A study of travel route estimation for improving the accuracy of traffic mode estimation in CO2 emission visualization applications

カテゴリ: 研究会(論文単位)

論文No: IS24026

グループ名: 【C】電子・情報・システム部門 情報システム研究会

発行日: 2024/09/24

タイトル(英語): A study of travel route estimation for improving the accuracy of traffic mode estimation in CO2 emission visualization applications

著者名: Zou Lubing(Hitachi, Ltd.),Matsushika Yayoi(Hitachi, Ltd.),Yonehara Miki(Hitachi, Ltd.),Tomiyama Tomoe(Hitachi, Ltd.),Teramura Keiko(Hitachi, Ltd.)

著者名(英語): Lubing Zou(Hitachi, Ltd.),Yayoi Matsushika(Hitachi, Ltd.),Miki Yonehara(Hitachi, Ltd.),Tomoe Tomiyama(Hitachi, Ltd.),Keiko Teramura(Hitachi, Ltd.)

キーワード: Public transport|Environmental impact visualization|Modal shift|Traffic mode estimation|Travel route estimation|Public transport|Environmental impact visualization|Modal shift|Traffic mode estimation|Travel route estimation

要約(日本語): Nowadays, visualization CO2 emission applications from daily traffic are as a novel method to incentivize private car users shift to public transport with low emission. These relies on high accuracy of traffic mode estimation, but previous studies focused on improving its accuracy of brief intervals in specific areas by using heavy learning sensor data. This research provides a low-cost function named travel route estimation, which improving accuracy of traffic mode estimation by comparing multiple mode attributes over a longer period such as moving speed and locations, not limited to sensor data, and then demonstrates its effectiveness through experiments. Our functional consideration is also expected to solve its misestimation in multiple geolocations in the future.

要約(英語): Nowadays, visualization CO2 emission applications from daily traffic are as a novel method to incentivize private car users shift to public transport with low emission. These relies on high accuracy of traffic mode estimation, but previous studies focused on improving its accuracy of brief intervals in specific areas by using heavy learning sensor data. This research provides a low-cost function named travel route estimation, which improving accuracy of traffic mode estimation by comparing multiple mode attributes over a longer period such as moving speed and locations, not limited to sensor data, and then demonstrates its effectiveness through experiments. Our functional consideration is also expected to solve its misestimation in multiple geolocations in the future.

本誌: 2024年9月27日情報システム研究会

本誌掲載ページ: 13-18 p

原稿種別: 英語

PDFファイルサイズ: 646 Kバイト