• Korean Journal of Culture and Social Issue
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• v.22 no.2
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• pp.285-311
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• 2016

This study analysed the published papers dealing with traffic behaviors since 2004 in south Korea. The following information was coded for each papers; year of publication, source, authors, main topic, and subtopic. The annual numbers of publication in 2004 and 2005 showed 6 articles and 7 articles. Since 2006, The annual numbers were increasing more than 10 papers. It means that the researches on traffic behavior were rich. The driver was main topic of 73.2% of articles. Cognition & Perception, Fatigue and Stress, and Alcohol were the main interest sub-topics dealing with main topic driver. Elderly driver was 10.4%, the interest in elderly drivers grew with population aging. And the dominant publications were Journal of traffic safety research, Journal of Korean Psychology Association, and Journal of the Koean Data Analysis Society with 60% of all articles for last 10 years.

• Journal of Korean Society for Geospatial Information Science
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• v.22 no.4
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• pp.135-142
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• 2014

As interest in social safety has recently increased at the national level, the various activities which can effectively prevent crimes are being carried out. Because the existing maps related to crimes provide the information about the present condition of crimes by administrative district for users, women and pedestrians who go by night could not actually grasp safe roads in advance. Therefore, this study developed the methodology that can easily extract dangerous areas due to crimes by the digital map 2.0. In the digital map 2.0, location and attribute information of center-lines of roads and building layers were used to find dangerous areas of crimes in these layers. Pavement materials and road width which are already built by the attribute information were used in the center-lines of roads. Crossing angles that roads and roads cross each other were additionally extracted and utilized. The attribute information about building types were input in the building layers of the digital map 2.0. The areas that are more the threshold values set by totaling up all the risk scores when considering pavement materials, road width, crossing angles of road, and building types in the center-lines of roads and road crossings were extracted as the dangerous areas that crimes can occur. Verification of the developed methodology was done by experiment. In the spatial apsect, the dangerous areas of crimes could be found by using the digital 2.0, roads, and building layers only through the experiment. In the administrative aspect to prevent crimes, additional installation of safety facilities such as street lights and security lights in the identified areas which are vulnerable for crimes is thought to be increasing safety of dangerous areas.

• Journal of Korean Society of Transportation
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• v.29 no.5
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• pp.157-167
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• 2011

Many problems, such as unexpected delay and collision with pedestrians or vehicles, occur generally at signalized intersections where bicycle users are frequently involved. These problems have hindered bicycle users from riding bicycles on urban highways. The aim of this study is to suggest proper traffic signal operation methods for safe and convenient highway crossing of bicycles. Three types of crossing methods at signalized intersections are proposed and analyzed: (1) indirect left turn, (2) direct left turn on an exclusive bicycle lane, and (3) direct left turn on a bicycle box. The VISSIM simulation tests were conducted based on fifty-four operation scenarios prepared by varying vehicle and bicycle traffic volumes. Both delay and the number of stops are used as the measures of effectiveness in the analysis. The results from the three-legged signalized intersections suggested that (1) the indirect left turn is appropriate when vehicle demand is high while bicycle demand is not, (2) direct left turn on an exclusive bicycle lane is appropriate when both vehicle and bicycle demands are high, and (3) direct left turn on a bicycle box is appropriate when both vehicle and bicycle demands are light.

• Spatial Information Research
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• v.22 no.6
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• pp.33-43
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• 2014

As the number of people who live indoor space has been increased, the interest in 3D indoor spatial information has been grown. Object-Oriented 3D indoor space modeling including indoor spatial information has performed in level of detail 4, and modeling data is able to be constructed based on various raw data which are as-built drawing, laser scanning, BIM data, and camera. 3D indoor space modeling has been worked based on established indoor space modeling process, and the result can be used for various application fields such as indoor space pedestrian navigation, facility management, disaster management, and so on. However, the modeling process has limitations to perform indoor space modeling efficiently, because the process is complicated and wastes time at modeling work. In this paper, we propose evaluation on practical use of raw data for 3D indoor space modeling purpose on supporting efficient indoor space modeling through analyzing the established process. Therefore, we define the requirements to evaluate the practical use of raw data and propose the verification method. In addition, as-built drawing which has been used in Seoul 3D indoor space modeling project will be applied to proposed method as a raw data.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.198-198
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• 2021

