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Article

Typology of E-Scooter Accidents in Pedestrian Spaces and Their Criminal Justice Policy Implications: An Empirical Analysis of Criminal Court Judgments

전동 킥보드 사고의 유형화와 특성 분석: 보행자 통행 공간을 중심으로

Jaegwan LEE1
,
Daesung KIM1
,
Jingi KIM1
,
Hyunjin LEE1
,
Sunghee KIM2*
이 재관1
,
김 대성1
,
김 진기1
,
이 현진1
,
김 성희2*
1Master’s Student, Graduate School of Forensic Science, Soonchunhyang University, Asan 31538, Korea
2Professor, Graduate School of Forensic Science, Soonchunhyang University, Asan 31538, Korea
1순천향대학교 법과학대학원 법과학과 석사과정
2순천향대학교 법과학대학원 교수
*Corresponding Author
31 October 2026. pp. 913-929
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Abstract

This study empirically examined the characteristics of e-scooter accidents occurring in pedestrian spaces following the amendment to the Road Traffic Act on May 13, 2021, and derived policy implications. The data consisted of 120 first-instance criminal court judgments related to e-scooter accidents that occurred between May 13, 2021, and May 12, 2024. Inter-coder reliability was verified using Cohen's kappa, ranging from .82 to .90. Accident types were identified through a two-step analysis combining multiple correspondence analysis (MCA) and K-means clustering, followed by cross-tabulation analysis. The results identified three accident types. The sidewalk-centered pedestrian collision type (40.8%) showed high rates of failure to keep a proper lookout (83.7%) and serious injury or death among victims (46.9%), indicating a relatively high level of accident severity. The side-street-centered drunk driving and hit-and-run type (10.8%) showed relatively high rates of drunk driving (23.1%) and hit-and-run incidents. The crosswalk-centered vehicle collision victim type (48.3%) mainly involved cases in which the e-scooter rider was the victim (84.5%). Cross-tabulation analysis revealed significant inter- cluster differences in failure to keep a proper lookout (χ2 = 46.472, p < .001) and hit-and-run behavior (χ2 = 10.839, p = .004), suggesting that the identified clusters meaningfully reflect real-world accident patterns. Based on these findings, this study proposes policy measures tailored to the characteristics of each accident type. These include the introduction of GPS-based geofencing and anti-tampering devices to strengthen sidewalk riding management, enhanced enforcement against drunk driving on side streets, improvements to neighborhood street environments, the establishment of accountability systems such as vehicle registration and liability insurance, improvements to crosswalk safety infrastructure and AI-based smart traffic safety technologies, and strengthened user safety education.

Keywords
cluster analysis
e-scooter accidents
multiple correspondence analysis
quantitative content analysis
traffic accident typology

본 연구는 ｢도로교통법｣ 개정(2021년 5월 13일) 이후 보행자 통행 공간에서 발생한 전동 킥보드 사고의 유형별 특성을 실증적으로 규명하고 정책적 시사점을 도출하는 것을 목적으로 한다. 분석 자료는 2021년 5월 13일부터 2024년 5월 12일까지 발생한 전동 킥보드 사고 관련 형사 제1심 판결문 120건이며 코딩의 객관성 확보를 위해 산출한 코더 간 신뢰도는 Cohen's Kappa κ=.82∼.90으로 나타났다. 분석 방법으로는 다중대응분석(MCA)과 K-평균 군집분석을 활용하여 사고 유형을 분류하였고, 교차분석을 통해 군집별 특성 차이를 검토하였다. 분석 결과, 전동 킥보드 사고는 세 가지 유형으로 구분되었다. ‘보도 중심 보행자 충돌형’(40.8%)은 전방주시태만(83.7%)과 피해자 중상 및 사망(46.9%) 비율이 높아 사고 심각도가 상대적으로 높게 나타났으며, ‘이면도로 중심 음주･도주형’(10.8%)은 음주운전(23.1%)과 사고 후 도주 비율이 다른 군집보다 상대적으로 높게 확인되었다. ‘횡단보도 중심 차량 충돌 피해 사고형’(48.3%)은 전동 킥보드 운전자가 피해자인 사례(84.5%)가 주를 이루었다. 교차분석 결과, 전방주시태만(χ2=46.472, p<.001)과 사고 후 도주(χ2=10.839, p=.004) 변수 모두 군집 간 유의한 차이가 확인되어 도출된 군집이 현실의 사고 패턴을 일정 부분 반영하고 있음을 보여주었다. 이상의 실증적 결과를 바탕으로 군집별 특성을 고려하여 보도 주행 관리 강화를 위한 GPS 기반 지오펜싱 및 개조 방지 장치 도입, 이면도로 중심의 음주운전 단속과 생활도로 환경 개선, 등록제･책임보험 등 책임관리 체계 구축, 횡단보도 안전 인프라 및 AI 기반 교통안전기술 확충, 그리고 안전교육 강화의 필요성을 제언하였다.

키워드
군집분석
전동 킥보드
다중대응분석
정량적 내용분석
교통사고 유형화
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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 : 44
  • No :5
  • Pages :913-929
  • Received Date : 2026-06-04
  • Revised Date : 2026-06-29
  • Accepted Date : 2026-07-14
  • DOI :https://doi.org/10.7470/jkst.2026.44.5.913
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