• Journal of Korean Society of Transportation
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• v.36 no.1
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• pp.13-22
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• 2018

Buses, one of the representative public transportation modes, are divided into a vareity of service types according to the purpose of operation, operating distance, and management agencies. Although bus-involved crashes may cause large amount of damage due to the higher number of passengers boarded on a bus, prior research has little focused on crash severity according to bus service types. This study aims to investigate factors influencing crash severity in bus-involved crashes and to present policy implications to reduce crash severity by bus service type. To do this, bus-involved crash data from the Traffic Accident Analysis System (TAAS) during five-year period are used. Ordered probit models for three types of bus service, i.e., city bus, suburban and express buses, and charter buses, are estimated to analyze the factors of accident severity. The results show that there are significant differences of factors affecting crash severity among the types of bus services while speed and road surface influence all the types of buses. In case of local buses, time of day, roadway alignment, and installation of a traffic signal are found to be statistically significant factors. Seat belt and road class have significant effects on injury severity of the intercity and express buses. Chartered buses have time of day, driving experience, seatbelt, traffic signal, and day of week as the significant factors. The results of this study are expected to contribute to the reduction of the crash severity by each bus service type.

• International Journal of Highway Engineering
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• v.10 no.4
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• pp.199-211
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• 2008

This study deals with the side right-angle collisions of 4-legged signalized intersections in Cheongju. The goals are to analyze the characteristics of accidents and to find out the accident factors that affect severity using ordered probit model. In pursuing the above, the study uses the data of 580 side right-angle collisions occurred at the 181 intersections(2004-2005). The analyses show that more accidents were occurred in the nighttime and in going straight. The main cause was analyzed to be the red-light violation. Also, the main results of modeling are the following, First, the likelihood ratio index is 0.094 and t-ratio values that explain goodness of fit are significant. Second, minor road traffic volumes, minor road lanes, major road left-turn lanes, major road left-turn signal, major road yellow signal time, cross angle, major and minor road speed limits are significant factors affecting crash severities at signalized intersections.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.5
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• pp.200-215
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• 2023

With the rapid advance of autonomous driving technology, the related vehicle market is experiencing explosive growth, and it is anticipated that the era of fully autonomous vehicles will arrive in the near future. However, along with the development of autonomous driving technology, questions regarding its safety and reliability continue to be raised. Concerns among technology adopters are increasing due to media reports of accidents involving autonomous vehicles. To promote the improvement of the safety of autonomous vehicles, it is essential to analyze previous accident cases and identify their causes. Therefore, in this study, we aimed to analyze the factors influencing the severity of autonomous vehicle accidents using previous accident cases and related data. The data used for this research primarily comprised autonomous vehicle accident reports collected and distributed by the California Department of Motor Vehicles (CA DMV). Spatial information on accident locations and additional traffic data were also collected and utilized. Given that the primary data used in this study were accident reports, a Poisson regression analysis was conducted to model the expected number of accidents. The research results indicated that the severity of autonomous vehicle accidents increases in areas with low lighting, the presence of bicycle or bus-exclusive lanes, and a history of pedestrian and bicycle accidents. These findings are expected to serve as foundational data for the development of algorithms to enhance the safety of autonomous vehicles and promote the installation of related transportation infrastructure.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.6
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• pp.49-60
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• 2020

The number of traffic control equipment installed to prevent traffic accidents increases every year due to continuous installation by the National Police Agency and local governments. However, it is installed based on qualitative judgment rather than engineering analysis results. The purpose of this study was to present additional installations in the future by presenting the installation criteria considering the severity of accidents for each road type and calculating the appropriate number of installations. ARI indicators that can indicate the severity of traffic accidents were developed, and road types were classified through analysis of variance and cluster analysis, and accident information by road type was analyzed to derive ARI of clusters with high traffic accident severity. The ARI values required to determine the installation of equipment for each road type were presented, and 5,244 additional installation points were analyzed.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.5
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• pp.1-14
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• 2020

The aim of this study is to analyze effects of factors on the number of vehicles involved in traffic accidents on freeway sections. In previous studies about traffic accident severity, the analysis of accidents involving multiple vehicles was insufficient. However, multiple-vehicle accidents are likely to cause casualties and are the main reasons increasing accident duration and social costs. In this study, the number of vehicles involved in an accident was interpreted as the result of the accident, not as the cause of the accident, and the impacts of each accident factor were analyzed using a multinomial logit model. The results indicate that multiple-vehicle accidents are mainly related to following factors: nighttime, driver's faults, obstacles on the road, a downhill slope, heavy vehicles, and freeway mainline sections including tunnels and bridges.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.6D
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• pp.577-585
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• 2010

