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TDCT: Transport Destination Calibration Based on Waybill Trajectories of Trucks

  • Kai Xuan Zhu
  • , Tao Wu
  • , Wenyi Shen
  • , Jiali Mao*
  • , Yue Shi
  • *此作品的通讯作者
  • East China Normal University

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

Accurate transport destination is significant for improving efficiency in bulk logistics. But actually, the address information and the coordinate of latitude and longitude of transport destination are often incorrect due to manual input errors or vague address. Constantly generated logistics data including trucks’ trajectories and waybills allows for the possibility of calibrating transport destination by analyzing staying behaviors of trucks. In this paper, we propose a transport destination calibration framework, called TDCT. Through clustering stay points into stay areas and then merging nearest stay areas based on turn-off location, stay hotspot can be ensured properly located. Further, a binary classification method by combining behavior features and area features is present to distinguish transport destination from other types of stay hotspots. Finally, a demo system is built for a steel logistics company to showcase the effectiveness of TDCT.

源语言英语
主期刊名Web and Big Data - 6th International Joint Conference, APWeb-WAIM 2022, Proceedings
编辑Bohan Li, Chuanqi Tao, Lin Yue, Xuming Han, Diego Calvanese, Toshiyuki Amagasa
出版商Springer Science and Business Media Deutschland GmbH
435-440
页数6
ISBN(印刷版)9783031252006
DOI
出版状态已出版 - 2023
活动6th International Joint Conference on Asia-Pacific Web (APWeb) and Web-Age Information Management (WAIM), APWeb-WAIM 2022 - Nanjing, 中国
期限: 25 11月 202227 11月 2022

出版系列

姓名Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
13423 LNCS
ISSN(印刷版)0302-9743
ISSN(电子版)1611-3349

会议

会议6th International Joint Conference on Asia-Pacific Web (APWeb) and Web-Age Information Management (WAIM), APWeb-WAIM 2022
国家/地区中国
Nanjing
时期25/11/2227/11/22

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