The performance of Tyne and Wear Metro system in the UK is measured on a headway basis, and gaps in service that are 4 min or more in excess of scheduled gaps are investigated and the cause documented. The metro system has a number of infrastructure constraints including single-line sections, junctions and level crossings, all of which have to be taken account of when constructing the timetable, in order to avoid trains being held by the signalling system, causing delays. The objective of this study is to analyse delays less than 4 min, which are not investigated or attributed to a cause, known as sub-threshold delays. The purpose of the analysis is to identify regularly occurring issues which are due to the timetable, in order to recommend changes. Two different data sets were used. The first data set explored specific trains, areas and times of day where delays were highest. The second data set allowed us to drill down on each of those in greater detail by studying station departure times for each train. A number of options to resolve the issues identified during the analysis are proposed. Whilst the results are specific to the Tyne and Wear Metro system, the methodology is suitable for use by other urban rail transit systems. The study identified several areas of future work including resolving data recording issues, carrying out further investigation of trains at peak times in particular scenarios, and automating the analysis through the use of other software.

中文翻译：

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数据分析研究泰恩河和磨损地铁列车的亚阈值延误

英国Tyne and Wear Metro系统的性能是按时进行衡量的，调查了超过预定间隔4分钟或更长时间的服务间隔，并记录了原因。地铁系统具有许多基础设施限制，包括单线路段，交叉路口和平交路口，在构建时间表时必须考虑所有这些限制，以避免信号系统持有火车而造成延误。这项研究的目的是分析少于4分钟的延迟，这些延迟没有被调查或归因于亚阈值延迟。分析的目的是确定由于时间表而经常发生的问题，以便提出更改建议。使用了两个不同的数据集。第一组数据探索了特定的火车，延误最大的区域和时间。第二个数据集使我们可以通过研究每列火车的发车时间来更详细地挖掘每个数据。提出了许多解决方案，以解决分析过程中发现的问题。虽然结果仅适用于泰恩威尔大街地铁系统，但该方法适用于其他城市轨道交通系统。该研究确定了未来工作的几个领域，包括解决数据记录问题，在特定情况下在高峰时间对火车进行进一步调查，以及通过使用其他软件来自动进行分析。提出了许多解决方案，以解决分析过程中发现的问题。虽然结果仅适用于泰恩威尔大街地铁系统，但该方法适用于其他城市轨道交通系统。该研究确定了未来工作的几个领域，包括解决数据记录问题，在特定情况下在高峰时间对火车进行进一步调查，以及通过使用其他软件来自动进行分析。提出了许多解决方案，以解决分析过程中发现的问题。虽然结果仅适用于泰恩威尔大街地铁系统，但该方法适用于其他城市轨道交通系统。该研究确定了未来工作的几个领域，包括解决数据记录问题，在特定情况下在高峰时间对火车进行进一步调查，以及通过使用其他软件来自动进行分析。