• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.1 no.1
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• pp.41-51
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• 2002

As Advanced Traveler Information System(ATIS) is the kernel of the Intelligent Transportation System, it is very important how to manage data from traffic information collectors on a road and have at borough grip of the travel time's change quickly and exactly for doing its part. Link travel time can be obtained by two method. One is measured by area detection systems and the other is estimated by point detection systems. Measured travel time by area detection systems has the limitation for real time information because it Is calculated by the probe which has already passed through the link. Estimated travel time by point detection systems is calculated by the data on the same time of each. section, this is, it use the characteristic of the various cars of each section to estimate travel time. For this reason, it has the difference with real travel time. In this study, Artificial Neural Networks is used for estimating link travel time concerned about the relationship with vehicle detector data and link travel time. The method of estimating link travel time are classified according to the kind of input data and the Absolute value of error between the estimated and the real are distributed within 5$\~$15minute over 90 percent with the result of testing the method using the vehicle detector data and AVI data of Namsan Tunnel $\#$1. It also reduces Time lag of the information offered time and draws late delay generation and dissolution.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.2
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• pp.36-44
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• 2009

In this paper, we suggest a system of detecting a vehicle with lane violation, which can detect the vehicle with lane violation, by using the feature point tracking. The whole algorithm in the suggested system of detecting a vehicle with lane violation is composed of three stages such as feature extraction, register and tracking in feature for the tracking-targeted vehicle, and detecting a vehicle with lane violation. In the stage of feature extraction, the feature is extracted from the inputted image by sing the feature-extraction algorithm available for the real-time processing. The extracted features are again selected the racking-targeted feature. The registered feature is tracked by using NCC(normalized cross correlation). Finally, whether or not lane violation is finally detected by using information on the tracked features. As a result of experimenting the suggested system by using the acquired image in the section with a ban on intervention, the excellent performance was shown with 99.09% for positive recognition ratio and 0.9% for error ratio. The fast processing speed could be obtained in 34.48 frames per second available for real-time processing.

• The Journal of the Korea Contents Association
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• v.17 no.11
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• pp.303-311
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• 2017

Safety accidents in railway work continue to increase every year; Engineer's negligence, trackside worker's sensory deprivation and signalman's mistake are the main reasons of such incidents. We consider this problem by far the most urgent matter in railway work because of its steady increase and risk of taking a person's life. Based on that account, a new alarm system has developed, that is called Railway Access Alarm System, to allow railway workers to sense the access of trains with not only vision, but also hearing. The detector device of this system is installed on both sides of the track locating 1.5km from the workplace. When the train enters the place, the detector device can sense the entering, sending the detect sign of train to the alarm unit, then the alarm unit warns the workers by the LED lighting and sirens. This system has several advantages compared to previous systems. First, it recognizes the train at a long distance. Secondly, there is no need for wiring work since it is a wireless system. At last, the system works by rechargeable batteries and solar charger so that it is installed in the work places where there is no external power supply. Moreover, it is proven that the system is 100% reliable by the successful on-the spot inspection evaluating the capability.

• Journal of Korean Society of Transportation
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• v.27 no.5
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• pp.97-111
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• 2009

Image-based traffic information collection systems have entered widespread adoption and use in many countries since these systems are not only capable of replacing existing loop-based detectors which have limitations in management and administration, but are also capable of providing and managing a wide variety of traffic related information. In addition, these systems are expanding rapidly in terms of purpose and scope of use. Currently, the utilization of image processing technology in the field of traffic accident management is limited to installing surveillance cameras on locations where traffic accidents are expected to occur and digitalizing of recorded data. Accurately recording the sequence of situations around a traffic accident in a signal intersection and then objectively and clearly analyzing how such accident occurred is more urgent and important than anything else in resolving a traffic accident. Therefore, in this research, we intend to present a technology capable of overcoming problems in which advanced existing technologies exhibited limitations in handling real-time due to large data capacity such as object separation of vehicles and tracking, which pose difficulties due to environmental diversities and changes at a signal intersection with complex traffic situations, as pointed out by many past researches while presenting and implementing an active and environmentally adaptive methodology capable of effectively reducing false detection situations which frequently occur even with the Gaussian complex model analytical method which has been considered the best among well-known environmental obstacle reduction methods. To prove that the technology developed by this research has performance advantage over existing automatic traffic accident recording systems, a test was performed by entering image data from an actually operating crossroad online in real-time. The test results were compared with the performance of other existing technologies.

