• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2004.10a
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• pp.65-70
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• 2004

This study is to improve location Precision of forest road map which is base of forest road management. The forest road map is constructed using satellite imagery data and GPS route survey, and compared with existing FGIS digital forest road map. And we proposed application of LiDAR data for extracting forest roads.

• Journal of Digital Contents Society
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• v.19 no.8
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• pp.1617-1623
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• 2018

It is necessary to develop a next generation location referencing method with higher accuracy as advanced technologies such as autonomous vehicles require higher accuracy of location data. Thus, we proposed a framework for a lane-level location referencing method (L-LRM) based on high-precision digital road network map, and developed a tool which is capable of analyzing and evaluating the proposed method. Firstly, the necessity and definition of location referencing method was presented, followed by the proposal of an L-LRM framework with a fundamental structure of high-precision digital road network map for the method. Secondly, an architecture of the analysis and evaluation tool was described and then the Windows application program was developed using C/C++ programming language. Finally, we demonstrated the performance of the proposed framework and the application program using two different high precision digital maps with randomly generated road event data.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.6
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• pp.208-218
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• 2017

This study aims to develop the Vehicle Local Dynamic Map (V-LDM) and demonstrate its performance for providing dynamic map data efficiently to the vehicle control module. Firstly, the concept of the in-vehicle LDM has been established and then the system has been carefully designed according to the international standards. The high-precision digital map embedded in LDM has been designed to incorporate the lane-level information of road network, and the Dynamic Map protocol (DM protocol) which is a message protocol including the road data with dynamic traffic event data has been defined. The performance test of the proposed system has been conducted in the uninterrupted road section of Kyungbu expressway, showing that both of the data size and the elapsed time to finish the process are almost linearly proportional to the length of target road. Finally, it is recommended that the length of target road for DM protocol be less than 250m.

• 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.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.12
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• pp.19-24
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• 2003

• Journal of the Korean Society for Precision Engineering
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• v.31 no.3
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• pp.253-259
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• 2014

This study proposes a map-based control method to improve a vehicle's lateral stability, and the performance of the proposed method is compared with that of the conventional model-referenced control method. Model-referenced control uses the sliding mode method to determine the compensated yaw moment; in contrast, the proposed map-based control uses the compensated yaw moment map acquired by vehicle stability analysis. The vehicle stability region is calculated by a topological method based on the trajectory reversal method. The performances of model-referenced control and map-based control are compared under various road conditions and driving inputs. Model-referenced control uses a control input to satisfy the linear reference model, and it generates unnecessary tire lateral forces that may lead to worse performance than an uncontrolled vehicle with step steering input on a road with low friction coefficient. The simulation results show that map-based control provides better stability than model-referenced control.

• Journal of the Korean Society of Industry Convergence
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• v.20 no.2
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• pp.125-132
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• 2017

The slope of the road in the forest area has a characteristic of steep slope, so natural disasters such as slope collapse occur. The slope displacement observation technique according to landslide is being studied as a method to observe a wide area and a method to observe a small area. This is a study on high-precision digital map generation using ground LiDAR. It is possible to create a high - precision digital map by minimizing the US side using the 3D LiDAR in the steep slope area where the GPS and Total Station measurement are difficult in the maintenance of the danger slope area. It is difficult to objectively evaluate whether the contour lines generated by LiDAR are correct and it is considered necessary to construct a test bed for this purpose. Based on this study, if terrain changes such as landslides occur in the future, it will be useful for measuring slope displacement.

• International Journal of Control, Automation, and Systems
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• v.3 no.1
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• pp.15-31
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• 2005

Nowadays, the road safety is an important research field. One of the principal research topics in this field is the vehicle localization in the road network. This article presents an approach of multi sensor fusion able to locate a vehicle with a decimeter precision. The different informations used in this method come from the following sensors: a low cost GPS, a numeric camera, an odometer and a steer angle sensor. Taking into account a complete model of errors on GPS data (bias on position and nonwhite errors) as well as the data provided by an original approach coupling a vision algorithm with a precise numerical map allow us to get this precision.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.4
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• pp.88-94
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• 2004

Recently, vehicle simulators are widely used to evaluate driver's responses and driver assistance systems. It needs much effort to construct the virtual driving environment for a vehicle simulator. In this study, it is described how to make effectively the roads and the driving environment for a vehicle simulator. The GIS (Geographic Information System) is used to construct the roads and the environment effectively. Because the GIS is the integrated system of geographical data, it contains useful data to make virtual driving environment. First, the outline and centerline of roads is abstracted from the GIS. From the road outline, the road width is calculated. Using the centerline, the grid model of roads is constructed. The final graphic model of roads is constructed by mapping road image to the grid model according to the number of lanes and the kind of surface. Data of buildings from the GIS are abstracted. Each shape and height of buildings is determined according to kind of buildings, the final graphic model of buildings is constructed. Then, the graphic model of roadside tree is also constructed. Finally, the driving environment for driving simulator is constructed by converting the three graphic models with the graphic format of Direct-X and by joining the three graphic models.

• 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.