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Ingegneria Sismica

Ingegneria Sismica

A Statistical Model Checking Approach to Reliability Assessment of Railway Marshalling-Yard Operation Plans

Author(s): Yong Zhang1, Hongyang Zhang2,3, Qiang Xu4
1School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, Beijing, China
2Communication and Signaling Research Institute, China Academy of Railway Sciences Corporation Limited, Beijing 100081, Beijing, China
3The Center of National Railway Intelligent Transportation System Engineering and Technology, China Academy of Railway Sciences Co., LTD, Beijing 100081, Beijing, China
4Beijing HUA-TIE Information Technology Co.,LTD, Beijing 100081, Beijing, China
Zhang, Yong., Zhang, Hongyang., and Xu, Qiang. “A Statistical Model Checking Approach to Reliability Assessment of Railway Marshalling-Yard Operation Plans.” Ingegneria Sismica Volume 43 Issue 2: 1-23, doi:10.65102/is2026916.

Abstract

Railway marshalling yard operation is developing towards high density, fast turnover and fine scheduling, which puts forward higher requirements for reliability verification of hump disassembly plan. The operation plan of a railyard involves discrete events such as train arrival, locomotive occupancy, hump authorization, carriage roll-off and fault recovery. Traditional empirical verification is difficult to accurately describe the completion probability under random disturbances. In this paper, statistical model checking method is used to analyze the reliability of railway marshalling yard operation plan. In this paper, the main controller, train, shunting locomotive and hump signal system are abstract as timed automata with stochastic time semantics. The synchronization channel is used to describe the events of unwinding start, roll-off success, roll-off failure and recovery confirmation. The results show that the number of cars in track 1 converges from 5 to 7, the unrecoverable failure probability is 0.48%±0.01%, and the completion probability of Train(2) reaches 0.9558 at 330min. Disturbance experiments show that the arrival rate and recovery rate will change the controller state occupancy time and the tail train completion probability. The results show that statistical model checking can provide quantitative verification basis for reliability evaluation of railway marshalling yard operation plan.

Keywords
Railway marshalling station; Statistical model checking; Sequential automata; Reliability evaluation

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