• Journal of The Korean Society of Agricultural Engineers
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• v.46 no.5
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• pp.117-127
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• 2004

A risk analysis on the cutting slope of roads near Cheongju area was carried out with the data from geological map, field investigation, and laboratory test and with the Geographic Information System. A risk analysis method on the cutting slope of road using the Geographic Information System was developed with the data from geological map, field investigation and laboratory tests. In the GIS, road factors which are safety factor, class of road, slake index, slope-protection works, and height of slope in the cutting slopes are classified into some ranks, and their weighting factors were taken into account. This method can be applied effectively to a road management.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.12
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• pp.1046-1052
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• 2016

For the safe driving of autonomous vehicles, accurate position estimation is required. Generally, position error must be less than 1m because of lane keeping. However, GPS positioning error is more than 1m. Therefore, we must correct this error and a map matching algorithm is generally used. Especially, road marking intensity map have been used in many studies. In previous work, 3D LIDAR with many vertical layers was used to generate a local intensity map. Because it can be obtained sufficient longitudinal information for map matching. However, it is expensive and sufficient road marking information cannot be obtained in rush hour situations. In this paper, we propose a localization algorithm using an accumulated intensity local map. An accumulated intensity local map can be generated with sufficient longitudinal information using 3D LIDAR with a few vertical layers. Using this algorithm, we can also obtain sufficient intensity information in rush hour situations. Thus, it is possible to increase the reliability of the map matching and get accurate position estimation result. In the experimental result, the lateral RMS position error is about 0.12m and the longitudinal RMS error is about 0.19m.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.2
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• pp.165-173
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• 2008

This study aims at generating automatically three dimensional geometric models of roads using LIDAR data and a digital map. The main processes in the proposed method are (1) generating a polygon encompassing a road region using a road layer from the digital map, (2) extracting LIDAR points within the road region using the polygon, (3) organizing the points into surface patches and grouping the patches into surface clusters, (4) searching the road surface clusters and generating the surface model from the points linked to the clusters, (5) refining the boundary using a digital map. By applying the proposed method to real data, we successfully generated the linear and surface information of the roads.

• Spatial Information Research
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• v.15 no.2
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• pp.95-109
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• 2007

Recently people have been offered location based services on road networks. The navigation system, one of applications, serves to find the nearest gas station or guide divers to the shortest path based 2D map. However 3D map is more important media than 2D map to make sense friendly for the real. Although 3D map's data size is huge, portable devices' storage space is small. In this paper, we define continuous perspective queries to support 3D map to mobile user on road networks and propose this queries processing method.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.2
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• pp.37-46
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• 2016

The difference between definition time of GPS (Global Positioning System) position data and actual display time of car positions on a map could reduce the accuracy of car positions displayed in PND (Portable Navigation Device)-type CNS (Car Navigation System). Due to the time difference, the position of the car displayed on the map is not its current position, so an improved method to fix these problems is required. It is expected that a method that uses predicted future positionsto compensate for the delay caused by processing and display of the received GPS signals could mitigate these problems. Therefore, in this study an analysis was conducted to correct late processing problems of map positions by mapmatching using a Kalman filter with only GPS position data and a RRF (Road Reduction Filter) technique in a light-weight CNS. The effects on routing services are examined by analyzing differences that are decomposed into along and across the road elements relative to the direction of advancing car. The results indicate that it is possible to improve the positional accuracy in the along-the-road direction of a light-weight CNS device that uses only GPS position data, by applying a Kalman filter and RRF.

