• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.6
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• pp.264-279
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• 2021

Most automated vehicle evaluation scenarios are developed based on the typical driving situations that automated vehicles will face. However, various situations occur during actual driving, and sometimes complex judgments are required. This study is to define a situation that requires complex judgment for safer driving of an automated vehicle as a dilemma situation, and to suggest a driving strategy necessary to secure driving safety in each situation. To this end, we defined dilemma situations based on the automated vehicle ethics guidelines, the criteria for recognition of error rate in automobile accidents, and suggestions from the automated vehicle developers. In addition, in the defined dilemma situations, the factors affecting movement for establishing driving strategies were explored, and the priorities of factors affecting driving according to the Road Traffic Act and driving strategies were derived accordingly.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.181-184
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• 2021

자율주행 기술이 고도화됨에 따라 사용자가 주행 상황을 실시간으로 모니터링하고 주행을 제어할 수 있는 자율주행 서비스가 필요하다고 생각했다. 또한, 돌발 장애물을 고려하며 정해진 경로로 주행하는 자율주행을 구현하고자 해당 시스템을 설계하게 되었다. 해당 시스템은 차량, 서버, 애플리케이션으로 구성되어있으며 구성요소 간의 실시간 통신을 통해 차량 주행 상황 및 사용자 제어 명령을 자유롭게 전달하고자 했다. 차량의 자율주행 알고리즘을 구현하기 위해 이미지 데이터 처리에 효과적인 CNN을 활용하여 장애물 회피 모델과 라인 트레이서 모델을 구현하여 해당 모델들을 하나의 솔루션으로 통합하였다. 해당 솔루션 구현을 통해 차량이 마주할 수 있는 돌발 상황에 대처하는 자율주행의 안전성을 높이고자 했으며 자율주행 환경에서 사용자 조작을 용이하게 하고자 하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.11a
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• pp.470-473
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• 2017

자율주행 자동차 기술이 발달하고 있는 가운데 기능안전과 관련한 이슈에 주목하여 자율주행 기술에서 주행 도중 발생하는 예외상황들과 이에 대해서 어떻게 처리해야 하는가에 대한 연구가 많지 않다. 따라서 상태천이도를 통한 예외상황들의 처리에 대해 연구해보았다. 위험한 상황 혹 조건들에서 발생한 예외상황을 조사해보고 적합한 처리방법을 고안하여 안전한 주행이 되도록 한다.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.6
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• pp.214-227
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• 2021

The purpose of this study is to find the driving difficulty of automated vehicles in terms of road infrastructure operation. It was judged out of this study that the level of automated driving would be enhanced if the road situation recognition ability was advanced through the presentation of infrastructure information during the difficult driving situations. The difficulty evaluation index was divided into three stages, and a survey of experts and an AHP were conducted. The result of the AHP showed that the driving difficulty of the interrupted flow was much higher than that of the uninterrupted flow. The AHP results also showed that and the driving difficulty of unsignalized intersections and roundabouts under an interrupted flow was evaluated as the highest. The top six driving situations with high difficulty were also evaluated to occur under unsignalized intersections and roundabouts.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.5
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• pp.216-223
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• 2023

As the technology and level of autonomous vehicles advance and they drive in more diverse road environments, an intuitive and efficient interaction system is needed to resolve and respond to the situations the vehicle faces. The development of driving technology from the perspective of autonomous driving has the ultimate goal of responding to situations involving humans or more. In particular, in complex road environments where mutual concessions must be made, the role of a system that can respond flexibly through efficient communication methods to understand each other's situation between vehicles or between pedestrians and vehicles is important. In order to resolve the status of the vehicle or the situation being faced, the provision and method of information must be intuitive and the efficient operation of an autonomous vehicle through interaction with intention is required. In this paper, we explain the vehicle structure and functions that can display information about the situation in which the autonomous vehicle driving in a living lab can drive stably and efficiently in a diverse and complex environment.

