영상검지자료를 활용한 신호교차로 접근차량의 탄소배출량 추정

초록

Carbon dioxide (CO2) emissions from the transportation sector in South Korea accounts for 16.5% of all CO2 emissions, and road transportation accounts for 96.5% of this sector’s emissions in South Korea. Hence, constant research is being carried out on methods to reduce CO2 emissions from this sector. With the emerging use of smart crossings, attempts to monitor individual vehicles are increasing. Moreover, the potential commercial deployment of autonomous vehicles increases the possibility of obtaining individual vehicle data. As such, CO2 emission research was conducted at five signalized intersections in the Gangnam District, Seoul, using data such as vehicle type, speed, acceleration, etc., obtained from image detectors located at each intersection. The collected data were then applied to the MOtor Vehicle Emission Simulator (MOVES)-Matrix model–which was developed to obtain second-by-second vehicle activity data and analyze daily CO2 emissions from the studied intersections. After analyzing two large and three small intersections, the results indicated that 3.1 metric tons of CO2 were emitted per day at each intersection. This study reveals a new possibility of analyzing CO2 emissions using actual individual vehicle data using an improved analysis model. This study also emphasizes the importance of more accurate CO2 emission analyses.

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