Analysing Capacity Bottlenecks in Rail Infrastructure by Episode Mining

被引：0

作者：

Berger, Philipp ^{[1
]}

Lenze, Wiebke ^{[2
]}

Noll, Thomas ^{[1
]}

Schotten, Simon ^{[3
]}

Bueker, Thorsten ^{[3
]}

Fietze, Mario ^{[4
]}

Kogel, Bastian ^{[2
]}

机构：

[1] Rhein Westfal TH Aachen, Software Modeling & Verificat Grp, Aachen, Germany

[2] Rhein Westfal TH Aachen, Inst Transport Sci, Aachen, Germany

[3] Quattron Management Consulting GmbH, Aachen, Germany

[4] German Ctr Rail Traff Res, Dresden, Germany

来源：

FORMAL METHODS FOR INDUSTRIAL CRITICAL SYSTEMS (FMICS 2022) | 2022年 / 13487卷

关键词：

Train delays; Capacity bottlenecks; Episode mining;

D O I：

10.1007/978-3-031-15008-1_9

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

We introduce a methodology to identify and analyse capacity bottlenecks in railway networks. It is based on operational data that has been recorded in real operation. In a first step, network areas that exhibit frequent and significant train delays are determined. Next, the actual causes of such delays are investigated by analysing interdependences between train runs and by distinguishing between primary and secondary delays. This is achieved by employing episode mining techniques to enable the systematic identification of temporal patterns that occur frequently in the data about train runs.

引用

页码：121 / 133

页数：13

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