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Spatial clustering of pedestrian traffic accidents in Daegu

대구광역시 교통약자 보행자 교통사고 공간 군집 분석

  • Hwang, Yeongeun (Department of Statistics, Daegu University) ;
  • Park, Seonghee (Division of Mathematics and Big data science, Daegu University) ;
  • Choi, Hwabeen (Division of Mathematics and Big data science, Daegu University) ;
  • Yoon, Sanghoo (Division of Mathematics and Big data science, Daegu University)
  • 황영은 (대구대학교 일반대학원 통계학과) ;
  • 박성희 (대구대학교 수리빅데이터학부) ;
  • 최화빈 (대구대학교 수리빅데이터학부) ;
  • 윤상후 (대구대학교 빅데이터학과)
  • Received : 2022.01.21
  • Accepted : 2022.03.20
  • Published : 2022.03.28

Abstract

Korea, which has the highest pedestrian fatality rate among OECD countries, is making efforts to improve the safe walking environment by enacting laws focusing on pedestrian. Spatial clustering was conducted with scan statistics after examining the social network data related to traffic accidents for children and seniors. The word cloud was used to examine people's recognition Campaigns for children and literature survey for seniors were in main concern. Naedang and Yongsan are the regions with the highest relative risk of weak pedestrian for children and seniors. On the contrary, Bongmu and Beomeo are the lowest relative risk region. Naedang-dong and Yongsan-dong of Daegu Metropolitan City were identified as vulnerable areas for pedestrian safety due to the high risk of pedestrian accidents for children and the elderly. This means that the scan statistics are effective in searching for traffic accident risk areas.

OECD 국가 중 보행자 사망 비율이 가장 높은 대한민국은 보행자 중심으로 법령이 제정하면서 안전한 보행환경 개선을 위해 노력하고 있다. 이 연구는 노인 인구와 학원이 밀도가 높은 대구광역시를 대상으로 보행자 교통사고 클러스터를 포아송분포를 이용한 스캔통계량으로 파악하고자 한다. 어린이와 노인에 관한 교통사고의 대중 인식을 수집하여 워드클라우드로 살펴본 결과 어린이는 정부와 기업인의 캠페인을 중심으로 노출되고 있고, 노인은 사고감소를 위한 정책연구를 중심으로 노출되고 있었다. 어린이 보행자 교통사고의 상대적 위험성은 공단이 많은 평리·내당·용산동에서 높았고, 학원 밀집도가 높은 만촌·봉무·범어동에서 낮았다. 노인 보행자 교통사고의 상대적 위험성은 도심에 가까운 용산·죽전·두류·내당동에서 높았고, 범어·삼덕·팔공·봉무동에서 낮았다. 대구광역시 내당동과 용산동은 어린이와 노인 보행사고 위험성이 높아 보행 안전 취약지역으로 파악되었다. 이는 스캔통계량이 교통사고 위험 지역 탐색에 효과적임을 의미한다.

Keywords

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