State Of The Railway Compiler Data Solution (SORClite): Open Access Real-Time Signalling Data
This project was one of the winners in the First Of A Kind 2022 competition run by Innovate UK.
In this document, this is said about the project.
Project No: 10038973
Project title: State Of The Railway Compiler Data Solution (SORClite): Open Access Real-Time Signalling Data
Lead organisation: PARK SIGNALLING LIMITED
Project grant: £217,128
Public description: Our project seeks to support Network Rail in regaining understanding and ownership of key
signalling asset information so that this data can be used to adopt new performance measures,
identify bottlenecks within the rail network and target the 800,000 unexplained delay minutes that
occur annually. The project combines a number of existing technologies to deliver the hardware,
pipeline, analytics, and visualisation as a working demonstration. The data stores will also be
available for use by train operators and the wider data analytics supply chain, removing some of
the systemic blockers around access to data.
My Thoughts And Conclusion
SBRI: FOAK 2022 Optimising Railway Possessions
This project was one of the winners in the First Of A Kind 2022 competition run by Innovate UK.
In this document, this is said about the project.
Project No: 10038228
Project title: SBRI: FOAK 2022 Optimising Railway Possessions
Lead organisation: FRAZER-NASH CONSULTANCY LIMITED
Project grant: £236,226
Public description: One of the biggest challenges facing the railway industry is the complex process of planning and
possession management. The logistics of diverting, blocking, or closing sections of track can have
implications across the network. As the rail timetable becomes more congested, with increased
services, there is more potential for disruption and less obvious times for possession. Delays on
main-lines could result in huge fines, consequently delivering works and handing back possession
on-time is vital.
In 2020/21, NR spent £1.6bn on enhancements, £1.9bn on maintenance, and £3.2bn on renewals
(Office of Rail and Road, 2021). This translates into thousands of engineering works, most of these
require possessions to allow safe, traffic-free worksites for maintenance activities (e.g. remedial
works, inspections, maintenance and planned renewals).
Possessions result in both planned and unplanned disruption. Unplanned disruption can occur for
many reasons; machine faults, access issues, staff planning, or wrong engineering train
arrangement – all demonstrating the complexity of planning possessions.
Getting staff and equipment to worksites on time and minimising travelling distances are critical
efficiency requirements. The barriers to this are mutual road and rail points, staff numbers and
equipment types. Furthermore, engineering trains typically start in sidings which may be in remote
locations due to available sidings being occupied during large possession works. Consequently,
this cause issues in both timetabling and plans that ensure that engineering trains reach worksites
at the correct time and in the correct formation.
With increasing traffic and reducing availability of possessions this problem is likely to be further
exacerbated. Network Rail have identified a requirement to develop solutions for planning
procedures such that possession efficiency is increased, resulting in the delivery of infrastructure
maintenance work with minimal disruption and cost.
Combining Frazer-Nash’s deep experience in optimisation of railway challenges and eviFile’s
possession management solution, we will innovate to develop a product that will support rapid
planning and replanning of possessions through the application of optimisation and ML algorithms
to identify potential optimal plans. Using wide-ranging railway possessions data we will research
and adapt algorithms that will consider (for example) multiple scenarios, locations and types of
work, and optimise and efficiently manage resources to ensure minimal impact to infrastructure
traffic and capacity.
This will deliver possessions more efficiently, help plan work-activities during possessions more
precisely, manage infrastructure access more efficiently, allow tasks to be planned more efficiently,
and predict the impact of possessions on overall network performance more accurately.
My Thoughts And Conclusion
One of the biggest construction sites near me was the A45 dualling of the 1970s. It was a nightmare as there was no system managing possessions and frequently there were temporary traffic lights and diversions.
Things have got better since then and roadworks on main roads don’t cause as much delay as they used to.
The same improvement that good project management has had on the roads, now needs to be applied to the railways.
Trains With Brains(R)
This project was one of the winners in the First Of A Kind 2022 competition run by Innovate UK.
In this document, this is said about the project.
Project No: 10036632
Project title: Trains With Brains(R)
Lead organisation: JR DYNAMICS LIMITED
Project grant: £248,046
Public description:
Trains with Brains(r) aims to integrate data from a range of remote condition monitoring sensors
into Network Rail’s monitoring and planning systems/processes, to enable operations and
maintenance teams to address key cost efficiency and performance priorities via more informed
possession planning.
This will be delivered via a head to toe monitoring solution, enabled via bi-directional integration
between Transmission Dynamics and Network Rail.
My Thoughts And Conclusion
Unauthorised Cable Removal And Fault Triage
This project was one of the winners in the First Of A Kind 2022 competition run by Innovate UK.
