• International Journal of Highway Engineering
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• v.16 no.6
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• pp.149-158
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• 2014

PURPOSES : The bridge section of the expressway has a worse driving environment than the general section. However, traffic safety countermeasures are focused only on the bridge section. Traffic safety countermeasures on the section before entry to the bridge and the section after exit from the bridge are applied only when the bridge has a long-span section. Accordingly, this study will verify the necessity of extending the application of traffic safety countermeasures to areas that are affected by the bridge. METHODS : This study determines the areas that are affected by the bridge as well as the areas that are affected by locations with frequent traffic accidents and suggests the risk factors by affected areas through canonical discriminant analysis. For the analysis, traffic accident data for 3 years, which occurred on bridge sections in six major expressway lines, were used. RESULTS : The numbers of traffic accidents were 469 before the bridge, 281 on the bridge, and 468 after the bridge. The variables that have impact on the seriousness of accidents are as follows: speeding, excess manipulation of the steering wheel, and failure to secure safety distance for accidents that occurred before the bridge section; speeding, excess manipulation of the steering wheel, and dozing off for accidents that occurred on the bridge; and speeding and failure to secure safety distance for accidents that occurred after the bridge section. CONCLUSIONS : Areas affected by the bridge show higher accident rates than the bridge section; therefore, imposing traffic safety countermeasures on the integrated section of the bridge and the affected areas is required. It is believed that the results suggested in this study could be effectively used in the prevention of traffic accidents by imposing custom-made safety countermeasures for each section.

• Journal of Korean Society of Transportation
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• v.5 no.2
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• pp.55-72
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• 1987

The work analyzes the existing situation and defines special problems concerning traffic accidents in the two countries. The report is divided into three parts: 1) Using the global approach of SMEED, the data were evaluated using multiple regression analysis, and homogeneous groups of countries were defined by cluster analysis. In the global approach, the linear model is better than SMEED's non-linear model in explaining the number of fatalities. Among the different groups of countries, the linear approach was found to be better suited for industrialized countries and the non-linear approach better for the developing countries. T도 comparison of traffic fatality data for the Federal Republic the developing countries. The comparison of traffic fatality data for the Federal Republic of Germany and the Republic of Korea showed different regression equations during the same time period. 2) The BOX/JENKINS time series analysis on a monthly basis points out clearly similar seasonal patterns for the two countries over the years studied. The decrease in traffic accidents following the intensification of the safety belt requirement was proved in the ARIMA model. It amounts to 7 to 8 percent fewer personal injury accidents and fatal accidents. The identified increase in safety in the Federal Republic of Germany since the 1970s is mainly due to the reduction of accident severity in residential areas. 3) Speeds and headways on motorways in th3e two countries were also compared. The measurements point out that German road users drive faster, take more risks, and accept shorter time gaps than Korean road users. However, the accident statistics show accident rates for Korea that are several times higher than those in the Federal Republic of Germany.

• Journal of Trauma and Injury
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• v.19 no.1
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• pp.74-80
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• 2006

Purpose: For prevention and suitable administration, the effect of age on the severity of injuries in traffic accidents should be considered when evaluating a patient, but there have not been enough epidemiological studies that evaluate the age factor in traffic accidents. For that reason, we investigated old-aged patients who were involved in traffic accidents (65 years old or more) and who were admitted to the emergency department of a college hospital in an urban city of Korea. Methods: We collected data from traffic-accident patients who came to the emergency room of a university hospital in Seoul from Jan.1, 2004 to Dec.31, 2005. We compared their abilities to ambulate and the RTSs (Revised trauma scores) by using a LSD (least significant difference), linear regression. Results: A total of 1460 patients were included. The mean RTS of all traffic-accident patients was $7.77{\pm}0.280$. The scores for drivers and passengers, motor-cycle drivers and passengers, bicycle drivers and passengers, and pedestrians were $7.79{\pm}0.21$, $7.78{\pm}0.22$, $7.54{\pm}0.25$, $7.77{\pm}0.20$, and $7.80{\pm}0.21$ respectively (p=0.000). There was no statistically significant difference between the RTS of patients over 65 years and that of other patients. In a regression analysis, the number of patients over 45 ages who were able to ambulate was lower than that of younger people, independently of other influencing factors (B=-0.330, R-square = 0.243, p=0.000). Conclusion: We expected that RTS of old age group more than 65 years old will significantly lower than that of others, but there was no statistically significant difference.

• Journal of Korean Society of Transportation
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• v.28 no.1
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• pp.157-163
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• 2010

It is well known that weather conditions are closely related with the number and severity of traffic accidents. At present, installation of safety countermeasures including systems is common approach to reduce the damage of traffic accidents at expressways. In this study, the differences of causation factors to influence traffic accidents considering road alignment characteristics and weather conditions. In order to identify the relationship between road and weather conditions, discriminant analysis has been performed with 500 traffic accident data at expressways. Weather conditions are divided into several categories such as snow, sunny, rain, fog, and cloud. Also, road conditions such as types of pavements, grades are analyzed. As the results, major impacting road conditions to traffic accidents are concrete pavement and 3% or more down grades. In these road conditions, visible distance will be reduced and actual braking distances will be increased. This study shows that the expressway sections under concrete pavement and down grades should be more cautious than other sections. It also shows that fog condition is the mose dangerous situation in terms of traffic accidents.

