• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.6
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• pp.363-369
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• 2021

High-definition road maps are used as the basic infrastructure for autonomous vehicles, so the latest road information must be quickly reflected. However, the current drawing and structural editing process of high-definition road maps are manually performed. In addition, it takes the longest time to generate road lanes, which are the main construction targets. In this study, the point cloud of the road lane markings, in which color types(white, blue, and yellow) were predicted through the PointNet model pre-trained in previous studies, were used as input data. Based on the point cloud, this study proposed a methodology for automatically drawing and structural editing of the layer of road lane markings. To verify the usability of the 3D vector data constructed through the proposed methodology, the accuracy was analyzed according to the quality inspection criteria of high-definition road maps. In the positional accuracy test of the vector data, the RMSE (Root Mean Square Error) for horizontal and vertical errors were within 0.1m to verify suitability. In the structural editing accuracy test of the vector data, the structural editing accuracy of the road lane markings type and kind were 88.235%, respectively, and the usability was verified. Therefore, it was found that the methodology proposed in this study can efficiently construct vector data of road lanes for high-definition road maps.

• Journal of the Korea Convergence Society
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• v.10 no.4
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• pp.33-38
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• 2019

Recently, to support location-based services, there have been many researches which consider the spatial network. For this, there are many experimental data for data processing on the road network. However, the data to process the trajectory of moving objects are not suitable. Therefore, we propose index structure to process the trajectory data on the road network and the trajectory data generation algorithm. In addition, to prove efficiency of our index structure and algorithm, we show that edge-based trajectory data are generated through the proposed algorithm using the map data of San Francisco Bay.

• Korean Journal of Remote Sensing
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• v.24 no.2
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• pp.153-164
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• 2008

According to the economic growth, many highways are constructed for increasing need of better life style. Especially roads and roadside facilities are used for accident prevention and offering mobility for drivers. For these purpose, roads and roadside facilities should be well maintained and managed. Now, many roads and roadside facilities are constructed in many areas. Because of traditional surveying method requires much time and surveying efforts, we designed and developed mobile mapping system for highway maintenance and management purpose using multi sensors. We tested our mobile mapping system and data management process. Using developed database, road managers can easily check the information of facility conditions, positions, and attributes. We are expecting low cost and efficient road maintenance process by using our system.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.11a
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• pp.907-908
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• 2009

지리정보 시스템에서의 지도 데이터 생성은 많은 양의 실세계의 데이터를 기반으로 하기 때문에 그 생성 및 변경에 있어서 많은 비용과 시간을 필요로 한다. 본 논문에서는 이러한 문제를 극복하기 위하여 경량의 차량 GPS 트레이스 데이터를 이용하여 높은 정확도의 도로 지도를 생성하는 방법을 제안하였다. 제안 방법론은 Intelligent Transportation System(ITS)의 중요 요소인 지리정보 생성에 있어 효율적이고 경제적인 도로 지도 생성을 가능하게 한다.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.5
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• pp.109-120
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• 2017

It is important to estimate objectively in the driving test. Especially, the driving test is examined by totally driving ability, rule observation and situational judgement. For this, a grading automation system for driving test was presented by using GPS, sensor data and equipment operation informations. This system is composed of vehicle mounted module, automatic grading terminal, data controller, data storage and processing server. The vehicle mounted module gathters sensor data in the car. The terminal performs automatic grading using the received sensor data according the driving test criterion. To overcome the misposition of vehicle in the map due to GPS error, we proposed the automatic grading system by map matching method, path deviation and return algorithm. In the experimental results, it was possible to grade automatically, display the right position of the car, and return to the right path under 10 seconds when the vehicle was out of the shadow region of the GPS. This system can be also applied to the driving education.

