• Journal of the Korea Society of Computer and Information
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• v.24 no.9
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• pp.83-95
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• 2019

Recently, a variety of IoT data is collected by attaching geosensors to many vehicles that are on the road. IoT data basically has time and space information and is composed of various data such as temperature, humidity, fine dust, Co2, etc. Although a certain sensor data can be retrieved using time, latitude and longitude, which are keys to the IoT data, advanced search engines for IoT data to handle high-level user queries are still limited. There is also a problem with searching large amounts of IoT data without generating indexes, which wastes a great deal of time through sequential scans. In this paper, we propose a unified spatial index model that handles both grid and trajectory queries using a cell-based space-filling curve method. also it presents a visualization method that helps user grasp intuitively. The Trajectory query is to aggregate the traffic of the trajectory cells passed by taxi on the road searched by the user. The grid query is to find the cells on the road searched by the user and to aggregate the fine dust. Based on the generated spatial index, the user interface quickly summarizes the trajectory and grid queries for specific road and all roads, and proposes a Web-based prototype system that can be analyzed intuitively through road and heat map visualization.

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

• Journal of Korean Society of Forest Science
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• v.105 no.1
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• pp.115-121
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• 2016

This study was conducted to provide the basic policy information for establishing efficient forest-road networks. Synthetic forest-road networks that consist of main and spur roads and forest-road networks with only main road (hereafter called "main-road network") were planned for the five forest-road experimental districts of Korea Forest Service in this study. Road density of the synthetic forest-road networks was calculated and compared with the road density of the main-road networks. The results showed that the optimum road density of the synthetic forest-road networks was 10.1~15.9 m/ha, and the road density of the main-road networks was 8.4~12.4 m/ha. The construction cost of the synthetic forest-road networks was estimated about 1~8% lower than the main-road networks, while the road density was 20~30% greater than the main-road networks. As timber volume and hauling cost increased, the optimum road density of the synthetic forest-road networks increased, within which the road density of highstandard main road rapidly increased. On the other hand, the spur road density increased with slope gradient.

• Proceedings of the IEEK Conference
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• 2000.06d
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• pp.163-166
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• 2000

Real-time traffic detection scheme based on Computer Vision is capable of efficient traffic control using automatically computed traffic information and obstacle detection in moving automobiles. Traffic information is extracted by segmenting vehicle region from road images, in traffic detection system. In this paper, we propose the advanced segmentation of vehicle from road images using multiple local region information. Because multiple local region overlapped in the same lane is processed sequentially from small, the traffic detection error can be corrected.

• Journal of the Korea Society of Computer and Information
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• v.23 no.1
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• pp.75-84
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• 2018

In this study, the researchers attempted to automate the process of painting the characters on the road surface, which is currently done by manual labor, by using the information and communication technology. Here are the descriptions of how we put in our efforts to achieve such a goal. First, we familiarized ourselves with the current regulations about painting letters or characters on the road, with reference to Road Mark Installation Management Manual of the National Police Agency. Regarding the graphemes, we adopted a new one using connection components, in Gothic print characters which was within the range of acceptance according to the aforementioned manual. We also made it possible for the automated program to recognize the graphemes by means of the feature dots of the isolated dots, end dots, 2-line gathering dots, and gathering dots of 3 lines or more. Regarding the database, we built graphemes database for plotting information, classified the characters by means of the arrangement information of the graphemes and the layers that the graphemes form within the characters, and last but not least, made the character shape information database for character plotting by using such data. We measured the layers and the arrangement information of the graphemes consisting the characters by using the information of: 1) the information of the position of the center of gravity, and 2) the information of the graphemes that was acquired through vertical exploration from the center of gravity in each grapheme. We identified and compared the group to which each character of the database belonged, and recognized the characters through the use of the information gathered using this method. We analyzed the input characters using the aforementioned analysis method and database, and then converted into plotting information. It was shown that the plotting was performed after the correction.

