• Title/Summary/Keyword: research road map

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Driving Strategy of Standardization Road-Map in Construction (건설표준화 로드맵 - 외국신기술 제도 중심으로)

  • Kim Jong-Gurl;Park Wook-Jae
    • Proceedings of the Safety Management and Science Conference
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    • 2006.04a
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    • pp.429-436
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    • 2006
  • Standardization strategy is considered as an important approach for the organization growth and competitiveness. Major contents of standardization are the selection of standardization area and management of standardization timing under limited resources. The developments of standardization road map and its driving strategy in construction area are important policy subjects in view of investment scale and national economy. In this paper, we aim to survey on the standardization theory and its application in construction field and suggest research direction for driving strategy of standardization road map development.

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Technology Road Map for Marine Safety and Pollution Control (해양안전기술로드맵 작성에 관한 연구)

  • Lee, Jong-Kap
    • Proceedings of KOSOMES biannual meeting
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    • 2004.05b
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    • pp.57-60
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    • 2004
  • In this paper, the technology road map, as a useful methodology for the planning of R&Ds in government and/or industries, is introduced Also the road map for the maritime safety technology, which is being developed in KRISO, is discussed as a framework for the planning of national R&D projects in maritime safety.

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Driving Strategy of Standardization Road-Map in Construction (표준화 로드맵 추진전략 - 건설분야 중심으로 -)

  • Kim Jong-Gurl;Park Yong-Soo
    • Proceedings of the Korean Society for Quality Management Conference
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    • 2004.04a
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    • pp.284-288
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    • 2004
  • Standardization strategy is considered as an important approach for the organization growth and competitiveness. Major contents of standardization are the selection of standardization area and management of standardization timing under limited resources. The developments of standardization road map and its driving strategy in construction area are important policy subjects in view of investment scale and national economy. In this paper, we aim to survey on the standardization theory and its application in construction field and suggest research direction for driving strategy of standardization road map development.

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A Study on Data Model Conversion Method for the Application of Autonomous Driving of Various Kinds of HD Map (다양한 정밀도로지도의 자율주행 적용을 위한 데이터 모델 변환 방안 연구)

  • Lee, Min-Hee;Jang, In-Sung;Kim, Min-Soo
    • Journal of Cadastre & Land InformatiX
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    • v.51 no.1
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    • pp.39-51
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    • 2021
  • Recently, there has been much interest in practical use of standardized HD map that can effectively define roads, lanes, junctions, road signs, and road facilities in autonomous driving. Various kinds of de jure or de facto standards such as ISO 22726-1, ISO 14296, HERE HD Live map, NDS open lane model, OpenDRIVE, and NGII HD map are currently being used. However, there are lots of differences in data modeling among these standards, it makes difficult to use them together in autonomous driving. Therefore, we propose a data model conversion method to enable an efficient use of various kinds of HD map standards in autonomous driving in this study. Specifically, we propose a conversion method between the NGII HD map model, which is easily accessible in the country, and the OpenDRIVE model, which is commonly used in the autonomous driving industry. The proposed method consists of simple conversion of NGII HD map layers into OpenDRIVE objects, new OpenDRIVE objects creation corresponding to NGII HD map layers, and linear transformation of NGII HD map layers for OpenDRIVE objects creation. Finally, we converted some test data of NGII HD map into OpenDRIVE objects, and checked the conversion results through Carla simulator. We expect that the proposed method will greatly contribute to improving the use of NGII HD map in autonomous driving.

