• Korean Journal of Environment and Ecology
• /
• v.17 no.1
• /
• pp.1-8
• /
• 2003

This study was conducted to investigate the effects of road on bird community by line transect census method from May 2000 to January 2001 in Mt. Geumsan, Namhae-Gun, Kyeongsangnam-do. Canopy layer was more developed in forest area than road area. Understory vegetation of road area was more developed than forest area. Twenty six and twenty three bird species were observed in road and forest area, respectively, White's thrush and ashy minivet were observed just only in forest area, and Siberian blue robin, blue-and-white flycatcher and gold crest were in road area. The birds being to bush nesting and foraging guilds in road area were more than forest area. It is known that the road construction was negatively affected on bird community. However, road construction would be not so negative on bird community according to the results of thie study. It would be needed the maintenance of upper canopy layer and understory vegetation to reduce negative effect of road on bird communities in forest area.

• Proceedings of the Korean Information Science Society Conference
• /
• 2007.06c
• /
• pp.407-411
• /
• 2007

이 논문은 우리나라 차량 영상에서 번호판 영역을 추출하는 알고리즘을 제안한다. 우리나라 번호판은 하단에 네개의 숫자를 포함하고 있으므로, 네 개의 숫자를 찾으면 번호판을 추출 할 수 있다. 제안하는 방법은 입력된 영상에서 숫자의 가능성을 가진 연결 요소를 검출하고 이들을 군집화 한다. 군집화 된 연결요소들을 바탕으로 숫자 네개(4-digits) 후보를 생성한다. 4-digits 후보들을 인식하여 숫자의 가능성을 측정하고, 적합도로 변환한다. 후보영역 중 적합도가 가장 높은 영역을 번호판 영역으로 추출한다. 적합도는 Perfect Metrics 방법으로 측정하였다. 제안하는 방법을 주간 영상 4600장과 야간 영상 264장으로 테스트 한 결과 각각 97.23%, 95.45%의 검출률과 0.09%, 0.11%의 오검출률을 얻었다.

• Proceedings of the IEEK Conference
• /
• 2008.06a
• /
• pp.1035-1036
• /
• 2008

본 논문은 주행 중인 자동차에서 획득한 영상에서 배경과 도로영역 및 물체를 분리하기 위한 영역분할 기법과 물체 검출 기법을 제안하고자 한다. 영상내의 에지라인의 화소 간 연결성을 이용한 라인검출을 이용하여 도로의 윤곽선 정보를 추출하고 컬러분포를 통해 배경과 도로영역을 분리한다. 물체가 가지는 코너 특성을 이용하여 나타난 정보들의 군집화를 통해 후보영역을 얻고 컬러 성분을 이용하여 개별 물체를 분리해냈다. 제안된 알고리즘은 복잡한 배경을 갖는 도로영상의 경우에도 도로영역과 물체의 검출에 강인함을 실험을 통해 검증하였다.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2023.05a
• /
• pp.409-410
• /
• 2023

제주특별자치도는 제주의 관광산업의 다양한 문제해결를 위해 제주데이터허브를 통한 제주의 다양한 관광데이터, 렌터카의 이동정보등을 제공하고 있다. 본 논문에서는 관광객 증가 및 렌터카 이용자의 증가로 인한 교통문제, 렌트카의 반납장소 문제등을 해결할 수 있도록 렌터카 차량의 군집데이터를 이용한 체류빈도를 시각화 하고자 한다.

• Journal of the Korean Society for Precision Engineering
• /
• v.18 no.1
• /
• pp.12-20
• /
• 2001

• Convergence Security Journal
• /
• v.18 no.2
• /
• pp.133-139
• /
• 2018

The 5 Game changer means the concepts of the army's operation against the enemy's asymmetric threats so that minimize damage to the public and leads to victory in war in the shortest time. A study of network architecture of Dronebot operation is a key study to carry out integrated operation with integrated C4I system by organically linking several drones battle groups through ICT. The NBC reconnaissance drones can be used instead of vehicles and humans to detect NBC materials and share situations quickly. However, there is still a lack of research on the swarm flight of the NBC reconnaissance drones and the weaknesses of cyber electronic warfare. In this study, we present weaknesses and countermeasures of CBRNs in swarm flight operations and provide a basis for future research.

