• Korean Journal of Remote Sensing
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• v.38 no.1
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• pp.1-20
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• 2022

As unmanned aerial vehicle (UAV) technology grew in popularity over the years, it was introduced for air quality monitoring. This can easily be used to estimate the sidewalk emission concentration by calculating road traffic emission factors of different vehicle types. These calculations require a simulation of the spread of pollutants from one or more sources given for estimation. For this purpose, a Gaussian plume dispersion model was developed based on the US EPA Motor Vehicle Emissions Simulator (MOVES), which provides an accurate estimate of fuel consumption and pollutant emissions from vehicles under a wide range of user-defined conditions. This paper describes a methodology for estimating emission concentration on the sidewalk emitted by different types of vehicles. This line source considers vehicle parameters, wind speed and direction, and pollutant concentration using a UAV equipped with a monocular camera. All were sampled over an hourly interval. In this article, the YOLOv5 deep learning model is developed, vehicle tracking is used through Deep SORT (Simple Online and Realtime Tracking), vehicle localization using a homography transformation matrix to locate each vehicle and calculate the parameters of speed and acceleration, and ultimately a Gaussian plume dispersion model was developed to estimate the CO, NOx concentrations at a sidewalk point. The results demonstrate that these estimated pollutants values are good to give a fast and reasonable indication for any near road receptor point using a cheap UAV without installing air monitoring stations along the road.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.10a
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• pp.265-268
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• 1997

In the recent day, fatigue life prediction techniques play a major role in the design of components in the ground vehicle industry. Full scale durability testing in the laboratory is an essential of any fatigue life evaluation of components or structures of the automotwe vehicle. Component testing is part~cularly important in today's highly competitive industries where the design to reduce weight and production costs must be balanced with the necessity to avoid expensive service failure. Generally, multi-axial road simulator is used to carry out the fatigue test and the vibration test. In this paper, the algorithm and software to realize the real road profile are developed. The validity of the software are verified by applying the belgian road, the city road, the highway, and the gravel road. The results of the above experiment show that the real road profiles are realized well after loth iteration.

• Journal of the Semiconductor & Display Technology
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• v.21 no.1
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• pp.22-26
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• 2022

This paper proposes a new method for the recognition of road surface marks and numbers. The proposed method designates a region of interest on the road surface without first detecting a lane. The road surface markings are extracted by location and size using a connection component analysis. Distortion due to the perspective effect is minimized by normalizing the size of the road markings. The road surface marking of the connected component is recognized by matching it with the stored road marking templates. The proposed method is implemented using C language in Raspberry Pi 4 system with a camera module for a real-time image processing. The system was fixedly installed in a moving vehicle, and it recorded a video like a vehicle black box. Each frame of the recorded video was extracted, and then the proposed method was tested. The results show that the proposed method is successful for the recognition of road surface marks and numbers.

• International Journal of Automotive Technology
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• v.7 no.4
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• pp.469-475
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• 2006

In this paper, an optimal suspension system with preview of the road input is synthesized for a half tracked vehicle. The main goal of this research is to improve the ride comfort characteristics of a fast moving tracked vehicle in order to maintain the driver's driving capability. Several different kinds of preview control algorithms are evaluated with active or semi-active suspension systems. The road information estimated from the motion of the 1st road-wheel is adequate to make the best use of the preview control algorithm for tracked vehicles. The ride-comfort characteristics of the tracked vehicle are more dependent on pitching angular acceleration than heaving acceleration. The pitching motion is reduced by the suspension system with hard outer suspensions and soft inner suspensions. Simulation results show that the performance of sky-hook algorithms for ride comfort nearly follow that of full state feedback algorithms.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.05a
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• pp.872-876
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• 2007

Road traffic noise map is effective method to save cost and time for environmental noise assessment. Generally, noise is calculated by using theoretical equation of noise prediction, and the calculated result can be influenced by various input factors. Especially, domestic vehicle classification method for traffic flow and heavy vehicle percentage is different from that of foreign countries. Thus, this can cause effect on the noise prediction results. In this study, noise prediction results by using domestic vehicle classification method are compared with those by foreign methods.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.4
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• pp.390-395
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• 2009

In this paper, we design an on-road vehicle detection system based on the combination of a camera and a LIDAR system. In the proposed system, the candidate area is selected from the LIDAR data using a grouping algorithm. Then, the selected candidate area is scanned by an SVM to find an actual vehicle. The morphological edged images are used as features in a camera. The principal components of the edged images called eigencar are employed to train the SVM. We conducted experiments to show that the on-road vehicle detection system developed in this paper demonstrates about 80% accuracy and runs with 20 scans per second on LIDAR and 10 frames per second on camera.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2012.04a
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• pp.298-304
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• 2012

The development of low rolling resistance tire with weight reduction in tire and vehicle may induce high level of tire/road noise, especially the rumble road noise on rough road. In this paper, the design factor for good rumble noise is considered in view of tire and vehicle. For the 3 mid-sized sedans, the rumble noise is very sensitive to the test vehicle. And it is concluded that the tire with high tread part stiffness and low sidewall part stiffness shows best rumble noise performance, and the rumble noise is in trade-off relation with cavity resonance noise. So, it is desirable to select and change proper construction design factors to have good tire/vehicle rumble noise.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.303-303
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• 2000

It is difficult to determine the static axle weight of a vehicle with weigh-in-motion systems which in absence measure instantaneous axle impact forces. The difficulty in determining a static axle weight results from dynamic effects induced by vehicle/road interactions. One method to improve the problem is to quantify a statistical confidence level for measured axle weight. The quarter-car model is used to simulate vehicle motion, Also, the road input to vehicle model can be characterized in statistical terms by PSD (power spectral density) of appropriate amplitude and frequency contents other than an exact spatial distribution. The confidence levels for the measured axle weight can be obtained by the random process analysis using both vehicle model and road input.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2011.04a
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• pp.361-364
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• 2011

In this paper, This work demonstrates a experimental evaluation for vehicle road noise NVH performance from the component-level NVH measurements of Tire. The power unit noise from tire emitted by cars has been reduced. It has been found that tire noise dominates noise produced by the power train when vehicles are driven at high constant speed. Therefore tire pattern noise is affected by pattern and vehicle and transmission loss. Tire noise mechanism is generated by several mechanisms. The sound of tire can propagate either through the air or through the structure of vehicle. Pattern noise is the result of pressure variations through the air to the interior side of vehicle. Especially, smooth asphalt, the periodicity of tread design, groove depth is important factor, which have an influence on the reduction of tire pattern noise.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.22 no.2
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• pp.193-197
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• 2012

Road traffic noise map is effective method to save cost and time for environmental noise assessment. Generally, noise is calculated by using theoretical equation of noise prediction, and the calculated result can be influenced by various input factors. Especially, domestic vehicle classification method for traffic flow and heavy vehicle percentage is different from that of foreign countries. Thus, this can cause effect on the noise prediction results. In this study, noise prediction results by using domestic vehicle classification method are compared with those by foreign methods.