Parking Space Recognition for Autonomous Valet Parking Using Height and Salient-Line Probability Maps

  • Han, Seung-Jun;Choi, Jeongdan
    • ETRI Journal
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    • v.37 no.6
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    • pp.1220-1230
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    • 2015
  • An autonomous valet parking (AVP) system is designed to locate a vacant parking space and park the vehicle in which it resides on behalf of the driver, once the driver has left the vehicle. In addition, the AVP is able to direct the vehicle to a location desired by the driver when requested. In this paper, for an AVP system, we introduce technology to recognize a parking space using image sensors. The proposed technology is mainly divided into three parts. First, spatial analysis is carried out using a height map that is based on dense motion stereo. Second, modelling of road markings is conducted using a probability map with a new salient-line feature extractor. Finally, parking space recognition is based on a Bayesian classifier. The experimental results show an execution time of up to 10 ms and a recognition rate of over 99%. Also, the performance and properties of the proposed technology were evaluated with a variety of data. Our algorithms, which are part of the proposed technology, are expected to apply to various research areas regarding autonomous vehicles, such as map generation, road marking recognition, localization, and environment recognition.

Making a Hazard Map of Road Slope Using a GIS and Logistic Regression Model (GIS와 Logistic 회귀모형을 이용한 접도사면 재해위험도 작성)

  • Kang, In-Joon;Kang, Ho-Yun;Jang, Yong-Gu;Kwak, Young-Joo
    • Journal of Korean Society for Geospatial Information Science
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    • v.14 no.1 s.35
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    • pp.85-91
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    • 2006
  • Recently, slope failures are happen to natural disastrous when they occur in mountainous areas adjoining highways in Korea. The accidents associated with slope failures have increased due to rapid urbanization of mountainous areas. Therefore, Regular maintenance is essential for all slope and needs maintenance of road safety as well as road function. In this study, we take priority of making a database of risk factor of the failure of a slope before assesment and analysis. The purpose of this paper is to recommend a standard of Slope Management Information Sheet(SMIS) like as Hazard Map. The next research, we suggest to pre-estimated model of a road slope using Logistic Regression Model.

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Process and Results of Seoul Metropolitan Government's Environmental Health Policy Road Map (서울시 환경보건정책 로드맵 수립)

  • Lim, Ji-Ae;Kwon, Ho-Jang;Kim, Shinbum;Chou, Youngeun;Gu, Seulgi;Jeong, Hoi-Seong;Kim, Myung Han;Choi, Kyungho
    • Journal of Environmental Health Sciences
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    • v.40 no.5
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    • pp.425-434
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    • 2014
  • Objectives: The purpose of this study is to introduce the establishment process and results of the Seoul Metropolitan Government's road map on environmental health policy. Methods: The process consisted of expert group meetings, civic participation, research, and questionnaire survey for priority environmental health policy agenda items in Seoul. Results: The announced vision for the environmental health policy was "a healthy environment, safety in Seoul". This policy was established in order to define environment health policy initiatives for a period of five years with an aim to protect Seoul citizens' health from hazardous environmental factors. The resulting Seoul environmental health policy consisted of four areas and 16 key agenda items. The four areas were "Protection for children against hazardous materials", "Enhancement of health and safety of all", "Carcinogen-free and endocrine-disrupting chemical-free Seoul (reducing environmental exposure to hazardous materials), and "Establish the foundation of environmental health policy". Sixteen key agenda items include the enhancement of management of spaces for children, certification of environmental health status at schools, establishment of a unit responsible for the environmental health of children, strengthening environmental health management for susceptible populations (children, the aged, and the socioeconomically vulnerable), management of hazardous materials, physical hazardous factors (noise, radiation, etc.), indoor air quality, and the enhancement of monitoring, research, and regulation of environment health. Conclusion: The Seoul Metropolitan Government established an environmental health policy road map for a five-year period (2013-2017). To implement this environmental health policy, budget allocation, and detailed execution plans are required.