최근 자연적, 사회적, 정책적 관점에서 하천관리의 중요성이 증대되면서 국가하천 정비를 통한 하천시설 관리의 책임이 증대되고 있다. 국가하천 5대강 본류의 친수지구 이용도 변화를 살펴보면 2015년에 비해 2019년에 면적당 이용객 수가 630,813(명/km²)이 증가하였음을 알 수 있었고(국토교통부, 2020) 본 연구에서는 이용자 수 증가율이 높은 편인 한강 내 하천이용시설을 대상으로 선정하여 해당 지역을 기계학습 기반의 수위예측 알고리즘에 적용하였다. 하천이용시설은 하천이용자가 편리하게 하천을 이용하기 위하여 설치한 시설로 공원시설(강서, 난지, 양화, 망원, 여의도, 이촌, 반포, 잠원, 뚝섬, 잠실, 광나루, 구리)을 위주로 분석하였다. 해당 시설의 침수피해를 고려하기 위해 시계열 자료에 특화된 LSTM(Long Short-term Memory)기법을 활용하여 수위예측 알고리즘을 개발하였고 이를 통해 도출된 홍수 예보로 재난을 대비하고 시설물을 체계적으로 관리하는 유지관리의 효과를 분석하고자 하였다. 입력 자료(input data)는 수위 (EL.m), 팔당댐 방류량 (m³/s), 강화대교의 조위(EL.m)를 사용하였으며 수위예측 알고리즘을 통해 6시간 후 예측 수위값을 도출하여 기존 2단계(주의보, 경보)였던 홍수 예보 단계에서 4단계(관심, 보행자통제, 차량통제, 경계)로 구축하였다. 기존과 세분화된 홍수예보를 적용했을 경우의 유지관리 비용과 편익을 산정하여 하천이용시설의 경제성을 비교·분석한 결과, 유지관리 비용이 기존 대비 약 5% 이상 절감되었고 편익은 약 1.5배 이상 증가하였으며 관리등급은 평균 C등급(보통) 이상 달성하였다. 이는 수위예측 알고리즘의 적용으로 하천이용 활성화 및 투자의 효율성에 목적을 두었으며 향후 분석결과를 토대로 경제성모델을 개발하여 국가하천 내 관리그룹에 적용하면 효율적인 유지관리체계를 제시할 수 있을 것으로 기대된다.

• Journal of Korean Tunnelling and Underground Space Association
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• v.24 no.3
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• pp.247-262
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• 2022

In domestic tunnels, it is mandatory to install CCTVs in tunnels longer than 200 m which are also recommended by installation of a CCTV-based automatic accident detection system. In general, the CCTVs in the tunnel are installed at a low height as well as near by the moving vehicles due to the spatial limitation of tunnel structure, so a severe perspective effect takes place in the distance of installed CCTV and moving vehicles. Because of this effect, conventional CCTV-based accident detection systems in tunnel are known in general to be very hard to achieve the performance in detection of unexpected accidents such as stop or reversely moving vehicles, person on the road and fires, especially far from 100 m. Therefore, in this study, the region of interest is set up and a new concept of inverse perspective transformation technique is introduced. Since moving vehicles in the transformed image is enlarged proportionally to the distance from CCTV, it is possible to achieve consistency in object detection and identification of actual speed of moving vehicles in distance. To show this aspect, two datasets in the same conditions are composed with the original and the transformed images of CCTV in tunnel, respectively. A comparison of variation of appearance speed and size of moving vehicles in distance are made. Then, the performances of the object detection in distance are compared with respect to the both trained deep-learning models. As a result, the model case with the transformed images are able to achieve consistent performance in object and accident detections in distance even by 200 m.