• 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.

• Proceedings of the KOR-KST Conference
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• 2007.05a
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• pp.218-226
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• 2007

• Proceedings of the KIEE Conference
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• 2004.11a
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• pp.126-128
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• 2004

본 연구에서는 인체모형을 이용하여 감전사고를 모의하고, 프로그램을 이용하여 해석하였다. 그리고 실험결과를 국내 감전사고자의 통계자료와 비교하였다. 향후 더 많은 사고모델에 대한 자료를 축적하면 감전사고 메커니즘을 체계적이고 정량적으로 입증할 수 있고, 이것은 관리자의 전기설비 이용요령, 사용자의 휴먼에러(human error)를 최소화할 수 있는 자료로 활용될 수 있을 것으로 기대된다.

• Journal of Korean Society of Transportation
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• v.35 no.2
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• pp.160-168
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• 2017

In the past 10 years, the accidents caused by drowsy driving have occupied about 23% of all traffic accidents in Korea expressway network and this rate is the highest one among all accident causes. Unlike other types of accidents caused by speeding and distraction to the road, the accidents by drowsy driving should be managed differently because the drowsiness might not be controlled by human's will. To reduce the number of accidents caused by drowsy driving, researchers previously focused on the spot based analysis. However, what we actually need is a segment (link) and occurring time based analysis, rather than spot based analysis. Hence, this research performs initial effort by adapting link concept in terms of drowsy driving on highway. First of all, we analyze the accidents caused by drowsy in historical accident data along with their road environments. Then, links associate with driving time are analyzed using digital tachograph (DTG) data. To carry this out, negative binomial regression models, which are broadly used in the field, including highway safety manual, are used to define the relationship between the number of traffic accidents on expressway and drivers' behavior derived from DTG. From the results, empirical Bayes (EB) and potential for safety improvement (PSI) analysis are performed for potential risk segments of accident caused by drowsy driving on the future. As the result of traffic accidents caused by drowsy driving, the number of the traffic accidents increases with increase in annual average daily traffic (AADT), the proportion of trucks, the amount of DTG data, the average proportion of speeding over 20km/h, the average proportion of deceleration, and the average proportion of sudden lane-changing.

• Journal of Korean Society of Transportation
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• v.28 no.2
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• pp.123-133
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• 2010

The national standards for the installation of pedestrian crosswalks prohibits installation of crosswalks within 200 meters of nearby overpasses, underpasses, or crosswalks. In case the exceptional installation is required, the feasibility study is to be thoroughly conducted by the local police agency. However, it is an undeniable fact that the specific installation standards for optimal types and locations of crosswalks are not yet to be established. This paper examines the development of traffic accident prediction model applicable to different types and locations of bus stops(type A and type B) at mid-block intersections. Furthermore, it develops the poisson regression model which sets the "number of traffic accidents" and "traffic accident severity" as dependent variables, while using "traffic volumes", "pedestrian traffic volumes" and "the distance between crosswalks and bus stops" as independent variables. According to the traffic accident prediction model applicable to the type A bus stop location, the traffic accident severity increases relative to the number of traffic volumes, the number of pedestrian traffic volumes, and the distance between crosswalks and bus stops. In case of the type B bus stop model, the further the bus stop is from crosswalks, the number of traffic accidents decreases while it increases when traffic volumes and pedestrian traffic volumes increase. Therefore, it is reasonable to state that the bus stop design which minimizes the traffic accidents is the type C design, which is the one in combination of type A and type B, and the optimal distance is found to be 65 meters. In case of the type A design and the type B design, the optimal distances are found to be within range 60~70meters.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.2
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• pp.12-28
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• 2019

Road geometry is one of the many factors that cause crashes, but the effect on traffic accident depends on weather conditions even under the same road geometry. This study identifies the variables affecting the crash severity by matching the highway accident data and weather data for 14 years from 2001 to 2014. A hierarchical ordered Logit model is used to reflect the effects of road geometry and weather condition interactions on crash severity, as well as the correlation between individual crashes in a region. Among the hierarchical models, we apply a random intercept model including interaction variables between road geometry and weather condition and a random coefficient model including regional weather characteristics as upper-level variables. As a result, it is confirmed that the effects of toll, ramp, downhill slope of 3% or more, and concrete barrier on the crash severity vary depending on weather conditions. It also shows that the combined effects of road geometry and weather conditions may not be linear depending on rainfall or snowfall levels. Finally, we suggest safety improvement measures based on the results of this study, which are expected to reduce the severity of traffic accidents in the future.

