친환경 정책수립을 위한 화물차 전용도로 지정 후보 구간 분석: 교통빅데이터 기반 Screening 기법 활용

Abstract

This study aims to identify high-risk sections of major arterial roads specifically expressways, urban expressways, and national support local roads where mid to large freight trucks are concentrated, leading to compounded externalities such as traffic congestion and environmental pollution. By emphasizing environmental sustainability, the study provides a data-driven foundation for eco-friendly policy planning. Utilizing the View-T traffic dataset developed by the Korea Transport Institute, a Screening Score was computed using Min-Max normalization of 13 indicators, including traffic volume, average speed, congestion intensity, congestion cost, and pollutant emissions (PM, CO2, NOx, CO, VOCs). After quantifying risk levels, a link continuity-based cluster analysis was performed to identify contiguous high-risk road sections suitable for environmental and transportation policy intervention. Policy-based filtering prioritized urban expressways in the Seoul Metropolitan Area, resulting in the selection of 30 high-priority candidate sections with the highest Screening Scores. Findings reveal that high-risk clusters are predominantly located along industrial corridors in the capital region, Daegu, Gyeongnam Province, and parts of Chungcheong Province, reflecting the spatial overlap between freight-intensive demand and both traffic and environmental stress. By integrating traffic and environmental dimensions into a unified risk index, this study presents a novel framework for evidence-based planning of truck-only roads that aligns with sustainable logistics infrastructure development and national carbon reduction goals.