• International Journal of Highway Engineering
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• v.10 no.3
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• pp.19-31
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• 2008

Video image processing systems(VIPS) offer numerous benefits to transportation models and applications, due to their ability to monitor traffic in real time. VIPS based on wide-area detection, i.e., multi-lane surveillance algorithm provide traffic parameters with single camera such as flow and velocity, as well as occupancy and density. However, most current commercial VIPS utilize a tripwire detection algorithm that examines image intensity changes in the detection regions to indicate vehicle presence and passage, i.e., they do not identify individual vehicles as unique targets. If VIPS are developed to track individual vehicles and thus trace vehicle trajectories, many existing transportation models will benefit from more detailed information of individual vehicles. Furthermore, additional information obtained from the vehicle trajectories will improve incident detection by identifying lane change maneuvers and acceleration/deceleration patterns. The objective of this research was to relate traffic safety to VIPS tracking and this paper has developed a computer vision system of monitoring individual vehicle trajectories based on image processing, and offer the detailed information, for example, volumes, speed, and occupancy rate as well as traffic information via tripwire image detectors. Also the developed system has been verified by comparing with commercial VIP detectors.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.3D
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• pp.353-359
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• 2006

Image frame analysis is a conventional way of evaluating loop detector's performance. In image frame analysis, the time to evaluate performance is linearly proportional to the number of evaluated subjects, and the results can be subjective, depending on operator's personal evaluation standards and physical condition. Also, this method is often inferior in accuracy to that provided by the evaluated devices. Therefore, it is critical to develop a portable standard system which has better accuracy and more objectivity in evaluating vehicle detectors. This paper discusses function and reliability of tape-switch detector, which can be a replacement for image frame analysis, for effectively measuring traffic volume, speed, and occupancy.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.2
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• pp.140-152
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• 2017

This Paper is for A study of sensor fusion using Radar sensor and Vision sensor in moving object detection. Radar sensor has some problems to detect object. When the sensor moves by wind or that kind of thing, it can happen to detect wrong object like building or tress. And vision sensor is very useful for all area. And it is also used so much. but there are some weakness that is influenced easily by the light of the area, shaking of the sensor device, and weather and so on. So in this paper I want to suggest to fuse these sensor to detect object. Each sensor can fill the other's weakness, so this kind of sensor fusion makes object detection much powerful.

• Journal of the Korea Society of Computer and Information
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• v.27 no.11
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• pp.181-190
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• 2022

In this paper, we use a LiDAR sensor and an image camera to detect a left-turning waiting vehicle in two ways, unlike the existing image-type or loop-type left-turn detection system, and a left-turn traffic signal corresponding to the waiting length of the left-turning lane. A system that can efficiently assign a system is introduced. For the LiDAR signal transmitted and received by the LiDAR sensor, the left-turn waiting vehicle is detected in real time, and the image by the video camera is analyzed in real time or at regular intervals, thereby reducing unnecessary computational processing and enabling real-time sensitive processing. As a result of performing a performance test for 5 hours every day for one week with an intersection simulation using an actual signal processor, a detection rate of 99.9%, which was improved by 3% to 5% compared to the existing method, was recorded. The advantage is that 99.9% of vehicles waiting to turn left are detected by the LiDAR sensor, and even if an intentional omission of detection occurs, an immediate response is possible through self-correction using the video, so the excessive waiting time of vehicles waiting to turn left is controlled by all lanes in the intersection. was able to guide the flow of traffic smoothly. In addition, when applied to an intersection in the outskirts of which left-turning vehicles are rare, service reliability and efficiency can be improved by reducing unnecessary signal costs.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.7 no.4
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• pp.13-24
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• 2008

Real-time traffic data are readily obtainable by traffic surveillance systems of intelligent transportation systems (ITS). Such data greatly support further applications in the field of traffic operations, planning, and safety. However, traffic data should be appropriately processed to fully exploit the benefits of data collection capability. Rather than developing individual data processing techniques, which is major concern of existing studies, this study proposes a novel methodology for evaluating data processing techniques in an integrated manner. Also, a tool for implementing the proposed methodology is developed. Users can extract useful and more reliable traffic data based upon their ultimate purpose of data usage by the evaluation tool developed in this study. Actual freeway traffic data are, as an example, fed into the evaluation tool, and results are discussed.

• Proceedings of the Korean Society of Computer Information Conference
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• 2010.07a
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• pp.137-140
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• 2010

교통사고의 발생은 교통 혼잡의 주요 원인으로 작용되어 교통사고에 의한 직 간접적 손해비용까지 지출되고 있다. 따라서 교통사고를 사전에 예방하거나 사고가 발생한 후 신속하게 처리할 수 있는 실시간 교통사고 대처 시스템이 요구되고 있다. 즉, 교통사고 자동검지 시스템의 필요성은 가 피해자의 구분에 활용하는 것 이외에 신속한 인명구조와 사고처리 등의 교차로 유고관리가 가능하며, 교통사고로 발생할 수 있는 교통 혼잡을 최소화 할 수 있다. 본 논문에서는 다양한 형태의 충돌 및 추돌 사고를 검지하는 시스템의 성능을 개선하기 위한 것으로 영상 또는 소리라는 매체에 기반을 둔 시스템에서 자동 검지의 한계성을 도출하고 개선하고자 하였다. 테스트 베드를 기반으로 자동검지 실패의 원인을 분석하고 그 원인에 따른 오인식의 문제점을 개선하여 운전자 단독사고로 인하여 차량 추적이 불가능한 경우, 소리 없이 발생한 사고, 야간에 발생한 사고 등의 문제점들을 극복함과 동시에 성능을 개선하는데 그 목적이 있다.