• 한국도로학회논문집
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• 제18권6호
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• pp.61-67
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• 2016

OBJECTIVES : The objective of this study is to detect road cavities using multi-channel 3D ground penetrating radar (GPR) tests owned by the Seoul Metropolitan Government. METHODS : Ground-penetrating radar tests were conducted on 204 road-cavity test sections, and the GPR signal patterns were analyzed to classify signal shape, amplitude, and phase change. RESULTS : The shapes of the GPR signals of road-cavity sections were circular or ellipsoidal in the plane image of the 3D GPR results. However, in the longitudinal or transverse direction, the signals showed mostly unsymmetrical (or symmetrical in some cases) parabolic shapes. The amplitude of the GPR signals reflected from road cavities was stronger than that from other media. No particular pattern of the amplitude was found because of nonuniform medium and utilities nearby. In many cases where road cavities extended to the bottom of the asphalt concrete layer, the signal phase was reversed. However, no reversed signal was found in subbase, subgrade, or deeper locations. CONCLUSIONS : For detecting road cavities, the results of the GPR signal-pattern analysis can be applied. In general, GPR signals on road cavity-sections had unsymmetrical hyperbolic shape, relatively stronger amplitude, and reversed phase. Owing to the uncertainties of underground materials, utilities, and road cavities, GPR signal interpretation was difficult. To perform quantitative analysis for road cavity detection, additional GPR tests and signal pattern analysis need to be conducted.

• 한국소음진동공학회논문집
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• 제22권8호
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• pp.720-728
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• 2012

It is important for identification of noise and vibration problem of tire to consider influence of interaction between road and tire. A quantification of road noise is a challenging issue in vehicle NVH due to extremely complicated transfer paths of road noise as well as the difficulty in an experimental identification of input force from tire-road interaction. A noise caused by tire is divided into road noise(structure-borne noise) and pattern noise(air-borne noise). Pattern noise is caused by pattern shape of tire, which has larger than 500 Hz, but road noise is generated by the interactions between a tire and a vehicle body. In this paper, we define the quantitative analysis for road noise caused by interactions between tire and road parameters. For the identification of road noise, the chassis dynamometer that is equipped $10mm{\times}10mm $ square cleat in the semi-anechoic chamber is used, and the tire spindle forces are measured by load cell. The vibro-acoustic transfer function between ear position and wheel center was measured by the vibro-acoustic reciprocity method. In this study three tires with different type of mechanical are used for the experiment work.

• 한국도로학회논문집
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• 제20권2호
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• pp.127-135
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• 2018

PURPOSES : This study develops various models that can estimate the pattern of road surface temperature changes using machine learning methods. METHODS : Both a thermal mapping system and weather forecast information were employed in order to collect data for developing the models. In previous studies, the authors defined road surface temperature data as a response, while vehicular ambient temperature, air temperature, and humidity were considered as predictors. In this research, two additional factors-road type and weather forecasts-were considered for the estimation of the road surface temperature change pattern. Finally, a total of six models for estimating the pattern of road surface temperature changes were developed using the MATLAB program, which provides the classification learner as a machine learning tool. RESULTS : Model 5 was considered the most superior owing to its high accuracy. It was seen that the accuracy of the model could increase when weather forecasts (e.g., Sky Status) were applied. A comparison between Models 4 and 5 showed that the influence of humidity on road surface temperature changes is negligible. CONCLUSIONS : Even though Models 4, 5, and 6 demonstrated the same performance in terms of average absolute error (AAE), Model 5 can be considered the optimal one from the point of view of accuracy.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2011년도 춘계학술대회 논문집
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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.

• 대한산업공학회지
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• 제30권1호
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• pp.50-57
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• 2004

The aim of this study is to collect driver's psychophysiological signal under various road condition and to select and quantify psychophysiological variables for diagnosis of road-driver compatibility. A 4x4 vehicle with measuring devices was developed to collect driver's psychophysiological signal and collected driver's psychophysiological signal under various road conditions. The collected data were analyzed by the temporal pattern of signal overtime. Thirteen bio-signals with consistent pattern were selected and quantified in terms of slope and amplitude of the signal. These quantified values could be used as a part of tool to diagnose the road-driver compatibility.

