The impact automation is making on our world is often measured in very specific ways: as it applies to certain technologies (cars, for example, or refrigerators) or in terms of how it has changed particular industries (manufacturing, logistics, and so on). Automation, at a grassroots level, is a concept typically brought to bear on specific types of work.
But, as the technology becomes more prevalent and diffuse, what about its aggregate effect? How might different kinds of automated process come together – incidentally or by design – to alter the overall complexion of our daily lives?
It is a question that arises when we consider the evolution of the city. Urban environments are dense with technology. They are also highly complex systems. In fact, they are systems made up of systems: transport, energy, sanitation, public order.
A glance at the various ways in which automation affects city life – and at the potential for their co-ordination – should suggest how far it might be possible to realise in the underlying, routine aspects of our experience the kind of efficiency gains that have been witnessed in parts of industry.
Take transport. Road and rail networks are the veins and arteries of a city; they keep people moving. Every congested road or cancelled train impacts on dozens or more of individuals. It is not surprising, therefore, that most cities’ underground train systems have already begun automating at least part of their operations.
The majority of London Underground trains, for example, now drive and stop themselves according to automatic signals, though each retains a driver to operate the doors, initiate departure from stations and override the system if necessary. The Copenhagen Metro is Europe’s most advanced: door operation, obstacle detection and emergency protocol are all automated.
A 2015 study by the Railway and Transport Strategy Centre at Imperial College, London found that fully automated metro systems ran trains that were more frequent (up to 42 per hour), more reliable and much more evenly spaced than non-automated. In addition, with less staff needed (by up to 70%), automated systems have more to invest in actual operations.
Driverless trains underground are likely to be followed at street level by driverless public shuttles, such as those currently being trialled in several cities around the world by French autonomous vehicle pioneer Navya. These electric buses provide cheap city mobility along preprogrammed routes without impacting on air quality and are easy to integrate into the urban infrastructure so long as they are restricted to uncomplicated, tram-like paths.
The furthest reaches of automated transport – driverless taxis, for example, navigating conventional traffic – will depend in equal measure on the requisite vehicle automation technology and on substantially updated road design, involving not least failsafe demarcations between pedestrian and vehicle spaces.
Data sharing will play an ever greater role in the automation of road traffic flow, above and beyond real-time satnav updates. And as street architecture itself becomes smarter, so data will become richer. Sensors embedded in road surfaces, for example, are already rewarding linked-in app users with a straightforward solution to the age-old problem of finding city centre parking spaces.
It is expected that a similar kind of street-level intelligence-gathering will facilitate automated maintenance of the fabric of urban public spaces. The UK’s Self-repairing Cities Project is exploring ways in which a host of specially-designed robots and drones might continuously inspect and repair everything from streetlamps to utility pipes, making unpredicted and disruptive road works a thing of the past.
Small robots tirelessly carrying out laborious tasks alongside human co-workers and operators could well become as familiar a sight in city life as it is on the factory floor. The Volvo Group-led ROAR (Robot-based Autonomous Refuse handling) Project recently envisaged a robot that would travel alongside a refuse collection vehicle, transferring the contents of household bins into the lorry along the route.
Such initiatives promise a more efficiently functioning urban system in part by reducing the kind of delays and disruptions that derive from the shortcomings of human labour, in part by enhancing, through the generation and analysis of data, the authorities’ understanding of how a city’s resources are (and might best be) deployed.
The Aspern Smart City Project – a research venture underway since 2013 in a district of Vienna, Austria – is exploring how the data streams from disparate building systems and the power grid can be integrated. The more efficient the data integration, the greater the potential for efficient energy exchange between buildings and optimal power consumption across the city.
Transport for London has pursued the same principle in its unification of the open data streams associated with its various modes of transport. This has resulted in a burgeoning of multi-mode transport apps, showing Londoners at a glance how best to exploit the relative advantages of bus, tube and train options at any given point in a journey.
Efficiency, as always with automation, rests on the fluent interaction of all system elements. In the case of the automated city, however, and as transport apps suggest, it also depends upon active citizen participation. And it may, in fact, be the nature of citizen involvement that turns out to be the biggest unknowable in the city of the future.
Citizens may not be as fully amenable to automation as a city’s hardware. They must be both willing and able to collaborate with each other and with any necessary technology. For example, where data commons may make something like taxi-sharing possible, evidence from a city like London suggests that not all individuals are willing to forgo their customary (though inefficient) privacy.
Public sector workers are also liable to resist any automation that might put them out of work. The introduction of driverless trains into the Paris Metro was only accepted on the condition that there were no redundancies (relevant staff were redeployed and promoted). In turn, redeployment in an environment increasingly populated by devices and machines is predicated on new levels of technological skill.
To obviate the unintended creation of any kind of civic underclass, both access to and literacy in the supporting hardware of the automated city need to be normalised. With these standards in place, however, the potential benefits general automation might bring to city life are wide-ranging indeed – measurable not just in terms of hoped-for efficiency gains, in other words, but also naturally implying new possibilities for social parity and cohesiveness.