• 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.

• Proceedings of the KOR-KST Conference
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• 2007.11a
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• pp.87-96
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• 2007

• Journal of the Society of Disaster Information
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• v.20 no.2
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• pp.440-447
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• 2024

Purpose: The number of registered vehicles in Korea continues to increase. As traffic volume increases gradually due to improved quality of life, the severity of accidents is expected to increase and congestion problems are also expected. Therefore, it is necessary to analyze the accident factors of pointed traffic accidents and non-pointed traffic accidents. Method: The severity of the apical and non-pointed traffic accidents in Incheon Metropolitan City is analyzed by dividing them into apical and non-pointed traffic accidents to investigate the factors affecting the accident. XGBoost machine learning techniques were applied to analyze the severity of pointed and non-pointed traffic accidents and visualized as plot through the results. Result: It was analyzed that during non-peak hours, such as the case of the victim's vehicle type at peak times, the victim's vehicle type and construction machinery are variables that increase the severity of the accident. Conclusion: It is meaningful to derive the seriousness factors of apical and non-pointed accidents, and it is hoped that it will be used to reduce congestion costs by reducing the seriousness of accidents in the case of apical and non-pointed in the future.

• Journal of Korean Society of Transportation
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• v.26 no.2
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• pp.25-33
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• 2008

This study was practiced in order to analyze the effect of concentrative lighting that is set up at night in some districts. For practicing this study, It was analyzed first, to study the past papers, second, to analyze the condition of the traffic accidents and the characteristics of the accidents, third, to study on the improvements of the high accident locations, finally to study the characteristics about the pedestrians' traffic accidents. The effects of road lighting improvements was analysed. The result of the analysis on concentrative lighting of crosswalk said that the night accidents was decreased to average 16.13% and the Net Present Value(NPV) on the analysis of the effect during using period is 25,648 million won, The B/C is 12.85. So, It was analysed that it is very effective.This study was practiced on the some districts and equipping time is different, and the number of samples is small. Because of this facts, This sample doesn't represent all of the concentrative lightings. But through the systematic analysis, this study can present the alternatives that can be materialized.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.4D
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• pp.351-360
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• 2010

In 2010, the number of registered vehicles reached almost at 17.48 millions in Korea. This dramatic increase of vehicles influenced to increase the number of traffic accidents which is one of the serious social problems and also to soar the personal and economic losses in Korea. Through this research, an enhanced intersection hazard prediction model by combining Genetic Algorithm and Artificial Neural Network will be developed in order to obtain the important data for developing the countermeasures of traffic accidents and eventually to reduce the traffic accidents in Korea. Firstly, this research has investigated the influencing factors of road geometric features on the traffic volume of each approaching for the intersections where traffic accidents and congestions frequently take place and, a linear regression model of traffic accidents and traffic conflicts were developed by examining the relationship between traffic accidents and traffic conflicts through the statistical significance tests. Secondly, this research also developed an intersection hazard prediction model by combining Genetic Algorithm and Artificial Neural Network through applying the intersection traffic volume, the road geometric features and the specific variables of traffic conflicts. Lastly, this research found out that the developed model is better than the existed forecasting models in terms of the reliability and accuracy by comparing the actual number of traffic accidents and the predicted number of accidents from the developed model. In conclusion, it is expect that the cost/effectiveness of any traffic safety improvement projects can be maximized if this developed intersection hazard prediction model by combining Genetic Algorithm and Artificial Neural Network use practically at field in the future.

• Proceedings of the Korean Society of Computer Information Conference
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• 2013.01a
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• pp.189-190
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• 2013

기존 차량용 블랙박스는 별도의 기기를 이용하는데, 이때 추가적인 비용이 발생하는 문제점이 있다. 또한 사고가 발생한 경우, 사용자의 의식을 체크 하지 못해 구조 신고를 보내는 등의 기능을 유연하게 추가하지 못하는 단점을 가지고 있다. 본 논문에서는 블랙박스 사용 시 발생하는 추가비용감소와 교통사고 발생 후 발생되는 환자의 응급 후송 및 뺑소니 등 2차 교통사고를 방지하기 위한 시스템의 필요성에 따라 아이폰에 있는 센서들을 활용하여 소프트웨어 방식의 차량용 블랙박스 시스템을 설계 및 구현하였다.

• 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.

• Journal of Korean Society of Transportation
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• v.21 no.1
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• pp.21-40
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• 2003

A traffic accident analysis method was developed and tested based on the highway alignment risk indices using geographic information systems(GIS). Impacts of the highway alignment on traffic accidents have been identified by examining accidents occurred on different alignment conditions and by investigating traffic accident risk indices(TARI). Evaluative criteria are suggested using geometric design elements as an independent variable. Traffic accident rates were forecasted more realistically and objectively by considering the interaction between highway alignment factors and the design consistency. And traffic accident risk indices and risk ratings were suggested based on model estimation results and accident data. Finally, forecasting traffic accident rates, evaluating the level of risk and then visualizing information graphically were combined into one system called risk assessment system by means of GIS. This risk assessment system is expected to play a major role in designing four-lane highways and developing remedies for highway sections susceptible to traffic accidents.

• Journal of Korean Society of Transportation
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• v.35 no.2
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• pp.105-115
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• 2017

Each year, a number of tourists visit Jeju Island, a popular tourist destination in the Republic of Korea. A large portion of the tourists (about 61%) use a rental car as a means of transportation. With this reason, the number of rental cars registered in Jeju was 15,517 in 2011, while the total number of the rental car has rapidly increased to 26,338 in 2015. For the same period, the number of rental car involved traffic accidents has been doubled. Thus, this study aims to analyze the rental car accidents' characteristics, clarifying primary factors related to rental car accidents in Jeju Island. To do this, 918 rental car accidents and 4,201 non-commercial passenger car accidents that occurred in Jeju island over the two years (2014-2015) were compared, using statistical methods such as chi-square test and z-test. The results show that the characteristics of rental car involved accidents are different from those caused by the passenger cars. Most of the rental car accidents in Jeju were caused by young drivers and drivers who had just obtained their driver's licenses. This study finds that driver immaturity, unfamiliar geography, and driving an unfamiliar vehicle are the main causes of the rental car accidents. Statistical analysis confirms that the characteristics of these accidents appeared significantly different from the passenger cars in terms of human and environmental factors. On the other hand, there is no clear evidence that vehicle-related characteristics are different between rental car and non-commercial passenger car accidents. The implications on transportation safety analysis and effective solutions to prevent rental car traffic accidents are discussed.

• Journal of the Korea Society of Computer and Information
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• v.29 no.8
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• pp.53-58
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• 2024

Traffic accidents are not only a threat to human lives but also pose significant societal costs. Recently, research has been conducted to address the issue of traffic accidents by predicting the risk using deep learning technology and spatiotemporal information of roads. However, while traffic accidents are influenced not only by the spatiotemporal information of roads but also by human factors, research on the latter has been relatively less active. This paper analyzes driver groups and characteristics by applying clustering techniques to a traffic accident dataset and proposes and applies a method to calculate the Risk Level for each driver group and characteristic. In this process, the preprocessing technique suggested in this paper demonstrates a higher Silhouette Score of 0.255 compared to the commonly used One-Hot Embedding & Min-Max Scaling techniques, indicating its suitability as a preprocessing method.