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