• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.30 no.3D
• /
• pp.199-204
• /
• 2010

The purpose of this study is to estimate the effectiveness of newly proposed guide sign system. Existing guide sign system on expressways in South Korea have point-based system with city, district names or land marks. They have also several problems as excessive amount of information, low use of exit number, and lack of lane designation arrows. Efficiency of existing guide sign system is deteriorated from these problems. The enhanced guide sign system is proposed to alleviate problems. The best alternative sign system is chosen from three different designs with preference survey and human factors evaluation. The new signs showed reduced time compared to existing signs with statical significance. The existing sign system conveys more information in farther distance and less information in nearer distance. Nevertheless new systems imparts more information i nearer distance. It is also suggested that lane designation signs should be established with overhead installation at 0m point for efficient direction choice.

• Journal of Korea Society of Industrial Information Systems
• /
• v.22 no.6
• /
• pp.9-16
• /
• 2017

An Algorithm for Lane Detection and Lane Departure Warning for a Vehicle Driving on Roads is proposed in This Paper. Using Images Obtained from On-board Cameras for Lane Detection has Some Difficulties, e.g. the Increase of Fault Detection Ratio Due to Symbols on Roads, Missing Yellow Lanes in the Tunnel due to a Similar Color Lighting, Missing Some Lanes in Rainy Days Due to Low Intensity of Illumination, and so on. The Proposed Algorithm has been developed Focusing on Solving These Problems. It also has an Additional Function to Determine How much the Vehicle is leaning to any Side between The Lanes and, If Necessary, to Give a Warning to a Driver. Experiments Using an Image Database Built by Collecting with Vehicle On-board Blackbox in Six Different Situations have been conducted for Validation of the Proposed Algorithm. The Experimental Results show a High Performance of the Proposed Algorithm with Overall 97% Detection Success Ratio.

• Proceedings of the KIEE Conference
• /
• 2011.07a
• /
• pp.1794-1795
• /
• 2011

본 연구에서는 가속도 센서의 값을 디지털 신호 처리 과정을 통하여 저역통과 필터(low pass filter), 벡터의 크기(vector magnitude), 롤(roll) 그리고 피치(pitch)를 계산하는 알고리즘을 적용하였다. 필터의 경우 IIR(Infinite Impulse Response)을 이용하였으며 차수는 9차로 하였다. 피험자의 연령은 $25{\pm}5$세의 10명을 기준으로 실험하였으며 앞, 뒤, 좌, 우 방향으로 직각 낙하하도록 하였고 센서 모듈은 오른쪽 허리의 정중앙에 착용하도록 하여 피험자간의 오차가 발생하지 않도록 하였다. 환자의 낙상을 검출하기 위해서 벡터의 크기를 사용하였고 롤과 피치를 이용하여 환자의 낙상 방향을 검출하였다. 결과적으로 피험자 10명의 경우 낙상의 검출률은 100% 였으며 낙상 방향에 따른 앞, 뒤, 좌, 우 판별 정확도는 95% 정도이다. 낙상 방향의 판별은 사고 후 환자를 다룰 때의 주의할 신체부위를 참고하며 재활 운동 시 하체의 어느 쪽이 낙상의 주요인인지 분석하는 보조 자료가 될 수 있다.

• International Journal of Highway Engineering
• /
• v.12 no.2
• /
• pp.91-97
• /
• 2010

This study started from the problem recognition of climbing lane installed in Korea roads. Because design standards of climbing lane installed don't match traffic pattern of korean drivers, coefficient of utilization of climbing lane is low and merging section between climbing lane and main lane has traffic accident possibilities. For this, brand-new design standards developed from the present lane design criterion, taper lenghs, and traffic signs, then field adoption test was carried out to prove the effectiveness. As a result, coefficient of utilization of climbing lane and average traffic velocity in climbing section are improved and the economic analysis also shows that brand-new standards has high feasibility for low cost. In case of broad application to not only expressway but national and local road based on the study, it could be a significant contribution to traffic flow improvement.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.34 no.4
• /
• pp.1181-1190
• /
• 2014

In this study, the erosional parameters for deposit beds were quantitatively estimated domestically for the first time through the erosion tests using an annular flume. Four erosion tests were carried out for the deposit beds with different consolidation structures, which were obtained by consolidating the kaolinite slurries for a given time durations. Results of erosion tests showed that the bed shear strength ${\tau}_s$ increased with the consolidation time and bed depth. The erosion rate ${\epsilon}$ was also shown to be related well with the excess shear stress ${\tau}_b-{\tau}_s$ which was given by the difference between flow shear stress ${\tau}_b$ and bed shear strength ${\tau}_s$. While the logarithm of the erosion rate was linearly related with the excess shear stress as ${\tau}_b-{\tau}_s{\geq}0.1N/m^2$, however, the erosion rate decreased rapidly with it when ${\tau}_b-{\tau}_s{\leq}0.1N/m^2$. These erosion test results were also shown to be good enough to verify by comparing with the test results from previous studies and a new equation was suggested to describe the erosion rate more well in the region of ${\tau}_b-{\tau}_s{\leq}0.1N/m^2$.

