• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.14 no.1
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• pp.94-102
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• 2015

The high-pass(brand name of Electronic Toll Collection System) utilization trend on the highway continues to grow as 59.4% (by the end of 2013). In this study, we applied the carbon balance method using a fuel chassis dynamometer with the four passenger car classes in order to measure the fuel consumption of the car using the expressway tollgate. We experimented 18 driving mode at general tollgate and high-pass tollgate. As a result, in case of entry/exit toll there were 21.0~56.4ml/veh fuel consumption savings, in case of open toll fuel consumption savings was analyzed as 10.5~28.1ml/veh. In addition, the annual fuel cost savings by virtue of high-pass was 28.2~57.3 billion won at 70% utilization rate, 32.2~65.5 billion won at 80%, 36.2~73.7 billion won at 90% and 40.3~81.9 billion won at 100%.

• Journal of the Korea institute for structural maintenance and inspection
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• v.23 no.1
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• pp.63-70
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• 2019

The number of vehicle-to-barrier collisions has increased due to improved driving environments. In addition, it is reported that the number of accidents led to impact severity larger than current capacity of a median barrier has increased. It is required to develop a high performance median barrier in order to secure expressway safety. This paper aims at proposing impact loading model and locations for a high performance median barrier based on analysis of median-barrier-related accident history. The SB6 test level (Impact severity: 420 kJ, Mass: 25 ton, Impact speed: 80 km/h, Impact angle: $15^{\circ}$) was suggested for target impact severity based on statistical data analysis. The suitable locations also were proposed from investigation of driver behaviors for installation and rehabilitation of high performance median barrier.

• Journal of the Korean GEO-environmental Society
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• v.23 no.8
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• pp.23-28
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• 2022

In Korea, 70% of the land is mountainous and structures occupy a high proportion in railway and road construction. In particular, in recent years, the construction of high-speed railways and highways for high-speed driving is rapidly increasing. At the same time, the construction of tunnels is also increasing. The number of tunnel construction cases in which long-term deformation occurs after tunnel excavation is completed is increasing. The stability of these tunnel structures depends entirely on the characteristics of the rock surrounding the tunnel excavation. In the case of pyroclastic rock, which is the subject of this study, it is generally vulnerable to weathering and has a characteristic that its strength decreases over a long period of time. Tunnel design and construction planning considering the strength characteristics of pyroclastic rocks are essential. This study analyzed the cases of over-deformation that occurred at the tunnel site in the pyroclastic section. Based on this study, a plan for tunnel design and construction management in an area where pyroclastic rock exist in the future is presented.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.4
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• pp.97-113
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• 2023

Swift and appropriate responses in emergency situations like objects falling on the road can bring convenience to road users and effectively reduces secondary traffic accidents. In Korea, current intelligent transportation system (ITS)-based detection systems for emergency road situations mainly rely on loop detectors and CCTV cameras, which only capture road data within detection range of the equipment. Therefore, a new detection method is needed to identify emergency situations in spatially shaded areas that existing ITS detection systems cannot reach. In this study, we propose a ResNet-based algorithm that detects and classifies emergency situations from vehicle camera footage. We collected front-view driving videos recorded on Korean highways, labeling each video by defining the type of emergency, and training the proposed algorithm with the data.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.3
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• pp.155-166
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• 2019

Road infrastructure has increased explosively due to economic development after industrialization and at present road infrastructure is being changed and increased by construction of new roads and maintenance and expansion of existing roads. Such road infrastructure should support safe driving. Road management plays an important role in safe driving. The purpose of this dissertation is to verify predictability of dangerous sections by analyzing road geometrical structure such as surface irregularity and superelevation for some sections in Central Inland Expressway by MMS and present ways of managing roads using MMS. Having analyzed surface irregularity of roads by using MMS, it was found that over 50 percent of all eight sections, targets of this study need betterments and for superelevation, over 50 percent of two sections goes against superelevation standard. Targets of this study are sections that accidents occurred frequently based on history of past accidents and predictability of dangerous sections can be verified through analysis of road geometrical structure using MMS. Using MMS data created by construction of high definition maps which are being undergone for all roads and methods proposed by this study will help investigate dangerous sections efficiently according to road environment. A result of MMS can be used for maintenance of road furniture.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.38 no.4
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• pp.587-593
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• 2018

