Estimating Vehicle-Specific Travel Distance Based on Mobile Communication Data for Carbon Emission Calculation

• Published in: Journal of Next-generation Convergence Information Services Technology Vol. 13; no. 5; pp. 615 - 623
• Main Authors: Kim, Jin-Guk, Yang, Choong-Heon
• Format: Journal Article
• Language: English
• Published: 차세대컨버전스정보서비스학회 31.10.2024
• Subjects: 학제간연구
• ISSN: 2384-101X; 2672-1163
• DOI: 10.29056/jncist.2024.10.04

In this study, a methodology is proposed to estimate driving distance more accurately by vehicle type using communication data to calculate carbon emissions. Traditional methods based on historical data collection have limitations in estimating driving distance accurately. However, utilizing communication data allows for more detailed estimation of driving distance across the traffic network, contributing to a more precise calculation of carbon emissions. Although various traffic monitoring devices are currently used to estimate driving distances, it remains challenging to estimate the total driving distance by vehicle type according to road classification. This approach yields higher accuracy and reliability than traditional sample-based estimation methods. The results of this study can be used as critical foundational data for formulating national policies on greenhouse gas reduction and are expected to significantly improve the accuracy of carbon emission calculations in the road sector. In particular, the methodology based on mobile communication data improves vehicle-specific travel distance estimation and enhances spatiotemporal analysis capabilities for road-sector carbon emissions. KCI Citation Count: 0