• Proceedings of the KOR-KST Conference
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• 1998.10b
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• pp.295-295
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• 1998

고속도로에서 교통류의 특성에 파악하여 교통류의 특성을 파악하여 동적행태로 교통상황을 분석하고 효과적인 제어전략, 시뮬레이션, 그리고 기하구조 개선등의 효율적이고 실용적인 적용을 위해서는 교통류의 정확한 모사가 필요하다. 시공간으로 표현되는 상태방정식을 포함하는 거시적 시뮬레이션 모델에 사용되는 연속류 모델은 이러한 교통류 특성을 모사하는데 적절하다. Lighthill과 Whitham(1955), Richard(1956)에 의해 일계도함수의 형태를 가지는 단순모델이 제시된 이후 모델의 결점을 보완하기 위해 많은 고계도 모델이 제시되었지만 고계도 모델이 가진 이론적인 결점에 대해서는 여러 연구들이 제시되어 있다. 또한 고계도 모델은 운동량 방정식의 유도, 정산, 구현의 어려움으로 널리 사용되기 힘들다는 단점을 가지고 있다. 만일 적절히 구현할 수 있다면 적용이 간단한 단순모델로도 보다 정확한 교통류 상황 모사가 가능하다. Ansorge는 혼잡교통류상황을 보다 정확하게 모사하기 위해 단순모델에 엔트로피 조건을 결합시킨 모델을 제시했다. Bui는 이 제안된 모델이 적절한 시뮬레이션 결과를 나타낸다는 것을 밝혔다. 그러나 이 모델은 차량의 재가속이 이루어지는 교통상황-stop-start wave의 경우 비현실적인 값을 가진다. 엔트로피조건에 의해 구해진 해는 실제보다 과다한 교통량을 추정하게 되는데 이런 결과는 위와 같은 교통상황에서 중요한 요소로 작용하는 가속효과가 무시되고 있기 때문이다. 따라서 본 연구에서는 stop-start wave 조건에서 가속도에 경계치를 부여하여 교통류율을 상한경계조건을 제시함으로써 교통상황에 맞는 교통류율을 산정하는 방법에 대해 제안하고자 한다.환승이라는 특정대안변수(Specific alternative variable)를 첨가하여 그것이 수단선택에 미치는 영향을 분석한다. 또한, 대중교통의 속성을 가지고 있는 지하철과 버스를 하나의 대안으로 묶어서 효용함수를 구한 다음 다시 승용차, 택시, 대중교통을 독립된 대안으로 두고 모형을 정립하는 NESTED LOGIT모형으로 파라메타를 추정하여 대중교통의 효용에 관해 분석·비교하였다. 본 논문에 이용된 자료는 공항을 이용하는 이용객들을 대상으로 직접 설문·면접조사한 자료이며 대상 교통수단은 승용차, 택시, 지하철, 버스로 설정하였다. 결과 적응형 알고리즘이 개개인의 최단시간 경로를 제공하는 사용자 평형 경로안내전략에 비해 교통혼잡도와 정체시간의 체류정도에 따라 3%에서 10%까지 전체통행시간을 절약할 수 있다는 결론을 얻었다.출발참, 구성대외개방선면축심, 실현국제항선적함접화국내항반적전항, 형성다축심복사식항선망; 가강기장건설, 개피포동제이국제기장건설, 괄응포동개발경제발전적수요. 부화개시일은 각 5월 26일과 5월 22일이었다. 11. 6월 중순에 애벌레를 대상으로 처리한 Phenthoate EC가 96.38%의 방제가로 약효가 가장 우수하였고 3월중순 및 4월중순 월동후 암컷을 대상으로 처리한 Machine oil, Phenthoate EC 및 Trichlorfon WP는 비교적 약효가 낮았다.>$^{\circ}$E/$\leq$30$^{\circ}$NW 단열군이 연구지역 내에서 지하수 유동성이 가장 높은 단열군으로 추정된다. 이러한 사실은 3개 시추공을 대상으로 실시한 시추공 내 물리검층과 정압주입시험에서도 확인된다.. It was result