The current road traffic noise prediction programs of Korea, which are widely used, are based upon foreign prediction model. Thus, it is necessary to verify foreign prediction models to find out whether they are suitable for the domestic road traffic environment. In addition, an analysis and an in-depth study on the main factors should be conducted in advance as the influence factors on the occurrence of traffic noise vary for each prediction model. Therefore, this study examined the influence factors and the existing prediction models used to forecast road traffic noise. Also, analyzed their relationship with the factors influencing the noise generated by driving vehicles through multiple regression analysis using a prediction model, taking into consideration of the traffic environment and the road geometric structure. In addition, this study will apply experimental values to the existing road traffic noise prediction model (NIER, RLS-90) and the deducted road traffic noise prediction model. As a result, the order of the absolute value sum of the errors are NIER, RLS-90, model value. Through comparison and verification, developed models are to be analyzed for providing basic research results for future study on road traffic noise prediction modeling.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.6D
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• pp.549-556
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• 2012

Longitudinal tunnels are defined as tunnels with length of over 1km. Because of Korea's topographical conditions and as safety measures for linear design, many tunnels are inevitably being constructed in Korea. The number of longitudinal tunnels constructed on expressways amounted to 104 as of the end of 2010 with a total length of 192km. Given the increasing demand for tunnels and the increasing length of tunnels, a safety evaluation of longitudinal tunnels needs to be conducted. As such, this study selected design elements, transportation environment and delineation system as elements to check and tried to determine factors influencing road crashes. For this, tunnels have been classified based on history of crashes; ones with crashes and ones without crashes and statistically meaningful explanatory variables were selected. By using these variables, a logit model was development in order to better grasp the factors that directly and strongly influence crashes. The result, related to crashes as well as the analysis were utility tunnel interior materials of driving lane and passing lane, which are related to driver's visibility, lateral width widening to consolidate space in a tunnel, and annual average daily traffic (AADT) per lane. These results may be used in the future as analysis indicators when drawing up plans to prevent crashes in longitudinal tunnels.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.5
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• pp.14-28
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• 2018

Thanks to technical improvement on the vehicle to vehicle communication and the intelligent transportation system, gradual introduction of the autonomous vehicles is expected soon in the market. The study analyzes the autonomous vehicles' impacts on the network efficiencies. In order to measure the network efficiencies, the study applies the sequential procedures that combines the microscopic and macroscopic simulations. The microscopic simulation attends to the capacity changes due to the autonomous vehicles' proportions on the roadway while the macroscopic simulation utilizes the simulation results in order to identify the network-wide improvement. As expected, the autonomous vehicles efficiently utilizes the existing capacity of the roadway than the human driving does. Particularly, the maximum capacity improvements are expected by the 190.5% on the expressway. The significant capacity change is observed when the autonomous vehicles' proportions are about 80% or more. These improvements are translated into the macroscopic model, which also yields overall network efficiency improvement by the autonomous vehicles' penetration. However, the study identifies that the market debut of the autonomous vehicles does not promise the free flow condition, which implies the possible needs of the system optimal routing scheme for the era of the autonomous vehicles.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.5
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• pp.95-107
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• 2016

The axle weight of a vehicle in motion can be measured with a low-speed or high-speed weigh-in-motion (WIM). However, the axial load dynamically change depending on the vehicle's characteristics-such as the chassis or axle structure-or the characteristics of the driving environment such as road flatness. The changes in dynamic load lead to differences between the vehicle's weight measured at rest and the vehicle's weight measured in motion. For this Study, an experiment was conducted with an instrumented vehicle to analyze the range of errors caused by uncontrollable environmental factors by identifying the characteristics of the dynamic load changes of a vehicle in motion, and determine the appropriate scale for the accuracy evaluation of a high-speed WIM, as a preparatory research for the introduction of unmanned overweight enforcement systems in the future. The key findings from the experiment are summarized as follows. First, The gross weight of the tested vehicle changed by approximately 1% at low velocities and approximately by 4% at high velocities, and the vehicle's axle weight changed by approximately 1-3%, at low velocities and by 2-9% at high velocities. A single axle showed larger weight changes than individual axles in a group. Secondly, The vehicle's gross weight and the axle weight on the impact section were up to eight times and three-to-twelve times higher, respectively, than its gross weight and the axle weight on the flat section. The vibration frequency of the vehicle's dynamic load was measured at between 2.4 and 5.8Hz, and found to return to the normal amplitude after moving approximately 30 meters.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.1
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• pp.117-130
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• 2017

Bicycles are leading to serious accidents in the event of a side collision, and it is very important to prevent accidents in advance because it is difficult to actively deal with them in a dangerous situation. As a part of the bicycle safety driving support technology, this study establishes bicycle accidents dangerous zone based on bicycle accident data and road property information of digital map nationwide and provides timely safety information to cyclists. The point selected by using actual accident data was called 'dangerous zone', and the potential accident occurrence point generated by modeling based on this 'dangerous zone' was called 'logical dangerous zone'. As a result of the research on the Designation of Logical Bicycle Accident Dangerous Zone, the regional specificity of the bicycle accident points across the nation was generalized to the form of the logical dangerous zone through the network data.