Train-movement situation recognition for safety justification using moving-horizon TBM-based multisensor data fusion
作者：
Highlights：
• The moving-horizon multisensor data fusion approach using transferable belief model is proposed.
• The proposed approach is used for train-movement situation recognition and safety justification.
• The satellite positioning system is utilized to improve train operation safety.
• The case study testifies the effectiveness at preventing railway accidents.
• The proposed approach provides a way to fault diagnosis of train control systems.
摘要
•The moving-horizon multisensor data fusion approach using transferable belief model is proposed.•The proposed approach is used for train-movement situation recognition and safety justification.•The satellite positioning system is utilized to improve train operation safety.•The case study testifies the effectiveness at preventing railway accidents.•The proposed approach provides a way to fault diagnosis of train control systems.
论文关键词：Evidence theory,Transferable belief model,Safety analysis,Train movement pattern,Automatic trajectory analysis,Fault diagnosis
论文评审过程：Received 16 February 2019, Revised 27 March 2019, Accepted 16 April 2019, Available online 20 April 2019, Version of Record 22 May 2019.
论文官网地址：https://doi.org/10.1016/j.knosys.2019.04.010
