• 한국자동차공학회논문집
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• 제5권1호
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• pp.136-145
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• 1997

To analyzed ride quality and to predict durability in vehicle dynamics, it is essential to describe a road surface profile precisely. This paper presents a technique to generate road surface profiles in a spatial domain by using a power spectral density function. A single track power spectral density function is proposed to describe a road surface profile, which is also applicable for multi-track vehicle response analysis, The derived road surfaces are compared to ISO(International Organization for Standardization) standards and classifications, proposed by the MIRA(Motor Industry Research Association). The methodology in this paper is also proposed to generate road roughness description with a limited external data. A small amount of external curve data is combined with an internal PSD function to generate road surface roughness in a spatial domain.

• 한국콘텐츠학회논문지
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• 제11권11호
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• pp.42-48
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• 2011

본 논문에서는 교량구간의 도로 결빙예측 및 감지를 위한 시스템 설계를 제안하였다. 센서 노드의 하드웨어는 마이크로프로세서, 온도 센서, 습도 센서, 그리고 Zigbee 무선 통신으로 구성되었다. 관제센터의 소프트웨어는 관제센터에 수집된 교량 온도, 습도 데이터로 관찰하기 위하여 구현되었다. 교량 노면의 결빙은 노면의 온도가 이슬점 온도 이하이면서 영하일 때 발생한다. 제안된 시스템을 이용하여 도로면의 온도 및 습도 분포를 측정하였다. 측정 데이터는 도로 결빙이 발생하는 시점을 예측하기 위하여 사용되었다. 실제 결빙되는 것보다 최소 30분 이전에 결빙시점을 예측하여 경고가 이루어진다. 이 결과로 결빙으로 인한 교통사고를 방지하기 위하여 사용 할 수 있다.

• 대한임베디드공학회논문지
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• 제17권3호
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• pp.149-155
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• 2022

This paper proposes a method for estimating the road surface condition and tilt angle using an inertial measurement unit (IMU) to improve the safety in the use of mobility aids for the elderly. The measurements of the accelerometers of the IMU usually include the accelerations caused by not only the gravitational force but also linear and rotational motions. Thus, the gravitational accelerations are first extracted using several physical constraints and then incorporated into the Kalman filter to estimate the tilt angle. In addition, because the magnitudes of the accelerations produced by the rotational motions (roll and pitch motions) vary with the road surface condition, a criterion based on such accelerations is presented to classify the condition of the road surface. The obtained road surface condition and tilt angle are finally combined to provide the safety information (e.g., safe, warning, and danger) for the user to improve the walking safety. Experiments were carried out and the results showed that the proposed method can provide the condition of the road surface, the tilt of the road surface, and the safety information correctly.

• 한국응용과학기술학회지
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• 제37권6호
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• pp.1507-1516
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• 2020

본 연구는 도로 노면결빙 판정 알고리즘을 적용하여 도로결빙 구간에 대한 시나리오를 분석하였다. 도로결빙 알고리즘 적용을 위해서, 도로 결빙에 대한 영향인자를 검토하고, 분석을 위해서 목감IC, 정릉터널, 성산대교, 염창교 등 4지점의 관측자료를 활용하였다. 관측소는 모두 고속화도로에 설치되어 있으며, 도로 결빙 특성 분석을 위하여 분류하였다. 도로 결빙 판정 알고리즘의 노면온도-노점온도 차가 3℃ 이하일 때 도로결빙 발생 구간을 확인하고 결빙 구간의 노면상태와 수막두께 변화를 통해 도로 결빙 판정을 도출하였다.

• 한국자동차공학회논문집
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• 제18권4호
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• pp.92-98
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• 2010

Virtual ground modeling is one of key topic for real-time vehicle dynamic simulation. This paper discusses about the virtual 3D road modeling process using parametric surface concept. General road data is a type of lumped position vector so interpolation process is required to compute contact of internal surface. The parametric surface has continuity and linearity within boundaries and functions are very simple to find out contact point. In this paper, the parametric surface formula is adopted to road modeling to calculate road hight. Position indexing method is proposed to reduce memory size and resource possession, and a simple mathematical method for contact patch searching is also proposed. The developed road process program is tested in dynamic driving simulation on off-road. Conclusively, the new virtual road program shows high performance of road hight computation in vast field of off-road simulation.

