• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.683-686
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• 2018

Autonomous vehicles are the 4th industrial revolution that utilizes artificial intelligence(AI) and superconducting technology, and is a world-wide investment and research project. However, a Uber vehicle under test in Arizona, USA, was accidentally killed by pedestrians crossing the road in the dark night, and accidents occurred when the Tesla vehicle was exposedto the backlightof the sun. These problems were caused by misunderstandings and choice about sensors mounted on autonomous vehicles due to bad weather such as snow, rain, and sunlight. In this paper, we analyze the composition of the autonomous vehicle and the cause of the accident, and consider the criteria that should be judged in case of emergency in which human accidents may occur. This paper analyzes the composition of autonomous vehicles and causes of accidents, and considers the criteria that should be choice in an emergency where an accident may occur.

• Convergence Security Journal
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• v.23 no.1
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• pp.89-95
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• 2023

In order to help reduce the medical expenses of patients with auto insurance accidents, this study predicted the treatment period, which is the most important factor in the medical expenses of patients in their 40s and 50s, and analyzed the factors affecting the treatment period. To this end, a mechine learning model using five algorithms such as Decision Tree was created, and its performance was compared and analyzed between models. There were three algorithms that showed good performance including Decison Tree, Gradient Boost, and XGBoost. In addition, as a result of analyzing the factors affecting the prediction of the treatment period, the type of hospital, the treatment area, age, and gender were found. Through these studies, easy research methods such as the use of AutoML were presented, and we hope that the results of this study will help policies to reduce medical expenses for automobile insurance accidents.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.6
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• pp.11-20
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• 2023

The cost of medical treatment for motor vehicle accidents is increasing every year. In this study, we created a model to predict long-term hospitalization(more than 18 days) among minor patients, which is the main item of increasing traffic accident medical expenses, using five algorithms such as decision tree, and analyzed the factors affecting long-term hospitalization. As a result, the accuracy of the prediction models ranged from 91.377 to 91.451, and there was no significant difference between each model, but the random forest and XGBoost models had the highest accuracy of 91.451. There were significant differences between models in the importance of explanatory variables, such as hospital location, name of disease, and type of hospital, between the long-stay and non-long-stay groups. Model validation was tested by comparing the average accuracy of each model cross-validated(10 times) on the training data with the accuracy of the validation data. To test of the explanatory variables, the chi-square test was used for categorical variables.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.6
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• pp.1321-1328
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• 2015

The automobiles in Korea have approximately 60 years of history and this is relatively short compared to advanced countries. However, considering the traffic accident rate or severity related to automobiles, various efforts are required to reduce traffic accidents. Various problems caused by traffic accidents are not only related to individual damages but also have become social problems. In order to resolve this, it is important to analyze the cause of traffic accidents. This study aims to suggest methods to reduce traffic accidents by analyzing driving behavior, which is one of the reasons for a number of traffic accidents that were collected through traffic accident videos reported using DVRs (Driving Video Recorder) and were aired to the public via a SBS TV program for the past two years and four months. In particular, unlike other existing studies that aim at analyzing the causes of traffic accidents simply using data, this study constructed a database by analyzing every single DVR that stores the situation before and after the accident using relatively high-resolution video information to provide practical plans to reduce traffic accidents through statistical analysis.

• Proceedings of the Korean Institute of Industrial Safety Conference
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• 1998.05a
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• pp.241-244
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• 1998

최근에 이르러 자동차 화재는 일반화재 보다 높은 연평균 16.5%의 증가율을 나타내며, 전체 화재 건수의 17%로 주택 및 아파트 다음으로 화재 발생 건수가 많다. 자동차 화재는 엔진과열, 전기장치의 불량, 전자 제어화에 따른 각종 감지기의 연결상태 및 기능 불량, 교통사고로 인한 엔진의 파괴 및 연료 누출등이 원인이 되고 있으며, 주로 엔진룸에서 화재가 발생하여 차량 내부로 전파되는 특징이 있다. 따라서 화재 발생 초기에 화재를 감지하여 운전자에게 경보를 발하고, 화재를 진압할 수 있는 자동차 화재 감지시스템의 개발이 중요해 지고 있다. (중략)

• Proceedings of the Korean Society of Disaster Information Conference
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• 2017.11a
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• pp.251-252
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• 2017

