• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.18 no.2
• /
• pp.12-28
• /
• 2019

Road geometry is one of the many factors that cause crashes, but the effect on traffic accident depends on weather conditions even under the same road geometry. This study identifies the variables affecting the crash severity by matching the highway accident data and weather data for 14 years from 2001 to 2014. A hierarchical ordered Logit model is used to reflect the effects of road geometry and weather condition interactions on crash severity, as well as the correlation between individual crashes in a region. Among the hierarchical models, we apply a random intercept model including interaction variables between road geometry and weather condition and a random coefficient model including regional weather characteristics as upper-level variables. As a result, it is confirmed that the effects of toll, ramp, downhill slope of 3% or more, and concrete barrier on the crash severity vary depending on weather conditions. It also shows that the combined effects of road geometry and weather conditions may not be linear depending on rainfall or snowfall levels. Finally, we suggest safety improvement measures based on the results of this study, which are expected to reduce the severity of traffic accidents in the future.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.12 no.3
• /
• pp.53-64
• /
• 2013

The car-following model is one of core models in Advanced Vehicle & Highway Systems (AVHS). The car-following model has been developed in aspects such as human factor and reduction error rates. However, the consideration of safety depending on weather condition has not been completed yet. In this paper, therefore, changes of driving condition for car-following due to different road condition were dealt with, and optimal safety distance corresponding to road condition such as dry, wet and snowy were computed. The GMIT(GM Model with Instantaneous T) model was picked over for simulation of adaptive cruise control applied the suggested optimal safety distance. As the results, the 1.7 times longer safety distance was required for wet road condition than dry road condition, and the 5.6 times longer safety distance was required for snowy road condition.

• The Science & Technology
• /
• v.33 no.4 s.371
• /
• pp.20-23
• /
• 2000

기상관측기술은 2차 세계대전을 통해 등장한 레이더와 57년에 발사된 인공위성이 지구선회에 성공함으로써 획기적인 발전을 거듭해 왔다. 이제는 기상관측은 물론 기상상태를 조절하는 기술이 발달하여 필요에 따라 마음대로 비나 눈도 내리게 할 수 있게 되었다. 앞으로는 기상위성을 통해 입체적으로 대기를 관측하고 또 슈퍼컴퓨터의 발달이 기상관측의 새로운 장을 열어 줄 것이다.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2014.10a
• /
• pp.943-947
• /
• 2014

NMPB 2008을 포함한 일부 소음 예측식에서는 기상학적 요소를 고려할 수 있다. 특히 NMPB 2008을 이용하여 소음을 예측할 경우에는 기상학적인 요소의 고려는 필수적이다. 하지만, 우리나라의 실제 기상 상황을 반영할 수 있는 방법이 없는 것이 현실이다. 본 연구에서는 기상학적 요소를 적용하기 위해서 하향 굴절 발생 빈도를 적용하여 소음도를 비교하였다. 기상학적 요소의 하향 굴절 발생 빈도의 증가에 따라 소음도가 증가하는 것을 확인하였고, 1kHz 이상의 주파수에서 거리에 따른 소음도의 차이에 상대적으로 큰 영향을 미치는 것을 확인하였다. 기상학적 요소의 적용은 예측 소음도의 정확도를 향상시킬 것으로 기대된다.

• Proceedings of the KIEE Conference
• /
• 2008.07a
• /
• pp.292-293
• /
• 2008

본 논문에서는 지역별로 다르게 나타날 수 있는 기상상태별 사고확률을 고려한 선로사고에 따른 전압안정도의 위반정도를 시험계통을 통해 계산해보고 그 결과를 전통적으로 사용되어져 오던 결정론적 방법과 비교해 봄을 통해 고장확률을 고려한 확률론적 안정도 평가의 영향을 살펴보았다.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
• /
• 2003.09a
• /
• pp.46-49
• /
• 2003

우리나라 고령지는 특이한 지형조건 때문에 집중강우가 많고 기상변동이 심하며 지역 간의 차이도 크다. 또한 고령지 밭토양은 경사지가 많아 유실이 심하여 대부분의 경작지는 토양환경이 불량한 상태에서 농업활동이 이루어진다. 이러한 고령지의 기상과 토양특성은 고랭지 농업생산성에서 볼 때 대단히 불리한 조건으로 작용하게 된다. 특히 토양의 수분상태는 작물의 수량에 직접적인 영향을 미칠 뿐만 아니라 병해의 발생에도 주요한 요인으로 작용하여 풍흉을 좌우하기도 한다.(중략)

• Journal of Korean Society of Transportation
• /
• v.28 no.1
• /
• pp.157-163
• /
• 2010

It is well known that weather conditions are closely related with the number and severity of traffic accidents. At present, installation of safety countermeasures including systems is common approach to reduce the damage of traffic accidents at expressways. In this study, the differences of causation factors to influence traffic accidents considering road alignment characteristics and weather conditions. In order to identify the relationship between road and weather conditions, discriminant analysis has been performed with 500 traffic accident data at expressways. Weather conditions are divided into several categories such as snow, sunny, rain, fog, and cloud. Also, road conditions such as types of pavements, grades are analyzed. As the results, major impacting road conditions to traffic accidents are concrete pavement and 3% or more down grades. In these road conditions, visible distance will be reduced and actual braking distances will be increased. This study shows that the expressway sections under concrete pavement and down grades should be more cautious than other sections. It also shows that fog condition is the mose dangerous situation in terms of traffic accidents.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
• /
• 2015.08a
• /
• pp.171-176
• /
• 2015

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.17 no.6
• /
• pp.121-132
• /
• 2018

Weather is an important factor affecting roadway transportation in many aspects such as traffic flow, driver 's driving patterns, and crashes. This study focuses on the relationship between weather and road surface condition and develops a model to estimate the road surface condition using machine learning. A road surface sensor was attached to the probe vehicle to collect road surface condition classified into three categories as 'dry', 'moist' and 'wet'. Road geometry information (curvature, gradient), traffic information (link speed), weather information (rainfall, humidity, temperature, wind speed) are utilized as variables to estimate the road surface condition. A variety of machine learning algorithms examined for predicting the road surface condition, and a two - stage classification model based on 'Random forest' which has the highest accuracy was constructed. 14 days of data were used to train the model and 2 days of data were used to test the accuracy of the model. As a result, a road surface state prediction model with 81.74% accuracy was constructed. The result of this study shows the possibility of estimating the road surface condition using the existing weather and traffic information without installing new equipment or sensors.

• Aerospace Engineering and Technology
• /
• v.3 no.2
• /
• pp.133-140
• /
• 2004

In some cases, the launch vehicle is fatally affected by the change of weather condition. Thus the real time monitoring of weather condition is indispensible for successful launch campaign. This paper described general characteristics of weather radar for space center. The analysis of weather radar requirements has been carried out focusing on the transmitting power, gain of antenna, half power beam width, and minimum detectable signal.