• Title/Summary/Keyword: 교통사고데이터

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자율운항선박 입출항 스케쥴링을 위한 AIS 기반 해상 교통 혼잡도 예측 기법 개발

  • 김세원;이서호;손준배;엄정온;이주향;김혜진;김동함;윤상웅
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • 2022.06a
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    • pp.295-296
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    • 2022
  • 자율운항선박은 선원의 항해 조작 없이 선박 스스로 운항하는 선박을 의미한다. 자율운항선박의 운항 시 충돌 및 사고 위험도가 큰 지역은 운항 중 선박을 많이 조우하게 되는 항 내 및 연안 지역이다. 실제로 충돌사고의 85% 이상이 항 내 및 연안 지역에서 발생한다. 따라서 자율운항선의 운항 안전성 확보를 위해 항 내 및 연안 지역에서의 운항 안전성을 검토하는 것은 미래 자율운항선 항 내 운용 체계에서 중요한 역할을 하게 된다. 대양에서는 선박 자체의 운항성능이 중요하지만, 항구 입출항 시에는 타선 및 터미널등과의 상호작용이 자율운항선의 입출항 안전성과 직결된다. 따라서 본 연구에서는 자율운항선이 항구 근처에 접근하여 입출항을 위해 대기하고 있는 경우에 입출항 결정을 내릴 수 있는 결정 알고리즘을 위한 해상혼잡도를 예측하는 알고리즘을 개발하는 과정을 소개한다. 혼잡 예측 알고리즘 개발을 위해 선박의 AIS통항 데이터를 분석하여 주요 항로를 구분하고 주요 항로의 이용 빈도 및 운항 시점의 선박 집중도 및 충돌위험 상황을 파라미터로 하여 특정 시간이 지난 후의 혼잡도를 예측하는 시스템을 개발하고자 한다.

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A Study on Safety Management of Day Care Center using disaster management system (재난관리스템을 이용한 어린이집 안전관리에 관한 연구)

  • Jeong, Chang-sik;Kwon, Mee-Rhan
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.18 no.1
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    • pp.29-35
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    • 2018
  • Safety accidents are frequently occurring in day care centers in recent years. The number of types of safety accidents is bumping into, falling, burning, school bus accident, insertion... etc., and the number of children who have died due to such accidents is increasing steadily every year. Therefore, it is urgent to prevent accidents at day care centers. IoT (Internet of Things) is managed by connecting various sensors and related products from the living space to the Internet in order to prevent them from being dangerous. In particular, IoT products can be automatically controlled by smart phones and sensors anytime and anywhere, thus saving energy, time, convenience and prompt accuracy. This paper proposes a research model to prevent and respond to disasters by using SK LoRa communication network and Arduino, which are Internet access networks for building disaster management in schools, kindergartens and day care centers. And various sensors needed for building disaster management express various safety states in the building and suggests a system that can control the residential environment by transmitting and receiving data to smart phone.

Methodology of Calibration for Falling Objects Accident-Risk-Zone Approach Detection Algorithm at Port Considering GPS Errors (GPS 오차를 고려한 항만 내 낙하물 사고위험 알고리즘 보정 방법론 개발)

  • Son, Seung-Oh;Kim, Hyeonseo;Park, Juneyoung
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.19 no.6
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    • pp.61-73
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    • 2020
  • Real-time location-sensing technology using location information collected from IoT devices is being applied for safety management purposes in many industries, such as ports. On the other hand, positional error is always present owing to the characteristics of GPS. Therefore, accident-risk detection algorithms must consider positional error. This paper proposes an methodology of calibration for falling object accident-risk-zone approach detection algorithm considering GPS errors. A probability density function was estimated, with positional error data collected from IoT devices as a probability variable. As a result of the verification, the algorithm showed a detection accuracy of 93% and 77%. Overall, the analysis results derived according to the GPS error level will be an important criterion for upgrading algorithms and real-time risk managements in the future.