• 제어로봇시스템학회논문지
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• 제15권11호
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• pp.1088-1095
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• 2009

In this paper, we describe the reorientation method of distorted road sign by using projection transformation for improving recognition rate of road sign. RSR (Road Sign Recognition) is one of the most important topics for implementing driver assistance in intelligent transportation systems using pattern recognition and vision technology. The RS (Road Sign) includes direction of road or place name, and intersection for obtaining the road information. We acquire input images from mounted camera on vehicle. However, the road signs are often appeared with rotation, skew, and distortion by perspective camera. In order to obtain the correct road sign overcoming these problems, projection transformation is used to transform from 4 points of image coordinate to 4 points of world coordinate. The 4 vertices points are obtained using the trajectory as the distance from the mass center to the boundary of the object. Then, the candidate areas of road sign are transformed from distorted image by using homography transformation matrix. Internal information of reoriented road signs is segmented with arrow and the corresponding indicated place name. Arrow area is the largest labeled one. Also, the number of group of place names equals to that of arrow heads. Characters of the road sign are segmented by using vertical and horizontal histograms, and each character is recognized by using SAD (Sum of Absolute Difference). From the experiments, the proposed method has shown the higher recognition results than the image without reorientation.

• 한국소음진동공학회논문집
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• 제23권4호
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• pp.315-323
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• 2013

Tire noise is divided into a road noise(structure-borne noise) and a pattern noise(air-borne noise). Whilst the road noise is caused by the structural vibration of the components on the transfer path from tire to car body, the pattern noise is generated by the air-pumping between tire and road. In this paper, a practical method to estimate the pattern noise inside a passenger car is proposed. The method is developed based on the sound intensity and airborne source quantification. Sound intensity is used for identifying the noise sources of tire. Airborne source quantification is used for estimating the sound pressure level generated by each noise source of a tire. In order to apply the airborne source quantification to the estimation of the sound pressure, the volume velocity of each source should be obtained. It is obtained by using metrics inverse method. The proposed method is successfully applied to the evaluation of the interior noises generated by four types of tires with different pattern each other.

• 대한교통학회지
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• 제30권1호
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• pp.31-43
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• 2012

한국이 UN 자동차 법규 표준화 기구(WP29) 주관의 소형차 배출가스 시험방법 국제 표준화(WLTP/DHC) 연구에 참여하게 됨에 따라 우리나라의 도로 종류 별, 주행 시간대 별 주행패턴 측정이 요구되었다. 이에 본 연구에서는 WP29에서 제안한 주행패턴 표준화 방법을 토대로, 우리나라의 도로 교통 특성을 반영한 실 도로 주행패턴을 측정하고, 대표성을 갖는 도로 종류 별 주행 시간대별 총 7가지 유형의 주행패턴을 분석하였다. 이를 위해 이동식 차량활동도 모니터링 장비(PAMS)를 이용하여 35,410km의 실주행자료를 수집하였으며, 각 유형별로 분석된 주행패턴은 서로 유의한 차이가 있는 것으로 나타났다.

• 한국도로학회논문집
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• 제14권4호
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• pp.163-173
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• 2012

PURPOSES : The purpose of this study is to check the possibilities of traffic pattern analysis using MatSIM for urban road network operation in incident case. METHODS : One of the stochastic dynamic models is MatSIM. MatSIM is a transportation simulation tool based on stochastic dynamic model and activity based model. It is an open source software developed by IVT, ETH zurich, Switzerland. In MatSIM, various scenario comparison analyses are possible and analyses results are expressed using the visualizer which shows individual vehicle movements and traffic patterns. In this study, trip distribution in 24-hour, traffic volume, and travel speed using MatSIM are similar to those of measured values. Therefore, results of MatSIM are reasonable comparing with measured values. Traffic patterns are changed according to incident from change of individual behavior. RESULTS : The simulation results and the actual measured values are similar. The simulation results show reasonable ranges which can be used for traffic pattern analysis. CONCLUSIONS : The change of traffic pattern including trip distribution, traffic volumes and speeds according to various incident scenarios can be used for traffic control policy decision to provide effective operation of urban road network.

• 한국소음진동공학회논문집
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• 제23권8호
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• pp.707-716
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• 2013

Tire noise is divided into two parts. One is pattern noise the other one is road noise. Pattern noise primarily occurs in over 500 Hz frequency but road noise occurs mainly in low frequency. It is important to develop a technology to predict the pattern noise at the design stage. Prediction technology of pattern noise has been developed by using image processing. Shape of tire pattern is computed by using imaging signal processing. Its results are different with the measured one. Therefore, the prediction of actual measured pattern noise is valuable. In the signal processing theory is applied to calculate the impulse response for the measurement environment. This impulse response used for the prediction of pattern noise by convolving this impulse response by the results of image processing of tire pattern.