Advanced monitoring and management information of railway operations

Improving the performance of railway infrastructure and train services is the core business of railway infrastructure managers and railway undertakings. Train delays decrease capacity, punctuality, reliability and safety, and should be prevented as much as possible. Furthermore, increasing infrastructure capacity utilization causes increased risk of route conflicts and secondary delays, which on its turn prevents increasing infrastructure capacity utilization. Dense railway operations therefore require feedback of operations data to improve planning and control. Typically, train delays at stations are monitored and registered online using train detection, train describers, and timetable databases, but the accuracy is insufficient for process improvements and, in particular, delays due to route conflicts are hard to recognize from delays at stations. To assess the problem of route conflicts, accurate data on the level of track sections and signal passages are required, which can be found in train describer records. This paper presents the data mining tool TNV-Conflict based on train describer records and the add-on analysis tool TNV-Statistics that automatically determines chains of route conflicts with associated secondary delays, and rankings of signals according to number of conflicts, time loss or delay jump. This information is used to automatically identify and analyze structural and serious route conflicts due to timetable flaws or capacity bottlenecks. The aim of TNV-Statistics is to relieve the analyst from routine, time-consuming, and error-prone data processing tasks, so that the available time can be devoted to analyze and manage revealed operations problems. A case-study of real data on a busy railway corridor in The Netherlands demonstrates the tool.