• Transactions of the Korean Society of Automotive Engineers
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• v.20 no.3
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• pp.67-76
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• 2012

In this paper, collision analysis of the full rake for the Next Generation High-speed EMU is conducted using a 3D/1D hybrid model, which combines 3-dimensional (3D) front-end structure of finite element model and 1-dimensional (1D) multi-body dynamics model in order to analyze train collision with a standard 3D deformable obstacle. The crush forces, passengers' accelerations and energy absorptions of a full rake train can be easily obtained through a simulation of a 1D dynamics model composed of nonlinear springs, dampers and masses. Also the obtained simulation results are very similar to those of a 3D model if an overriding behavior does not occur during collision. The standard obstacle in TSI regulation has been changed from a rigid body to a deformable body, and therefore 3D collision simulations should be conducted because their simulation results depends on the front-end structure of a train. According to the obstacle collision analysis of this study, the obstacle collides with the driver's upper structure after overriding over the front-end module. The 3D/1D hybrid model is effective to evaluate a main energy-absorbing module that is frequently changed during design process and reduce the need time of the modeling and analysis when compared to a 3D full car body.

• International Journal of Highway Engineering
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• v.14 no.3
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• pp.77-85
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• 2012

Most of Automatic Accident Detection Algorithm has a problem of detecting an accident as traffic congestion. Actually, center's managers deal with accidents depend on watching CCTV or accident report by drivers even though they run the Automatic Accident Detection system. It is because of the system's detecting errors such as detecting non-accidents as accidents, and it makes decreasing in the system's overall reliability. It means that Automatic Accident Detection Algorithm should not only have high detection probability but also have low false alarm probability, and it has to detect accurate accident spot. The study tries to verify and evaluate the effectiveness of using Gaussian Mixture Model and individual vehicle tracking to adapt Accident Detection Algorithm to Center Management System by measuring accident detection probability and false alarm probability's frequency in the real accident.

• Journal of Korean Society of Transportation
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• v.28 no.6
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• pp.75-84
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• 2010

Controlled traffic intersection is critical point in terms of transportation network performance, where the most of traffic congestion arises. One of the most important and favorable measure of effectiveness in the signal controlled intersection is approach delay. Although lots of efforts to develop traffic delay estimation models have been made throughout the years, most of them were focusing on homogeneous traffic flow. The purpose of this research is to develop a traffic delay estimation model for traffic flow mixed with bus based on the horizontal shockwave theory. Traffic simulation is performed to test the adaptation level of the model in generic environment. The result shows that the delay increases with increasing bus traffic. Overall model accuracy comparing simulation result is acceptable, that shows the error range around 10 percent.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.10
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• pp.81-87
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• 2017

This paper describes the dynamic behavior and enhancement of Korean high-speed trains. The tail vibration reduction method of the yaw damper installation method change, which was derived from previous research, was applied to the running test of high-speed train. In addition, the vibration reduction method for the entire vehicle was derived by a numerical method and its effect was confirmed by a running test. The improved design was applied to the double-deck high-speed train coaches and the commissioning proceeded without problems in dynamic behavior. Sensitivity analysis of the suspension parameters affecting the critical speed of Korean next-generation high-speed trains was performed and four design variables that greatly affected the critical speed were derived. These were in the order of the primary elastic joint x-directional stiffness, the secondary yaw damper series stiffness, the secondary lateral damper damping coefficient, and the carbody damper damping coefficient. By optimizing the design variables, the suspension parameter that improves the critical speed by 23.3% can be used in the commercial designs of Korean next-generation high-speed trains.

