• Journal of the Korean Association of Geographic Information Studies
• /
• v.22 no.3
• /
• pp.133-145
• /
• 2019

Building and researching high definition maps that support autonomous vehicles, one of Korea's key challenges for the future, are being actively propelled in both private and government sectors with the goal of fast commercialization. Under this perspective, update methods that secure up-to-date information are emerging as key tasks. To provide a plan for establishing efficient renewal systems for high definition maps, we analyzed the present condition of road types, causes of road changes and its annual change rates, and examined where and how such road change information is managed. Furthermore, the method of collection and detection of road change information and the renewal system of high definition maps are defined based on the current study. At the end of the paper, a step-by-step renewal system is proposed through the examination of renewal cycles, contents, and region of high definition maps.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2022.06a
• /
• pp.269-270
• /
• 2022

자율주행 자동차의 개발을 위해서는 다양한 기능 평가, 성능 평가, 안전성 평가 등이 필수적이다. 이러한 평가는 컴퓨터 시뮬레이션과 실제 주행을 통해 이뤄질 수 있으며, 현실의 도로 상황을 고려한 단위시험환경들을 조합 구성한 통합시험환경에서 수행하는 것이 일반적이다. 여기서 단위시험환경은 도로망 구성, 장애물, 표지판 등의 정보를 포함하는 정밀도로지도를 기반으로 주행차량수, 보행자, 기상환경, 동적 이벤트 요소 등을 고려하여 구성할 수 있다. 본 논문에서는 이러한 단위시험환경을 구성하기 위한 정밀도로지도 처리 방법을 소개한다. 구체적으로는 정밀도로지도 처리를 포함하는 데이터 파이프라인을 설계하고, 정밀도로지도 객체분석을 통해 시험환경의 특성 및 상호 유사성을 파악한다. 국토지리정보원에서 배포한 정밀도로지도를 사용하여 객체를 추출하고 분석하는 실험을 수행했으며 전반적인 동작 상태를 확인했다. 개발한 소프트웨어는 향후 자율주행 학습을 위한 단위 및 통합 시험환경 구축 및 법규 및 규제 대응 서비스 시나리오의 구성에 활용할 예정이다.

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

• Journal of the Korean Association of Geographic Information Studies
• /
• v.23 no.3
• /
• pp.132-145
• /
• 2020

By coming of the 4th industrial revolution era, HD map have became a key infrastructure for determining precise location of autonomous driving in areas of futuristic cars, logistics and robots. Autonomous vehicles have became more dependent on HD map to determine the exact location of objects detected by various sensors such as LiDAR, GNSS, Radar, and stereo cameras as well as self-location decisions. By actualizing autonomous driving and C-ITS technologies, the demand for precise information on HD map have increased. And also the demand for the creation of new information based on the convergence of various changes and real-time information have increased. In this study, domestic and international HD map standards and related environments have analyzed. Based on this, usability has researched which comparison with standard HD map established by various institutions. Additionally, usability of standard HD map have studied for applying actual autonomous vehicles by reworking HD map. By the result of study, standard HD map have well established to use by various institutions. If further research about layer classification and definition by institutions will carried out based on this study, it has expected that and efficient establishment and renewal of HD map will take place.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.21 no.1
• /
• pp.273-286
• /
• 2022

An HD map is essential in the automated driving of level 4 and above to generate the vehicle's global path since it contains road information and each road's lane information. Therefore, all the road elements in the HD map must be correctly defined to construct the correct road network necessary to generate the global path. But unfortunately, it is not difficult to find various errors even in the most recent HD maps. Hence, a preprocessing algorithm has been developed to detect and correct errors in the HD map. This error detection and correction result in constructing the correct road network for use in global path planning. Furthermore, the algorithm was tested on real roads' HD maps, demonstrating its validity.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.22 no.3
• /
• pp.120-132
• /
• 2019

