• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.4
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• pp.1-12
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• 2021

Emergence of the COVID 19 pandemic has resulted in a sharp increase in the number of two-wheeler vehicular traffic accidents, prompting the introduction of numerous efforts for their prevention. This study applied XGBoost to determine the factors that affect severity of two-wheeled vehicular traffic accidents, by examining data collected over the past 10 years and analyzing the influence of each factor. Among the total factors assessed, variables affecting the severity of traffic accidents were overwhelmingly high in cases of signal violations, followed by the age group of drivers (60s or older), factors pertaining only to the car, and cases of centerline infringement. Based on the research results, a reasonable legal reform plan was proposed to prevent serious traffic accidents and strengthen safety management of two-wheeled vehicles. Based on the research results, we propose a reasonable legal reform plan to prevent serious traffic accidents and strengthen safety management of two-wheeled vehicles.

• Knowledge Management Research
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• v.25 no.1
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• pp.217-233
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• 2024

The demand for two-wheelers has increased in recent years, driven by the growing delivery culture, which has also led to a rise in the number of two-wheelers. Although two-wheelers are economically efficient in congested traffic conditions, reckless driving and ambiguous traffic laws for two-wheelers have turned two-wheeler accidents into a significant social issue. Given the high fatality rate associated with two-wheelers, the severity and risk of two-wheeler accidents are considerable. It is, therefore, crucial to thoroughly understand the characteristics of two-wheeler accidents by analyzing their attributes. In this study, the characteristics of two-wheeled vehicle accidents were categorized using the K-prototypes algorithm, based on data from two-wheeled vehicle accidents. As a result, the accidents were divided into four clusters according to their characteristics. Each cluster showed distinct traits in terms of the roads where accidents occurred, the major laws violated, the types of accidents, and the times of accident occurrences. By tailoring enforcement methods and regulations to the specific characteristics of each type of accident, we can reduce the incidence of accidents involving two-wheelers in metropolitan areas, thereby enhancing road safety. Furthermore, by applying machine learning techniques to urban transportation and safety, this study adds to the body of related literature.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.1
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• pp.28-38
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• 2016

Cooperative-Intelligent Transport Systems (c-ITS) has emphasized a real-time traffic safety service in urgent situations among highway infrastructure and four-wheeled vehicles, while two-wheeled vehicles, e.g. bicycles and motorcycle, sharing highway space and endangering highway safety, have yet been out of its interest. This paper delivers the results of a study conducted to analyze the patterns of two-wheeled-vehicle traffic accidents experienced in the past, the last three years (2011~2013), and to propose the types of service enhancing the safety of the riders of those. It was found from the analysis of historical accident data that the side collision on a link section should be taken care of for further safety treatment, while the old female drivers need additional care to decrease their fatality rate. By combining the services proposed for bicycles and motorcycles, this paper proposes (1) eight different bicycle-to-everything (B2X) services which can be eventually provided in c-ITS and (2) three of those that would be available in the near future with the current communication technologies.