• Journal of the Society of Disaster Information
• /
• v.17 no.1
• /
• pp.165-175
• /
• 2021

Purpose: The purpose of this study is to quantitatively present the carbon dioxide(CO₂) emission change according to the application of autonomous driving technology at the network level for waste vehicles in the metropolitan area. Method: The target year was set to 2030, and the analysis method estimated the carbon dioxide (CO₂) emissions for each road link through user equilibrium assignment when unapplied scenario. The application scenario performed traffic assignment using route data on the premise that the group was running in accordance with the application of autonomous driving technology to waste vehicles. In addition, the other means estimated the carbon dioxide emissions through user balance allocation by reflecting the results of the waste vehicle allocation. Result: As a result of the analysis, carbon dioxide(CO₂) emissions were found to be reduced by about 56.9ton/day from the national network level, and the Seoul metropolitan area was analyzed to be reduced by about 54.7ton/day. Conclusion: This study quantitatively presented environmental impacts among various social effects that autonomous driving technology will bring, and in the future, development of various analytical methodologies and related studies should be continuously conducted.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.21 no.6
• /
• pp.132-145
• /
• 2022

This study was based on the black box images of traffic accidents on highways, cluster analysis and prediction model comparisons were carried out. As analysis data, vehicle driving behavior and road surface conditions that can grasp road and traffic conditions just before the accident were used as explanatory variables. Considering that traffic accident data is affected by many factors, cluster analysis reflecting data heterogeneity is used. Each cluster classified by cluster analysis was divided based on the ratio of the severity level of the accident, and then an accident prediction evaluation was performed. As a result of applying the Logit model, the accident prediction model showed excellent predictive ability when classifying groups by cluster analysis and predicting them rather than analyzing the entire data. It is judged that it is more effective to predict accidents by reflecting the characteristics of accidents by group and the severity of accidents. In addition, it was found that a collision accident during stopping such as a secondary accident and a side collision accident during lane change act as important driving behavior variables.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.7 no.1
• /
• pp.59-67
• /
• 2008

In this paper we propose an algorithm to extract the license plate regions from Korean car images. The idea of this paper is that we first find the four digits in the input car image and then segment the plate region using the digit information. Out method has advantage of segmenting simultaneously the plate regions and four digits regions. The first step finds and groups the connected components with proper sizes as candidate digits. The second step applies an serial alignment condition to find out probable 4-digits. In the third step, we recognize the candidate digits and assign the confidence values to each of them. The final step extracts the license plate region which has the highest confidence value. We used the Perfect Metrics classification algorithm to estimate the confidence. In our experiment, we got 97.23% and 95.45% correct detection rates, 0.09% and 0.11% false detection rates for 4,600 daytime and 264 nighttime images, respectively.

• Journal of the HCI Society of Korea
• /
• v.14 no.2
• /
• pp.49-60
• /
• 2019

With the appearance of self-driving cars and electric cars, the automobile industry is rapidly changing. In the midst of these changes, HMI studies are becoming more important as to how the driver obtains safety and convenience with controlling the vehicle. This study sought to understand how automobile manufacturers understand the driving situation, and how they define and limit driver interaction. For this, prior studies about HMI were reviewed and 15 participants performed an on-road study to drive vehicles from five manufacturers with using their interfaces. The results of the study confirmed that buttons and switches that are easily controlled by the user while driving were different from manufacturer to manufacturer. And there are some buttons that are more intensively controlled and others that are difficult to control while driving. It was able to derive 'selection and concentration' from Audi's vehicle, 'optimization of the driving ' from BMW's, 'simple and minimize' from Benz's vehicle, 'remove the manual distraction' from the vehicle of Lexus, and 'visual stability' from KIA's vehicle as the distinctive keywords for the HMI. This shows that each manufacturer has a different definition and interpretation of the driver's driving control area. This study has a distinct value in that it has identified the characteristics of vehicle-specific HMI in actual driving conditions, which is not apparent in appearance. It is expected that this research approach can be useful to see differences in interaction through actual driving despite changes in driving environment such as vehicle platooning and self-driving technology.