• Journal of Korean Society of Transportation
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• v.31 no.1
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• pp.37-46
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• 2013

Lane closure in freeway work zone due to maintenance and repair of freeway facilities results in abrupt change of traffic flow. Sudden change of traffic flow results strong interactions among vehicles, and reduces capacity compared to the ordinary traffic condition. Such capacity reduction is likely to cause congestion, traffic queues, and economic loss cost. This study aims to determine the base capacity for a short-term freeway work zone that can be used to establish a work zone schedule in advance without any traffic impact. First, the research collected detector data and schedule data of road works on all freeways in Korea. Second, the research determined 23 study sites finding the capacity values of work zone after matching two kinds of data. All study sites had varying characteristics regarding traffic flow being adjacent to work zone during road works. The capacity values were reviewed in terms of lane closure configuration, the types of work, and design speed. Finally, research proposed capacity values for a short-term freeway work zone with the design speeds of 100 kph, 120 kph and 1,700 pcphpl, 1,750 pcphpl, respectively.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.2 no.1 s.2
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• pp.25-40
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• 2003

The purpose of this thesis is development of detection algorithm for stop-line detector. Detail detection area is set in basing detection area($1.8{\times}4.0m$) and traffic information(volume, occupancy, nonoccupancy) is collected by passive infrared detector at designing detection area. The basis detection area($1.8{\times}4.0m$) is named existing PIR and detection area applied on development algorithm is named proposal PIR. The proposal PIR is collected data such volume, occupancy, nonoccupancy, speed and lane change, but this thesis is limited to evaluate for volume, occupancy and nonoccupancy The procedure and each step of being developed algorithm is described in the next (1) The detection area of proposal PIR is made up of 2 of $1.8{\times}0.6m$ size(the detection area is named 1 and 3) and 1 of $1.8{\times}1.78m$ size(the detection area is named 2) (2) The image detection area is set on monitor to analyze outdoor photographing data then video frame analysis has been done by analyzer. (3) The occupancy, nonoccupancy and speed data of vehicle have been collected with the detection area 1 and 3 and lane change has been collected with combination of detection area 1, 2 and 3 The MAD and MAPE have been utilized to being compared with volume, occupancy and nonoccupancy for the field application and evaluation of a algorithm As the result, the proposal PIR data have been identified superior to the existing PIR data and the effect has been improved its information(volume, occupancy and nonoccupancy)

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2010.07a
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• pp.70-73
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• 2010

최근 IT 기술이 융합된 지능형 자동차 기술에 대한 관심이 높아짐에 따라 이에 대한 연구가 활발히 진행되고 있다. 차선 검출은 지능형 자동차의 주요 과제인 첨단 안전자동차 기술의 핵심적인 부분으로 국내외에서 다양한 방법들에 대한 연구가 진행되었다. 차량의 안전을 향상시키기 위해서는 충분한 제동거리 확보가 가능한 거리까지 정확하고 빠른 차선 검출이 이루어져야 한다. 기존의 경계선 검출기반 차선 검출은 소실점 근처에서 경계선 검출이 이루어지지 않았다. 이는 차선과 도로의 색이 잘 구분되지 않는 채널을 사용하는 문제에서 기인한다. 따라서 본 논문에서는 선형 판별 분석 기법을 이용하여 차선과 도로 색을 가장 잘 구분할 수 있는 RGB 가중치를 계산하여 이로부터 projection 영상을 만들고, 변환한 영상에서 경계선 검출을 수행함으로써 보다 정확한 경계선 검출 결과를 얻는 방법을 제안한다. 제안한 방법으로 얻은 영상과 기존의 흑백 영상에 동일한 경계선 검출기를 적용하여 성능을 비교하고, 이를 적용한 차선검출 실험결과를 제시한다.

• Journal of Korea Multimedia Society
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• v.13 no.7
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• pp.983-990
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• 2010

The image processing technique is very sensitive to the variation of external environment, so it tends to lose a lot of accuracy when the external environment changes rapidly. In this paper, we propose a vehicle detecting and tracking system for crime prevention suitable for an external environments with various changes using the image processing technique. Because the vehicle camera detector for crime prevention extracts and tracks the vehicle within one lane, it is important to classify a characteristic region rather than the contour of a vehicle. The proposed system detects the entrance of the vehicle using optical flow and tracks the vehicle by classifying the headlights, the bonnet, the front-window and the roof area of the vehicle. Experimental results show that the proposed method is robust to the environmental changes such as type, speed and time of a vehicle.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.5A
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• pp.673-683
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• 2008

