디지털운행기록계 자료를 활용한 버스의 주행패턴 분석 연구
A Study for Bus Driving Patterns Using Digital Tachograph Data
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초록
최근 자동차 빅데이터 활용 기술 발전, 교통환경 개선 정책의 다양성 확대 및 기술 혁신으로 사회문제(미세먼지, 탄소 등)의 통합적 해결을 모색하는 추세이다. 본 연구는 버스의 디지털운행기록계 자료를 활용하여 시공간 등 다양한 유형 간 버스 주행패턴 차이를 비교하고, 그에따른 연료사용량 및 온실가스 배출량을 분석하여 시사점을 도출하였다. 연구 결과, 비수도권보다 수도권에서, 비첨두보다 첨두에서, CNG보다 경유 버스에서 가속도 분산값이 높게 나타났으며, 버스의 주행패턴 차이로 인해, 수도권 주말 대비 경기도 평일의 버스 온실가스 단위 배출량은 약 16% 높은 것으로 분석되었다. 본 연구 방법론 및 결과는 DRT 등 버스 운영의 경제성향상을 위한 자율주행 버스 등의 표준 버스 주행모드 설정, 버스 운전자의 경제운전 가이드를위한 주행패턴 등 다양한 분야에 활용될 수 있을 것으로 기대된다.
Abstract
In recent years, there has been a trend towards seeking an integrated solution to social problems (fine dust, carbon emissions, etc.) through technological advancements in the utilization of automotive big data, the diversification of traffic environment improvement policies, and technological innovations. This study compares the differences in bus travel patterns between various types of buses in time and space by using digital odometer data, and draws implications by analyzing fuel consumption and greenhouse gas GHG emissions. As a result of the study, the acceleration dispersion value for diesel buses was higher than for CNG buses. The units of GHG emissions buses on weekdays in the metropolitan area of Gyeonggi-do were about 16% higher than on weekends compared to nonmetropolitan areas due to differences in driving patterns. The methodology and results of this study are expected to be utilized in various fields, such as setting standard bus driving modes for autonomous buses, improving the economic efficiency of DRT buses, and in developing patterns to drive buses more economically.
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