Traffic accidents are caused by several factors such as drivers, vehicles, and road environment. It is necessary to investigate and analyze them in advance to prevent similar and repetitive traffic accidents. Especially, the human factor is most significant element and traffic accidents by drinking-driving caused from human factor have become social problem to be paid attention to. The study analyzes traffic accidents resulting from drinking-driving and the effects of driver's attributes and environmental factors on them. The study is composed as two parts. First, the log-linear model is applied to analyze that accidents by drinking or non-drinking driving associate with road geometry, weather condition and personal characteristics. Probability is tested for drinking-driving accidents relative to non-drinking drive accidents. The study analyzes probability differences between genders, between ages, and between kinds of vehicles through odds multipliers. Second, traffic accidents related to drinking are classified into property damage, minor injury, heavy injury, and death according to their severity. Heavy injury is more serious than minor one and death is more serious than heavy injury. The ordinal regression models are established to find effecting factors on traffic accident severity.

• 한국ITS학회:학술대회논문집
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• 2010.05a
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• pp.163-167
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• 2010

• Proceedings of the KOR-KST Conference
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• 2007.11a
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• pp.323-328
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• 2007

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.5
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• pp.53-73
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• 2023

Although it is mandatory to wear a seat belt that can minimize human injury when traffic accident occurs, the number of traffic accident casualties not wearing seat belts still accounts for a significant proportion.The seat belt wearing detection system for all seats is a system that identifies whether all seat passengers wear a seat belt and encourages their usage, also it can be a useful technical countermeasure. Firstly, this study established the viability of system implementation by assessing the factors influencing the severity of injuries in traffic accidents through the development of an ordered probit model. Analysis results showed that the use of seat belts has statistically significant effects on the severity of traffic accidents, reducing the probability of death or serious injury by 0.054 times in the event of a traffic accident. Secondly, a meta-analysis was conducted based on prior research related to seat belts and injuries in traffic accidents to estimate the expected reduction in accident severity upon the implementation of the system.The analysis of the effect of accident severity reduction revealed that wearing seat belts would lead to a 63.3% decrease in fatal accidents, with the front seats showing a reduction of 75.7% and the rear seats showing a reduction of 58.1% in fatal accidents. Lastly, Using the results of the meta-analysis and traffic accident statistics, the expected decrease in the number of traffic accident casualties with the implementation of the system was derived to analyze the traffic safety effects of the proposed detection system. The analysis demonstrated that with an increase in the adoption rate of the system, the number of casualties in accidents where seat belts were not worn decreased. Specifically, at a system adoption rate of 60%, it is anticipated that the number of fatalities would decrease by more than three times compared to the current scenario. Based on the analysis results, operational strategies for the system were proposed to increase seat belt usage rates and reduce accident severity.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.05a
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• pp.156-157
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• 2023

중앙해양안전심판원의 연간 통계에 따르면 어선의 충돌사고가 전체 충돌사고 중 과반 이상을 점유한다. 충돌사고에서 어선은 타선종보다 규모가 작고 빠른 속력으로 통항함에 따라 중대 사고의 비율도 높다. 이에 따라 충돌요인을 기반으로 한 사고 심각도간의 관계 규명이 필요하다. 본 논문에서는 도로 교통공학에서 다루고 있는 유효충돌속도의 개념을 활용하여, 어선 충돌 시 유효충돌속도를 산출하는 방법을 제시하였다. 그리고 유효충돌속도가 증가할수록 사고 선체 손상 심각도가 증가하는지를 확인하기 위해, 순서형 로지스틱 회귀분석 방법으로 중앙해양안전심판원 해양사고 재결서 5년간(2016~2020년)의 데이터 286건을 분석하였다. 분석결과, 충돌 당시 산출된 유효충돌속도가 클수록 중손과 전손사고의 확률은 증가하는 것을 확인할 수 있었다. 본 연구 결과는 추후 유효충돌속도를 기반으로 한 어선의 적정항행 속력이나 제한 속력의 제한 등에 활용될 수 있을 것으로 기대된다.