• Journal of Advanced Navigation Technology
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• v.28 no.4
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• pp.559-565
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• 2024

Research on autonomous vehicles is being actively conducted. As autonomous vehicles emerge, there will be a transitional period in which traditional and autonomous vehicles coexist, potentially leading to a higher accident rate. Currently, when a traffic accident occurs, the fault ratio is determined according to the criteria set by the General Insurance Association of Korea. However, the time required to investigate the type of accident is substantial. Additionally, there is an increasing trend in fault ratio disputes, with requests for reconsideration even after the fault ratio has been determined. To reduce these temporal and material costs, we propose a deep learning model that automatically determines fault ratios. In this study, we aimed to determine fault ratios based on accident video through a image classification model based on ResNet-18 and video action recognition using TSN. If this model commercialized, could significantly reduce the time required to measure fault ratios. Moreover, it provides an objective metric for fault ratios that can be offered to the parties involved, potentially alleviating fault ratio disputes.

• International Journal of Highway Engineering
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• v.18 no.5
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• pp.63-73
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• 2016

PURPOSES : The objective of this study was to analyze variations in the vehicle driving behavior characteristics on signalized intersections according to the use of traffic enforcement camera (red light camera). METHODS : In order to analyze the driving behavior characteristics on signalized intersections when red light camera are installed, the target sites for investigation were selected depending on whether the red light camera is installed and accident rates increased after the installation. In particular, to analyze the characteristics of dilemma zones in signalized intersections, approach speed and deceleration speed of 3 type vehicles (passing vehicles during a yellow light, stopping at a yellow light, passing vehicles during a green light) were examined. Based on these data, the starting point, ending point, and distance of the dilemma zones were calculated. Also, the locations of increased traffic accidents and decreased accidents after the installation of the equipment were distinguished when analyzing the traffic accident characteristics. RESULTS : Analysis results revealed that there was a tendency for the dilemma zone distance to decrease after the installation of equipment(red light camera) in most sites. This tendency was found to be due to the decrease in the approaching speed of vehicles at intersections after the installation of equipment, resulting in the starting and ending points of dilemma zone to become closer to the stop line. Moreover, analysis showed that the number of traffic accidents decreased for most intersections after the installation of equipment and safety of the intersections increased somewhat. CONCLUSIONS : In general, installation of equipment(red light camera) caused the intersections approaching speed and dilemma zone distance to decrease. Decision-making is difficult for drivers in the dilemma zone, so the decrease in the dilemma zone distance implies an improvement in traffic safety. Furthermore, the number of accidents within intersections significantly decreased after the equipment was installed, leading to the conclusion that installation of the equipment affected the decrease in traffic accidents.

• Journal of Hydrogen and New Energy
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• v.31 no.6
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• pp.605-613
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• 2020

In July and October of this year, the government announced the 'Green new deal plan within the Korean new deal policy' and 'Strategies for proliferation of future vehicles and market preoccupation'. And, in response to changes in the global climate agreement, it has decided to expand green mobility such as electric vehicles and hydrogen electric vehicles with the aim of a "net-zero" society. Accordingly, the goal is to build 310 hydrogen refueling stations along with the supply of 60,000 hydrogen vehicles in 2022, and the hydrogen infrastructure is being expanded. however, it is difficult to secure hydrogen infrastructure due to expensive construction costs and difficulty the selection of a site. In Korea, it is possible to build a mobile hydrogen station according to the safety standards covering special case of the Ministry of Industry. Since the mobile hydrogen station can be charged while moving between authorized place, it has the advantage of being able to meet a large number of demands with only one hydrogen refueling station, so it is proposed as a model suitable for the early market of hydrogen infrastructure. This study demonstrates the establishment of a hydrogen refueling station by deriving a virtual accident scenario for leakage and catastrupture for each facility for the risk factors in a mobile hydrogen station, and performing a quantitative risk assessment through the derived scenario. Through the virtual accident scenario, direction of demonstration and implications for the construction of a mobile hydrogen refueling station were derived.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.39 no.9
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• pp.885-892
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• 2015

In this study, we simulate the railway crash accident that occurred at the Sangwangsimni station on the Seoul Metro Line #2, and we propose a solution to minimize the damage. We use LS-DYNA, which is the commercial software employed for collision analysis to perform 1-D and 3-D simulations for the recurrence of accidents. By performing 1-D simulations, we analyze the load, displacement, absorbed energy of the couplers, and acceleration of vehicles, and we evaluate the safety in accidental collisions. By performing 3-D simulations, we analyze the deformation of the car and over-ridding. We propose methods to improve the safety in collisions involving railway vehicles, and we perform collision accident simulations to determine improvements when applying a high-performance energy absorber to the front car.

• Journal of Platform Technology
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• v.6 no.3
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• pp.10-16
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• 2018

Bicycle shares road with various traffic elements like car, pedestrian and, the number of bicycle user is increasing in recent. Therefore, bicycle accident continuously increases. Especially in complex traffic environment, bicycle accident which collides with moving object such as pedestrian occupies many parts of bicycle accident in the reason that the cyclist does not recognize moving object. In this paper, to reduce or avoid the bicycle accident, we propose the architecture of bicycle collision avoidance system in which that cyclist can get the information about moving object by connecting bicycle to network of vehicles and does some action for avoiding collision. In our architecture, when traffic element such as car recognizes moving object, it decides the moving direction of object, and transfers information about moving direction via vehicles network. Bicycle collision avoidance system from our proposed architecture receives this information, and alerts to cyclist when the moving object influences the safety of bicycle.

