of autonomous vehicle V2X. In addition, a fault injection scenario was presented to verify the fail-safe of the simulation-based intersection scenario.