• Wind and Structures
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• v.20 no.2
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• pp.249-274
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• 2015

Long-span cable-stayed bridges exhibit some features which are more critical than typical long span bridges such as geometric and aerodynamic nonlinearities, higher probability of the presence of multiple vehicles on the bridge, and more significant influence of wind loads acting on the ultra high pylon and super long cables. A three-dimensional nonlinear fully-coupled analytical model is developed in this study to improve the dynamic performance prediction of long cable-stayed bridges under combined traffic and wind loads. The modified spectral representation method is introduced to simulate the fluctuating wind field of all the components of the whole bridge simultaneously with high accuracy and efficiency. Then, the aerostatic and aerodynamic wind forces acting on the whole bridge including the bridge deck, pylon, cables and even piers are all derived. The cellular automation method is applied to simulate the stochastic traffic flow which can reflect the real traffic properties on the long span bridge such as lane changing, acceleration, or deceleration. The dynamic interaction between vehicles and the bridge depends on both the geometrical and mechanical relationships between the wheels of vehicles and the contact points on the bridge deck. Nonlinear properties such as geometric nonlinearity and aerodynamic nonlinearity are fully considered. The equations of motion of the coupled wind-traffic-bridge system are derived and solved with a nonlinear separate iteration method which can considerably improve the calculation efficiency. A long cable-stayed bridge, Sutong Bridge across the Yangze River in China, is selected as a numerical example to demonstrate the dynamic interaction of the coupled system. The influences of the whole bridge wind field as well as the geometric and aerodynamic nonlinearities on the responses of the wind-traffic-bridge system are discussed.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.5
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• pp.83-99
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• 2021

With the advent of the fourth industrial revolution, studies on driving management and driving strategies of autonomous vehicles are emerging. While obtaining microscopic traffic data on vehicles is essential for such research, we also see that conventional traffic data collection methods cannot collect the driving behavior of individual vehicles. In this study, UAV videos were used to collect traffic data from the viewpoint of the aerial base that is microscopic. To overcome the limitations of the related research in the literature, the micro-traffic data were estimated using the multiple object tracking of deep learning and an image registration technique. As a result, the speed obtained error rates of MAE 3.49 km/h, RMSE 4.43 km/h, and MAPE 5.18 km/h, and the traffic obtained a precision of 98.07% and a recall of 97.86%.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.4
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• pp.1-12
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• 2021

Emergence of the COVID 19 pandemic has resulted in a sharp increase in the number of two-wheeler vehicular traffic accidents, prompting the introduction of numerous efforts for their prevention. This study applied XGBoost to determine the factors that affect severity of two-wheeled vehicular traffic accidents, by examining data collected over the past 10 years and analyzing the influence of each factor. Among the total factors assessed, variables affecting the severity of traffic accidents were overwhelmingly high in cases of signal violations, followed by the age group of drivers (60s or older), factors pertaining only to the car, and cases of centerline infringement. Based on the research results, a reasonable legal reform plan was proposed to prevent serious traffic accidents and strengthen safety management of two-wheeled vehicles. Based on the research results, we propose a reasonable legal reform plan to prevent serious traffic accidents and strengthen safety management of two-wheeled vehicles.

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.1
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• pp.1-15
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• 2022

In order to trust and use autonomous vehicles, safe driving on the road must be guaranteed. For this, the first infrastructure to be equipped with autonomous driving is traffic safety facility. On the other hand, autonomous vehicles(Level 3) and general vehicles are driving on the road, it is necessary to additionally manage existing general traffic safety facilities. In this study, a field management system for traffic safety facilities based on autonomous driving infrastructure was studied, and a pilot field management system was implemented in the demonstration area(Pangyo). The pilot system consists of a GNSS(Global Navigation Satellite System) receiver, a field management equipment, and a field management app. As a result of field demonstration,, it was confirmed that traffic safety facility information was easily transmitted and received even in downtown areas and that could be efficiently operated and managed. It is expected that the results of this study will be used as reference materials for the spread of autonomous driving infrastructure to local governments and infrastructure construction in the future.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.6
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• pp.250-265
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• 2022

Positive effects such as significantly reducing traffic accidents caused by human error can be expected by the introduction of Automated vehicles (AV). However, as new traffic safety issues are expected to occur in the future due to errors in H/W or S/W of autonomous vehicles and lack of its function, it is necessary to establish a scenario to evaluate the driving safety of AV. Therefore, in this study, functional scenario was developed to evaluate the driving safety of AV based on traffic accident data of the National Police Agency. Using the GIS program, QGIS, traffic accident data that occurred in the toll gate and ramp sections of expressway were extracted and accident summary items were checked to classify the types of accident. In addition, based on the results of accident type classification, functional scenario were developed that contains various dangerous situations in the tollgate and ramp sections.

