• Journal of Korean Society of Transportation
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• v.29 no.2
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• pp.111-121
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• 2011

This paper discusses a method for optimizing the semi-actuated traffic signal control system by adjusting the initial interval according to the number of vehicles waiting for the green light in the actuated phase. We also present a Left-Turn actuated traffic signal control strategy that examines the vehicular noise in the detection area and determines the phase extension and the gap-out. In order to detect the vehicles in real-time, an image detector's Video Image Tracking technology was adopted. A 'Zone in Zone'method was implemented, and the image detection area is segmented into three zones: 1) Zone1 for verifying a vehicles obligatory presence, 2) Zone2 for counting the standby vehicles, and 3) Zone3 for examining the number of vehicles that have passed. The on-site assessment of the Left Turn Actuated Control is carried out using CORSIM, and the results show that the Control Delay decreased by 23.10%, 15.06%, and 4.34% compared to the delays resulted from pre-timed control, semi-actuated control-1 and semi-actuated control-2 traffic signal control systems respectively. The Queue Time also decreased by 36.24%, 20.10% and the Total Time by 14.36%, 7.02% for the same scenario. Which clearly demonstrates the operational efficiency. A sensitivity analysis reveals that the improvement from the propose traffic control strategy tends to increase as the through traffic volume reaches a saturated condition and the left-turn traffic volume decreases.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.2
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• pp.105-115
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• 2017

Conventional traffic detection sensors such as loop detectors and image sensors are expensive to install and maintain and require different detection algorithms depending on the night and day and have a disadvantage that the detection rate varies widely depending on the weather. On the other hand, the millimeter-wave radar is not affected by bad weather and can obtain constant detection performance regardless of day or night. In addition, there is no need for blocking trafficl for installation and maintenance, and multiple vehicles can be detected at the same time. In this study, a multi-target detection algorithm for a radar sensor with this advantage was devised / implemented by applying a conventional single target detection algorithm. We performed the evaluation and the meaningful results were obtained.

• The KIPS Transactions:PartB
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• v.15B no.6
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• pp.543-552
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• 2008

ATIS(Advanced Traveler Information System) is the system to offer a real-time traffic information or traffic situation for the benefit of the client. One of traffic information collection methods for ATIS research is the method of image analysis. The method is divided into two : one is the method to set two loop detectors at the area and the other is the method detecting the vehicle through an image analysis. In this paper, we propose a real-time traffic information collection system to mix two methods. The system installs multiple virtual detection lines and traces the location of the vehicle. Use of multiple virtual detection lines supplements the defect of the method of loop detectors. And we drew a representative pixels in the detecting area and used it for image analysis. This is to solve the problem of time delay which increases as the image size increases. We gathered traffic images and experimented using the system and got 92.32% of detection accuracy.

• Journal of Korea Spatial Information System Society
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• v.9 no.1
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• pp.79-90
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• 2007

In this paper we proposed and implemented an incident detection model which combines fuzzy algorithm and traffic pattern in order to enhance the efficiency of incident detection for the highways with lamps. Most of the existing algorithms dealt with highways without lamps and can not be used for detecting incidents in the highways with lamps. The data used for model building are traffic volume, occupancy, and speed data. They have been collected by a loop sensor at 5 minutes interval at a point in the Internal Circular Highway of Seoul for the period of 3 months. In this model, the three parameters collected by sensor were fuzzified and combined with the daily traffic pattern of the link. The test of efficiency of the propsed model was performed by comparing the result of proposed model with traditional APID algorithm and fuzzy algorithm without the pattern data respectively. The result showed significant amount of improvement in reducing the false incident detection rate by 18%.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.4
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• pp.97-113
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• 2023

Swift and appropriate responses in emergency situations like objects falling on the road can bring convenience to road users and effectively reduces secondary traffic accidents. In Korea, current intelligent transportation system (ITS)-based detection systems for emergency road situations mainly rely on loop detectors and CCTV cameras, which only capture road data within detection range of the equipment. Therefore, a new detection method is needed to identify emergency situations in spatially shaded areas that existing ITS detection systems cannot reach. In this study, we propose a ResNet-based algorithm that detects and classifies emergency situations from vehicle camera footage. We collected front-view driving videos recorded on Korean highways, labeling each video by defining the type of emergency, and training the proposed algorithm with the data.