• Journal of Digital Convergence
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• v.19 no.4
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• pp.25-31
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• 2021

Moving toward an aged society, traffic accidents involving elderly drivers have also attracted broader public attention. A rapid increase of senior involvement in crashes calls for developing appropriate crash-severity prediction models specific to senior drivers. In that regard, this study leverages machine learning (ML) algorithms so as to predict the severity of vehicle-pedestrian collisions induced by elderly drivers. Specifically, four ML algorithms (i.e., Logistic model, K-nearest Neighbor (KNN), Random Forest (RF), and Support Vector Machine (SVM)) have been developed and compared. Our results show that Logistic model and SVM have outperformed their rivals in terms of the overall prediction accuracy, while precision measure exhibits in favor of RF. We also clarify that driver education and technology development would be effective countermeasures against severity risks of senior driver-induced collisions. These allow us to support informed decision making for policymakers to enhance public safety.

• Journal of Korean Society of Transportation
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• v.34 no.2
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• pp.123-134
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• 2016

Traffic accident at intersections takes 44.3% of total number of accidents on entire road network of Korea in 2014. Although several studies addressed contributory factors of accidents at signalized intersection, very few is known about the factors at rural unsignalized intersections. The objective of this study is therefore to investigate specific characteristics of crashes at rural unsignalized intersection and to identify contributory factors in causing crashes by statistical approach using the Ordered Logistic Regression Model. The results show that main type of car crashes at unsignalized intersection during the daytime is T-bone crashes and the number of crashes at 4-legged intersections are 1.53 times more than that at 3-legged intersections. Most collisions are caused by negligence of drivers and violation of Right of Way. Based upon the analysis, accident severity is modeled as classified by two types such as 3-legged intersection and 4-legged intersection. It shows that contributory factors in causing crashes at rural unsignalized intersections are poor sight distance problem, average daily traffic, time of day(night, or day), angle of intersection, ratio of heavy vehicles, number of traffic violations at intersection, and number of lanes on minor street.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.5
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• pp.74-91
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• 2023

Several that analyzed the effectiveness of traffic safety facilities a method of comparing changes in the number of accidents, accident severity, speed through traffic accident data before and after installation or speed data collected from vehicle detection systems (VDS). , when traffic accident data is used, it takes a long time to collect because must be collected for at least one year before and after installation. , the road environment may change during this period, such as the addition of other traffic safety facilities in addition to the facilities to be analyzed. , the location of the VDSs for speed data is often different from the location where analysis is required, and there is a problem in that the investigators are exposed to the risk of traffic accident during on-site investigation. Therefore, this study a case study by establishing a methodology to determine effectiveness video images with a drone, extracting data using a program, and comparing vehicle driving speeds before and after speed reduction facilities. Vehicle speed surveys using drones are much safer than observational surveys conducted on highways and have the advantage of tracking speed changes along the vehicle, it is expected that they will be used for various traffic surveys in the future.

• Proceedings of the Korean Society of Disaster Information Conference
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• 2023.11a
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• pp.257-258
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• 2023

본 연구는 2019년부터 2021년의 고속도로 교통사고 위치 좌표를 콘존 데이터와 결합한 후 파이캐럿을 활용하여 고속도로 교통사고 심각도에 영향을 끼치는 요인을 분석할 수 있는 최적 모델을 선정하고 채택된 Random Forest 기법으로 고속도로 교통사고 심각도에 영향을 끼치는 요인을 분석하고자 하였으며, 향후 전국 고속도로 교통사고에 영향을 주는 요인으로 확대하여 분석하고 사고 심각도 개선을 위한 대안 방안 마련이 가능할 것으로 판단된다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.6
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• pp.1321-1328
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• 2015

The automobiles in Korea have approximately 60 years of history and this is relatively short compared to advanced countries. However, considering the traffic accident rate or severity related to automobiles, various efforts are required to reduce traffic accidents. Various problems caused by traffic accidents are not only related to individual damages but also have become social problems. In order to resolve this, it is important to analyze the cause of traffic accidents. This study aims to suggest methods to reduce traffic accidents by analyzing driving behavior, which is one of the reasons for a number of traffic accidents that were collected through traffic accident videos reported using DVRs (Driving Video Recorder) and were aired to the public via a SBS TV program for the past two years and four months. In particular, unlike other existing studies that aim at analyzing the causes of traffic accidents simply using data, this study constructed a database by analyzing every single DVR that stores the situation before and after the accident using relatively high-resolution video information to provide practical plans to reduce traffic accidents through statistical analysis.

• Journal of Korean Society of Transportation
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• v.23 no.4 s.82
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• pp.47-55
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• 2005

In recent years, the rapid growth of vehicles have increased traffic crashes. Since they can cause the economic losses and have put the life qualify in danger, there should be numerous efforts to reduce traffic crashes. To reduce traffic crashes, this research seeks to improve the safety of intersections by analysing causations of injury severity with Ordered Probability Model. This research applied the Ordered Probit Model, which assumes that ${\epsilon}_i$(random error) is normally distributed, for model calibration and used $p^2$ (likelihood ratio) and $x^2$ (Chi-square) for model selection. The results show that minor road traffic, heavy vehicle rates, major and minor right-turn rates, presence of lightings, speed limits, instructive line for left-turn traffic are significant factors affecting crash severities at signalized intersections.