{"title":"A stochastic model for reliability analysis of periodic train timetables","authors":"Mehmet Sirin Artan, İ. Şahin","doi":"10.1080/21680566.2022.2103051","DOIUrl":null,"url":null,"abstract":"Deteriorations are considered in the design phase of timetables to maintain reliability in actual operations. The response of periodic timetables to deteriorating events should be tracked and delays are desired to settle within a reasonable amount of time. We analysed an urban and intercity train service operating in separate lines in the Dutch railway network to measure their service reliability. Because trains are supposed to periodically depart from their respective terminals according to their schedules, their arrival delays and the allocated terminal slacks play a crucial role in reliability. We adopted a Markov chain model to represent the delay evolution of trains and examine their recovery patterns. The steady-state probabilities were uniquely and precisely obtained using the non-homogeneous matrices of the successive processes in combination within a cycle. It is observed that the timetables of the two train services can return to their periodicity and steady-state at most in one cycle.","PeriodicalId":48872,"journal":{"name":"Transportmetrica B-Transport Dynamics","volume":" ","pages":""},"PeriodicalIF":3.3000,"publicationDate":"2022-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Transportmetrica B-Transport Dynamics","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1080/21680566.2022.2103051","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"TRANSPORTATION","Score":null,"Total":0}
引用次数: 2
Abstract
Deteriorations are considered in the design phase of timetables to maintain reliability in actual operations. The response of periodic timetables to deteriorating events should be tracked and delays are desired to settle within a reasonable amount of time. We analysed an urban and intercity train service operating in separate lines in the Dutch railway network to measure their service reliability. Because trains are supposed to periodically depart from their respective terminals according to their schedules, their arrival delays and the allocated terminal slacks play a crucial role in reliability. We adopted a Markov chain model to represent the delay evolution of trains and examine their recovery patterns. The steady-state probabilities were uniquely and precisely obtained using the non-homogeneous matrices of the successive processes in combination within a cycle. It is observed that the timetables of the two train services can return to their periodicity and steady-state at most in one cycle.
期刊介绍:
Transportmetrica B is an international journal that aims to bring together contributions of advanced research in understanding and practical experience in handling the dynamic aspects of transport systems and behavior, and hence the sub-title is set as “Transport Dynamics”.
Transport dynamics can be considered from various scales and scopes ranging from dynamics in traffic flow, travel behavior (e.g. learning process), logistics, transport policy, to traffic control. Thus, the journal welcomes research papers that address transport dynamics from a broad perspective, ranging from theoretical studies to empirical analysis of transport systems or behavior based on actual data.
The scope of Transportmetrica B includes, but is not limited to, the following: dynamic traffic assignment, dynamic transit assignment, dynamic activity-based modeling, applications of system dynamics in transport planning, logistics planning and optimization, traffic flow analysis, dynamic programming in transport modeling and optimization, traffic control, land-use and transport dynamics, day-to-day learning process (model and behavioral studies), time-series analysis of transport data and demand, traffic emission modeling, time-dependent transport policy analysis, transportation network reliability and vulnerability, simulation of traffic system and travel behavior, longitudinal analysis of traveler behavior, etc.