현재 우리나라는 자동차 수의 폭발적인 증가에도 불구하고 전체적인 교통사고 건수는 감소되는 추세를 보이고 있는데 반해 고속도로에서 발생하는 사고는 증가 추세를 보이고 있다. 따라서 고속도로의 사고 특성을 파악하여 사고를 감소시키기 위한 다양한 연구가 많이 진행되고 있다. 하지만 다양한 사고 유발요인들과 사고 데이터 제공의 한계로 인해 고속도로 교통사고의 특성에 대해 명확히 규명한 연구는 부족한 실정이다. 본 연구에서는 전국고속도로 3개년도(2013~2015)의 자료를 활용하여 전국 고속도로 교통사고의 특성을 파악하고 사고건당 EPDO(Equivalent Property Damage Only)를 계산하여 EPDO 값과 사고원인별, 도로 기하구조별, 기상조건, 운전자 성별, 나이대별 등 여러 사고 조건과의 상관관계를 회귀분석을 통해 분석하였다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.315-318
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• 2013

지금의 자동차는 정보기술(IT)기술과 융합되어 기존의 운송기능에서 운전자의 편의를 제공하는 기능을 제공한다. 운행 중 운전자에게 교통상황과 목적지로 가는 길을 알려주는 내비게이션은 운전자에게 효율적인 운전을 유도 할 수 있는 환경 만들어 준다. 하지만 운전자의 안전을 위해 자동차 상태를 자동으로 점검하여 알려주는 기능은 미비한 실정이다. 본 논문에서 개발하고자 하는 자동차 인포테인먼트 시스템은 안드로이드 플랫폼 기반 임베디드 장비를 이용하여 안드로이드에서 기본적으로 제공하는 기능을 통해 기존 자동차 엔터테인먼트 기능을 제공하며, 추가적으로 자동차 주행정보를 기록하여 사고유무를 확인하는 블랙박스 기능, 주행정보를 활용하여 자동차 소모품들의 수명을 점검하고, 자동차 내부 고장정보를 발견하고 알려주는 자동차 자가진단기능을 제공한다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.6
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• pp.1125-1132
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• 2012

The researches on driver assistance systems that can prevent an accident have been actively performed due to social issues of traffic accidents with development of vehicle industry in recent. It is required for researchers to develope systems which assist driver's perception and judgment when considering that over 70% of traffic accidents occur by drivers' carelessness and 75% of the total accidents occur at the speed of less 29km per hour. In this paper, we implemented a front and rear vehicle monitoring system that monitors distance from a vehicle to obstacles in real-time at the low-speed or back-ward driving. The proposed system consists of ultrasonic sensors of high angle and wide angle of beam spread, ATmega128, and DSP processor.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.6
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• pp.222-234
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• 2020

Autonomous vehicles are equipped with a wide rage of sensors such as GPS, RADAR, LIDAR, camera, IMU, etc. and are driven by recognizing and judging various transportation systems at intersections in the city. The accident ratio of the intersection of the autonomous vehicles is 88% of all accidents due to the limitation of prediction and judgment of an area outside the sensing distance. Not only research on non-signalized intersection collision avoidance strategies through V2V and V2I is underway, but also research on safe intersection driving in failure situations is underway, but verification and fragments through simple intersection scenarios Only typical V2V failures are presented. In this paper, we analyzed the architecture of the V2V module, analyzed the causal factors for each V2V module, and defined the failure mode. We presented intersection scenarios for various road conditions and traffic volumes. we used the ISO-26262 Part3 Process and performed HARA (Hazard Analysis and Risk Assessment) to analyze the risk of autonomous vehicle based on the simulation. We presented ASIL, which is the result of risk analysis, proposed a monitoring concept for each component of the V2V module, and presented monitoring coverage.

• Journal of Auto-vehicle Safety Association
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• v.11 no.3
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• pp.43-47
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• 2019

Developed countries are operating an in-depth database in motor vehicle crashes nationwide. They do not rely solely on the police investigation reports that are responsible for motor vehicle crashes in each country but are developing into a useful database by expanding the categories of data through more indicators addition. In Korea, after implementing comprehensive measures to reduce traffic accident deaths in 2013, the medical centers participated in establishing the actual accident investigation system, which was called as the Korean In-Depth Accident Study (hereinafter KIDAS). This KIDAS database included more in-depth indicators as the types of accidents, types of vehicles, the injury severity, adequacy of safety devices, seating position of passengers. Although there are difficulties in establishing an actual accident investigation system including data collection due to various restrictions, if the system can cooperate with each other such as medical centers, insurance companies, police, fire and rescue services, towing companies, and car repair shops in the future, It would be expected to contribute to the development of safer vehicle, treatment system and traffic safety policy that lower the injury severity of occupant in the event of a motor vehicle crashes.