• Korean Journal of Culture and Social Issue
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• v.13 no.4
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• pp.101-112
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• 2007

We investigated the influences of 'Circumstance Insensibility', 'Unsafe Driving', 'Incautious Driving', and 'Self-efficacy of Driving', consisting of driving confidence level, on traffic accidents. 1055 drivers conducted Driving Confidence Level Questionnaire, items about their dangerous driving experience and traffic accidents. Among them, after checking the missing items, we analyzed data of 998 drivers. As a result, we found the relation between driving confidence levels and traffic accidents. Specially, 'Circumstance Insensibility' and 'Unsafe Driving' influenced traffic accidents. However 'Circumstance Insensibility' had negative effects, the other side 'Unsafe Driving' had positive effects on traffic accidents. This result means each factor of driving confidence levels have different relation with traffic accidents. 'Incautious Driving' and 'Self-efficacy of Driving' didn't have any effects on traffic accidents in this research. In future, it should be investigated 'Incautious Driving' and 'Self-efficacy of Driving'.

• Transportation Technology and Policy
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• v.8 no.2
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• pp.79-84
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• 2011

• Transportation Technology and Policy
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• v.1 no.1
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• pp.57-74
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• 2004

• Journal of the Korean Data and Information Science Society
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• v.26 no.3
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• pp.661-668
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• 2015

Them traffic accidents have been increased every year due to increasing of vehicles numbers as well as the gravitation of the population. The carelessness of drivers, many road weather factors have a great influence on the traffic accidents. Especially, the number of traffic accident is governed by precipitation, visibility, humidity, cloud amounts and temperature. The purpose of this paper is to analyse the effect of road weather factors on traffic accident. We use the data of traffic accident, AWS weather factors (precipitation, existence of rainfall, temperature, wind speed), time zone and day of the week in 2013. We did statistical analysis using logistic regression analysis and decision tree analysis. These prediction models may be used to predict the traffic accident according to the weather condition.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.2
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• pp.118-127
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• 2009

This study tries to develop model in order to assess personal factors of senior traffic accidents that are widely recognized as one of the social problems. For the current practice. it gathers data (Simulation & Questionnaire Survey) of KOTSA and conducts Poisson and Negative Binomial Regression Analysis to develop traffic accident severity model. The results show that elderly drivers' accidents are mainly affected by attentiveness selection, velocity prediction ability and attentiveness distribution ability in a positive(+) way. Second, non-senior drivers' accidents are also positively(+) influenced by attentiveness selection, velocity prediction, distance perception, attentiveness distribution ability and attentiveness diversion ability. Therefore, influencing factors of senior and non-senior drivers to vehicle accidents are different. This eventually poses a indication that preliminary education for car accident prevention should be implemented based up[n the distinction between senior drivers and non-senior drivers.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.2
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• pp.561-571
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• 2014

This study analyzes traffic accident severity of old age drivers in fourteen cities and counties of Jeonbuk Province. It is assumed that traffic accident effecting factors have two staged structure by personal and driving environment and urban characteristics. Multilevel Analysis Model is used under the assumption of hierarchical characteristics to analyze factors effecting severity. As the driver's age increases after sixty-five years old, accident damages become severe. The drunk driving is likely to make traffic accident damage more severer. The number of fatal accident by old age drivers is about three time more than by no old age drivers. Old age drivers have higher number of night traffic accidents but severer ones in daytime. Old age drivers show the higher number of traffic accidents but severer ones in fine weather. Wet road surface also influences damage severity and especially old age drivers show higher serious damage and fatal than no old drivers.

• Journal of Korean Society of Transportation
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• v.24 no.1 s.87
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• pp.39-52
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• 2006

This study divided the large-scale traffic accident locations into its own characteristics by using Cluster Analysis. Also, Quantification II and Classification and Regression Tree methods were used enabling evaluation for the amount of affecting influence by the crash type. After these analyses, we tested the fitness of the results and suggested the simplification of the quantification index. With the results from the discussed procedure, obvious differences were observed by groups according to the characteristics of crash type from the Discrimination and Classification analysis of divided four groups. Thus, measures and supplementary measures for the traffic accidents could be suggested in groups systematically. However, a lot of missing values in variables caused a huge loss of data and made this study difficult for more detailed analysis, With this difficulty. recording mandatory log files with a standardized format is also recommended to Prevent this Problem in advance.