• 한국콘크리트학회:학술대회논문집
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• 한국콘크리트학회 2010년도 춘계 학술대회 제22권1호
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• pp.391-392
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• 2010

도로의 결빙은 겨울철 차량사고의 큰 원인으로 작용하며, 특히 고속도로에서의 노면결빙은 대형사고로 이어질 수 있다. 이러한 노면결빙으로 인한 사고는 노면상태를 파악하여 사전에 결빙을 방지함으로서 효과적으로 감소시킬 수 있다. 따라서 본 연구에서는 고속도로에 적용된 콘크리트 포장체의 노면상태를 평가하기 위하여 상습결빙구간에 포장체 깊이별로 온도센서를 설치하였다. 이 결과는 향후 결빙 사전예측을 위한 노면상태판정의 기초자료로 효과적으로 활용될 것이다.

• 한국소음진동공학회논문집
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• 제16권10호
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• pp.1067-1073
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• 2006

In this paper, we present noise measurement results of 8 vehicles. The measurement was done by a close proximity method attaching surface microphones on the test vehicle. For the 9 road surface types constructed at Korean highway test road, the vehicles were tested from 50 to 120 km/h at the interval of 10 km/h in normal steady state and inertia cruising conditions. Using the results, we evaluate and discuss the effect of vehicle noise generation depending on the different conditions for vehicle type, speed, road surface and loading condition, especially focused on friction noise between tyre and road surface.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2006년도 춘계학술대회논문집
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• pp.428-433
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• 2006

In this paper, we present noise measurement results of 8 vehicles. The measurement was done by a close proximity method attaching surface microphones on the test vehicle. For the 9 road surface types constructed at Korean highway test road, the vehicles were tested from 50 to 120 km/h at the interval of 10 km/h in normal steady state and inertia cruising conditions. Using the results, we evaluate and discuss the effect of vehicle noise generation depending on the different conditions for vehicle type, speed, road surface and loading condition, especially focused on friction noise between tyre and road surface.

• 한국도로학회논문집
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• 제19권2호
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• pp.35-44
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• 2017

PURPOSES: This study suggests a specific methodology for the prediction of road surface temperature using vehicular ambient temperature sensors. In addition, four kind of models is developed based on machine learning algorithms. METHODS : Thermal Mapping System is employed to collect road surface and vehicular ambient temperature data on the defined survey route in 2015 and 2016 year, respectively. For modelling, all types of collected temperature data should be classified into response and predictor before applying a machine learning tool such as MATLAB. In this study, collected road surface temperature are considered as response while vehicular ambient temperatures defied as predictor. Through data learning using machine learning tool, models were developed and finally compared predicted and actual temperature based on average absolute error. RESULTS : According to comparison results, model enables to estimate actual road surface temperature variation pattern along the roads very well. Model III is slightly better than the rest of models in terms of estimation performance. CONCLUSIONS : When correlation between response and predictor is high, when plenty of historical data exists, and when a lot of predictors are available, estimation performance of would be much better.

• 한국인공지능학회지
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• 제11권4호
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• pp.21-27
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• 2023

This paper discusses a deep learning-based road surface analysis system that collects data by installing vibration sensors on the 4-axis wheel bearings of a vehicle, analyzes the data, and appropriately classifies the characteristics of the current driving road surface for use in the vehicle's control system. The data used for road surface analysis is real-time large-capacity data, with 48K samples per second, and the A2B protocol, which is used for large-capacity real-time data communication in modern vehicles, was used to collect the data. CAN and CAN-FD commonly used in vehicle communication, are unable to perform real-time road surface analysis due to bandwidth limitations. By using A2B communication, data was collected at a maximum bandwidth for real-time analysis, requiring a minimum of 24K samples/sec for evaluation. Based on the data collected for real-time analysis, performance was assessed using deep learning models such as LSTM, GRU, and RNN. The results showed similar road surface classification performance across all models. It was also observed that the quality of data used during the training process had an impact on the performance of each model.