• IE interfaces
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• v.25 no.4
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• pp.393-404
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• 2012

Increasing safety requirements of automobile are asking companies to find out solutions, based on the ISO 26262 which is a functional safety standard. ISO 26262 is an adaptation of the IEC 61508 for automotive electric/electronic systems. ISO 26262 provides a V model for ECU (Electronic Control Unit) development process to secure safety against vehicle. It well describes the requirements, necessary works and their resulting products for each development phase. However, it is difficult to apply to product development for achieving functional safety in the electric/electronic systems of an automobile because it lacks explanation on the working steps to follow and the methodologies and tools to be used in each step. In this paper, we introduce the outline of the ISO 26262 product development process and present a DFSS (Design For Six Sigma) road-map based on the ISO 26262 product development process as a way to operate efficiently the ISO 26262 product development process. The DFSS road-map consists of five phases: Define, Measure, Analyze, Design, and Verify. The detailed activities, tools, inputs, and work products are given for each phase.

• Journal of Korea Port Economic Association
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• v.20 no.2
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• pp.187-216
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• 2004

Northeast Asia logistics hub strategy was undertaken by Korean Government to gain a national competitive advantage in Northeast Asia. Current Government has Northeast Asian Economic Hub Strategy including construction of SOC in Northeast Asia for promoting peace, promotion of formation of Northeast Asia Community, logistics hub, Financial hub and national innovation for R&D Cluster. To realize Northeast Asian logistics hub, the Northeast Asia logistics hub road map has undertaken as follows: expansion of logistics infra in Incheon Airport, Busan Port and Gwangyang Port, systematic improvements such as adjustment of investment distribution, special logistics companies, transparent customs in logistics transactions, logistics manpower, improvement of system supporting global logistics and attraction of international logistics companies to the logistics center, construction of seamless and paperless logistics information network, Northeast Asia railway infra. The purpose of this paper is to study investment priority and improvements in the Northeast Asia Logistics Hub Road Map and to contribute to gain the national competitive advantage as logistics hub in Northeast Asia

• Journal of Korean Society for Geospatial Information Science
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• v.21 no.3
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• pp.47-54
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• 2013

Real estate development promotes the efficient management of the land and has immense impact on national economy. So, it is necessary to establish a comprehensive policy by accumulating related information. Real estate development map must have the information about a parcel and adjacent parcel to make it possible to analysis in spatial domain, because error will be manifested in analysis using only real estate attribute information. This can be allocate the attribute of public management information about real estate on cadastral information and spatial information for social infrastructure and buildings. Especially, it must maintain the latest information of changes in the shape and the attributes of the buildings. This study suggested a method for developing a real estate development map based on road name address map and a method to maintain the latest information through the connection with related systems.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.10
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• pp.803-810
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• 2016

This paper presents a study of localization methods based on particle filter using 2D laser sensor measurements and road feature map information, for autonomous vehicles. In order to navigate in an urban environment, an autonomous vehicle should be able to estimate the location of the ego-vehicle with reasonable accuracy. In this study, road features such as curbs and road markings are detected to construct a grid-based feature map using 2D laser range finder measurements. Then, we describe a particle filter-based method for accurate positional estimation of the autonomous vehicle in real-time. Finally, the performance of the proposed method is verified through real road driving experiments, in comparison with accurate DGPS data as a reference.

• Journal of IKEEE
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• v.25 no.4
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• pp.756-761
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• 2021

Dynamic route guidance (DRG) finds the fastest path from a source to a destination location considering the real-time congestion information. In Korea, the traffic state information is available by the public transportation data (PTD) which is indexed on top of the node-link map (NLM). While the NLM is the authoritative low-detailed road network for major roads only, the OpenStreetMap road network (ORN) supports not only a high-detailed road network but also a few open-source routing engines, such as OSRM and Valhalla. In this paper, we propose a DRG framework based on road network matching between the NLM and ORN. This framework regularly retrieves the NLM-indexed PTD to construct a historical speed profile which is then mapped to ORN. Next, we extend the Valhalla routing engine to support dynamic routing based on the historical speed profile. The numerical results at the Yeoui-do island with collected 11-month PTD show that our DRG framework reduces the travel time up to 15.24 % and improves the estimation accuracy of travel time more than 5 times.