• The Transactions of the Korean Institute of Electrical Engineers P
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• v.62 no.3
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• pp.111-116
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• 2013

Noise problem that occurs on the road is raising a lot of problems in the economic, social and environmental aspects. The objective of this paper is to propose ANC(active noise cancellation)-based road traffic noise reduction algorithm-model which can reduce noise by generating frequency opposed to noise sources to improve and complement the problem that existing physical form of a noise barrier. In this paper, we measured the noise characteristic from collection of two difference car noise also ANC simulation has been performed by using road traffic noises input. In order to compare the control performance, we performed noise reduction simulation of ANC by filtered-X LMS algorithm and delayed control signal injection. As a result of this simulation, we confirmed that convergence performance and noise decrease effect to the filtered-X LMS algorithm by inputting the road traffic noise.

• Korean Journal of Geomatics
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• v.3 no.1
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• pp.67-72
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• 2003

We have seen rapid changes in road systems and networks in urban areas due to fast urbanization and increased traffic demands. As a result, many researchers have put greater importance on extraction, correction and updating of information about road systems. Also, by using the various data on road systems and its condition, we can manage our road more efficiently and economically. Furthermore, such information can be used as input for digital map and GIS analysis. In this research, we used a high resolution aerial photo of the roads in Seongnam area. First, we applied the top-hat filter to the area of interest so that the road markings could be extracted in an efficient manner. The lane separation lines were selected, considering the shape similarity between the selected lane separation line and reference data. Next, we extracted the roads in the urban area using the aforementioned road marking. Using this technique, we could easily extract roads in urban area in semi-automatic way.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.1
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• pp.85-96
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• 2023

The number of traffic accidents caused by wet or icy road surface conditions is on the rise every year. Car crashes in such bad road conditions can increase fatalities and serious injuries. Historical data (from the year 2016 to the year 2020) on weather-related traffic accidents show that the fatality rates are fairly high in Korea. This requires accurate prediction and identification of hazardous road conditions. In this study, a forecasting model is developed to predict the chances of traffic accidents that can occur on roads affected by weather and road surface conditions. Multiple deep learning algorithms taking into account AlexNet and 2D-CNN are employed. Data on orthophoto images, automatic weather systems, automated synoptic observing systems, and road surfaces are used for training and testing purposes. The orthophotos images are pre-processed before using them as input data for the modeling process. The procedure involves image segmentation techniques as well as the Z-Curve index. Results indicate that there is an acceptable performance of prediction such as 65% for dry, 46% for moist, and 33% for wet road conditions. The overall accuracy of the model is 53%. The findings of the study may contribute to developing comprehensive measures for enhancing road safety.

• International Journal of Highway Engineering
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• v.15 no.6
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• pp.41-47
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• 2013

PURPOSES : The purpose of this study is about noise which is generated from roads and is consist of irregular frequency variation from low frequency to various band. The existing methods of noise reduction are sound barrier that uses insulation material and absorbing material or have applied passive technology of noise reduction by devices. The total frequency band is needed to apply active noise control. METHODS : In this study applies to the field of road traffic environment, signal processing controller and various analog signal input/output, the amplifier module is based on parallel-core embedded processor designed. DSP performs the control algorithm of the road traffic noise. Noise sources in the open space performance of evaluation were applied. In this study, controller of active signal processor was designed based on the module of audio input/output and main controller of embedded process. The controller of active signal processor operates noise reduction algorithm and performance tests of noise reduction in inside and outside environment were executed. RESULTS : The signal processing controller with OMAP-L137 parallel-core processors as the center, DSP processors in the active control operations dealt with quickly. To maximize the operation speed of an object and ARM processor is external function keys and display for functions and evaluating the performance management system was designed for the purpose of the interface. Therefore the reduction of road traffic noise has established an electronic controller-based noise reduction. CONCLUSIONS : It is shown that noise reduction is effective in the case of pour tonal sound and complex tonal sound below 500Hz by appling to Fx-LMS.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.11a
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• pp.709-714
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• 2008

