The CEO of Germany’s railways, Ruediger Grube, does not want to fall behind the auto industry with autonomous mobility and has announced that Deutsche Bahn (German Railways) will operate on parts of the railway network with full autonomy “by 2021, 2022, or 2023″. Test are already underway on a part of the German railway network in Eastern Germany.
The technology for autonomous long distance trains differs greatly from the technology for autonomous metro-trains and subways which already operate in many cities of the world. In the latter case, most of the intelligence for autonomous driving is embedded into the railroad infrastructure and a centralized controller that is in constant communication with all trains; the trains themselves, in contrast have little intelligence; they don’t operate autonomously. This approach is not viable for long-distance networks because upgrading thousands of kilometers of the network with controllers and sensors would be much to costly. Therefore most of the intelligence has to be embedded within the locomotive. Fully autonomous long distance trains therefore need to be equipped with sensors and algorithms that are very similar to those used in self-driving cars.
The advantage of self-driving trains does not lie so much in cost reduction but in the ability to increase network capacity because trains can be operated with higher frequencies and at shorter distances. This also increase the flexibility of rail-based transportation solutions and makes new services possible. These capabilities are essential if railroads want to survive against the greatly intensifying competition from fully autonomous self-driving cars, trucks and buses.
German unions immediately criticized their plans. But they fail to understand that fully autonomous road-based transportation will provide an enormous challenge for the railroads. Deutsche Bahn is on the right track. They should do everything to accelerate their introduction of autonomous long distance trains.
Being fixed to a track, trains are much better suited for autonomous operation than road-based vehicles. But most of the innovation in autonomous vehicles is occurring on the road. Worldwide there are only very few efforts to develop autonomous trains (automated subways and metro lines are not autonomous – their cars are usually controlled by a central server and these lines require significant extensions of the track-side sensors and safety mechanisms which doesn’t scale for long distance rail networks). Fortunately some isolated efforts are now moving autonomous trains forward:
Global mining powerhouse Rio Tinto operates its own 1700km rail network in Australia to transport iron ire from its 15 mines to the sea ports. The company is spending more than 500 million USD to equip all its locomotives with radar, sensors and mapping technology for autonomous operation. The first trial runs have been completed successfully at the end of 2014 and up to 41 autonomous trains may begin operation in the second half of 2015! Is it a surprise that these autonomous trains are being developed by a commercial company that has its own extensive rail network rather than a traditional railway operator?
Although autonomous trains could significantly lower costs, increase capacity and flexibility, most railways are heavily regulated and are unlikely to adopt autonomous driving technology on long distance trains soon. This is unfortunate because the extreme focus on safety actually prevents useful innovations from being adopted and pushes people to other transportation mediums such as the road – with much higher risks and casualty levels.
Fortunately, the effort to develop a European Railway Traffic Managment System (ERTMS) has laid some groundwork which could be leveraged for autonomous operation: ERTMS distinguishes four levels of train control: Levels 0 to 2 rely on standard trackside infrastructure for train control – including signs and balises (transponders embedded in the track which digitally transmit location and track constraint information to the train ). But level 3 allows trains to localize themselves via sensor and retrieve track constrains and movement authority via mobile internet (GSM-Rail). This greatly increases flexibility and should simplify the introduction of autonomous railways on the many routes that are not yet equipped with automated train control infrastructure.
Mining giant Rio Tinto will invest U$518 million in autonomous trains for its long distance heavy haul rail network. The company plans to put the first autonomous train into operation in 2014. Rio Tinto currently operates 41 trains from its Australian mines to ports with 148 locomotives and 9400 iron ore cars.
The company expects productivity improvements because of greater flexibility in train scheduling and the removal of driver changeover times. Besides increased network capacity, they also expect more efficient fuel use and thus lower carbon emissions.
Generally trains are much better suited for autonomous operation than road-based vehicles because of their fixed tracks. Unfortunately, very few truly autonomous driverless trains are in operation today. While some cities have driverless commuter systems, these typically operate in carefully controlled environments where most of the intelligence is located within the rail network and little intelligence within the locomotive itself. The Rio Tinto approach needs to be different: because of the size of the rail network (1500km) most of the intelligence will have to be placed within the locomotive. Hopefully Rio Tinto will be able to demonstrate quickly that significant productivity improvements are possible by using autonomous trains and thus start the transition towards more efficient and cost effective public transportation systems. It remains to be seen, however, to what degree labour unions and train regulators will be able to limit progress in this area.
Image © Copyright 2012 Rio Tinto