• Journal of the Korea institute for structural maintenance and inspection
• /
• v.26 no.5
• /
• pp.30-42
• /
• 2022

Due to the increase in construction of tunnels, the burdens of maintenance works for tunnel structures have been increasing in Korea. In addition, the increase of traffic volume and aging of materials also threatens the safety of tunnel facilities, therefore, maintenance costs are expected to increase significantly in the future. Accordingly, automated condition assessment technologies like image-based tunnel scanning system for inspection and diagnosis of tunnel facilities have been proposed. For image-based tunnel scanning system, it is key to create a planar image through stitching of multiple images captured by tunnel scanning system. In this study, performance of feature-based stitching algorithms suitable for stitching tunnel scanning images was evaluated. In order to find a suitable algorithm SIFT, ORB, and BRISK are compared. The performance of the proposed algorithm was determined by the number of feature extraction, calculation speed, accuracy of feature matching, and image stitching result. As for stitching performance, SIFT algorithm was the best in all parts of tunnel image. ORB and BRISK also showed satisfactory performance and short calculation time. SIFT can be used to generate precise planar images. ORB and BRISK also showed satisfactory stitching results, confirming the possibility of being used when real-time stitching is required.

• Journal of Internet Computing and Services
• /
• v.23 no.5
• /
• pp.47-58
• /
• 2022

In recent years, navigation aids, which plays as sea traffic lights, have been digitized, and are developing beyond simple sign purpose to provide various functions such as marine information collection, supervision, control, etc. For example, Busan Port which is located in South Korea is leading the application of the advanced technologies by installing cameras on buoys and recording video images to supervise maritime accidents. However, there are difficulties to perform their major functions since the advanced technologies require long-term battery operation and also management and maintenance of them are hampered by marine characteristics. This study proposes a system that can automatically notify maritime objects passing around buoys by analyzing image information. In the existing sensor-based accident prevention systems, the alarms are generated by a collision detection sensor. The system can identify the cause of the accident whilst even though it is difficult not possible to fundamentally prevent the accidents. Therefore, in order to overcome these limitations, the proposed a maritime object detection system is based on marine characteristics. The experiments demonstrate that the proposed system shows about 5 times faster processing speed than other existing algorithms.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.21 no.3
• /
• pp.18-29
• /
• 2022

Recently, cooperative intelligent transport systems (C-ITS) testbeds have been deployed in great numbers, and advanced autonomous driving research using V2X communication technology has been conducted actively worldwide. In particular, the broadcasting services in their beginning days, giving warning messages, basic safety messages, traffic information, etc., gradually developed into advanced network services, such as platooning, remote driving, and sensor sharing, that need to perform real-time. In addition, technologies improving these advanced network services' throughput and latency are being developed on many fronts to support these services. Notably, this research analyzed the network latency requirements of the advanced network services to develop a remote driving service for the droid type low-speed robot based on the 3GPP C-V2X communication technology. Subsequently, this remote driving service's performance was evaluated using system modeling (that included the operator behavior) and simulation. This evaluation showed that a respective core and access network latency of less than 30 ms was required to meet more than 90 % of the remote driving service's performance requirements under the given test conditions.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2022.10a
• /
• pp.562-565
• /
• 2022

Recently, the increasing number of overloaded vehicles on the road poses a risk to traffic safety, such as falling objects, road damage, and chain collisions due to the abnormal weight distribution, and can cause great damage once an accident occurs. However, this irregular weight distribution is not possible to be recognized with the current weight measurement system for vehicles on roads. To address this limitation, we propose to build an object detection-based AI model to identify overloaded vehicles that cause such social problems. In addition, we present a simple yet effective method to construct an object detection model for the large-scale vehicle images. In particular, we utilize the large-scale of vehicle image sets provided by open AI-Hub, which include the overloaded vehicles from the CCTV, black box, and hand-held camera point of view. We inspected the specific features of sizes of vehicles and types of image sources, and pre-processed these images to train a deep learning-based object detection model. Finally, we demonstrated that the detection performance of the overloaded vehicle was improved by about 23% compared to the one using raw data. From the result, we believe that public big data can be utilized more efficiently and applied to the development of an object detection-based overloaded vehicle detection model.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.22 no.1
• /
• pp.192-207
• /
• 2023

Commercialization of level-4 (Lv.4) autonomous driving applications requires the definition of a safe road environment under which autonomous vehicles can operate safely. Thus, a risk assessment model is required to determine whether the operation of autonomous vehicles can provide safety to is sufficiently prepared for future real-life traffic problems. Although the risk factors of autonomous vehicles were selected and graded, the decision-making method was applied as qualitative data using a survey of experts in the field of autonomous driving due to the cause of the accident and difficulty in obtaining autonomous driving data. The fuzzy linguistic representation of decision-makers and the fuzzy analytic hierarchy process (AHP), which converts uncertainty into quantitative figures, were implemented to compensate for the AHP shortcomings of the multi-standard decision-making technique. Through the process of deriving the weights of the upper and lower attributes, the road alignment, which is a physical infrastructure, was analyzed as the most important risk factor in the operation risk of autonomous vehicles. In addition, the operation risk of autonomous vehicles was derived through the example of the risk of operating autonomous vehicles for the 5 areas to be evaluated.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.22 no.1
• /
• pp.161-171
• /
• 2023