In this document, this is said about the project.
Project No: 10038790
Project title: Unauthorised Cable Removal And Fault Triage
Lead organisation: FOCUS SENSORS LIMITED
Project grant: £215,310
Public description: When cable thefts occur the operation of the railway, often in nationally critical locations, can be
brought to a standstill with significant impact on passengers and freight supply-chains. Under
extreme industry and public pressure, Network Rail must delay scheduled activities and scramble
teams to effect repairs and get critical railway operational systems working again. Current
technology may not be able to locate the break to better than a few km accuracy, meaning long
periods of manual inspection are required to locate the exact position of the theft before the repair
can be started. This wastes valuable time, increasing the effect of the theft on the efficiency of the
network and creating cost for operators and delays for customers.
This proposal is for a technology solution, using existing trackside optical fibre cables, which can be
used to locate cable thefts instantly to within +/- 1m. After a theft is reported or detected by other
system, automatic analysis will pinpoint the location of the acoustic signatures of the theft activity.
The location of the theft will be instantly displayed, both on a map overlay with geographical
coordinates, and as a linear ELR, miles and yards track location. This will enable first-responder
policing and security to be deployed sooner and more accurately. Secondly, with an accurately
timed and positioned event signature, there is an opportunity for other parties with evidence
collecting abilities (e.g. Forward Facing CCTV on trains) to more proactively, and possibly
automatically, to retain evidence which may support prosecution. Thirdly the Network Rail
engineering team will be given advanced information to allow them to attend the site with the right
materials and resource to affect an earlier resolution.
As secondary activity we will enable location of optical cable by creating a companion
georeferencing co-reference for the trackside fibre cable, so that faults and fibre issues can be
located instantly to a more precise physical location. This provides a valuable tool for Network
Rail’s engineering teams, to reduce time for maintenance and fault finding.
My Thoughts And Conclusions
My software; Daisy was used by British Rail or was it Railtrack to analyse cable faults many years ago. Because of the discussions, we had at the time, I believe that this could be a very successful project.
Optimal Prediction of Sand For Adhesion
This project was one of the winners in the First Of A Kind 2022 competition run by Innovate UK.
In this document, this is said about the project.
Project No: 10039258
Project title: Optimal Prediction of Sand For Adhesion
Lead organisation: GOVIA THAMESLINK RAILWAY LIMITED
Project grant: £153,228
Public description: Train services are affected by seasonal variables particularly leaf fall between September and
December. They can also be compromised by wet weather, icy and snowy conditions at a regional
or very localised level on a particular route. Maintaining wheel-rail contact to ensure adequate and
safe braking requires the use of sand in low adhesion conditions. Sand is dispensed to trains in
response to a combination of train service plans and of weather forecast. However, not all trains
are currently able to be replenished during overnight stabling and servicing with attendant risks of
delays and damage to trains and infrastructure. Also, there is a high level of safety risk when sand
replenishment on trains is carried out on a third-rail yard.
“Optimal Prediction of Sand for Adhesion” (OPSA) lead by Govia Thameslink Railway, the major
Train Operating Company on third rail in the UK, will deliver a more efficient and cost-effective
means of predicting the dispensing of sand to trains to ensure services are not compromised by
adhesion losses and train sets are not required to be removed from planned operating diagrams
because of inadequate on board sand supplies. The algorithm developed as a results of this project
will base the estimates on an integrated framework that includes the forecast adhesion, track
maintenance and the expected speed profile in order to capture the change in weather and the seasonal factors.
The algorithm developed represents a cost effective solution to predict the use of sand and
schedule the maintenance of trains enhancing in turn safety and reducing the impact of delays on
the timetable. The algorithm will be developed including direct measure of sand dispersion, braking,
wheel slip and line speed diagram also accounting for human behaviour effects such as driving
style.
Govia Thameslink Railway has engaged with Cranfield University to deliver the disruptive
innovation proposed in this project. The algorithm will enable a more efficient train scheduling
improving public performance measure (PPM) addressing train delay targeting in particular the
25% of delay up to 15 minutes cause by several concurrent issues including train rescheduling and
the National Rail Passenger Survey satisfaction.
My Thoughts And Conclusions
FEIDS – FOAS Enabled Intruder Detection System
This project was one of the winners in the First Of A Kind 2022 competition run by Innovate UK.
In this document, this is said about the project.
Project No: 10038989
Project title: FEIDS – FOAS Enabled Intruder Detection System
Lead organisation: THALES GROUND TRANSPORTATION SYSTEMS LIMITED
Project grant: £223,660
Public description: Intruders in a railway environment and critical sites are a major problem for the rail industry, and
one that can cause severe delays if not prevented. Conventional monitoring technology is low
range, impractical and has a high deployment and operational cost. Instead, a system that can
monitor the perimeter of a large area with minimal human supervision and can be used to direct rail
staff to the correct location is required to introduce work efficiencies.