• International Journal of Highway Engineering
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• v.19 no.6
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• pp.155-164
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• 2017

PURPOSES : Owing to the growth of income and socio-economic levels, demands from road users have diversified. Accordingly, new road policies are being actively sought. The metropolitan city government of Busan has been focused on constructing and expanding roads to accommodate the increasing traffic demand. Given the increase in functional characteristics, we need to re-evaluate the hierarchy and function of roads, and specifically remodel the road planning and operations that fit into their functions. METHODS : First, this study focuses on introducing the minimum condition required to redefine the hierarchy of the roads. Second, the authors propose a new model that identifies the impact level of road hierarchy adopting discriminated analysis technique. RESULTS : Authors suggest that we redefine the hierarchy of roads in the central business distinct in Busan, and specifically the arterial roads in Busan, namely, Joonang-daero and Gaya-ro. These roads need to be reequipped with cross walks, a lower speed limit, and exclusive bus lanes to improve their accessibility. CONCLUSIONS : The authors found that the sub-arterial and collector roads have been subjected to excessive loads, owing to inappropriate functions being assigned to the main arterial road. Moreover, given that through traffic is concentrated on the sub-arterial and collector roads, over-speeding and other safety issues are consequently created.

• Journal of Industrial Convergence
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• v.22 no.10
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• pp.21-28
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• 2024

Personal Mobility devices pose a significant safety risk to users depending on road conditions. With the recent surge in usage, the number of accidents has also increased, highlighting the need for a preventative system. This study aims to design and develop a warning system to enhance the safety of drivers by detecting road obstacles. To achieve this, a dataset is constructed using images of road obstacles, and the YOLOv5 model is trained. The system is based on the Raspberry Pi 4B, which processes video frames captured by a camera in real-time and triggers an LED warning when an obstacle is detected. The Flask framework is used to monitor the obstacle detection status in real time. Additionally, a GPS sensor is utilized to collect the user's location and speed data, and an auditory warning is triggered via a buzzer if the set speed is exceeded. In the future, this system could be expanded to transmit detected road obstacles and GPS information to a server, providing users with real-time road safety information. The results of this study can serve as essential technology for developing such a system.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.2
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• pp.30-42
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• 2021

The amount of compensation and the number of cases owing to car damage from pot holes on highways across the country increased by about 4.2 times and 3.5 times, respectively, in 2019 compared to 2015. Due to the increase in damage caused by these road hazards, the Ministry of Land, Infrastructure and Transport is developing technologies and services that can collect road hazard information by using devices on commercial vehicles (DTGs, black boxes, ADASs). In preparation for the development of these technologies, this study conducted an integrated assessment of algorithms developed for interrupted-flow and uninterrupted-flow traffic under three scenarios in order to provide road hazard information to drivers and road managers. As a result, the overall accuracy of the integrated assessment was derived at 81.88%. Errors generated in this integrated assessment reflect only missing data in less than 1 minute, GPS coordinate location and algorithm related errors, taking into account the purpose and assumptions of the assessment. Among them, we derive an accuracy of 90.15%overall by calibrating GPS error data. The results of this study can be used as basic data for improving the accuracy of location-based information collected by commercial vehicles and for policy development.

• Journal of the Korean Association of Geographic Information Studies
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• v.19 no.3
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• pp.89-101
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• 2016

This study examined spatial disposition of wildlife highway mortality using road-kill GIS database and Naver panoramic 360 degree views to find out which habitat and road variables most influenced road-kill numbers for each mammal species and how the landscape and road elements are connected on highway. Road-kills on Yeongdong(YD) and Jungbu highway(JB) generally tended to be higher in natural barren, grassland and cropland due to its value of preferred habitats of nocturnal and multihabitat species like water deer(Hydropotes inermis argyropus), raccoon(Nyctereutes procyonoides) and hare(Lepus coreanus). Land cover in YD showed no difference between species (p=0.165) while JB did by species (p=0.001). This may be explained by disparate landscape between mountain and urban or the fact that YD in long term operation might have enabled consistent crossing pattern compared to JB experiencing continuous extension works which may in turn have deviated the road crossing. Although road-kill prevention effect of local topography alone was appreciable, compared to less significant or ineffective fence and guardrail, gentle slope declining in a direction to the road turned out to offset the preventive effect of juxtaposed fence. Furthermore, green patches on road near intersection were deemed a visual stepping stone facilitating wildlife attempted crossing and local roads juxtaposed with a highway were especially left defenceless to road-kill without road barriers.

• 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.