Big Data to avoid SPADs (Rail Technology Mag)

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“New tool uses ‘incontrovertibly accurate’ big data algorithm to avert SPADs – A new software has used big data involving more than a hundred million incidences of trains approaching signals on the UK rail network in order to help operators ensure that the likelihood of trains passing red lights are vastly reduced.

“Created by the University of Huddersfield’s Institute of Railway Research (IRR) in partnership with the RSSB, the software – called RAATS, or Red Aspect Approach to Signals – analysed Network Rail’s live feeds to develop an algorithm that provides, for the first time ever, an “incontrovertibly accurate figure” for the number of times on which the signals are at red – meaning the driver must brake.

“IRR experts explained that the data is important in itself for understanding the overall likelihood of SPADs and working to prevent them. But the software will also be of huge value to rail companies, which will now be able to focus on individual signals and the number of occasions on which they have been red when approached by a train.

“This can therefore have significant implications for driver training on specific routes, timetable planning and other strategic issues…”

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Written by Long Branch Mike