Much of today’s railway relies on a system that was built by its Victorian founders, and reminders are everywhere – from the use of historic station buildings that are over a century old to paper tickets. Yet, quietly, out of sight of most, a digital revolution is beginning on the UK’s railway.
Connected sensors, the internet of things and smart data analytics are being used to cut costs, improve services and allow innovations from reactive, dynamic timetables to driverless trains.
Digital rail is the use of smart, connected technologies to modernise signalling, control centres and maintenance for trains and rail infrastructure. Such ideas are a social innovation that stands to benefit everyone, from train operators to passengers to governments funding public transport. "Rail is perfect for digital, absolutely perfect. It's been on the journey for quite a few years, though people don't realise that's what's enabling these changes to happen," says Alistair Dormer, group CEO for Hitachi Rail.
One of the first places digital rail has arrived is signalling. Rather than a driver looking at rail-side signals – which Dormer refers to as "lights on sticks" – the connected train can pick up necessary information from smart infrastructure. "You don't need lights on sticks anymore when the train knows where it is," he says. That allows trains to "know" about delays ahead, automatically adjust speeds for fuel efficiency, and travel more closely together, helping to boost capacity on the network. "Even if you still keep drivers, which many people want to do, you can have driver advisory systems that suggest timetables optimised for efficiency and fuel savings," he adds.
Smart, connected trains can also help when delays or other perturbations hit a network. Hitachi’s traffic management software is being installed across Thameslink services and will pull data from the train, the planned schedule and the rest of the network, analysing it all in real time to understand how to readjust timetables, platforms and train services to restore normal service. Such readjustments take four times as long with a human brain running the show, compared with the traffic management system, Dormer says. "We modelled a system where a train had broken down," he explains. "Using the human brain, it took something like four and a half hours for the timetable to get back to where it was supposed to be… what the system did, using mathematical optimisation that recommended 400 changes to different trains – hold that one, move that train, change this platform – solved the whole situation in less than an hour." That means faster, more reliable journeys for passengers and fewer complaints for operators.
That system is already in use in the UK, though it is limited to offering advice to human controllers on how to fix problems. In Japan, it's linked up to digital signalling and is therefore fully automated – when trouble hits, the trains fix themselves. Indeed, such systems work best the more automated a network is, making them ideal for metros with driverless trains.
And although driverless trains aren't in use across UK railways, the innovative technology has been deployed across smaller, more contained metro networks, including on the DLR and London Underground. But one project proves the technology can be used on longer train journeys: "We've taken that to the next level in Australia with Rio Tinto," Dormer says. "We're driving 2.5km-long driverless freight trains between the mine and the port. It takes 43 hours to do that cycle time in northwest Australia, and not having a driver introduces phenomenal efficiency." That's partially because human drivers would need to be switched out, meaning they'd need to travel with the train or be swapped in the middle of the desert, but the smart trains also boost fuel efficiency.
The more automated a system is, the more dynamic a timetable can be. Dormer reveals that in Copenhagen, Denmark, which has a driverless metro system, Hitachi was able to build a reactive timetable that shifted more trains to busy locations such as after football matches or concerts. "We tapped into the camera data in the stations so we knew how many people were waiting for a train," he explains. "We can analyse that and dynamically flex the timetable to stick more trains into that area and thin out the service in other places where there's fewer people waiting."
Digital rail isn't only about running trains more efficiently and getting them back on track when problems do arise. Connected sensors and the IoT are ideal for monitoring and maintenance, helping operators cut costs and keep trains running. "The trains are pumping about 15GB of data a day," says Dormer. That can be anything from monitoring the track and overhead wires to tracking wear and tear on components, and even watching when toilets need emptying.
For example, Dormer says sensors on wheel bearings help gather information to schedule maintenance as well as data about operating conditions. "The design standard for a bearing is to operate up to 200 degrees Celsius, and [because of sensors] we know it never goes above 60 degrees," he says. "Why are we building in this additional engineering when we can make it lighter, cheaper and smaller by changing the regulation and the standard with this digital evidence?"
Another example of the usefulness of the IoT is maintenance of rail infrastructure. In the UK, a special maintenance train – known as the flying banana train because of its yellow colour – is periodically run down tracks to inspect them with cameras. Those cameras and sensors, Dormer says, could easily be installed on passenger trains; indeed, they are on many already. That would avoid or at least reduce the need to send a specialised inspection train down rails in off hours, interrupting key track maintenance.
Bringing digital technologies to trains is a social innovation that can improve the lives of passengers and the budgets of operators, but it needs to be at the core of how rail infrastructure runs, Dormer adds, with everything connected and data analysed intelligently. "If you connect all the pieces of the railway, you can use analytics to find out how to dramatically improve it. We've never been able to take on such a complex picture before." And that's an innovation that helps everyone.
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This article was originally published by WIRED UK
