[논문]부상 심각도에 의한 초기 및 후기 고령 운전자 사고 특성 분석

김상수; 최보림; 정연식

doi:10.12652/ksce.2023.43.4.0477

부상 심각도에 의한 초기 및 후기 고령 운전자 사고 특성 분석
Characteristics of Crashes with Early and Late Elderly Drivers by Injury Severity 원문보기

KSCE Journal of Civil and Environmental Engineering Research = 대한토목학회논문집, v.43 no.4, 2023년, pp.477 - 484

김상수 (영남대학교 도시공학과) , 최보림 (영남대학교 도시공학과) , 정연식 (영남대학교 도시공학과)

초록
AI-Helper

인구의 수명 연장에 따라 고령 운전자 수와 연령대는 지속적으로 증가하고 있다. 따라서 교통에서 고령 운전자의 연령대별 차별화된 관리를 위한 노력이 필요하다. 본 연구의 목적은 비고령 운전자 대비 초기 및 후기 고령 운전자의 부상 심각도에 영향을 미치는 인자들을 파악하여, 이들 그룹간 특성을 분석하는 것이다. 과거 5년간(2017-2021) 전국 도로에서 발생된 교통사고 자료를 적용하였으며, 기존 연구와 달리, 본 연구에서는 노안이 시작되는 40대 이후 운전자만을 대상으로 하였으며, 중년 운전자(40-64), 초기 고령 운전자(65-74), 후기 고령 운전자(75+)로 구분하여 분석을 진행하였다. 로지스틱 회귀 분석 결과, 초기 및 후기 고령 운전자의 중상 및 사망사고에 영향을 미치는 변수는 총 18개로 나타났으며, 이들 변수는 대부분 후기 고령 운전자 그룹에서 보다 민감하게 심각도를 형성하는 것으로 나타났다. 연구의 결과는 향후 고령 운전자 교통안전 정책수립을 위한 기반정보로 유용하게 활용될 것으로 기대된다.

Abstract ▼ AI-Helper

The number and age of elderly drivers are continuously increasing according to the extension of the human lifespan. Therefore, in transportation, efforts are being made to differentiate and manage elderly drivers by age group. This study aims to identify the factors affecting the crash severity of early and late elderly drivers, compared to middle-aged drivers, and to identify the characteristics between these groups. Crash data that occurred on nationwide roads for the past 5 years (2017-2021) was applied. Unlike previous studies, this study only targeted drivers in their 40s and older, when presbyopia begins: middle-aged driver (40-64), early elderly driver (65-74), and late elderly driver (75+). As a result of logistic regression analysis, a total of 18 variables were found to affect serious injuries including fatalities in early and late elderly drivers. Most of these variables appeared to lead to severity more sensitively in the late elderly group. The results of this study are expected to be useful as basic information for establishing traffic safety policies for elderly drivers in the future.

주제어

표/그림 (2)

표 Table 1. Summary of Candidate Variables
표 Table 2. Logistic Regression Model Results

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표제어: PCR

동의어: Packet Collision Rate

용어 설명 출처 목록 (6)

용어 설명: PCR은 세균 특이성이 있는 primer를 이용하여 적은 수의 세균이 있을지라도 쉽게 검출할 수 있는 유용한 방법이며, 이를 이용하여 구강 내 치면세균막이나 타액에서 직접 세균을 검출할 수 있게 되었다[8].

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