Spatio-temporal trajectory estimation based on incomplete Wi-Fi probe data in urban rail transit network
作者：
Highlights：
• This study extends personalization and timeliness into the SST estimation.
• A new algorithm is developed by integrating structurally heterogeneous data sources.
• The estimated trajectory describes detailed information both on-board and at stations.
• Real-world analyses are conducted for the URT network with the largest route length in China.
• This is the first attempt to find out all the routes and trains at the network level.
摘要
•This study extends personalization and timeliness into the SST estimation.•A new algorithm is developed by integrating structurally heterogeneous data sources.•The estimated trajectory describes detailed information both on-board and at stations.•Real-world analyses are conducted for the URT network with the largest route length in China.•This is the first attempt to find out all the routes and trains at the network level.
论文关键词：Urban rail transit,Trajectory estimation,Spatio-temporal network,n-gram method,Wi-Fi probe data
论文评审过程：Received 26 June 2020, Revised 6 October 2020, Accepted 12 October 2020, Available online 16 October 2020, Version of Record 27 October 2020.
论文官网地址：https://doi.org/10.1016/j.knosys.2020.106528
