Xiong Yang
National Engineering Laboratory of Integrated Transportation Big Data Application, Technology, Chengdu Sichuan/National United Engineering Laboratory of Integrated and Intelligent Transportation, China Southwest Jiaotong University, Chengdu Sichuan, China
Yafei Hou
National Engineering Laboratory of Integrated Transportation Big Data Application, Technology, Chengdu Sichuan/National United Engineering Laboratory of Integrated and Intelligent Transportation, China Southwest Jiaotong University, Chengdu Sichuan, China
Li Li
National Engineering Laboratory of Integrated Transportation Big Data Application, Technology, Chengdu Sichuan/National United Engineering Laboratory of Integrated and Intelligent Transportation, China Southwest Jiaotong University, Chengdu Sichuan, China
Chao Wen
National Engineering Laboratory of Integrated Transportation Big Data Application, Technology, Chengdu Sichuan/National United Engineering Laboratory of Integrated and Intelligent Transportation, China Southwest Jiaotong University, Chengdu Sichuan, China
Download articlePublished in: RailNorrköping 2019. 8th International Conference on Railway Operations Modelling and Analysis (ICROMA), Norrköping, Sweden, June 17th – 20th, 2019
Linköping Electronic Conference Proceedings 69:76, p. 1158-1173
Published: 2019-09-13
ISBN: 978-91-7929-992-7
ISSN: 1650-3686 (print), 1650-3740 (online)
Trains are inevitably subject to interference from the external environment and internal systems during operation, leading to delays and conflicts. In this regard, there are usually buffer times allocated at (in) the station (section) in the train timetable, to recover delays. Most of the existing methods that deal with the buffer time allocation mainly consider the length of the section and the traffic density. These methods usually fail to consider the impact of the actual delay of trains, and the buffer time allocation (BTA) is unreasonable. The integration of the actual delay effects into the BTA needs to be resolved. Based on this, in this work, a delay time distribution model was established, and the models were compared according to the standard error of each parameter in the model. Subsequently, based on the delay distribution, a BTA model with weighted average delay expectation time as the objective function was constructed in which the weight coefficients were determined based on the delay strength, and the model was solved by a mathematical analysis method. Different allocation models were designed for different ranges of the total buffer time values. Finally, taking the Dutch railway network trunk section Maarssen–Utrecht Centraal (Mas–Ut) as an example, the results show that the buffer time after redistribution of the BTA model reduces the expected delay time in the segment by 5.25% compared with the original buffer time of the station, indicating that the BTA is reasonable.