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Discernment Model of Traffic Accident for an Age-old Driver's License Management

고령운전자 면허관리를 위한 교통사고발생 판별모형 개발

  • Park, Jun-Tae (Department of Transportation Engineering, University of Seoul) ;
  • Lee, Soo-Beom (Department of Transportation Engineering, University of Seoul) ;
  • Lee, Soo-IL (Hyundai Insurance Research Center)
  • 박준태 (서울시립대학교 교통공학과) ;
  • 이수범 (서울시립대학교 교통공학과) ;
  • 이수일 (현대해상 교통기후환경연구소)
  • Received : 2010.02.18
  • Accepted : 2011.06.02
  • Published : 2011.06.30

Abstract

The weight of elderly people in Korea has been increasing. Statistics show that the percentage of the elderly people in Korea was 3.1% in 1970; 3.8% in 1980; 5.1% in 1990, and 7.2% in 2000. Based on this trend, thus, the number of elderly people could be estimated to be 14% of the whole Korean population in 2018. This reveals that Korea is entering a super-aging society with remarkable fast pace. In such a change, the statistics related to elderly people driving license and the occurrence of traffic accidents are showing a noticeable numerical value. The number of traffic accident fatality in Korea ranks the highest value in OECD Countries. However, the research on old drivers in the nation is going on partially centering on system improvement and management scheme. Thus, first of all, researches about the linkage & characteristics between the driving behavior of old drivers and traffic accident should be implemented, in order properly to draw system improvement and management scheme for the old drivers. Therefore, the focus of this study is the influence model for discerning the severity of the age-old-caused traffic accidents by inquiring into the relation between the Driving Aptitude Test items that make it possible to measure their behavioral characteristics and influential factors by age group on the basis of the data on traffic accidents. The analysis results can be used as basic data for suggesting the behavioral research and countermeasure for traffic safety and its management for old driver in preparation for the aging society.

Keywords

CART(Classification and Regression Tree);discriminant analysis;driving aptitude;older driver

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