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Red Aspect Approaches to Signals (RAATS)

‘Big Data’ techniques are providing the rail industry with better information on its exposure to the risk from signals passed at danger, which could provide benefits beyond safety.

As part of a strategic partnership with the University of Huddersfield, RSSB has analysed over 100 million incidences of trains approaching signals on the UK network. The analysis was used to develop an algorithm for the Red Aspect Approach to Signals (RAATS) toolkit.

RAATS identifies the number of times signals are approached at red, which was previously estimated based on information from driver surveys. It provides a breakdown of the different types of approaches and considers factors such as the train type, the time of day and the day of the week.  This helps the industry understand the overall likelihood of Signals Passed at Danger (SPADs), and this information can be used to enhance driver training and timetable planning. RAATS, which is available to operators free of charge, is currently being refined and tested, and the relaunch of RAATs with an up-to-date data set is planned for late spring/early summer 2019. 

A follow-on project is combining RAATS analysis with TRUST data to provide a method for analysing red aspect approach data for particular train journeys. Red Aspect Approaches by Train Journey (RABYTs) will expand the range of industry stakeholders that can benefit from the data by presenting it in a form that helps operators identify and understand the causes of service delays, and by providing the ability to analyse and understand where time is lost in order to reduce delays. Initial results are expected by the end of 2019.

Watch a short video below of George describing the RAATS tool.

Topics covered

  • Red Aspect Approaches to Signals (RAATS)
  • Signals Passed at Danger (SPADs)
  • Risk management
  • Driver training
  • Timetable planning
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