• Journal of Korean Society of Transportation
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• v.17 no.5
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• pp.57-65
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• 1999

본 연구에서는 지금가지 통근통행자의 활동참여 분석(activity Participation analysis)이 주로 일과후 활동참여(postwork activity participation)에 초점이 주어졌다는 점을 감안하여 일과전 활동참여(preworkactivity Participation)를 분석하고자 하였다. 이러한 연구배경하에서 본 연구는 통근통행자의 통근통행 이전의 비 통근통행 발생여부와 교통수단 선택의 행태를 네스티드 로짓모형을 이용하여 분석하였다. 본 연구는 모형의 경험적 추정을 위해 1995년 미국 Nationwide Personal Transportation Survey (NPTS)의 일부분으로 수집된 뉴욕 대도시지역의 설문조사자료를 이용하였으며, 추정된 경험적 모형을 바탕으로 의미 있는 결과를 논의하였다. 본 연구에서 추정된 통근통행 이전의 비 통근통행 발생여부와 교통수단 선택의 네스티드 로짓모형은 통계적 측면이나 행태적 측면에서 볼 때 대체로 타당한 분석결과를 보여준다. 교통수단 선택모형(조건부 모형)의 추정결과를 보면 나이, 운전면허 소지여부, 가구내 차량보유대수, 가구내 직장인수, 연간 가구소득, 교통수단의 통행시간이 통근통행자의 교통수단 선택에 의미 있는 영향을 미치는 것으로 확인되었다. 한편 통근통행 이전의 비통근통행 발생여부 선택모형(한계모형)의 추정결과를 보면 나이 성별, 가구내 차량보유대수, 가구의 생애주기가 통근통행자의 비 통근통행 발생여부에 의미 있는 영향을 미치는 것으로 확인되었다. 본 연구로부터의 중요한 발견은 추정된 네스티드 로짓모형의 inclusive value의 추정계수값을 살펴봄으로써 가능한데, 모형의 경험적 추정결과는 본 연구에서 가설화된 네스티드 로짓모형구조의 타당성을 입증시켜 준다. 아울러 직장인의 교통수단 선택은 통근통행 이전의 비 통근통행 발생여부의 선택과 밀접한 관련을 가지면서 이루어진다는 사실을 확인할 수 있었다.

• Journal of the Korean association of regional geographers
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• v.21 no.3
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• pp.503-514
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• 2015

This study aims to analyze the relationship between transport infrastructure investment and rural development in Korea in a more systematic and empirical way. To do so, we formulate research framework to examine the multi-faceted relationship through extensive literature review and carry out a descriptive study on the spatial patterns of road investment and rural development in Korea. Finally, using the structural equation model, this study carries out the exploratory empirical analysis on the direct and indirect relationship between transport infrastructure investment and rural development. The study finds that the transport infrastructure investment in rural Korea impacts clearly on both the population base promotion and production and income growth through better accessibility. In addition, the investment has an indirect effects on the production and income growth through its influence on the population base promotion. This implies that the transport infrastructure investment in rural Korea so far exerts both long-term and short-term influences on rural development through various channels of impacts.

• Journal of the Society of Disaster Information
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• v.20 no.1
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• pp.222-231
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• 2024

Purpose: The purpose of this study is to study how to activate the use of public transportation by identifying the main factors that reduce the use of public transportation due to external influences such as COVID-19 infectious diseases. Method: This study analyzed the connection between the traffic behavior and the characteristics of public transportation use in the metropolitan area changed by COVID-19 with COVID-19 indicators, and analyzed social and environmental factors affecting traffic. Results: It was analyzed that the traffic behavior in the metropolitan area moves from commercial areas to tourist resort areas, the number of COVID-19 deaths affects the use of public transportation, and the lower the deviation between population density, agricultural and forestry areas, and gender ratios due to social and environmental factors, the more significant differences are shown. Conclusion: In the future, it will be able to be activated as a basic analysis model for revitalizing the city's transportation system, regional bases, and various social and economic indicators, such as quarantine of public transportation and social distancing, and can be used as basic data for establishing public transport policy directions according to major influencing factors.