Thales’ subcontractor Focus Sensors have developed the technologies capable of delivering a
persistent perimeter detection system that can detect persons approaching a site before they reach
the perimeter boundary and alert railway staff to their precise location. This will support railway staff
to respond effectively and reduce delay minutes, insuring efficiency and cost benefits.
We propose to showcase a first-of-a-kind application of Focus Sensors’ next-generation Fibre Optic
Acoustic Sensing (FOAS) technology to deliver accurate and real-time information and alerts on
intruders or potential intruders in a rail environment using our lateral-positioning technology
developed for detection trains. This capability will enable security staff to rapidly respond to
incidents and ensure intruders can be dealt with quickly and efficiently.
The FOAS-Enabled Intrusion Detection System (FEIDS) will use FOAS to detect objects moving
near the fibre/perimeter, identify them and determine the distance from a boundary. This monitoring
is both real-time and persistent, enabling alerts to be sent when a person or vehicle gets too close
to or crosses a boundary. The high fidelity of the system means that an intruder’s location can be
determined to an accuracy of +/- 50cm, and this information is crucial to ensuring that on-site
security teams are able to quickly and efficiently deal with the intruder.
This technology can be utilised both along sections of the railway and at specific, sensitive sites.
Due to the long range and autonomous nature of the system, it drastically reduces the workload of
railway staff. Staff will be provided with an automatic alert that will provide them with information on
the nature of the intruder(s) and the exact location. This reduces the time for intervention, enabling
trains slowed due to the risk to resume at normal speed quicker, lowering the impact of trespass. It
also increases the likelihood of trespassers being stopped committing vandalism, which can disrupt
operations, and reduces the likelihood of reoffending.
My Thoughts And Conclusions
NextGen Data-Driven Timetable Performance Optimisation Tool
This project was one of the winners in the First Of A Kind 2022 competition run by Innovate UK.
In this document, this is said about the project.
Project No: 10037862
Project title: NextGen Data-Driven Timetable Performance Optimisation Tool
Lead organisation: ARTONEZERO LIMITED
Project grant: ££157,826
Public description:
During the pandemic, the on-time reliability of services significantly increased due to the reduction
in the number of services and passengers.
However, as passengers have returned to the railway performance has once again deteriorated.
This has an even greater impact on the industry post-pandemic as passengers’ expectations for services that are reliable and run on-time is even higher. Increased delays and passenger dissatisfaction therefore leads to an even greater decreased revenue from ticket sales.
Poor performance is in large part due to a poorly planned timetable that is often operationally unachievable or cannot handle minor perturbations. This is due to the timetable usually being planned with simulations and the method does not in how trains performing in reality at junction or stations.
Through years of working closely with performance, planning and operational teams, we’ve identified that by using granular train movement data and machine learning techniques, the actual performance of the existing timetable could be accurately calculated. This would enable planners with accurate information to make faster and better planning decisions that are based on real-world evidence.
Our Timetable Analysis tool will deliver automatically updated insights and recommendations to planners that is highly aligned to the planning process. Utilising both on-track (track circuit) and onfleet (GPS and OTMR) data, the tool will provide an integrated view to both Network Rail and TOC teams.
Fundamentally this tool will result in a step change in the speed and quality of timetable planning, moving away from the use of limited simulations and anecdotal experience to a fully evidenced-based approach.
EventGo – Intelligent Rail Service Demand Forecasting for Event-Based Travel
This project was one of the winners in the First Of A Kind 2022 competition run by Innovate UK.
In this document, this is said about the project.
Project No: 10037294
Project title: EventGo – Intelligent Rail Service Demand Forecasting for Event-Based Travel
Lead organisation: YOU. SMART. THING. LIMITED
Project grant: £249,946
Public description:
Aim: EventGo will demonstrate a first-of-a-kind solution for accurately predicting how large visitor events impact demand for specific railway services, generating advance insight on rail capacity, and enhancing the ability of TOC planning teams to optimally plan and deliver railway timetables and services. Data-enabled decision-making is expected to improve overall TOC operational performance, as demand is more precisely matched with supply in order to realise new cost efficiencies, improve yield, and deliver enhanced customer experiences. The project outcomes address the competition’s plan resilience and recoverability theme.
Challenge: Large visitor events create extreme demand peaks within the railway network. Though such events are often scheduled months in advance, accurately predicting how this demand is likely to impact a specific scheduled railway service is notoriously complex due to the lack of advance data about visitors’ travel plans. In leu, TOCs often rely on best guess estimations. As recent UEFA Champions League finals in Pairs demonstrated, underestimating visitor travel can have severe consequences for an organisation’s reputation, and visitor safety.