• Wind and Structures
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• v.20 no.2
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• pp.275-292
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• 2015

The presence of traffic on a slender long-span bridge deck will modify the cross-section profile of the bridge, which may influence the flutter derivatives and in turn, the critical flutter wind velocity of the bridge. Studies on the influence of vehicles on the flutter derivatives and the critical flutter wind velocity of bridges are rather rare as compared to the investigations on the coupled buffeting vibration of the wind-vehicle-bridge system. A typical streamlined cross-section for long-span bridges is adopted for both experimental and analytical studies. The scaled bridge section model with vehicle models distributed on the bridge deck considering different traffic flow scenarios has been tested in the wind tunnel. The flutter derivatives of the modified bridge cross section have been identified using forced vibration method and the results suggest that the influence of vehicles on the flutter derivatives of the typical streamlined cross-section cannot be ignored. Based on the identified flutter derivatives, the influence of vehicles on the flutter stability of the bridge is investigated. The results show that the effect of vehicles on the flutter wind velocity is obvious.

• Proceedings of the Korea Contents Association Conference
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• 2006.05a
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• pp.332-336
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• 2006

According to the recent statistics of Korean National Police which analyze the present status on the rate of the traffic accidents and their effects in Korea, the number of casualties by traffic accidents of 2004 amounted to 6,563, which means that the average number of casualties per 10,000 vehicles is 3.99. The figure of 3.99 is much larger than 1.85 of U.S.A, 1.10 of Japan, 1.14 of U.K., and 1.23 of Germany. The number of registered vehicles of Korea is steeply increasing since 1997 when it reached 10,000,000. Since then, the number of annual increase is estimated at 860,000 except for the year 1998 when the Korean economy was under the control of IMF, and over 14 million vehicles are registered as of the end of the year 2004. With the increase of vehicles, the violations of traffic rules, crimes using vehicles, car thefts, etc have been imposing a lot of serious problems on our society. On this thesis, we are aiming at analyzing some characteristics of traffic accidents reported to the police and suggesting some kinds of the police activities for securing the safety of the transportation. On this thesis, we are aiming at analyzing some characteristics of traffic accidents reported to the police and suggesting some kinds of the police activities for securing the safety of the transportation.

• Journal of Industrial Convergence
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• v.18 no.3
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• pp.53-61
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• 2020

Travel speed is an important parameter for measuring road traffic and incident detection system. In this paper I suggests a model developed for estimating reliable and accurate average roadway link travel speeds using image processing sensor. This method extracts the vehicles from the video image from CCTV, tracks the moving vehicles using deep neural network, and extracts traffic information such as link travel speeds and volume. The algorithm estimates link travel speeds using a robust data-fusion procedure to provide accurate link travel speeds and traffic information to the public. In the field tests, the new model performed better than existing methods.

• Journal of the Semiconductor & Display Technology
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• v.14 no.2
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• pp.29-34
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• 2015

Traffic lights are common in cities and are important cues for the path planning of intelligent vehicles. In this paper, we propose a robust and efficient algorithm for recognizing traffic lights from video sequences captured by a low cost off-the-shelf camera. Instead of using color information for recognizing traffic lights, a shape based approach is adopted. In learning and detection phase, Histogram of Oriented Gradients (HOG) feature is used and a cascade classifier based on Adaboost algorithm is adopted as the main classifier for locating traffic lights. To decide the color of the traffic light, a technique based on histogram analysis in HSV color space is utilized. Experimental results on several video sequences from typical urban environment prove the effectiveness of the proposed algorithm.

• Wind and Structures
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• v.23 no.1
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• pp.19-43
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• 2016

In the present study, a new methodology is presented to study the ride comfort and bridge responses of a long-span bridge-traffic-wind coupled vibration system considering stochastic characteristics of traffic flow and bridge surface progressive deterioration. A three-dimensional vehicle model with 24 degrees-of-freedoms (DOFs) including a three-dimensional non-linear suspension seat model and the longitudinal vibration of the vehicle is firstly presented to study the ride comfort. An improved cellular automaton (CA) model considering the influence of the next-nearest neighbor vehicles and a progressive deterioration model for bridge surface roughness are firstly introduced. Based on the equivalent dynamic vehicle model approach, the bridge-traffic-wind coupled equations are established by combining the equations of motion of both the bridge and vehicles in traffic using the displacement relationship and interaction force relationship at the patch contact. The numerical simulations show that the proposed method can simulate rationally the ride comfort and bridge responses of the bridge-traffic-wind coupled system; and the vertical, lateral, and longitudinal vibrations of the driver seat model can affect significantly the driver's comfort, as expected.