The various computer programs are used in computer simulation of the traffic noise prediction. But the difference or problem of calculation method used for road traffic noise prediction is not exactly investigated. In this paper, Road traffic noise is predicted on the specific regions by using four prediction methods such as XPS31-133 model(France), RLS-90 model(Germany), ASJ RTN model(Japan) and FHWA model(U.S.A.), which are operated by a program named SoundPLAN, a program to predict road traffic noise. Those prediction values are compared with a measurement value. The results show that four prediction values for taraffic noise are a little different, because of various input factors according to the prediction methods.

• Transactions of the Korean Society of Automotive Engineers
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• v.10 no.5
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• pp.147-159
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• 2002

This paper proposes a method to recognize the noisiness of road images connected with the extraction of lane-related information in order to prevent the usage of erroneous information. The proposed method uses a fuzzy neural network(FNN) with the back-Propagation loaming algorithm. The U decides road images good or bad with respect to visibility of lane marks on road images. Most input parameters to the FNN are extracted from an edge distribution function(EDF), a function of edge histogram constructed by edge phase and norm. The shape of the EDF is deeply correlated to the visibility of lane marks of road image. Experimental results obtained by simulations with real images taken by various lighting and weather conditions show that the proposed method was quite successful, providing decision-making of noisiness with about 99%.

• Journal of the Korea Society of Computer and Information
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• v.4 no.2
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• pp.95-104
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• 1999

With the increasing of cars, general studies of them for the traffic safety have been raised as important problems. Visual system to radio-controled driving is to sample road traffic information as reconstructing a model from lots of road traffic information which is successively input in order to drive on unknown road. This paper proposes a sampling process of the road traffic information board needed in automatic driving under automatic drive system using Hough Transform and Genetic Alorithm.

• Transactions of the Korean Society of Automotive Engineers
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• v.22 no.3
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• pp.50-59
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• 2014

This paper proposes a method of localization of vehicle especially the horizontal position for the purpose of recognizing the driving lane. Through tracking road signs, the relative position between the vehicle and the sign is calculated and the absolute position is obtained using the known information from the regulation for installation. The proposed method uses Kalman filter for road sign tracking and analyzes the motion using the pinhole camera model. In order to classify the road sign, ORB(Oriented fast and Rotated BRIEF) features from the input image and DB are matched. From the absolute position of the vehicle, the driving lane is recognized. The Experiments are performed on videos from the highway driving and the results shows that the proposed method is able to compensate the common GPS localization errors.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.62 no.4
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• pp.192-197
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• 2013

Road traffic noise barriers being used to reduce the noise, but the city surroundings inhibition, ecosystem disturbance, and it is difficult to maintain. Can enhance or complement the existing noise barrier performance, so that it is necessary to develop an electronic noise-reduction system In this paper, we proposed an electronic road noise reduction devices to reduce road noise for a DSP-based signal processing and analog signal input-output controller. In order to verify the control performance, we performed noise reduction experimentation of ANC by filtered-X LMS algorithm and traffic noise signal injection. The controller is equipped with noise reduction algorithms were tested on the characteristics of directional and omnidirectional speaker.

• Transactions of the KSME C: Technology and Education
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• v.3 no.2
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• pp.83-88
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• 2015

Agricultural tractors are utilized on rough road such as rice paddy field. Therefore, static and dynamic load should be considered when simulating structural analysis with finite element analysis (FEA). But it consumes a lot of time and effort to measure dynamic load because of difficulty and complexity in modeling various field working load conditions and kinematics of machinery. In this paper, to reduce the efforts, 4-post road simulator is developed for agricultural tractor like modeling commercial vehicle. In proving ground test in our facility, I measured acceleration of front/rare axle and strain of body frame to validate input loads. The acceleration is used for defining input loads. And strain is validated with dynamics analysis including mode superposition method. As a result, I was able to calculate 4-post input road profiles, which represent similar proving ground profile with good reliability.