A study on accident prevention AI system based on estimation of bus passengers' intentions (시내버스 승하차 의도분석 기반 사고방지 AI 시스템 연구)

  • Seonghwan Park;Sunoh Byun;Junghoon Park
    • Smart Media Journal
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    • v.12 no.11
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    • pp.57-66
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    • 2023
  • In this paper, we present a study on an AI-based system utilizing the CCTV system within city buses to predict the intentions of boarding and alighting passengers, with the aim of preventing accidents. The proposed system employs the YOLOv7 Pose model to detect passengers, while utilizing an LSTM model to predict intentions of tracked passengers. The system can be installed on the bus's CCTV terminals, allowing for real-time visual confirmation of passengers' intentions throughout driving. It also provides alerts to the driver, mitigating potential accidents during passenger transitions. Test results show accuracy rates of 0.81 for analyzing boarding intentions and 0.79 for predicting alighting intentions onboard. To ensure real-time performance, we verified that a minimum of 5 frames per second analysis is achievable in a GPU environment. his algorithm enhance the safety of passenger transitions during bus operations. In the future, with improved hardware specifications and abundant data collection, the system's expansion into various safety-related metrics is promising. This algorithm is anticipated to play a pivotal role in ensuring safety when autonomous driving becomes commercialized. Additionally, its applicability could extend to other modes of public transportation, such as subways and all forms of mass transit, contributing to the overall safety of public transportation systems.

An analysis of behavioral characteristics in drivers in roll-over accident (전복사고 운전자를 대상으로 자동차 안전장치에 대한 행동특성 분석)

  • Lee, Hyo-Ju;Kim, Ho-Jung;Lee, Kang-Hyun;Lee, Myung-Lyeol;Choi, Hyo-Jueng
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.16 no.11
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    • pp.7329-7334
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    • 2015
  • This is to analyze of driver behavioral and the accident characteristics in rollover. The study period was January 2011 to May 2014 and the subject of study was 102 person who were drivers visited the emergency room. Research tool includes a damage information of the vehicle, accident mechanism, damage to the patient clinical information with the injury data from the ROAD Traffic Authority. For data analysis, SPSS 18.0 was used for t-test, ANOVA and Chi-square test. Injury Severity Score average score according to the vehicle type is 6.00 points in the smaller vehicle, at high vehicle 11.78 points, from the other vehicle that showed 14.70 points. Significant differences between the three groups did not show (P=.267). Men did not use a seat belt significantly compared to women(P=.007). Vehicle type and weather, this was no correlation with whether or not use the seat belt(P=.755, P=.793). But showed a tendency to smaller size vehicles drivers do not use a seat belt, the weather could see a little more inclined to use a seat belt rather than a sunny day. Finally, in rollover accidents as in other types of accident it was confirmed that the seat belt has a great influence on the damage.

Development of The Safe Driving Reward System for Truck Digital Tachograph using Hyperledger Fabric (하이퍼레저 패브릭을 이용한 화물차 디지털 운행기록 단말기의 안전운행 보상시스템 구현)

  • Kim, Yong-bae;Back, Juyong;Kim, Jongweon
    • Journal of Internet Computing and Services
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    • v.23 no.3
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    • pp.47-56
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    • 2022
  • The safe driving reward system aims to reduce the loss of life and property by reducing the occurrence of accidents by motivating safe driving and encouraging active participation by providing direct reward to vehicle drivers who have performed safe driving. In the case of the existing digital tachograph, the goal is to limit dangerous driving by recording the driving status of the vehicle whereas the safe driving reward system is a support measure to increase the effect of accident prevention and induces safe driving with financial reward when safe driving is performed. In other words, in an area where accidents due to speeding are high, direct reward is provided to motivate safe driving to prevent traffic accidents when safe driving instructions such as speed compliance, maintaining distance between vehicles, and driving in designated lanes are performed. Since these safe operation data and reward histories must be managed transparently and safely, the reward evidences and histories were constructed using the closed blockchain Hyperledger Fabric. However, while transparency and safety are guaranteed in the blockchain system, low data processing speed is a problem. In this study, the sequential block generation speed was as low as 10 TPS(transaction per second), and as a result of applying the acceleration function a high-performance network of 1,000 TPS or more was implemented.