Research on Longitudinal Slope Estimation Using Digital Elevation Model (수치표고모델 정보를 활용한 도로 종단경사 산출 연구)

  • Han, Yohee;Jung, Yeonghun;Chun, Uibum;Kim, Youngchan;Park, Shin Hyoung
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.20 no.6
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    • pp.84-99
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    • 2021
  • As the micro-mobility market grows, the demand for route guidance, that includes uphill information as well, is increasing. Since the climbing angle depends on the electric motor uesed, it is necessary to establish an uphill road DB according to the threshold standard. Although road alignment information is a very important element in the basic information of the roads, there is no information currently on the longitudinal slope in the road digital map. The High Definition(HD) map which is being built as a preparation for the era of autonomous vehicles has the altitude value, unlike the existing standard node link system. However, the HD map is very insufficient because it has the altitude value only for some sections of the road network. This paper, hence, intends to propose a method to generate the road longitudinal slope using currently available data. We developed a method of computing the longitudinal slope by combining the digital elevation model and the standard link system. After creating an altitude at the road link point divided by 4m based on the Seoul road network, we calculated individual slope per unit distance of the road. After designating a representative slope for each road link, we have extracted the very steep road that cannot be climbed with personal mobility and the slippery roads that cannot be used during heavy snowfall. We additionally described errors in the altitude values due to surrounding terrain and the issues related to the slope calculation method. In the future, we expect that the road longitudinal slope information will be used as basic data that can be used for various convergence analyses.

Study on Map Building Performance Using OSM in Virtual Environment for Application to Self-Driving Vehicle (가상환경에서 OSM을 활용한 자율주행 실증 맵 성능 연구)

  • MinHyeok Baek;Jinu Pahk;JungSeok Shim;SeongJeong Park;YongSeob Lim;GyeungHo Choi
    • Journal of Auto-vehicle Safety Association
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    • v.15 no.2
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    • pp.42-48
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    • 2023
  • In recent years, automated vehicles have garnered attention in the multidisciplinary research field, promising increased safety on the road and new opportunities for passengers. High-Definition (HD) maps have been in development for many years as they offer roadmaps with inch-perfect accuracy and high environmental fidelity, containing precise information about pedestrian crossings, traffic lights/signs, barriers, and more. Demonstrating autonomous driving requires verification of driving on actual roads, but this can be challenging, time-consuming, and costly. To overcome these obstacles, creating HD maps of real roads in a simulation and conducting virtual driving has become an alternative solution. However, existing HD maps using high-precision data are expensive and time-consuming to build, which limits their verification in various environments and on different roads. Thus, it is challenging to demonstrate autonomous driving on anything other than extremely limited roads and environments. In this paper, we propose a new and simple method for implementing HD maps that are more accessible for autonomous driving demonstrations. Our HD map combines the CARLA simulator and OpenStreetMap (OSM) data, which are both open-source, allowing for the creation of HD maps containing high-accuracy road information globally with minimal dependence. Our results show that our easily accessible HD map has an accuracy of 98.28% for longitudinal length on straight roads and 98.42% on curved roads. Moreover, the accuracy for the lateral direction for the road width represented 100% compared to the manual method reflected with the exact road data. The proposed method can contribute to the advancement of autonomous driving and enable its demonstration in diverse environments and on various roads.

Automatic Construction of Deep Learning Training Data for High-Definition Road Maps Using Mobile Mapping System (정밀도로지도 제작을 위한 모바일매핑시스템 기반 딥러닝 학습데이터의 자동 구축)

  • Choi, In Ha;Kim, Eui Myoung
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.39 no.3
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    • pp.133-139
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    • 2021
  • Currently, the process of constructing a high-definition road map has a high proportion of manual labor, so there are limitations in construction time and cost. Research to automate map production with high-definition road maps using artificial intelligence is being actively conducted, but since the construction of training data for the map construction is also done manually, there is a need to automatically build training data. Therefore, in this study, after converting to images using point clouds acquired by a mobile mapping system, the road marking areas were extracted through image reclassification and overlap analysis using thresholds. Then, a methodology was proposed to automatically construct training data for deep learning data for the high-definition road map through the classification of the polygon types in the extracted regions. As a result of training 2,764 lane data constructed through the proposed methodology on a deep learning-based PointNet model, the training accuracy was 99.977%, and as a result of predicting the lanes of three color types using the trained model, the accuracy was 99.566%. Therefore, it was found that the methodology proposed in this study can efficiently produce training data for high-definition road maps, and it is believed that the map production process of road markings can also be automated.