• 전기학회논문지P
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• 제58권1호
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• pp.48-55
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• 2009

In order to keep safe driving conditions under road networks, there are several formations such as road structure, road surface condition, traffic occupancy and supplement of an accurate information of traffic status ahead To support safe-driving on each road formation, each formation is supplied with various information to help the driver. However, in some cases like rapid status change at local-scale geography, traffic information systems often displays insufficient information because of the lack of information correlation. In order to accurately aware the driver, all road formation must be in sync. It is important to supply accurate information to the driver because this information directly impacts the drivers on the road. This paper discusses the amber information to keep the least safety driving over road formations including tunnels and bridges. This paper also will propose the informations for safe-driving conditions, information linkage on the road and rule-base safety information, as ITS technology, being displayed for all drivers under the worst weather conditions.

• 자동차안전학회지
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• 제10권1호
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• pp.38-44
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• 2018

This paper presents an analysis on driving safety in lane change situation based on road driving data. Autonomous driving is a global trend in vehicle industry. LKAS technologies are already applied in commercial vehicle and researches about lane change maneuver have been actively studied. In autonomous vehicle, not only safety control issue but also imitating human driving maneuver is important. Driving data analysis in lane change situation has been usually dealt with ego vehicle information such as longitudinal acceleration, yaw rate, and steering angle. For this reason, developing safety index according to surrounding vehicle information based on human driving data is needed. In this research, driving data is collected from perception module using LIDAR, radar and RT-GPS sensors. By analyzing human driving pattern in lane change maneuver, safety index that considers both ego vehicle and surrounding vehicle state by using relative velocity and longitudinal clearance has been designed.

• 한국지리정보학회지
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• 제22권3호
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• pp.133-145
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• 2019

우리나라 미래 핵심과제 중 하나인 자율주행자동차를 지원하는 정밀도로지도에 대한 구축과 연구가 민간, 국가 차원에서 빠른 실용화를 목표로 적극적으로 추진되고 있다. 이러한 상황에서 정밀도로지도의 변화정보의 최신성 확보 및 갱신에 대한 방법이 핵심과제로 부각되고 있다. 따라서 이 연구에서는 정밀도로지도의 효율적인 갱신체계 정립 방안을 마련하기 위하여 도로의 종류, 도로변화의 원인과 연간 변화율 등의 현황과 정밀도로지도 관련 시스템과 정밀도로지도 갱신체계 구축을 위한 고려사항을 분석하였다. 이러한 현황분석을 토대로 정밀도로지도의 전각문자, 내용, 지역 등을 고려하여 도로변화 정보의 수집 탐지 방법과 정밀도로지도의 갱신체계를 단기적 방안과 중장기적 방안으로 제시하였다. 현재는 기술적, 시스템적 제한으로 인해 단기적 갱신체계를 적용해야 할 것으로 판단되었으며 향후에는 기술개발과 업무협조 체계 구축 등 시스템적 개선을 통해 중장기 갱신체계 방안을 조속히 도입해 효율적이고 실시간적인 정밀도로지도 갱신체계를 구축해야 할 것으로 판단된다.

• 한국도로학회논문집
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• 제15권5호
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• pp.177-185
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• 2013

PURPOSES : This study attempts to design and establish the road surface condition detection system by using the image processing that is expected to help implement the low-cost and high-efficiency road information detection system by examining technology trends in the field of road surface condition information detection and related case studies. METHODS : Adapted visual information collecting method(setting a stereo camera outside of the vehicle) and visual information algorithm(transform a Wavelet Transform, using the K-means clustering) Experiments and Analysis on Real-road, just as four states(Dry, Wet, Snow, Ice). RESULTS : Test results showed that detection rate of 95% or more was found under the wet road surface, and the detection rate of 85% or more in snowy road surface. However, the low detection rate of 30% was found under the icy road surface. CONCLUSIONS : As a method to improve the detection rate of the mobile road surface condition information detection system developed in this study, more accurate phase analysis in the image processing process was needed. If periodic synchronization through automatic settings of the camera according to weather or ambient light was not made at the time of image acquisition, a significant change in the values of polarization coefficients occurs.

• 한국공간정보시스템학회:학술대회논문집
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• 한국공간정보시스템학회 2005년도 추계학술대회
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• pp.257-270
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• 2005

