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2022 Vol.40, Issue 4

Article

Analysis of Factors Affecting Commercial Vehicle Driver Crash Severity Using Wellness Data: Focused on the Comparison of Elderly Drivers and Non-Elderly Drivers

Wellness 데이터를 이용한 여객부문 사업용 차량 운전자 사고심각도 영향요인 도출: 고령 및 비고령운전자 비교를 중심으로

Jiwon PARK1
,
Eunsol CHO1
,
Yunjong KIM2
,
Cheol OH3*
박 지원1
,
조 은솔1
,
김 윤종2
,
오 철3*
1Graduate Student Researcher, Transportation and Logistics Engineering, Hanyang University, Gyeonggi 15588, Korea
2Senior Researcher, C&M Standard Laboratory, LG Electronics, Seoul 06772, Korea
3Professor, Transportation and Logistics Engineering, Hanyang University, Gyeonggi 15588, Korea
1한양대학교 교통 ‧ 물류공학과 박사과정
2LG전자 CTO부문 ICT기술센터 C&M 표준연구소 선임연구원
3한양대학교 교통 ‧ 물류공학과 교수
*Corresponding Author
31 August 2022. pp. 431-448
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Abstract

It is known that the main causes of commercial vehicle traffic accidents are driver factors such as driver’s drowsiness and negligence in forward gaze. Identifying the relationship between traffic accident and intrinsic characteristics such as health, fatigue, stress, and work environment characteristics is the basis for establishing more fundamental measures to improve traffic safety. This study defined wellness data as data that can represent the health, living, work, and welfare environment of commercial vehicle drivers that affect traffic safety. A ordered probit model was applied to the wellness data to determine the elderly and non-elderly commercial vehicle drivers. Wellness data were collected and used for ordered probit model analysis through an in-depth survey of 1,005 city bus drivers and 781 corporate taxi drivers in 2019 and 2020. For the dependent variable, an ordered probit model was constructed for each driver of an elderly and non-elderly commercial vehicle by using data classified as high, medium, and low for individual accident severity based on the driver’s traffic accident history data for the past three years. In the case of elderly drivers, the work performance of traffic safety manager and average sleep time of drivers affect the severity of the accident. Regarding non-elderly drivers, it was analyzed that the efficient use of leisure time and the presence or absence of stress caused by the work environment affect the severity of accidents. Using the results of the analysis, eight wellness-based policy implications were derived for traffic safety and accident severity reduction for elderly and non-elderly commercial vehicle drivers. In order to improve traffic safety of elderly and non-elderly commercial vehicle drivers, detailed development directions for eight policy implications were discussed.

Keywords
commercial vehicle
driver characteristic
intrinsic factor
ordered probit model
traffic accident severity

사업용 차량 교통사고의 주원인은 운전자의 졸음, 전방주시 태만 등의 인적 요인인 것으로 알려져 있다. 인적요인에 영향을 미치는 내면적인 특성인 건강, 피로, 스트레스, 근무환경 특성과 교통사고와의 관계를 규명하는 것은 보다 근본적인 교통안전개선 대책을 수립하는 데 기초가 된다. 본 연구에서는 교통안전에 영향을 미치는 사업용 차량의 운전자의 건강, 생활, 근로, 복지환경을 나타낼 수 있는 자료를 Wellness 요인으로 정의하고, Wellness 자료를 대상으로 순서형 프로빗 모형을 적용하여 고령 및 비고령 여객부문 사업용 차량 운전자의 교통사고 심각도 영향요인을 분석하였다. 2019년과 2020에 걸친 시내버스 운전자 1,005명과 법인택시 운전자 781명을 대상으로 한 심층 설문조사를 통하여 Wellness 자료를 수집하여 독립변수로 활용하였다. 종속변수의 경우 운전자의 과거 3년간 교통사고 이력자료를 기반으로 개개인의 사고심각도를 상, 중, 하로 분류된 자료를 활용하여 고령 및 비고령 사업용 차량 운전자별 순서형 프로빗 모형을 구축하였다. 고령운전자의 경우 운수업체 교통안전담당자의 업무수행능력, 평균 수면시간 등이 사고심각도에 영향을 미치며, 비고령운전자의 경우 여가시간의 효율적 사용 여부와 업무환경으로 인한 스트레스 발생 유무 등이 사고심각도에 영향을 미치는 것으로 분석되었다. 순서형 프로빗 모형 결과를 기반으로 고령 및 비고령 사업용 차량 운전자의 교통안전 및 사고심각도 저감을 위한 Wellness 기반 8가지 정책적 시사점을 도출하였으며, 세부적인 정책 개발 방향을 제안함으로써 고령 및 비고령 여객부문 사업용 차량 운전자를 대상으로 법 ‧ 제도적 교통안전 증진 방안을 제시하였다.

키워드
사업용 자동차
운전자 특성
내재적 사고요인
순서형 프로빗 모형
교통사고 심각도
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Information
  • Publisher :Korean Society of Transportation
  • Publisher(Ko) :대한교통학회
  • Journal Title :Journal of Korean Society of Transportation
  • Journal Title(Ko) :대한교통학회지
  • Volume : 40
  • No :4
  • Pages :431-448
  • Received Date : 2021-12-22
  • Revised Date : 2022-01-30
  • Accepted Date : 2022-06-28
  • DOI :https://doi.org/10.7470/jkst.2022.40.4.431
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