Using AI to improve punctuality and minimise the effects of disruption and its impact on passengers

Relevant RTS critical priority(ies):
Optimised train operations; Data driven

Rail tech disruptor, JNCTION, has launched a new Decision Support Tool (DST) to manage services and assist Train Operating Companies (TOCs) to keep delays to a minimum – addressing the leading cause of dissatisfaction for passengers.

The DST is a first-of-a-kind, real-time machine-learning tool to assist TOC Control and Service Delivery teams in making faster, more consistent and more informed decisions during disruption, reducing the associated delays and their impact.

The Software as a Service system integrates live and historical data feeds into an easy-to-use point and click interface, providing users with instant delay predictions and alerts to support them in managing the service.

The system combines multiple real-time data feeds including TRUST, incident reports from Network Rail and TOC staff, together with crew and stock diagrams, GPS positioning, and loading information, when available, to provide a dashboard of the working timetable and live mapping which shows the location of all services, and possible diversions, on the network.

Machine Learning models predict delays based on incident location, time and type and these estimates are used to calculate the impact of major disruption on the working timetable and stock and crew diagrams. DST algorithms advise train plans that will get services back to the timetable as soon as possible.

With funding from Innovate UK’s FOAK scheme, JNCTION worked closely with LNER to develop the tool, which is now deployed on the East Coast Mainline at York Rail Operating Centre (ROC).

Key features of the Decision Support Tool are the integration and co-existence with existing legacy systems, full network coverage from day one and a SaaS model that can be deployed in months instead of years.

JNCTION won another Innovate UK First of a Kind competition, for a companion project (Customer Experience Information System or CEIS) to the DST to improve customer information during disruption. The project will use AI in the form of an expert system to improve the rate and quality of information delivered to staff and customers, to address the biggest cause of dissatisfaction for passengers.

To learn more about how JNCTION are improving the travel experience of every passenger, click here.