Many studies states that improperly uprising of infrastructure may cause leading the forest degradation and canopy reduction in many tropical forest of Asian countries. Other studies revealed that habitat destruction and fragmentation, edge effects, exotic species invasions, pollution are provoked by roads. Similarly, environmental effects of road construction in forests are problematic. Similarly, many researches have been indicated that roads have a far greater impact on forests than simply allowing greater access for human use. Moreover, people using river as means of transportation hence illegal logging and felling cause canopy depletion in many countries. Therefore, it is important to comprehend the study about spatial relation of road, river and suburb followed by temporal change of forest canopy phenomena. This study also tried to examine the effect of road, river and suburb in forest canopy density change of Terai forest of Nepal from you 1988 to 2001. So, Landsat TM88, 92 and 001 and FCD (Forest Canopy Density) mapper were used to perform the spatial .elation of canopy density change. ILWIS (Integrated Land and Water Information System) which is GIS software and compatible with remote sensing data was used to execute analysis and visualize the results. Study found that influence of distance to suburb and river had statistically significance influenced in canopy change. Though road also influenced canopy density much but didn't show a statistical relation. It can be concluded from this research that understanding of spatial relation of factors respect with canopy change is quite complex phenomena unless detail analysis of surrounding environment. Hence, it is better to carry out comprehensive analysis with other additional factors such as biophysical, anthropogenic, social, and institutional factors for proper approach of their effect on canopy change.

• 한국환경과학회지
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• 제31권4호
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• pp.329-339
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• 2022

Better understanding the mechanism of black ice occurrence on the road in winter is necessary to reduce the socio-economic damage it causes. In this study, intensive observations of road weather elements and surface information under the influence of synoptic high-pressure patterns (22^nd December, 2020 and 29^th January, and 25^th February, 2021) were carried out using a mobile observation vehicle. We found that temperature and road surface temperature change is significantly influenced by observation time, altitude and structure of the road, surrounding terrain, and traffic volume, especially in tunnels and bridges. In addition, even if the spatial distribution of temperature and road surface temperature for the entire observation route is similar, there is a difference between air and road surface temperatures due to the influence of current weather conditions. The observed road temperature, air temperature and air pressure in Nongong Bridge were significantly different to other fixed road weather observation points.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권9호
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• pp.3377-3395
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• 2015

Recently, several approaches to share road conditions and/or digital contents through VANETs have been proposed, and such approaches have generally considered the radial distance from the information source as well as the TTL to provision an ephemeral, geographically-limited information sharing service. However, they implement general MANETs and have not been tailored to the constrained movement of vehicles on roads that are mostly linear. In this paper, we propose a novel application-level mechanism that can be used to share road conditions, including accidents, detours and congestion, through a VANET. We assign probabilities to roads around each of the intersections in the neighborhood road network. We then use the graph representation of the road network to build a spanning tree of roads with the information source as the root node. Nodes below the root represent junctions, and the edges represent inter-connecting road segments. Messages propagate along the branches of the tree, and as the information propagates down the branches, the probability of replication decreases. The information is replicated until a threshold probability has been reached, and our method also ensures that messages are not delivered to irrelevant vehicles, independently of their proximity to the source. We evaluated the success rate and performance of this approach using NS-3 simulations, and we used IDM car following and MOBIL lane change models to provide realistic modeling of the vehicle mobility.

• 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.

• Journal of information and communication convergence engineering
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• 제15권3호
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• pp.187-192
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• 2017

Autonomous driving vehicle research demands complex road and lane understanding such as lane departure warning, adaptive cruise control, lane keeping and centering, lane change and turn assist, and driving under complex road conditions. A fast and robust road lane detection subsystem is a basic but important building block for this type of research. In this paper, we propose a method that performs road lane detection from black box input. The proposed system applies Random Sample Consensus to find the best model of road lanes passing through divided regions of the input image under HSV color model. HSV color model is chosen since it explicitly separates chromaticity and luminosity and the narrower hue distribution greatly assists in later segmentation of the frames by limiting color saturation. The implemented method was successful in lane detection on real world on-board testing, exhibiting 86.21% accuracy with 4.3% standard deviation in real time.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2015년도 추계학술대회
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• pp.687-690
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• 2015

전방 추돌 경보 시스템(FCWS) 및 차선 이탈 경보 시스템(LDWS)에서 차선 및 객체 검출을 위한 관심영역은 차도영역으로 설정되어야 한다. 분수계 분할(watershed segmentation)방법은 차도영역을 분리하기에 효과적인 알고리즘이다. 이 알고리즘은 초기 seed에 속해있는 watershed line과 국부 최소값에 따라서 분할 결과가 다르게 나타나는데 차도 seed에 그 이외의 영역이나 차량이 포함될 경우에 차도 이외의 부분이 차도영역으로 포함되어 분할된다. 이런 문제점을 보완하기 위해 도로 환경에 따라 차도 seed를 적응적으로 변경해야 한다. 그 방법으로 영상을 여러 개의 관심영역으로 분할하여 차선을 검출하고 자기차선을 잇는 직선을 초기 seed로 설정한다. 설정된 seed에 차량이 검출되면 seed 위치를 조정하고 조정된 위치에서 차선을 지나지 않는다면 차선을 지나도록 seed의 크기를 조정하여 최종적인 seed를 결정한다. 최종적으로 결정된 seed를 통해서 도로환경에 따라 적응적으로 차도영역을 검출을 가능하게 한다.