The Seasonal Intelligence Platform

The Friction Affliction: How falling leaves cause delays on the railway

Every Autumn in the UK, thousands of tonnes of leaves fall on to the railway line. This causes a thin film to build on the top of the rail, which gets more slippery with each passing train. Special treatment trains have to be used to clean the track and prevent the build up of any fallen leaves.

The RSSB estimates that poor rail adhesion has a £290 million negative impact on performance every autumn and costs £64 million to prevent and clean the railways. Low adhesion causes a safety risk through longer braking distances, and slows passenger services through poor traction and drivers having to navigate more carefully.

To combat these issues, Route Reports and Porterbrook have collaborated with Network Rail to deliver the Seasonal Intelligence Platform, a complete solution for monitoring both network adhesion and seasonal treatment strategies.

At present, the Seasonal Intelligence Platform is driven by data from Porterbrook’s Electrostar fleet, currently operated by Southern Railways.

Porterbrook’s Passenger Fleet Data Offering

Porterbrook's passenger vehicles make thousands of journeys daily. Collectively, the fleet travels across the entire UK railway network several times a day - generating and recording billions of event-based data points.

The Potential of Network Rail’s Treatment Trains

Network Rail has a large number of treatment trains, including Multi-purpose vehicles (MPVs), Railhead Treatment Trains (RHTTs) and Snow and Ice Treatment Trains (SITTs), which are highly active in the autumn and winter months. However, these fleets are not digitally well-equipped for tracking and recording data, and much of their operation is documented manually. As part of the Seasonal Intelligence Platform, Route Reports' devices are installed on the trains to track vehicle location and exactly where treatments have or have not occurred - integrating into the Seasonal Intelligence Platform.

Core Features

Near Real-Time Low Adhesion Mapping

Passenger fleets generate millions of data points daily. Opportunities have previously been identified by the RSSB for using this data for identifying areas of poor adhesion.

The Seasonal Intelligence Platform takes the raw passenger train data and turns it into valuable insights. This allows treatment controllers to know exactly where, when and why an adhesion event has occurred. The benefit of this is further multiplied as over 100 trains currently send data into the platform- allowing decisions to be made with the entire network in mind.

The platform can also identify issues with specific trains, allowing fixes to be actioned to ensure better service quality.

Individual Adhesion Hotspots are shown, compared to areas of delay

Treatment Train Monitoring

To provide Adhesion Controllers and managers with the information needed to manage the network, data about the treatments is as important as data about the low-adhesion problem areas. However, this data is typically not digitised, and accessing it is time-consuming and provides very approximate data. 

Route Reports have fitted hardware to the treatment fleet which provides information on where the trains are (and have been) at 1-second granularity, which track sections were treated or not (including both water jetting and de-icing), and the speed of travel during the treatment. 

This data is passed from the devices every second, allowing for real-time tracking of the fleet positions and the treatment status of all track sections. 

Each section can be selected to show detailed information

Benefits and Efficiencies

Monitoring Effectiveness of Treatments

While treatment plans have been laid out on the basis of the experience of staff, and on a reasonable scientific and intuitive basis, it is currently difficult to exactly assess how effective the treatment strategies are. Without this knowledge, it is then difficult to determine how best to improve the treatment routes, timings, methods, and planning. 

Combining the objective WSP and treatment data allows for in-depth analysis of the effect of individual treatments on each track section. 

The following graph demonstrates the possibilities provided by the datasets gathered within the Seasonal Intelligence Platform. The vertical dotted lines indicate the timing of treatments across a 50m section of track, and the blue line indicates WSP activations, with line increasing by 1 step for each activation.

Through this analysis, different types of treatment (such as at different speeds) can be compared in order to understand their effect on adhesion, and to drive progress in new treatment methodologies. For example, the average decrease in the occurrence of WSPs after a treatment can be calculated, as well as the length of time for which a treatment remains effective after one pass - providing data for altering the frequency of treatments.

This can be repeated for various track sections to identify differences in the response to treatment, which can allow for the reprovisioning of resources to areas that need it more.

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