• Title/Summary/Keyword: 음주운전 재범

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Comparison of Behavior Patterns between First and Repeated Offenders in Driving While Intoxicated(DWI) (음주운전 초.재범자 특성 비교)

  • Jeong, Cheol-U;Jang, Myeong-Sun
    • Journal of Korean Society of Transportation
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    • v.27 no.3
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    • pp.149-160
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    • 2009
  • The purpose of this study is to comparatively analyse the behavior patterns of the first and the repeated offenders in DWI, and to develope the models of BAC(Blood Alcohol Concentration) by using multiple regression analysis method and a model of repeated DWI conviction by using logistic regression analysis method. The main results are as follows. First, the repeated offenders are more in criminal and traffic accidents records than that of the first offenders. The unlicenced drivers are in higher BAC than licenced drivers. Second, multiple regression model of BAC was developed, and the model revealed that criminal records and driving distance were important factors. Third, a model of repeated DWI conviction was developed, and the model revealed that traffic accidents records, whether or not having licence, and criminal records were most important factors.

Analysis of Effectiveness of Traffic Safety Education on DWI(Driving While Intoxicated) Deterrence (교통안전교육의 음주운전억제 효과분석)

  • Jeong, Cheol-U;Jang, Myeong-Sun
    • Journal of Korean Society of Transportation
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    • v.29 no.3
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    • pp.21-29
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    • 2011
  • The purpose of this study is to analyze the deterrence effect of traffic safety education on DWI(Driving While Intoxicated) offenders which is proposed as a incentive policy measure. For the analysis, 3512 drivers whose licenses were suspended due to DWI offence within the jurisdiction of Seongnam city in 2003, and whose driving behavior were traced for 5 years are collected. MOEs used in the study are the number of repeated DWI offence and DWI abidance duration. The statistics of analysis of covariance are used to compare the deterrence effectiveness of traffic safety education by adjusted means between groups. The results show that compared to uneducated group, educated group reveals to make less number of repeated DWI offence with longer DWI abidance period The resulting statistic also shows that active participation in the discussion during the class is more effective than just giving lecture. The former way for education can further reduce the repeated DWI by 12% and increase DWI abidance duration by 5.7% than the latter.

Identifying the Effects of Drivers' Behavior on Habitual Drunk Driving with Truncated Count Data Model (절단된 가산자료모형을 이용한 상습 음주운전자들의 습관적 음주운전 행태분석)

  • Yang, Si-Hun;Kim, Do-Gyeong
    • Journal of Korean Society of Transportation
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    • v.29 no.5
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    • pp.7-17
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    • 2011
  • Traffic problems caused by drunk drivers have been steadily raised from the past. Even though the previous researches have focused on the development of countermeasures for preventing drunk driving, the number of drivers violating the DUI (Driving-Under-Influence) regulation is still increasing. Many studies seek countermeasures for preventing drunk driving by comparing the differences between general and drunk drivers. However, few researches have investigated focusing only on the characteristics of drunk drivers. It is well known that characteristics of general drivers are different from those of drunk drivers, and also habitual drunk drivers have different characteristics from non-habitual drunk drivers. Motivated by this fact, only the drivers who have violated DUI regulation are considered in the analysis. This study primarily aims to provide alternative solutions for reducing habitual drunk drivers who are highly inclined to do drunk driving repeatedly. For the analysis, various types of variables potentially effecting drunk driving behavior were investigated, and then truncated count data models were developed to analyze the effects of the variables selected on drunk driving. The results showed that 1) a truncated negative binomial model is better fitted to the data; and 2) five variables including experiential learning, the lack of self-control, self-reflection, the fear of crackdown, and the level of dependence on vehicles were found to be statistically significant.

Development of System for Drunk Driving Prevention using Big Data in IoT environment (IoT 환경에서 빅데이터를 활용한 음주 운전 방지 시스템 개발)

  • Shin, Dong-Jin;Hwang, Seung-Yeon;Kim, Jeong-Joon
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.22 no.6
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    • pp.69-74
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    • 2022
  • Even after the drunk driving law was revised through the Yoon Chang-ho Act in 2019, the proportion of habitual offenders among all drunk drivers in 2021 was 4.7%, up 0.5% from 2018. In addition, drunk driving is not easily stopped due to the addiction of alcohol, and there is a high probability of recidivism in accidents as it is often driven again. Therefore, in this paper, to prevent this, when alcohol is measured using its own sensor rather than a manual police measure, the vehicle stops and related data such as the current location and time are automatically saved. Since it is not possible to develop directly on the car, this system was developed by converging various technologies and sensors such as Arduino board, Firebase, and GPS based on the IoT environment in consideration of the simulation environment.