Project: A mature EventGo prototype solution will be deployed by UK TOC planning team to predict how a series of sporting fixtures between January and March 2023 in the Yorkshire region are likely to impact time-tabled railway services. During this period, partners will investigate how advanced insight generated by EventGo can be exploited by planners to make intelligent adjustments to scheduled services, e.g., adding capacity to specific services to match high
demand, to ensure optimal asset utilisation and deliver the highest level of customer experience.
Value: Demonstration in a live railway environment allows partners to both verify the accuracy of the model’s rail travel demand prediction, and to evidence the business value such intelligence can have on TOC operations. In addition, accrued results will facilitate product approval procedures and raise the visibility of the novel solution in the target market.
Consortium: The project is led by You. Smart. Thing. (“YST”), a specialist in intelligent mobility solutions, and supported by two UK TOCs, a top-tier sporting institution and stadium management company, and regional government partners. Professional project management is provided by In The Round (“ITR”), a UK-based consultancy specialising large visitor events travel management.
My Thoughts And Conclusions
I have been caught up in bad event planning several times and feel that this project could be very useful to plan passenger movement at large events.
I doubt, it will be a solution, that only has UK applications.
Automating Freight Access Right Management And Spot Bidding Using Novel And Modern Software To Drive Modal Shift From Road To Rail
This project was one of the winners in the First Of A Kind 2022 competition run by Innovate UK.
In this document, this is said about the project.
Project No: 10039135
Project title: Automating Freight Access Right Management And Spot Bidding Using Novel And Modern Software To Drive Modal Shift From Road To Rail
Lead organisation: HACK PARTNERS LTD.
Project grant: ££322,420
Public description: Automating today’s manual processes associated with access right management and spot bidding and wrapping these digital processes in an intuitive, integrated, modern, bespoke and scalable user system. The benefits of this innovation are not only cost efficiency but also enabling a much better experience to freight customers to drive modal shift.
Levelling Up Freight
This project was one of the winners in the First Of A Kind 2022 competition run by Innovate UK.
In this document, this is said about the project.
Project No: 10037240
Project title: Levelling Up Freight
Lead organisation: 3SQUARED LTD.
Project grant: £393,271
Public description:
Background
Rail freight is vital to Britain. It contributes almost £2.5bn to the economy and plays a big part in reducing congestion and emissions. Rail is more environmentally friendly than road, with every tonne of freight transported by rail producing 76% less emissions compared to road (RDG “Levelling Up Britain” 2021). The green benefits of rail freight are being driven heavily by the DfT with incentive schemes such as Modal Shift Revenue Support (MSRS) – a £20m grant, which
freight carriers can bid for a share of to support modal shift to rail.
Despite widescale use of MSRS, finding new freight routes for additional trains is challenging because:
- Road haulage is seen as easier and more accessible than rail freight, especially at short
notice, for short journeys and for single containers. - Highways are less regulated with no significant barriers to commercial participation, and
therefore are free to use the latest technologies to develop and evolve solutions at a faster
pace. - Railway planning systems and processes limit the availability and visibility of freight paths
(slots in the timetable which can accept a freight train) resulting in under-utilisation of
network capacity.
Our innovative freight planning solution (PathPlanner) will make the use of rail for freight as
accessible and easy to use as the road network. PathPlanner is specifically designed to overcome
the current operational challenges and blockers that make moving to rail prohibitive.
Proof-of-Concept Demonstration
In 2021, NR completed a £17m upgrade around Southampton to enable longer trains in/out of the docks. Completing April 2023, Solent Stevedores is investing c.£3m to strengthen their capability to receive and dispatch longer and more trains – from 9 to 16 per day.
However, NR’s business case did not include any understanding of capacity in/out of the port, so
Solent Stevedores is currently unsighted as to how, or if, they can find the additional paths.
There are significant gains to be made if they can; 7 extra trains equate to:
- £12.6m additional revenue p.a.
- A reduction of 55,000 HGVs.
- A reduction of carbon by 1,165 tonnes.
Our project will demonstrate a Proof-of-Concept solution at Southampton Docks that will facilitate
Solent Stevedores, and Eddie Stobart Logistics (ESL) – 2 off our project partners – to find additional
freight paths and transfer containers from HGVs to trains.
My Thoughts And Conclusions
As I programmed scheduling and resource allocation systems for forty years, I am probably one of the most experienced programmers at writing this type of system.
That experience suggests that their objectives are possible.
The Anonymous Widower 