• Journal of Korean Society of Transportation
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• v.29 no.4
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• pp.103-111
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• 2011

The speed is one of the significant factors affecting accident occurrence. In particular, freeway accidents are highly associated with the speed because vehicles travel on the freeway at higher speed leading to greater potential of severer injury. Efforts attempting to relating speed with accident occurrence have not been significantly made in Korea. The objective of this study is to model the relationship between speed and accident rate on freeways. Loop detector data and accident data obtained from a stretch of Kyungboo freeway during the recent five years, 2005-2009, were used to establish the model. Multiple linear regression analyses showed that median, minimum and standard deviation of speed were contributing variables in the model. The statistical significance identified by the analyses supports the feasibility of the model in evaluating various transportation policies and operations strategies in terms of traffic safety.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.2
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• pp.36-54
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• 2017

The purpose of this paper is to develop a multi-sensor fusion-based traffic information acquisition system with robust to environmental changes. it combines the characteristics of each sensor and is more robust to the environmental changes than the video detector. Moreover, it is not affected by the time of day and night, and has less maintenance cost than the inductive-loop traffic detector. This is accomplished by synthesizing object tracking informations based on a radar, vehicle classification informations based on a video detector and reliable object detections of a infrared range finder. To prove the effectiveness of the proposed system, I conducted experiments for 6 hours over 5 days of the daytime and early evening on the pedestrian - accessible road. According to the experimental results, it has 88.7% classification accuracy and 95.5% vehicle detection rate. If the parameters of this system is optimized to adapt to the experimental environment changes, it is expected that it will contribute to the advancement of ITS.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.10 no.4
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• pp.564-581
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• 1999

This paper introduces a new, small, low cost, robust and quick replaceable pavement-based vehicle detector using CW radar, magnetometer, and UHF small antennal techniques. The detector has been developed for a replacement of loop detectors having wide surface areas, for a more accurate operation under all weather conditions, and for no algorithmic change of the existing traffic information system. The detected vehicle information is sent by a small helical antenna embedded in a plastic material and received by a 5/8 $\lambda$ long GP antenna for signal processing. In a relatively good weather condition, the detector operates at 24 GHz. But in a heavy rain condition, magnetometer is activated by automatic switching.

• Journal of Advanced Navigation Technology
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• v.7 no.2
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• pp.108-117
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• 2003

In this paper, two types of radar vehicle detectors compatible with currently being used ILD(Inductive Loop Detector) without any modification has been developed. With these vehicle detectors based on FMCW altimeter and Doppler speedometer techniques at 24 GHz, the length and speed of a vehicle can be detected. For signal processing part, we have used DAQ board and programmed with LabView. For compatibility with traffic information network connected with existing ILD's, traffic information has been sent to VDS by using RS-232C standard interface. This development has improved approximately 10% in accuracy in terms of the speed and length information compared with that of the installed ILD in the test field.

• Proceedings of the Korea Information Processing Society Conference
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• 2006.05a
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• pp.341-344
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• 2006

유고란 도로상에서 교통량의 주기적인 집중에 의한 혼잡과는 구별되는 개념으로 교통사고, 도로보수 그리고 자연재해와 같은 비 반복적인 정체의 상황을 일컫는다. 이러한 유고는 막대한 통행시간이 추가로 발생하고 연료소모, 환경피해 등의 문제가 발생하므로 이러한 교통손실을 최소화하기 위하여 자동유고감지 알고리즘의 개발이 필수적이다. 이를 위하여 현재 다양한 검지기에서 수집된 교통 데이터를 바탕으로 유고를 감지하는 연구가 많이 진행되고 있다. 본 논문에서는 각종 유고 상황을 인지하여 제2의 사고를 예방할 수 있는 효율적인 유고감지 알고리즘을 개발하기 위하여 퍼지논리와 패턴을 함께 사용하였다. 먼저 퍼지논리와 패턴에 사용되는 데이터는 루프 검지기에서 5분 마다 수집된 교통정보(교통량, 점유율, 속도)를 이용하였다. 교통정보를 이용하여 구축된 요일 및 시간대별 패턴과 함께 퍼지논리를 이용하여 도출된 유고 소속도를 가지고 유고를 감지하였다.