• Journal of Korean Society of Transportation
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• v.21 no.4
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• pp.29-44
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• 2003

A balanced evaluation system for a bus route network was proposed for a mid-sized suburban city. The evaluation system consists of 7 criteria-accessibility, riding comfort. transfer rate, directness of route, productivity of operation, regional equity, and minimum requirement of bus fleet - and quantitative indicators representing each of the criteria. The proposed system was applied in Siheung, a suburban city in Seoul Metropolitan Area. Four alternative scenarios of bus route network including the existing one were evaluated. The results showed that the suggested criteria and indicators are acceptable for the evaluation of a bus route network. In order to enhance the proposed evaluation procedure, further studies on the normalization of produced values and weights for each of the indicators are needed.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.20-29
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• 2021

In the Industry 4.0 era, artificial intelligence has attracted considerable interest for learning mass data to improve the accuracy of forecasting and classification. On the other hand, the current method of detecting anomalies relies on traditional statistical methods for a limited amount of data, making it difficult to detect accurate anomalies. Therefore, this paper proposes an artificial intelligence-based anomaly detection methodology to improve the prediction accuracy and identify new data patterns. In particular, data were collected and analyzed from the point of view that sensor data collected at vehicle idle could be used to detect abnormalities. To this end, a sensor was designed to determine the appropriate time length of the data entered into the forecast model, compare the results of idling data with the overall driving data utilization, and make optimal predictions through a combination of various sensor data. In addition, the predictive accuracy of artificial intelligence techniques was presented by comparing Convolutional Neural Networks (CNN) and Long Short Term Memory (LSTM) as the predictive methodologies. According to the analysis, using idle data, using 1.5 times of the data for the idling periods, and using CNN over LSTM showed better prediction results.

• Journal of the Korea Society of Computer and Information
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• v.27 no.8
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• pp.69-75
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• 2022

In this paper, a method for predicting the speed for each lane from the link speed using an artificial neural network is presented to increase the accuracy of predicting the required time of a driving route. The time required for passing through a link is observed differently depending on the direction of going straight, turning right, or turning left at the intersection of the end of the link. Therefore, it is necessary to predict the speed according to the vehicle's traveling direction. Data required for learning and verification were constructed by refining the data measured at the Gongpyeong intersection of Gukchaebosang-ro in Daegu Metropolitan City and four adjacent intersections around it. Five neural network models were used. In addition, error analysis of the prediction was performed to select a neural network experimentally suitable for the research purpose. Experimental results showed that the error in the estimation of the time required for each lane decreased by 17.4% for the straight lane, 4.4% for the right-turn lane, and 3.9% for the left-turn lane. This experiment is the result of analyzing only one link. If the entire pathway is tested, the effect is expected to be greater.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.3
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• pp.83-95
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• 2022

This paper proposes a system that performs object detection and distance estimation for application to autonomous vehicles. Object detection is performed by a network that adjusts the split grid to the input image ratio using the characteristics of the recently actively used deep learning model YOLOv4, and is trained to a custom dataset. The distance to the detected object is estimated using a bounding box and homography. As a result of the experiment, the proposed method improved in overall detection performance and processing speed close to real-time. Compared to the existing YOLOv4, the total mAP of the proposed method increased by 4.03%. The accuracy of object recognition such as pedestrians, vehicles, construction sites, and PE drums, which frequently occur when driving to the city center, has been improved. The processing speed is approximately 55 FPS. The average of the distance estimation error was 5.25m in the X coordinate and 0.97m in the Y coordinate.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.4D
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• pp.491-497
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• 2009

This paper presents the results of accelerated pavement tests (APT) that simulate permanent deformation (rutting) of asphalt concrete pavements under different temperatures and loading courses. Also, finite element (FE) analysis has been conducted to predict the test results. Test section for APT is the same as one of test sections at Korea Expressway Corporation test road and is subjected to a constant moving dual tire wheel load of APT at three different temperatures: 30, 40, $50^{\circ}C$. The moving wheel is applied at different loading courses within a 75cm wide wheel path to account for traffic wandering. Also, the effect of wandering on permanent deformation development is investigated numerically with three wandering schemes. In this study, ABAQUS is adopted to model APT pavement section with plain stain elements and creep strain rate model is used to take into account viscoplastic stain of asphalt concrete mixtures, and elastic layer properties are back-calculated from FWD measurements. Plus, the effect of boundary condition and subgrade on FE permanent deformation predictions is investigated. A full FE model that accounted for subgrade provided more realistic rut depth predictions, indicating subgrade has contributed to surface rutting.