As a key infrastructure for positioning autonomous vehicles, HD maps are making efforts to equip autonomous vehicles and connect them with services worldwide. Global companies like Here and TomTom have contracted an agreement with three German automobile companies(BMW, Audi, Daimler) by establishing systems including from the production of HD maps to loading autonomous vehicles. Japan has organized a DMP(Dynamic Map Platform) by collaborating public and private section and performing establishment of HD map on private section-oriented. Korean companies related with autonomous vehicles are also cooperating with various companies such as vehicles, sensors and maps. But public and private sections are establishing HD maps respectively. Accordingly, Ministry of Land, Infrastructure and Transport implemented and signed memorandum for private and public cooperation in April 2019, Joint establishment council of HD map has launched in August 2019. This study performed domestic and foreign trend analysis about HD map and interviewed to related companies. And analyzed solutions for interactive cooperation of private and public section in HD map industry, purposed step-by-step strategy for operation and operation plan for joint establishment council of HD map.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.38 no.4
• /
• pp.375-382
• /
• 2020

As the 4th Industrial Revolution era in worldwide, interest in autonomous vehicles is increasing. but due to recent safety issues such as pedestrian accidents and car accidents, as a technical model for this, the demand for 3D HD maps (High Definition maps) is increasing in including lanes, road markings, road information, traffic lights and traffic signs etc. However, since some complementary points have been continuously raised according to demand, It is necessary to collect the opinions of institutions and companies utilizing HD maps and to improve HD maps. This study was conducted by utilizing the results of the contest for usability verification of HD Maps hosted by the National Geographic Information Institute and organized by the Spatial Information Industry Promotion Institute. For this study, we researched HD maps' layers and codes for HD maps object usability to improve HD maps, constructed HD maps object usability items accordingly, and contested usability verification of HD maps according to the items The contestants conducted verification and analyzed the results. As a result, the most frequently used code for each layer was the flat intersection, and the code showing the highest usage rate was a safety sign. In addition, the use rate of the sub-section and height obstacles was 16.67% and 8.88%, respectively, showing a low ratio. In order to utilize HD maps in the future, this study is expected to require research to continuously collect opinions from customers and improve data objects and data models that are actually needed by customers.

• Korean Journal of Remote Sensing
• /
• v.37 no.5_1
• /
• pp.1163-1175
• /
• 2021

In autonomous driving, road markings are an essential element for object tracking, path planning and they are able to provide important information for localization. This paper presents an approach to update and measure road surface markers with HD maps as well as matching using inverse perspective mapping. The IPM removes perspective effects from the vehicle's front camera image and remaps them to the 2D domain to create a bird-view region to fit with HD map regions. In addition, letters and arrows such as stop lines, crosswalks, dotted lines, and straight lines are recognized and compared to objects on the HD map to determine whether they are updated. The localization of a newly installed object can be obtained by referring to the measurement value of the surrounding object on the HD map. Therefore, we are able to obtain high accuracy update results with very low computational costs and low-cost cameras and GNSS/INS sensors alone.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.22 no.3
• /
• pp.146-154
• /
• 2019

Recently, a system has been developed and applied to establish and utilize HD maps through R&D. The biggest problem, however, is the lack of a proper HD map update system, which requires the development and adoption of such a system as soon as possible. In addition, in the case of updating HD maps for automated driving, integrity and accuracy of maps are required for safe driving, so an test of these technologies and data quality is required. In April 2018, the Ministry of Land, Infrastructure and Transport implemented a project to 'Develop Technology to Demonstrate and Share the Instant Road Change Detection and Update Technology for automated driving. This paper analyzed the technology for updating map based on the investigation and analysis of relevant technology trends for the development of integrated demonstration and sharing technology of road change rapid detection and updating map technology, and put forward the criteria for road change rapid detection, integrated quality verification of update technology. It is expected that the results of this study will contribute to quality assurance of HD maps that support safety driving for automated vehicles.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.39 no.3
• /
• pp.133-139
• /
• 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.