Design and Implementation of Emergency Calamity System within Wireless Personal Area Network (근거리 무선 통신을 이용한 긴급재난상황 설계 및 구현)

  • Kim, Young-Ji;Lim, Choong-Soo
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2008.06a
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    • pp.269-273
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    • 2008
  • 본 논문에서는 근거리 무선 통신을 이용하여 사용자의 현재 위치에서 일어나고 있는 교통사고, 화재, 환자발생 등의 긴급재난상황 목격시 사용자가 해당 상황을 ZigBee 기반의 무선 센서 네트워크 사용자에게 알리고, 알린 정보를 실시간 쉽게 확인 할 수 있도록 긴급재난상황을 모니터링 하는 시스템을 제안하였다. 근거리 무선 통신 중센서와 사용자 무선 단말기 사이의 데이터 전송 구조가 간단하고, 초저가의 센서 네트워크 구성시 낮은 전력을 소모하는 장점을 가진 ZigBee로 구현하였다. 현재 사용자 주변의 일어나는 긴급재난 상황을 주변 사용자와 ZigBee 기반의 무선 센서 네트워크를 구축하여 실시간으로 보다 정확한 정보를 주변 사용자에게 알려주거나 혹은 사용자가 모니터링을 하여 사용자의 피해를 최소화로 줄여 사용자의 안전과 편의를 향상시킨다.

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A Quantitative Collision Probability Analysis in Port Waterway (항만수로의 정량적인 충돌확률 분석)

  • Jeong, Jung-Sik;Kim, Kwang-Il;Park, Gyei-Kark
    • Journal of the Korean Institute of Intelligent Systems
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    • v.22 no.3
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    • pp.373-378
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    • 2012
  • In terms of the maritime accident prevention, risk analysis at targeted warterways is important for planning safety waterways. This paper analyzes the maritime accidents probability in the Mokpo waterways, South Korea, based on the IWRAP(IALA Waterway Risk Assessment) of the quantitative accident probability tool. Vessel collision probability cate is calculated by vessels meeting direction, using IWRAP. This paper contribute to advance improvement of vessel traffic service by VTS sector providing vessel fairway risk data.

Data Fusion, Ensemble and Clustering for the Severity Classification of Road Traffic Accident in Korea (데이터융합, 앙상블과 클러스터링을 이용한 교통사고 심각도 분류분석)

  • Sohn, So-Young;Lee, Sung-Ho
    • Journal of Korean Institute of Industrial Engineers
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    • v.26 no.4
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    • pp.354-362
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    • 2000
  • Increasing amount of road tragic in 90's has drawn much attention in Korea due to its influence on safety problems. Various types of data analyses are done in order to analyze the relationship between the severity of road traffic accident and driving conditions based on traffic accident records. Accurate results of such accident data analysis can provide crucial information for road accident prevention policy. In this paper, we apply several data fusion, ensemble and clustering algorithms in an effort to increase the accuracy of individual classifiers for the accident severity. An empirical study results indicated that clustering works best for road traffic accident classification in Korea.

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Outlier Distinction Algorithm via Vessel Representative Trajectory Extraction (선박 대표 궤적 추출을 통한 Outlier 판별 알고리즘)

  • Park, Jin-Gwan;Oh, Joo-Seong;Kim, Bum-Mu;Jeon, Sung-Min;Lee, Sung-Ro;Jeong, Min-A
    • Annual Conference of KIPS
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    • 2014.11a
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    • pp.102-104
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    • 2014
  • 본 논문은 해상 교통량 증가로 급증하는 선박 사고 위험을 줄이기 위해 안전 운항을 위한 대규모 선박 궤적 클러스터링을 제안한다. 선박의 위도와 경도, 이름 및 상태, 속도, 선수 방향 등이 기록된 대용량의 데이터집합을 바탕으로 선박 궤적 클러스터링을 통해 총 2개의 선박 대표 궤적을 추출한다. 해당 선박의 이전까지의 대표 궤적, 그리고 해당 해상의 모든 선박의 대표 궤적을 추출한 후 현재 해당 선박의 궤적패턴과 비교하여 유사하지 않으면 Outlier로 판별하여 이상 거동 및 불규칙 움직임, 충돌상황을 대비할 수 있도록 의사결정에 도움을 줄 수 있는 알고리즘을 제안하였다.