A new predictive delay tool introduced by LNER is set to help the rail operator plan more effectively, keeping customers and trains on the move.
Machine learning experts at LNER have developed technology to predict train delays. It takes data from previous train performance, adds factors such as the number of people travelling and weather conditions, and highlights services that may encounter a delay at LNER stations.
Following a successful trial at Peterborough and Newark Northgate stations, the tool has been introduced across the LNER station network.
Available to all colleagues via their LNER mobile phone, staff can identify services with the potential for delay and adapt the support they provide for customers.
The extra foresight and planning mean that across the trial, dwell times of LNER trains at Peterborough and Newark Northgate stations improved.
Data collected showed that over 450 potential delays were avoided, helping LNER to keep trains running in accordance with the timetable.
Steven Lloyd, Machine Learning Product Lead for LNER, said: “We saw an opportunity to provide a solution for our teams, which would help them to not only deliver fantastic service to customers, but also enable them to get ahead of any potential issues.
“This solution really is the embodiment of the saying ‘to be forewarned is to be forearmed’. It highlights pinch points, enabling teams to be proactive in reducing the reason for delay.
“The data captured from the trial has been positive, so we’re now rolling out the capability across our whole station network. It’s not just the time saved either, we’re also considering the carbon savings of trains being on the move more and dwelling at platforms less. So, this solution may have even more benefits than initially estimated.”