• Science of Emotion and Sensibility
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• v.2 no.1
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• pp.61-68
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• 1999

본 연구의 목적은 운전 상황과 도로 상황에 따른 자율신경계의 반응을 측정하는 것이다. 지금까지의 생리 신호는 대부분 제한된 실험실에서 측정되었고, 이 결과들은 자연스러운 상황에 측정된 데이터와는 차이가 있을 것이다. 그러므로 보다 동적인 환경에서 인간의 감성을 추출하고자 본 연구를 수행하였다. 건강한 5명의 피험자로부터 심박 변화율, 피부 저항, 피부온도 등의 생리 신호를 측정하였다. 먼저, 정차, 정속 주행, 급출발, 급제동의 운전 상황 변화에 따른 자율신경계의 반응을 측정하였고, 둘째로, 직선 도로와 굴곡이 심한 도로에서 정속 주행을 하면서 생리 신호를 측정하여 도로상황 변화에 따른 자율신경계의 반응을 측정하였다. 정차 및 정속 주행에 비해 급출발, 급제동일 때, 직선도로에 비해 굴곡이 심한 도로에서 주행을 할 때 평균 R-R 간격은 감소하였고, 전력 스펙트럼의 (LF+MF)/HF비는 증가하였고, 피부온도는 감소하였고, 피부저항은 증가하였다. 본 연구로부터, 정차 및 정속 주행에 비해 급출발, 급제동일 때 그리고 직선도로에 비해 굴곡이 심한 도로에서 주행을 할 때 교감신경계의 활성화비가 증가한다는 일치된 경향을 관찰할 수 있었다. 앞으로 피실험자수를 늘려 보다 정확한 통계적 분석을 하고자 한다.

• The Journal of the Convergence on Culture Technology
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• v.7 no.4
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• pp.641-652
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• 2021

Drivers have willing to do secondary tasks in situations deemed safe autonomous driving. I studied that positive notifications for secure areas could improve situation awareness and driving performance after TOR(Take over request) in autonomous driving. Comparing TOR alert only and monitoring alert conditions, participants in the positive notification condition showed higher situation awareness and driving performance. Also, in emotional assessment, the positive notification condition showed higher positive evaluation than other conditions. Due to Covid-19, I designed experiments separate online with driving videos in experiment 1 and offline using a driving simulator in experiment 2. This study has implications that presented a different perspective on autonomous driving notification design.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.6
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• pp.235-249
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• 2020

The Ministry of Land, Infrastructure and Transport established safety standards for Level 3 autonomous vehicles for the first time in the world in December 2019, and specified the safety standards for conditional autonomous driving systems. Accordingly, it is necessary to analyze the influence of various driving environments on take-over. In this study, using a driving simulator, we investigated how traffic conditions and weather conditions affect take-over time and stabilization time. The experimental procedure was conducted in the order of preliminary training, practice driving, and test driving, and the test driving was conducted by dividing into a traffic density and geometry experiment and a weather environment experiment. As a result of the experiment, it was analyzed that the traffic volume and weather environment did not affect the take-over time and take-over stabilization time, and only the curve radius affects take-over stabilization time.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2016.11a
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• pp.169-171
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• 2016

본 논문에서는 일반 자연 영상에서 주로 적용되어 왔던 안개 제거 기법을 기반으로 하여 악천후 상황의 도로 주행 영상을 개선하는 방법을 제안한다. 악천후 상황이란 안개가 있거나 비, 눈이 오는 상황을 의미한다. 도로를 주행하는 환경에서는 비나 눈이 오는 경우에도 안개가 있는 상황과 비슷하기 때문에 안개 제거 기법을 기반으로 하여 악천후 환경의 영상을 개선한다. 우선 최신의 안개 제거 기법 중 하나인 non-local prior 기반의 기법을 도로 주행 영상에 적용 하였을 경우 문제점이 발생하게 되는데 그에 대한 원인을 분석한다. 그리고 이러한 문제점을 해결하기 위하여 예상된 전달량을 보정한다. 모의 실험을 통해 제안하는 방법을 적용하여 도로 주행 영상에서 발생한 문제점을 완화하고 악천후 상황이 개선된 결과를 얻었다.

• The Journal of the Korea Contents Association
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• v.22 no.4
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• pp.70-82
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• 2022

At the current stage of a semi-autonomous vehicle, there are situations in which the vehicle has to request take-over control to the driver quickly. However, current self-driving cars use only simple messages and warning sounds to notify drivers when handing over control, so they do not adequately convey considerations of individual characteristics or explanations of various emergent situations. This study investigated how visual and auditory information and the efficacy of drivers in self-driving cars can improve efficient take-over requests between the car and the driver. We found that there were significant differences in driver's cognitive load, reliability, safety, usability, and usefulness according to the combination of three visual and auditory information provided in the experiment of the take-over request situation. The results of this study are expected to help design self-driving vehicles that can communicate more safely and efficiently with drivers in urgent control transition situations.