• Journal of the Korean Society for Library and Information Science
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• v.32 no.4
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• pp.87-103
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• 1998

What is the reason that the use of an Information Processing Model (PM) contributes to enhancement of students' creativity? Postulated creativity is generated from integration of information, the author discloses the function of a human information processing system and an IPM is an integrating process of information which produces creativity. Also the use of IPM as a tool influences favorably the integration of information within the human thinking system because the function of psychological tool helps the integration of information that produces creativity.

• Journal of Korean Society of Transportation
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• v.30 no.6
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• pp.37-46
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• 2012

The number of traffic accidents caused by elderly drivers over the age of 65 has surged over the past ten years from 37,000 to 274,000 cases. The proportion of elderly drivers' accidents has jumped 3.1 times from 1.2% to 3.7% out of all traffic accidents, and traffic safety organizations are pursuing diverse measures to address the situation. Above all, connecting safety measures with an in-depth research on behavioral and physical characteristics of elderly drivers will prove vital. This study conducted an empirical research linking the driving characteristics and traffic accidents by elderly drivers based on the Driving Aptitude Test items and traffic accident data, which enabled the measurement of behavioral characteristics of elderly drivers. In developing the Influence Model, we applied the zero-inflated Poisson (ZIP) regression model and selected an accident prediction model based on the Bayesian Influence in regards to the ZIP regression model and the zero-inflated negative binomial (ZINB) regression model. According to the results of the AAE analysis, the ZIP regression model was more appropriate and it was found that three variables? prediction of velocity, diversion, and cognitive ability? had a relation of influence with traffic accidents caused by elderly drivers.

• Journal of Korean Society of Transportation
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• v.32 no.1
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• pp.50-62
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• 2014

The number of traffic accidents has been decreased since 2000; however, the downward trend of crash occurrence has been slower after 2006. A few decades ago, physical improvement projects such as alignment improvement and the installation of safety facilities were usually implemented to decrease the occurrence of traffic accidents, but the effects of physical improvement on safety have been gradually decreased. The main objective of this study is to identify how the drivers' characteristics affect and/or are related to traffic accidents. Most of previous works have focused on revealing the difference of the nature of the drivers between the drivers who have no experience and the drivers with experience of traffic accidents. This study tries to analyze the habitual accidents proneness through a survey of drivers' personalities for drivers who were involved in traffic accidents at least once. As a result, nine personality factors were found to be statistically significant: Neuroticism(N), Lie(L), Psychoticism* Neuroticism(PN), Psychoticism*Lie(PL), Extraversion*Lie(EL), Neuroticism*Lie(NL), Impulsiveness(IMP), Venturesomeness(VEN), Empathy(EMP). Among these factors, single character factors were found to increase accidents, whereas complex factors were found to decrease the occurrence of accidents.

• Journal of Digital Convergence
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• v.17 no.10
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• pp.23-35
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• 2019

In order to cultivate talented people who have problem solving ability due to computational thinking according to the trend of the fourth industrial revolution, each university is actively promoting software education. This study suggests that understanding-oriented SW curriculum is needed for non-majors students to improve computational thinking. In order to achieve the purpose of the study, this study designed the basic education program based on the understanding of the SW with the backward design model. The SW Basic Education Program was applied to 15 weeks of instruction and conducted three surveys. The positive effects of the understanding-oriented SW basic education on the computational thinking efficacy and the computer perception were verified. In addition, it was found that the understanding-oriented computational thinking and programming education are effective when they are linked to one process. It is expected that understanding-based SW based education, which uses the backward design model, can be applied as one of the efficient ways to improve computational thinking in the education field.