• Journal of KIISE:Software and Applications
• /
• v.27 no.12
• /
• pp.1174-1182
• /
• 2000

본 논문은 주행중인 자동차 환경에서 운전자의 안전성 및 편의성의 동시 확보를 위하여, 보조적인 스위치 조작 없이 상시 음성의 입, 출력이 가능한 시스템을 제안하였다. 이대 잡음에 강인한 threshold 값을 구하기 위하여, 1.5초마다 기준 에너지와 영 교차율을 변경하였으며 대역 통과 여과기를 이용하여 1차, 2차로 나누어 실시간 상태에서 자동으로, 정확하게 끝점 검출을 처리하였다. 또한 남성, 여성을 피치검출로 구분하여 모델을 선택하게 하였고, 주행중인 자동차 속도에 따라 가장 적합한 모델을 사용하기 위하여 Idle-40km, 40-80km, 80-100km로 구분하여 남성, 여성 모델을 각각 구분하여 인식할 수 있게 하였다. 그리고, 음성의 특징 벡터와 인식 알고리즘은 PLP 13차와 OSDP(one-Stage Dynamic Programming)을 사용하였다. 본 실험은 서울시내 도로 및 내부 순환도로에서 각각 속도별로 구분하여 화자독립 인식 실험을 한 결과 40-80km 상태에서 남자는 96.8%, 여자는 95.1%, 80-100km 상태에서는 남자 91.6%, 여자는 90.6%의 인식결과를 얻을 수 있었고, 화자종속 인식실험 결과 40-80km 상태에서 남자는 98%, 여자는 96%, 80-100km 상태에서는 남자는 96%, 여자는 94%의 높은 인식률을 얻었으므로, system의 유효성을 입증하였다.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.21 no.6
• /
• pp.374-382
• /
• 2020

The purpose of this study is to improve the learning speed of an ammunition stockpile reliability classification artificial neural network model by proposing a normalization method that reduces the number of input variables based on the characteristic of Ammunition Stockpile Reliability Program (ASRP) data without loss of classification performance. Ammunition's performance requirements are specified in the Korea Defense Specification (KDS) and Ammunition Stockpile reliability Test Procedure (ASTP). Based on the characteristic of the ASRP data, input variables can be normalized to estimate the lot percent nonconforming or failure rate. To maintain the unitary hypercube condition of the input variables, min-max normalization method is also used. Area Under the ROC Curve (AUC) of general min-max normalization and proposed 2-step normalization is over 0.95 and speed-up for marching learning based on ASRP field data is improved 1.74 ~ 1.99 times depending on the numbers of training data and of hidden layer's node.

• The Journal of the Korea Contents Association
• /
• v.22 no.10
• /
• pp.535-545
• /
• 2022

The purpose of this study is to classify the various problems in surface road according to their severity and to propose a priority decision making process for road policy makers. For this purpose, the road problems reported by Cheok-cheok app were classified, and the EPDO was adopted and calculated as an index of their severity. To test applicability of the proposed process, some images of road problems reported by the app were classified and annotated, and the Deep Learning was used for machine learning of the curated images, and then the other images of road problems were used for verification. The detecting success rate of the road problems with high severity such as road kills, obstacles in a lane, road surface cracks was over 90%, which shows the applicability of the proposed process. It is expected that the proposed process will make the app possible to be used in the filed to make a priority decision making by classifying the level of severity of the reported road problems automatically.

• Proceedings of the KSR Conference
• /
• 2007.05a
• /
• pp.1807-1813
• /
• 2007

The study aims at analyzing an underground station refuge model using EXODUS, one of the refuge simulation programs. The model for simulation is the Daegu Subway (Joongang-ro station). The details of the accident are referred to as the simulation condition the refuge time of traveling from the $3^{rd}$ basement platform to the $1^{st}$ basement is mainly calculated, with passengers numbering 1,000 including 329 at car 1079, 320 at car 1080, and 360 who are not on board. Reference data is used to set up the position of passengers. CFAST fire simulator is also used, and a fast curve among the $t^2$ growth curves, selected as fire growth scenario. The zone is divided into a total of 24 including 18 at the $3^{rd}$ basement platform and 6 at the $2^{nd}$ basement the $1^{st}$ basement is excluded in the fire simulation, however.

• KIPS Transactions on Software and Data Engineering
• /
• v.5 no.8
• /
• pp.369-376
• /
• 2016

Among various vehicle extraction techniques, OBPCA (Object-Based Point Cloud Analysis) calculates features quickly by coarse-grained rectangles from top-view of the vehicle candidates. However, it uses only a top-view rectangle to detect a vehicle. Thus, it is hard to extract rectangular objects with similar size. For this reason, accuracy issue has raised on the OBPCA method which influences on DEM generation and traffic monitoring tasks. In this paper, we propose a novel method which uses the most distinguishing vertical elevations to calculate additional features. Our proposed method uses same features with top-view, determines new thresholds, and decides whether the candidate is vehicle or not. We compared the accuracy and execution time between original OBPCA and the proposed one. The experiment result shows that our method produces 6.61% increase of precision and 13.96% decrease of false positive rate despite with marginal increase of execution time. We can see that the proposed method can reduce misclassification.