A piece looking ahead to Machine With Vision’s participation at ‘The Rise of IoT and Big Data in Rail’ 2024 event in Cologne, Germany.

What does Network Rail’s new positioning standard state, what has changed and why is RailLoc different to GNSS and Inertial based systems?

Continuing our involvement with Network Rail's Class 153 project, which now includes the next generation of Plain Line Pattern Recognition (PLPR). Our RailLoc system working hand in hand with OmniVision Edge from Omnicom Balfour Beatty to provide accurate and timely results to the end users.

Why do we need accurate location?

Accurate positional data and location is needed for superior Infrastructure Measurement (IM), leading to gains in process, safety, productivity, time and of course cost.

GNSS

There are now multiple GNSS (Global Navigation Satellite Systems) constellations available for our use. The original one Navstar (commonly known as GPS – Global positioning System) was developed by the US in the late ‘70s. This is now supplemented by Glonass (Russia), Galileo (Europe), Beidou (China), QZSS (Japan), IRNSS (India). In the UK for instance, we typically get good coverage from GPS, Glonass and more recently as newer receivers support it, Galileo becoming operational.

Other sources of error

The errors in GNSS/INS measurement are not the only source of positional error - a set of Lat/Long coordinates in a certain datum is probably no use to anyone, these need either attribution against a network model (to get some kind of engineering geography reference and linear measure) or a separate device to interpret them (such as a handheld GNSS device to direct maintenance workers to their target). If we start with the latter, we send a maintenance worker out with a pair of coordinates alone to fix a fault - will they be able to find it?

Other sources of position

So, what can be done to correct/supplement the position to ensure correctness? There are a number of existing methods out there. The first one we have discussed is a correction service to try and remove GNSS errors (RTK, PPK, Terrastar) - there are constraints with these, availability of correction service, time constraints and satellite availability. There is the option to use physical infrastructure such as balises, RFID tags - these rely on physical installation (and survey), maintenance and are not available throughout the network. Care also must be given to ensuring that the events generated by these are consumed at the correct level by dependant systems (so not to introduce a time-based error). These also must be “mapped” to the network model being used (this not only involves traditional survey, but a potential shift and attribution to the network model so that these “speak” the same language as the positioning and measurement systems) .

RailLoc

Traditionally other sources of position have been used to supplement GNSS (including using Inertial Measurement units for navigation), if we had a more consistent version of the truth, we could flip this on its head and use this as the source and supplement with GNSS (and inertial) where this information is not available.

Additional possibilities with RailLoc

Change detection

As the infrastructure changes, the features used in the RailLoc map do too. This could involve a feature gradually moving (as bits of ballast shift and settle) or a feature no longer being present. Both can lead to additional benefits.

We are really proud of the work and collaboration with Network Rail, Porterbrook, DG8, One Big Circle on the Class 153 project for ‘Safer Switches and Crossings’. This industry-changing work was a real collaborative achievement and demontrated a significant can-do attitude by all those involved in a very compressed time frame.

Things you should know about Machines With Vision’s RailLoc:

• Positions data to 30mm (validated by @NR)

• Works everywhere on the railway including tunnels and station areas

• Works in all conditions, light/dark, rain, wind

• Geospatial and linear reporting

• Works at speeds up to 125mph (proven recently in Switzerland)

RailLoc from Machines with Vision positions your measurement data to 30mm time after time. This level of accuracy has been demonstrated at the RIDC on one of the new Class 153 VIU trains. This level of accuracy is available to any system that is tightly synchronised to RailLoc, the accuracy remains the same even in areas such as tunnels and covered stations and has been approved by Network Rail, with assistance from Brendan Rice MSc, CEng MIET. It surpasses the requirements in the current positioning standards.

Our logo is looking great along with our partners on the snazzy new livery for Network Rail’s Class 153 fleet.

We are delighted to share that Machines With Vision are Carbon Neutral.

Machines With Vision are getting ready to take part in this week’s Rail Live, a key event in the industry calendar attended by delegates from across the rail sector at the Long Marston Rail Innovation Centre in Warwickshire.

Last week, the Machines With Vision team were out in Cologne, Germany at the ‘Rise of IoT and Big Data in Rail’ event, with delegates from across the global technology and transportation worlds.

In advance of next week’s ‘Rise of IoT and Big Data in Rail’ event in Cologne and for our very first ‘Mind behind the machine’ article, we recently sat down with Anthony Ashbrook, Co-founder and CEO, to discuss all things innovation, robotics and Machines With Vision’s foray into the world of rail.

Machines With Vision are set to exhibit and present its industry changing innovations for the very first time at the world renowned ‘Rise of IoT and Big Data in Rail’ event, since securing its £2.6m investment earlier this year.

Test evidence from a recent project shows that Machines With Vision’s RailLoc improves repeatability, when compared to the existing positioning system, by an incredible factor of 100

From reactive, preventative, condition-based and towards effective condition mapping and predictive maintenance.