• 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.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.04a
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• pp.367-371
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• 2007

최근 여러 지역에서 발생되는 지하철 참사 및 대형화재 또는 지하철 역사, 대형 지하상가, 백화점, 지하공간, 대형쇼핑센터, 숙박업소, 공공건물등 대형 다중이용시설 등에서 발생될 수 있는 예측 불가능한 인재, 천재지변에 안전하게 대피하기 위한 수단으로 비상등 및 여러 감지기들이 소방법 개정으로 의무설치 하고 있다. 비상등 및 감지기들은 비상시 위험 감지 및 경고 전파를 위해 사용되는데 방음벽이나 격벽, 경고 거리의 제한으로 인해 경고 전달의 어려움이 있다. 본 논문에서는 무선 데이터 전송기능 및 경고등, 음성전파 기능을 갖는 무선 지능형 화재 감지/경고시스템을 설계하고자 한다.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.4
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• pp.36-43
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• 2011

The forward collision of vehicles in high speed can cause a chain collisions and high fatality rate. Most of the forward collisions are caused by insufficient braking distance due to detection time of driver and safe distance. Also, accumulated detection time of driver is cause of chain collisions after the forward collision. The FVCWS prevents the forward collision by maintaining the safety distance inter-vehicle and reducing detection time of driver. However the FVCWS can cause chain collisions because the system that interacts only forward vehicle has accumulated detection time of driver. In this paper, we analyze forward and chain collisions of normal vehicles and FVCWS vehicles on static traveling scenario. And then, we analyze and compare V2V based FVCWS with them after explaining the system. The V2V FVCWS reduces detection time of driver alike FVCWS as well as remove accumulated detection time of driver by broadcasting emergence message to backward vehicles at the same time. Therefore, the system decrease possibility of forward and chain collisions. All backward normal vehicles and 3~4 backward FVCWS vehicles have possibility of forward and chain collisions in result of analysis. However V2V FVCWS vehicles almost do not chain collisions in the result.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.3
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• pp.310-315
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• 2007

When a mail was given to users, each user's response could be different according to his or her preference. This paper presents a solution for this situation by constructing a u!;or preferred ontology for anti-spam systems. To define an ontology for describing user behaviors, we applied associative classification mining to study preference information of users and their responses to emails. Generated classification rules can be represented in a formal ontology language. A user preferred ontology can explain why mail is decided to be spam or non-spam in a meaningful way. We also suggest a nor rule optimization procedure inspired from logic synthesis to improve comprehensibility and exclude redundant rules.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.3B
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• pp.165-173
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• 2012

In this paper, we propose a random backoff scheme for Emergency Warning Messages (EWMs) in the vehicle-to-vehicle environment. The EWMs are disseminated from a vehicle that detects an emergency situation to other vehicles in a multi-hop fashion. Since the vehicle-to-vehicle communication based on IEEE 802.11 adapts CSMA/CA, the density of vehicles increase the probability of collisions between transmissions. Moreover, in the presence of background traffic, the EWM should have a higher priority than that of other messages in neighboring vehicles. To that end, we propose the Distant-Dependent Adaptive Backoff (DDAB) scheme, which set a different contention window for random backoff depending on the distance from the sender to the receiver. In the case when a vehicle is expected to located in the outskirts of the communication boundary, the proposed scheme makes the contention window size small in order to compete the background traffic transmission. Otherwise the contention window is set to a large number to reduce the collision possibility among the EWM transmissions. Via simulations, we show that the proposed scheme performs better than the previous schemes for EWM.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2015.07a
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• pp.338-339
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• 2015

VTS Decision Support System can be defined a tool which assists VTS operator for decision-making at operational, planning and management level especially for the safety and efficiency of vessel traffic. This paper presents classification of VTS Decision Support System, detailed definition of alerts, and operational and functional requirements of VTS Decision Support System.

• Proceedings of the KAIS Fall Conference
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• 2009.05a
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• pp.709-712
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• 2009

대부분의 고속도로 안개경고시스템은 시정측정을 위해 고가의 광학센서를 사용하고 있으나 운전자의 시정감각과 유사하면서도 비교적 저가인 CCTV를 이용한 시정측정에 관한 연구가 활발히 이루어지고 있다. 그러나 대부분의 CCTV를 이용한 시정측정 방법은 ROI를 기반으로 하고 있어 설치가 까다롭고 기존 CCTV를 활용하기 어렵다는 문제점을 가지고 있다. 본 논문에서는 고속도로상의 안개경고는 약 1~2Km이내의 시정일 때 발생되며, 눈으로 물체를 식별할 수 있는 최대거리가 시정이라는 기초적인 개념에 근거하여 고속도로 안개경고시스템에 사용될 수 있는 Non-ROI 기반의 실시간 CCTV 시정측정 방법을 제안한다. 이를 위해 본 논문에서는 고속도로상에 주행중인 차량의 실시간 이동영역과 가시선을 검출하고 카메라와 도로간의 상관관계를 나타내는 도로모델을 이용하여 시정측정을 수행하는 방법을 제시한다. 제안된 방법은 1~2Km 이내의 시정측정을 위한 방법으로 ROI가 필요없고 직관적이고 현실적인 주야간 시정측정이 가능하며 기존의 고속도로 CCTV에 바로 적용할 수 있다는 장점이 있다.

• Journal of Korean Society of Transportation
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• v.30 no.2
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• pp.43-52
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• 2012

A lane departure warning system (LDWS) is an effective technology-based countermeasure for preventing traffic crashes as it provides warning information to drivers. Understanding the characteristics of perception and satisfaction levels on LDWS is fundamental for deriving better performance and functionality enhancements of the system. The purpose of this study is to evaluate the user satisfaction of LDWS. A survey to collect user perception and user preference data was conducted. Both cross-tabulation analysis and binary logistic regression technique were adopted to identify the factors affecting user satisfaction for LDWS. The results revealed that the accuracy and timeliness of warning information was significant for evaluating the effectiveness of LDWS. In particular, the warning accuracy at a curve segment on the road was the most dominant factor affecting user satisfaction. The outcome of this study would be valuable in evaluating and designing LDWS functionalities.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1531-1532
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• 2008

본 논문은 앞을 볼 수 없는 시각 장애인의 보행 시 장애물에 대한 안전을 고려한 시스템으로 보행 시 전방에 보행 장애 물체가 나타날 경우 초음파 센서가 장애물의 위치거리를 측정하고 측정된 거리 데이터를 근거리 무선통신을 통해 송.수신하여 이를 최종적으로 사용자인 시각 장애인에게 음성으로 사전 경고함으로써 발생할 수 있는 위험 요소를 대처하는데 기여할 수 있도록 설계하였다. 설계된 시스템은 IT관련 기술을 활용함으로써 휴먼 IT기술을 구현하고자 하였다.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.3
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• pp.86-99
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• 2021

This research proposes the Accident Prevention System to prevent collision accident that can occur due to blind spots such as crossway or school zone using V2I communication. Vision sensor and LiDAR sensor located in the infrastructure of crossway somewhere like that recognize objects and warn vehicles at risk of accidents to prevent accidents in advance. Using deep learning-based YOLOv4 to recognize the object entering the intersection and using the Manhattan Distance value with LiDAR sensors to calculate the expected collision time and the weight of braking distance and secure safe distance. V2I communication used ROS (Robot Operating System) communication to prevent accidents in advance by conveying various information to the vehicle, including class, distance, and speed of entry objects, in addition to collision warning.