It is largely agreed that elderly drivers (over 64 years) are more likely to cause fatal crashes than other age groups. According to national road crash statistics 2021, the number of road fatalities per 10,000 drivers over 64 years old was 1.77, while that of drivers in their 30s was 0.55. This indicates a 2.67 times higher probability of causing crashes among the former than the latter. The current study estimates how rear-end crashes may be reduced by installing Automatic Emergency Braking Systems (AEBS), particularly for elderly drivers. We analyzed data from Samsung Fire & Marine Insurance. The results show that the Odds Ratio of rear-end crash occurrence between vehicles with AEBS and without AEBS is 0.75, implying there were lesser rear-end crashes in the vehicles installed with AEBS. The Odds Ratio of male drivers was determined to be 0.78, which was lesser than the 0.81 Odds Ratio obtained for female drivers. Elderly drivers who had installed AEBS in their vehicles showed an Odds Ratio of 0.76, implying crash reduction. In particular, the Odds Ratio of male elderly drivers was found to be the lowest at 0.49. We believe incentivizing by giving discounted insurance premiums to the elderly who drive vehicles installed with AEBS will help reduce rear-end crashes.

• Journal of the Korean Geotechnical Society
• /
• v.22 no.6
• /
• pp.27-40
• /
• 2006

Damage of cut-and-cover tunnel lining can be attributed to physical and mechanical factors. Physical factors include material property, reinforcement corrosion, etc. while mechanical factors include underground water pressure, vehicle loads, etc. This study is limited to the modeling of rigid circular cut and cover tunnel constructed at a depth of $1.0{\sim}1.5D$ in loose sandy ground and subjected to a vibration frequency of 100 Hz. In this study, only damages due to mechanical factors in the form of additional loads were considered. Among the different types of additional, excessive earth pressure acting on the cut-and-cover tunnel lining is considered as one of the major factors that induce deformation and damage of tunnels after the construction is completed. Excessive earth pressure may be attributed to insufficient compaction, consolidation due to self-weight of backfill soil, precipitation and vibration caused by traffic. Laboratory tunnel model tests were performed in order to determine the earth pressure acting on the tunnel lining and to investigate the applicability of existing earth pressure formulas. Based on the difference in the monitored and computed earth pressure, a factor of safety was recommended. Soil deformation mechanism around the tunnel was also presented using the picture analysis method.

• Journal of the Korean Geotechnical Society
• /
• v.26 no.3
• /
• pp.59-68
• /
• 2010

Systematic risk management is necessary in grand scaled urban construction because of the existence of complicated and various risk factors. Problems of obstructions, adjacent structures, safety, environment, traffic and geotechnical properties need to be solved because urban construction is progressed in limited space not as general earthwork. Therefore the establishment of special risk management system is necessary to manage not only geotechnical properties but also social and cultural uncertainties. This research presents the technique analysis by the current state of risk management technique. Risk factors were noticed and the importance of each factor was estimated through survey. The systemically categorized database was established. Risk extraction module, matrix and score module were developed based on the database. Expected construction budget and time distribution can be computed by Monte Carlo analysis of probabilities and influences. Construction budgets and time distributions of before and after response can be compared and analyzed 80 the risks are manageable for entire whole construction time. This system will be the foundation of standardization and integration. Procurement, efficiency improvement, effective time and resource management are available through integrated management technique development and application. Conclusively decrease in cost and time is expected by systemization of project management.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.28 no.1D
• /
• pp.11-19
• /
• 2008

Currently, existing car following models among several basic systems of advanced vehicle systems are almost developed related to the physical relation between two vehicles except for the driver's behavior or environmental factors. But the consideration of driver's character and environmental factors on driving are very essential factors for actual application. Hence, we suggested calibrating the degree of driver's discomfort on driving that is the former study to develop a new car following model of advanced vehicle to use in actuality. The degree of driver's discomfortness (Measure-of-Alarmness; MOA)is measured related to the relationship between the following vehicle and the preceding vehicle, the environmental factors and driver's characters in ubiquitous traffic. We made up questions to drivers to obtain the general and the objective measurement of driver's MOA. And the fuzzy logic model for measurement of MOA was constructed based on the results of survey. We verified the suitability of fuzzy logic model through the computation of MOA with several scenarios. And we measured the quantitative degree of driver's discomfortness on car following related to several factors which affect drivers. In accordance with this study, development of car following model applying driver's MOA will promote the actual application of advanced vehicle more effectively than the existing models. Finally, we thought the measurement of driver's MOA will be applied significantly to evaluate safety and comfort of drivers on driving.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.30 no.4D
• /
• pp.395-402
• /
• 2010

The seriousness of a traffic accident appears relatively higher on the curve sections compared with the straight sections due to a change in speed caused by a change in the driver's sight. In particular, the visual distortion phenomenon, one of the dangerous factors taking place on the curve sections, appears different according to the road's geometric design. Although it is a genuinely principal design factor which should be necessarily considered in designing a road, the previous researches on establishing the design standards for it have been insufficiently conducted. As a result, the establishment of the road design standards for the curve sections considering the sight distortion phenomenon is desperately required. This research examined the previous researches on the driver's behaviors, the driver's sight characteristics and the perceived curve radius on the curve sections, and developed the theoretical model of perceived curve radius to which a mathematical technique is applied in consideration of the visual distortion phenomenon on the two-lane curve sections in a local area. In addition, after the theoretical visual distortion was calculated on the basis of the theoretical model of perceived curve radius, the range of error on the theoretical recognition radius model formula was verified through comparing it with the previous researches' experiential visual distortion level and analyzing both of them. As a result, it was observed that as the curve radius practically increases in the theoretical recognition curve radius, the range of error tends to go down, which reflects well the characteristics of the curve sections on the road. Based on this research, it is expected that this research will be helpful to eliminate the safety defects when designing the curve sections and contribute to develop the road design standards considering human factors in the future.