This study improved the existing method of using the longitudinal strain and concept of influence line to develop Bridge Weigh-in-Motion system without axle detector using the dynamic strain of the bridge girders and concrete slab. This paper first describes the considered algorithms of extracting passing vehicle information from the dynamic strain signal measured at the bridge slab, girders, and cross beams. Two different analysis methods of 1) influence line method, and 2) neural network method are considered, and parameter study of measurement locations is also performed. Then the procedures and the results of field tests are described. The field tests are performed to acquire training sets and test sets for neural networks, and also to verify and compare performances of the considered algorithms. Finally, comparison between the results of different algorithms and discussions are followed. For a PSC I-girder bridge, vehicle weight can be calculated within a reasonable error range using the dynamic strain gauge installed on the girders. The passing lane and passing speed of the vehicle can be accurately estimated using the strain signal from the concrete slab. The passing speed and peak duration were added to the input variables to reflect the influence of the dynamic interaction between the bridge and vehicles, and impact of the distance between axles, respectively; thus improving the accuracy of the weight calculation.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.6
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• pp.108-117
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• 2011

Seoul metropolitan government has been operating traffic signal control system with the name of COSMOS since 2001. COSMOS uses the degrees of saturation and congestion which are calculated by installing loop detectors. At present, inductive loop detector is generally used for detecting vehicles but it is inconvenient and costly for maintenance since it is buried on the road. In addition, the estimated queue length might be influenced in case of error occurred in measuring speed, because it only uses the speed of vehicles passing by the detector. A traffic signal control algorithm which enables smooth traffic flow at intersection is proposed. The proposed algorithm assigns vehicles to the group of each lane and calculates traffic volume and congestion degree using traffic information of each group using VANETs(Vehicular Ad-hoc Networks) inter-vehicle communication. It does not demand additional devices installation such as cameras, sensors or image processing units. In this paper, the algorithm we suggest is verified for AJWT(Average Junction Waiting Time) and TQL(Total Queue Length) under single intersection model based on GLD(Green Light District) Simulator. And the result is better than Random control method and Best first control method. In case real-time control method with VANETs is generalized, this research that suggests the technology of traffic control in signalized intersections using wireless communication will be highly useful.

• Journal of Korean Society of Transportation
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• v.28 no.3
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• pp.157-167
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• 2010

Density is the most important congestion indicator among the three fundamental flow variables, flow, speed and density. Measuring density in the field has two different ways, direct and indirect. Taking photos with wide views is one of direct ways, which is not widely used because of its cost and lacking of proper positions. Another direct density measuring method using two point detectors has been introduced with the concept of instantaneous density, average density and measurement interval. The relationship between accuracy and measurement interval has been investigated using the SIMULATION data produced by Paramics Application Programming Interface function. We analyze the affect of segment density accuracy by sensing gap each road condition such as sensing segment length, lane and LOS after gathering data by Paramics Application Programming Interface.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.3
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• pp.9-15
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• 2011

The left-turn actuated signal control method has been occurred various problems under the COSMOS. one of problems is a early termination for left-turn phase by u-turn vehicles at left-turn lane. Therefore, the purpose of this study is a development of the efficient left-turn actuated signal control method to improve the problem. This study was considered that setback the left-turn vehicle detector to the start point of u-turn line and adjustment of the passage time. For effective analysis of developed method, Traffic simulation was simulated by T-7F and VISSIM under various traffic conditions. The result was proved that the developed Method improved the effectiveness.

• Journal of Korean Society of Transportation
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• v.19 no.6
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• pp.143-160
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• 2001

Micro-simulation models have been recognized as an efficient assessment tool in developing traffic signal control technologies. In this paper a prototype of a microscopic simulation model which can be applied to evaluate the performance of traffic-adaptive signal control strategies was developed. In the simulation process, space-based arrays were appled to estimate parameters of car following and lane changing models. Two levels of link types, a micro-type and macro-type links, were also embodied in the simulation process. The proposed model was tested on a test network consists of 9 intersections. The performance of the proposed model was evaluated in link by link comparisons with the results of NETSIM. The results show that the proposed model could appropriately simulate traffic flows of the test network. The model also produces traffic adaptive signal timings, cycle lengths and green times for turning movements, based on the detector data. It implies that the optimization process of the model produces reasonable signal timings for the test network on the cycle basis.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.1 no.1
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• pp.22-32
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• 2002

This paper describes about non-burial AVI (Automatic Vehicle Identification) system using general vehicle as probe car for obtaining more accurate traffic information while conserving road pavement surface. Existing spot traffic detectors have their own limits of not obtaining right information owing to its mathematical method. Burial AVI systems have some defects, causing traffic jam, needing much maintenance cost because of frequent cutting of loop and piezo-electric sensors. Especially, they have hard time to make right detection, when it comes to jamming time. Therefore, in this paper, we propose non-burial AVI system with laser trigger unit. Proposed non-burial AVI system is developed to obtain regional traffic information from normal Passing vehicle by automatic license number recognition technology. We have adapted it to national highway section between Suwon city and Pyong$\~$Taek city(9.5km) and get affirmative results. Vehicle detection rate of laser trigger unit is more than 95$\%$, vehicle recognition rate is 87.8$\%$ and vehicle matching rate is about 14.3$\%$. So we regard these as satisfying results to use the system for traffic information service. We evaluate proposed AVI system by regulation of some institutions which are using similar AVI system and the proposed system satisfies all conditions. For future study, we have plan of detailed research about proper lane number from all of the target lanes, optimal section length, information service period, and data fusion method for existing spot detector.