• Journal of Korean Society of Transportation
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• v.32 no.2
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• pp.119-129
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• 2014

This study aims to evaluate the accident reduction effects of 'Section Speed Enforcement System' (SSES) operation in freeways. In pursuing the above, this study collects the accident data for 5 years (2 years before operation and 3 years after operation) at all 9 sections where SSESs are operated, and evaluates annually the effects before and after operation using the comparison group method (C.G. Method). The measures of effectiveness are total accidents (TAs), fatal and serious accidents (FSAs), total injuries (TIs) and fatal and serious injuries (FSIs). The main results are as follows. First, TAs and TIs are reduced to 41.7 and 17.1%, respectively. Second, FSAs and FSIs are reduced to 41.7 and 32.2%, respectively. Therefore, SSES has more effectiveness at fatal and serious accident. Third, the accident reduction effect has been increasing, and particularly the effect of 'after three years' is evaluated to be notable.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1999.04a
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• pp.227-227
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• 1999

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

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.9
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• pp.89-96
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• 2016

According to the promoting policy for bicycle riding, the bicycle road infrastructure in Korea has been widely established. As the number of bicycle rider increases, bicycle traffic accidents also increase year after year. In this paper, we analyze bicycle traffic accident data from 2007 to 2014 which is provided by Road Traffic Authority and present statistical results of bicycle traffic accidents. And also regression analysis is applied to predict the number of daily traffic accidents in Seoul using ASOS(Automated Synoptic Observing System) climate data observed in the Seoul sector which are provided by Korea Meteorological Administration. In addition, decision tree analysis techniques are used to forecast the level of traffic accidents severity. In the analytic results of this research, we expect that it will be helpful to establish the collective policy of bicycle accident data and protective strategy in order to reduce the number of bicycle accidents.

• 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.

• Journal of Korean Society of Transportation
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• v.27 no.3
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• pp.17-28
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• 2009

To analyze the risk according to accident types by novice and experienced drivers, it is used the accidents data which occurred for 2 years(2005~2006) in Korea. It is defined that novice driver is a people who is not passed 1 year after getting a driving licence and experienced driver is a people who is passed 1 year in this study. It is used a risk model to compare and analyze about the risk between two groups. The risk model is developed to apply together two variables which is accidents frequency and severity. Then it is used a conceptual weight to find that proper rate between accident frequency and fatal accident frequency. It is found a weight($\omega=0.6$) to suitable value to apply a risk model. The results showed that collision with obstacles, angle collision($90^{\circ}$) types to novice driver group have bigger risk than experienced driver group.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.6
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• pp.168-181
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• 2023

This study analyzed the effects of traffic enforcement on accident reduction. The results revealed a significant reduction in both overall accidents (28.53%) and fatal accidents (39.44%). Notably, enforcement equipment targeting speed limits of 30 km/h and 50 km/h demonstrated similar accident reduction rates of 42.23% and 25.85%, respectively. However, variations were observed based on accident types and types of traffic violations. Therefore, it is evident that enforcement equipment yields distinct accident reduction effects depending on speed limits and types of traffic accidents. This finding underscores the potential for making informed policy decisions to enhance traffic safety measures.

• Journal of Korean Society of Transportation
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• v.30 no.3
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• pp.119-127
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• 2012

For traffic safety, it is imperative for motorists to secure their clear view and to maintain a similar speed with others while driving in a lane. Large-sized vehicles at lower speeds, however, are likely to increase the risk of accident when they share a lane with cars. Although to overcome this complication the Korean Road Traffic Act established rules for the safe use of roads, the reality is that the rules are seldom observed strictly. In this light, this study was designed to analyze the severity of truck-involved accidents, thereby providing justification for the need of truck-designated lanes and thus contributing to measuring road safety more precisely. A binomial logistic regression model was applied to analyze the severity of truck-involved accidents. The analysis showed that several variables affect the severity of truck-involved accidents on freeways; i.e., violation against the rule of truck-designated lanes, weather, difference between daytime and nighttime, and parking on road shoulder. Moreover, the strong enforcement will be needed to make motorists observe the rule, because a Wald statistical test showed that the violation against the rule of truck-designated lanes has the largest influence on the severity.

• 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.

• Journal of Korea Planning Association
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• v.53 no.7
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• pp.49-66
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• 2018

The purpose of this study is to analyze neighborhood environmental factors affecting bicycle accidents and accidental severity in Seoul, Korea. The use of bicycles has increased rapidly as daily transportation means in recent years. As a result, bicycle accidents are also steadily increasing. Using Traffic Accident Analysis System (TAAS) data from 2015 to 2017, this study uses negative binomial regression analysis to identify neighborhood environmental factors affecting bicycle accidents and accidential severity. The main results are as follows. First, bicycle accidents are more likely to occur in commercial and mixed land use areas where pedestrians, bicycle and vehicles are moving together. Second, bicycle accidents are positively associated with road structures such as four-way intersection. In contrast, three-way intersection is negatively associated with serious bicycle accidents. The density of speed hump or street tree is negatively associated with bicycle accidents and accidential severity. This finding indicates the effect of speed limit or street trees on bicycle safety. Fourth, bicycle infrastructures are also important factors affecting bicycle accidents and accidential severity. Bicycle-exclusive roads or bicycle-pedestrian mixed roads are positively associated with bicycle accidents and accidential severity. Finally, this study suggests policy implications to improve bicycle safety.