Autonomous mobility will be collective, systemic, connected and tailored

For rail to be the most attractive option for urban, regional and international travel, trains need to provide the highest levels of quality, reliability and efficiency. This is where autonomous train operation comes into play. Digitalising certain train operations, compiling data and employing the advanced processing capacities of artificial intelligence can ensure a shift towards sustainable rail transportation by making journeys faster, more comfortable and more punctual.

While there are many benefits of autonomous train operation for both operators and passengers, in order for it to become the standard for rail everywhere, autonomous mobility has four main requirements:

Collective: working together for a greener world

Even if low-carbon alternatives such as electric or hybrid vehicles are available, private autonomous vehicle use is not compatible with reducing traffic congestion and greenhouse gas emissions, especially as urban populations are steadily growing. Autonomous mobility must therefore be collective, meaning services will need to be provided through collective transportation in order to ease congestion and reduce ecological footprints. Rail is and will remain the backbone of mobility in a sustainable world, supplemented by lighter transportation modes, such as public or private vehicles, for first-and-last-mile journeys.

Systemic: autonomous fleet orchestration

For efficient and safe mobility, autonomous vehicles need to be able to work together as a fleet in order to get the right transport mode to the right traveler, at the right time. True multimodal transportation requires centralised control centres, at the urban or even national level, that can orchestrate autonomous mobility and respond to disruptions throughout the entire system. Thanks to the data gleaned from autonomous trains and digital trackside equipment, operators can then identify problems remotely and quickly adjust other transportation offers to meet demand, in an efficient and coordinated response.

Connected:  autonomous mobility connected to intelligent infrastructure

The rail industry is already used to developing complex systems that involve the use of both trackside infrastructure and on-board intelligence. This is important, as trackside infrastructure remains necessary not only to collect signalling data, but also to interpret it. There is no need to install digital technology, like a camera for example, on an autonomous train to help it decide whether a signal is red or green when the intelligent infrastructure is already capable of relaying that information. In short, it is more efficient and cost-effective for the operator to have the train receive information from existing intelligent infrastructure than to alter the train’s intelligence to be able to read and interpret signals itself.

Tailored: the right amount of automation

The objective of Alstom and collective mobility operators is not to make all trains everywhere fully automatic. Many factors come into play when determining the level of automation for a particular line: public interest (reopening of low-density lines), economic viability, purpose, availability (shortages of drivers in some areas) and progress is not just about the technology being ready, local regulations also need to be in place. Autonomy needs to be tailored to the right level of automation, optimising the balance between cost and results.