• Spatial Information Research
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• v.23 no.5
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• pp.9-19
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• 2015

The popularity of smart devices and Location Based Services (LBSes) is increasing in part due to users demand for personalized information associated with their location. These services provide intuitive and realistic information by adopting Augmented Reality (AR) technology. This technology utilizes various sensors embedded in the mobile devices. However, these services have inherent problems due to the devices small screen size and the complexity of the real world environment; overlapping content on a small screen and placing icons without considering the user's possible movement. In order to solve these problems, this paper proposes a Mobile Augmented Reality Model with the application of Street Data. The model consists of two layers: "Real Space" and "Information Space". In the model, a user creates a query by scanning the nearby street with a camera in real space and searches accessible content along the street through the use of the information space. Furthermore, the results are placed on both sides of the street to solve the issue of Overlapping. Also, the proposed model is implemented for region "Aenigol", and the efficiency and usefulness of the model are verified.

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.4
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• pp.181-199
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• 2022

This study presented a methodology for evaluating the performance of the lane departure warning system was derived by calculating the relationship between the behavior information of the car and the location of the high-precision map using a high-precision map. The evaluation criteria of the mood and lane departure warning system for the installation of road markings in Korea were analyzed, a high-precision map was constructed to meet the evaluation criteria, and an evaluation system was constructed to verify the proposed methodology. Evaluation of lane departure warning systems using high-precision maps can be quantified and applied to various road environments through accurate location-based comparative analysis and reduced manual post-processing work time to confirm evaluation results.

• Proceedings of the Korea Information Processing Society Conference
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• 2007.05a
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• pp.69-70
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• 2007

최근, 궤적 정보를 이용한 많은 연구들이 진행되고 있다. 그러나 이동 객체의 실제 궤적 데이터를 획득하기는 어렵기 때문에 대부분의 연구들은 궤적 생성기에 의해 생성된 데이터를 이용하고 있다. 그러나 기존의 궤적 생성기들은 대부분 유클리디언 공간을 바탕으로 궤적을 생성하기 때문에 도로 네트워크 공간에서는 적용될 수 없다. 본 논문에서는 도로 네트워크 공간을 바탕으로 한 이동 객체의 궤적 생성 방안을 제안한다. 실제 이동 객체의 움직임과 비슷한 궤적을 생성하기 위하여 이동 객체는 출발지에서 목적지까지의 최단 경로에 근접하여 움직인다는 현실세계의 특징을 반영한다. 제안하는 기법을 이용하여 생성된 궤적 데이터는 현실 세계를 반영하면서 사용자가 원하는 궤적 데이터를 제공할 수 있기 때문에 다양한 연구에 사용될 수 있다.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2009.04a
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• pp.273-274
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• 2009

도로네트워크 데이터는 교통 정보, 경로 안내서비스 등 실시간 정보제공을 위해 차량 항법용 데이터에서 가장 핵심적인 영역에 해당하며 효율적인 관리와 유지가 필수적이다. 기존 파일 기반 시스템인 미디어 포맷(KIWI, GDF 등)에서는 콤팩트한 데이터 구성으로 읽기 위주의 빠른 매체 접근 등에 좋은 이점이 있지만, 최근 모바일 시스템 환경에 DBMS를 활용한 위치 기반 서비스(LBS)에 대한 관심이 증가 하고 있다. 이에 본 연구에서는 임베디드 DBMS를 이용하여 네트워크의 계층성을 지원하는 데이터 모델과 이를 활용한 탐색 알고리듬을 설계하고 프로토타입 시스템을 구현하였다. 특히 대규모 도로망의 원거리 탐색을 대상으로 메모리 구성과 탐색 시간 측면에서 일반 영역 탐색방법과 계층 탐색방법의 검색 결과를 비교하여 계층 탐색 방법의 효율성을 검증하였다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2018.07a
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• pp.501-502
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• 2018

본 논문은 건설CALS시스템에 20년간 축적된 데이터를 활용하기 위해서 2018년부터 2020년까지 개발 예정인 과적단속 최적 위치 시기 예측 서비스, 비탈면 붕괴 위험도예측서비스, 도로점용(연결) 허가 가능구간 예측 서비스, 보상비 예측 서비스 등 4종의 건설CALS 빅데이터 서비스 기술 개발을 위한 현황분석을 기술하였다. 개발된 서비스는 2020년에 국토교통부 소속기관인 지방국토관리청과 국토관리사무소의 업무담당자 및 국민에게 시범 적용하여 빅데이터 서비스의 효과를 검증하고, 단계적으로 국토교통부 도로관리 업무에 적용할 계획이다.