• Journal of Korean Society of Transportation
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• v.19 no.5
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• pp.109-117
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• 2001

The median encroachment accident model proposed in this paper is the first step to develop cost-effective criteria about installing facilities preventing traffic accidents by median encroachment. This model consists of expected annual number of median encroachment on roadway and conditional probability to collide with vehicles on opposite lane after encroachment. Expected encroachment number is related to traffic volume and quote from a study of Hutchinson & Kennedy(1966). The probability of vehicle collision is composed of assumed headway distribution of opposite directional vehicles (negative exponential distribution), driving time of encroaching vehicle and Gap & Gap acceptance model. By using expected accident number yielded from the presented model, it will be able to calculate the benefit of reduced accident and to analyze the cost of installing facilities. Therefore this will help develop cost-effective criteria of what, to install in the median.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.6
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• pp.1123-1130
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• 2020

This study aims to classify the severity in car crashes using five classification learning models. The dataset used in this study contains 21,013 vehicle crashes, obtained from Korea Expressway Corporation, between the year of 2015-2017 and the LightGBM(Light Gradient Boosting Model) performed well with the highest accuracy. LightGBM, the number of involved vehicles, type of accident, incident location, incident lane type, types of accidents, types of vehicles involved in accidents were shown as priority factors. Based on the results of this model, the establishment of a management strategy for response of highway traffic accident should be presented through a consistent prediction process of accident severity level. This study identifies applicability of Machine Learning Models for Predicting of the Severity of Car Traffic Accidents on a Highway and suggests that various machine learning techniques based on big data that can be used in the future.

• Journal of Korean Tunnelling and Underground Space Association
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• v.24 no.3
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• pp.247-262
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• 2022

In domestic tunnels, it is mandatory to install CCTVs in tunnels longer than 200 m which are also recommended by installation of a CCTV-based automatic accident detection system. In general, the CCTVs in the tunnel are installed at a low height as well as near by the moving vehicles due to the spatial limitation of tunnel structure, so a severe perspective effect takes place in the distance of installed CCTV and moving vehicles. Because of this effect, conventional CCTV-based accident detection systems in tunnel are known in general to be very hard to achieve the performance in detection of unexpected accidents such as stop or reversely moving vehicles, person on the road and fires, especially far from 100 m. Therefore, in this study, the region of interest is set up and a new concept of inverse perspective transformation technique is introduced. Since moving vehicles in the transformed image is enlarged proportionally to the distance from CCTV, it is possible to achieve consistency in object detection and identification of actual speed of moving vehicles in distance. To show this aspect, two datasets in the same conditions are composed with the original and the transformed images of CCTV in tunnel, respectively. A comparison of variation of appearance speed and size of moving vehicles in distance are made. Then, the performances of the object detection in distance are compared with respect to the both trained deep-learning models. As a result, the model case with the transformed images are able to achieve consistent performance in object and accident detections in distance even by 200 m.

• Journal of Auto-vehicle Safety Association
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• v.13 no.3
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• pp.78-85
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• 2021

Recently a traffic accident of heavy duty vehicles under the mandatory installation of ADAS (Advanced Driver Assistance System) is often reported in the media. Heavy duty vehicle accidents are normally occurring a high number of passenger's injury. According to report of Insurance Institute for Highway Safety, FCW (Forward Collision Warning) and AEB (Automatic Emergency Braking) were associated with a statistically significant 12% reduction in the rate of police-reportable crashes per vehicle miles traveled, and a significant 41% reduction in the rear-end crash rate of large trucks. Also many countries around the world, including Korea, are studying the effects of ADAS installation on accident reduction. Traffic accident statistics of passenger vehicle for business purpose in TMACS (Traffic safety information Management Complex System in Korea) tends to remarkably reduce the number of deaths due to the accident (2017(211), 2018(170), 2019(139)), but the number of traffic accidents (2017(8,939), 2018(9,181), 2019(10,095)) increases. In this paper, it is introduced a traffic accident case that could lead to high injury traffic accidents by being equipped with AEB in a bus. AEB reduces accidents and damage in general but malfunction of AEB could occur severe accident. Therefore, proper education is required to use AEB system, simply instead of focusing on developing and installing AEB to prevent traffic accidents. Traffic accident of AEB equipped vehicle may arise a new dispute between a driver's fault and vehicle defect. It is highly recommended to regulate an advanced event data recorder system.

• Journal of Auto-vehicle Safety Association
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• v.11 no.2
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• pp.44-52
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• 2019

In this study a safety evaluation method is presented for a ADAS vehicle to be tested in collision situation when multiple vehicles are present on a single lane. Test scenarios are developed based on Euro-NCAP assessment scenarios, accident database and related simulation results in previous works. An automated evaluation system that is called as the K-target mover is used for active safety evaluation experiments. The experiments are conducted with two types of tests. First, the rear-end collision tests with 25% and 50% overlap for the test vehicle and target vehicle are conducted with the two kinds of test vehicles. On the other hand, the rear-end collision tests which include multiple vehicles in a single lane with 25% and 50% overlaps, are also conducted. Experimental results show that the test vehicles with ADAS cannot recognize the collision situation sometimes in the developed test scenarios, even in the case that the test vehicle showed stable performance in the simple overlap scenarios.