<p><a class="link-style-default link-page" href="#!/page/65e0928503ed1f3a8edad6cd/1" link-style="Default" data-link-target="New tab" target="_blank" data-link-type="page">G-FORCE decision-making tool becomes part of the national training programme </a>| <a class="link-style-default link-page" href="#!/page/65e0928503ed1f3a8edad6cd/3" link-style="Default" data-link-target="New tab" target="_blank" data-link-type="page">Automated Driver Competency Indicators in trial on West Midlands Trains</a> | <a class="link-style-default link-page" href="#!/page/65e0928503ed1f3a8edad6cd/5" link-style="Default" data-link-target="New tab" target="_blank" data-link-type="page">Successful demonstration of intelligent freight wagons</a> | <a class="link-style-default link-page" href="#!/page/65e0928503ed1f3a8edad6cd/6" link-style="Default" data-link-target="New tab" target="_blank" data-link-type="page">Sanding trials data continues to bring value to new research</a></p>
Helping operational staff to make confident and safe decisions when rules conflict, don’t apply, or would lead to unsafe outcomes.
Opportunities to stop small incidents escalating can be missed when front line staff lack the confidence to use their professional judgement. The best course of action when faced with specific and changing circumstances is often not captured in rules. Sometimes, dynamic reassessment of situations is needed.
Making operational decisions to keep trains moving as safely as possible is tough. We ask a lot from all of our people in very challenging situations, where rules may not exist or don’t support the best way of managing the whole-system risk. Therefore, training people in how to do this with confidence and sound rationale that is recorded to support their decision is critical. G-FORCE training really helps with this.
A review of operational decision making in rail revealed a lack of training and skills in these scenarios. The G-FORCE model was developed to address this gap. It was inspired by successful approaches in other safety-critical sectors. G-FORCE is a practical decision-making framework. It’s supported by comprehensive training and guidance materials. It gives staff the tools to navigate complex and changing situations effectively. G-FORCE plays a crucial role in reducing potential incidents and raising safety standards across the rail network.
In 2020, trials were carried out to test and refine the G-FORCE approach. The trials ran in collaboration with industry partners East Midlands Railway, Network Rail’s London and North Eastern route, VolkerRail, and North Yorkshire Moors Railway. G-FORCE has gained widespread acceptance among various train operators and Network Rail routes. It’s already empowering staff to make informed decisions that enhance safety and operational efficiency.
More recently, G-FORCE has been added to Network Rail's national training programme. Mobile and local operations managers across the country will now be trained to use the decision-making model. It will support them in making better operational decisions.
Find G-FORCE information and resources at rssb.co.uk/g-force.
We offer bespoke training to organisations on the G-FORCE model. See full details at rssb.co.uk/services-and-resources/training/operational-decision-making-using-the-g-force-model
To read about the research behind G-FORCE, go to rssb.co.uk/research-catalogue (search for T1135).
If you have any other queries about using G-FORCE in your organisation, contact Marcus Carmichael, Professional Lead, Operations and Performance: Marcus.Carmichael@rssb.co.uk
In-service trial uses train data to provide objective, long-term insights into driver performance.
West Midlands Trains is trialling Automated Driver Competence Indicators (ADCIs). The aim is to give drivers objective insights into their performance for self-improvement. This will help them prevent incidents.
The trial involves the operator’s fleet of Class 196s on the Shrewsbury to Birmingham New Street route. It uses TrainServ software to integrate OTDR data with infrastructure, signalling, and timetabling data.
The first phase of the trial gave us new insights into sub-threshold delays and dwell times, to drive performance and planning improvements. The trial has now entered a second phase. It will give individual drivers an objective and more detailed understanding of their own performance. This includes specific insights to support self-improvement. It should allow driver managers’ time to be spent more effectively on providing targeted support to drivers.
The feasibility and soundness of the ADCIs concept was first shown as part of the RSSB and the University of Huddersfield strategic partnership. Further development work with Cogitare integrated this in their TrainServ software. It showed, on a much larger scale, how the automatic processing of OTDR data could save time. Also, how it could provide richer information about driver performance.
We are looking forward to trialling a new concept of competence management where performance can be reviewed over a longer period of time than the 60-90 minutes current methods provide. We hope to identify development needs that will be instrumental in incident prevention and feed improvements in training methods, content, and error management.
Read the initial research at rssb.co.uk/research-catalogue (search for IMP-ADCI).
For more information about ADCIs and the opportunities they present for operators, contact Melissa Frewin, Senior Partnership and Research Grant Manager:
Melissa.Frewin@rssb.co.uk
Delivering some benefits of EU digital auto couplers, with less cost and disruption.
The EU is proposing to fit all freight wagons with Digital Auto-Couplers (DAC). These automatically couple wagons in a freight train. They do this both physically, via the mechanical connection and the air line for braking, and digitally, via electrical power and data connection.
The adoption of DAC requires significant investment. It would also cause disruption as wagons and locomotives need to be retrofitted. The business case for use on the GB network was therefore uncertain. In 2022, RSSB did detailed analysis to explore the benefits of DAC in the GB context.
The analysis did not find a positive business case for DAC adoption. However, there are significant advantages in having an ‘intelligent wagon’—one that enables data and power links across the formation. This could be achieved in other ways.
These conclusions supported Network Rail to unlock innovation funding to develop the intelligent wagon concept. This work was led by RailFreight Consulting. In February 2024, a six-wagon smart formation freight train was successfully demonstrated at Barrow Hill Roundhouse. It was able to provide derailment, handbrake status, loading status, axle rotation, vibration, and heat source notifications.
While this technology clearly has safety benefits, it will also promote efficient operations. Intelligent wagons can raise alarms about their condition. This is a game changer for the way wagons are maintained in the future.
For more on the DAC research, go to rssb.co.uk/research-catalogue (search for T1264).
To discuss RSSB’s programme of freight research, contact Aaron Barrett, Lead Research Analyst:
Aaron.Barrett@rssb.co.uk
For the intelligent wagon initiative, contact Peter Williams, Operations and Safety Manager at Network Rail:
Peter.Williams2@networkrail.co.uk
Wider use shows the importance of sharing publicly funded research and supporting data.
RSSB’s sander trials (T1107) led to a step change in understanding sand’s role in braking in low-adhesion conditions. The three-month programme of track testing on Class 387 four and eight-car trains returned 225 individual tests. As well as the benefits of the project’s findings, the trials also generated a valuable dataset. This is available to industry bodies and academics researching low adhesion mitigations.
The dataset includes a wide range of sanded and non-sanded tests. It also has information on site conditions, such as weather information and track condition. The richness of the data makes it ideal for use by researchers.
The dataset was first used by the University of Huddersfield. It was used to support the validation of the LABRADOR train braking model and improve understanding of the wheel slide protection performance, sanding, and cleaning effects.
Researchers at Knorr Bremse also used the data. They are part of the team working on Europe’s Rail Flagship Project 2 which aims to enable autonomous train operation. They highlighted how data from the sanders trials has been valuable to inform the work on next generation brake systems and adhesion management.
This important contribution to other projects shows the value of widespread data sharing in the industry. Also, of providing access to both the outputs and the underpinning data of publicly funded research.
To request access to this adhesion dataset, contact Sharon Odetunde, Head of Partnerships:
Sharon.Odetunde@rssb.co.uk