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2025 Vol.43, Issue 2 Preview Page

Article

Identification of Micro-level Hotspots at Signalized Intersections Trough Refined Traffic Conflict Measures Using Drone Data

드론 영상데이터를 활용한 신호 교차로 세부 상충 위험 구간 식별

Nuri PARK1
,
Juneyoung PARK2*
,
Yang Jun JOO3
,
Dong-Kyu KIM4
박 누리1
,
박 준영2*
,
주 양준3
,
김 동규4
1Ph.D. Student, Department of Smart City Engineering, Hanyang University, Ansan 15588, Korea
2Associate Professor, Department of Transportation & Logistics Engineering / Smart City Engineering, Hanyang University, Ansan 15588, Korea
3Postdoctoral Researcher, Department of Civil, Environment & Construction Engineering, University of Central Florida, Orlando, FL 32816, United States
4Professor, Department of Civil and Environmental Engineering / Institute of Construction and Environmental Engineering, Seoul National University, Seoul 08826, Korea
1한양대학교 스마트시티공학과 박사과정
2한양대학교 교통·물류공학과/스마트시티공학과 부교수
3University of Central Florida, Department of Civil, Environment & Construction Engineering, 박사후과정
4서울대학교 건설환경공학부/건설환경종합연구소 교수
*Corresponding Author
30 April 2025. pp. 210-221
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Abstract

Signalized intersection is a complex road section where various modes of transportation, such as pedestrians, bicycles, and vehicles, converge, requiring heightened attention to traffic safety. Traffic crashes occurring at intersections, particularly those involving vulnerable road users, can result in severe injuries. Therefore, identifying risky areas in advance and developing detailed safety management strategies for these locations are crucial to preventing crashes and mitigating their severity. This study proposes a traffic conflict indicator-based micro-hotspot identification methodology to detect detailed high crash risk sections at signalized intersections and design safety interventions considering their infrastructural and traffic environment characteristics. The study derived traffic conflict indicators, including Time to Collision (TTC), Modified TTC (MTTC), and Post Encroachment Time (PET). To determine the most effective conflict indicator and its threshold for representing crash risks, a generalized linear model was constructed, using crash frequency as the dependent variable and traffic conflict indicators as independent variables. By employing this model, micro-hotspots were identified based on the conflict indicator that most effectively captured crash-prone areas. The analysis revealed that MTTC with thresholds of 1.8 seconds and 1.2 seconds, and PET with a threshold of 1.7 seconds, effectively represented high-risk situations at three intersections, respectively. These indicators highlighted micro-hotspots such as intersection approaches and sections where physically unsegregated bicycle lanes were present, exhibiting elevated crash risks. The findings of this study are expected to contribute to the identification of detailed high-risk segments at signalized intersections. Furthermore, they provide a foundation for developing more refined traffic safety management strategies by analyzing roadway geometry, traffic characteristics, and other factors associated with micro-hotspots.

Keywords
crash hotspot
drone data
signalized intersection
traffic conflict
traffic safety

도심부 교차로는 보행자, 자전거, 차량 등 다양한 이동 수단이 혼재되어 있어 교통안전에 각별한 주의가 필요하다. 특히, 교차로에서 발생한 사고는 보행자처럼 취약한 도로 이용자와 관련되어 심각한 사고를 초래할 수 있다. 따라서 사고 위험 발생 예방과 사고 심각도 감소를 위하여 교통안전에 취약한 구간을 사전에 식별하고 해당 구간 특성에 맞는 안전 관리 전략을 마련해야 한다. 본 연구에서는 신호 교차로 세부 위험 구간을 식별하고 해당 구간의 인프라적 특성과 교통환경 특성에 맞는 안전조치를 마련하기 위한 교통 상충 지표 기반의 micro-hotspot 식별 방법론을 제안하였다. 교통 상충 지표로는 Time to collision(TTC), Modified time to collision(MTTC), Post encroachment time(PET)을 산출하였으며, 신호 교차로에서의 사고 위험을 가장 잘 나타내는 상충 지표와 그 임곗값을 찾기 위해 사고 빈도를 종속변수로, 교통 상충 지표를 독립변수로 한 일반화 선형 모형을 구축하였다. 해당 모형을 통해 신호 교차로에서 사고 다발 구간을 가장 잘 포착할 수 있는 상충 지표를 선정하여 micro-hotspot을 식별하였다. 분석 결과, 세 개의 교차로에서 각각 임곗값 1.8s의 MTTC, 임곗값 1.2s의 MTTC, 임곗값 1.7s의 PET 지표가 사고 위험 상황을 잘 나타내는 것으로 도출되었으며, 해당 지표로 교차로의 micro-hotspot을 확인한 결과, 교차로 접근부, 물리적으로 분리되지 않은 자전거 도로가 함께 있는 구간 등에서 사고 위험도가 높게 나타났다. 본 연구의 분석 결과를 활용하여 신호 교차로에서의 세부 위험 구간을 식별하고, 해당 구간의 도로 기하구조와 교통 특성, 보행 특성 및 기타 다양한 도로 교통 환경 요인을 파악하여 보다 상세한 교통안전 관리전략을 수립할 수 있을 것으로 기대한다.

키워드
사고 핫스팟
드론 데이터
신호 교차로
교통 상충
교통안전
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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 : 43
  • No :2
  • Pages :210-221
  • Received Date : 2024-12-05
  • Revised Date : 2024-12-30
  • Accepted Date : 2025-02-04
  • DOI :https://doi.org/10.7470/jkst.2025.43.2.210
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