Let’s build smart, sustainable, human cities

A special report by Fast Future on creating an intelligent, connected and mobile society

AI-based Travel and Transport Management System (TTMS) process vast amounts of data using human expertise, AI-based transport infrastructure planning and traffic management algorithms, and predictive analysis

AI-based Travel and Transport Management System (TTMS) process vast amounts of data using human expertise, AI-based transport infrastructure planning and traffic management algorithms, and predictive analysis

Idealised visions of ‘The City of the Future’ are often presented as a symbol of progress. Whilst specific visions differ, the common element is the notion that in the future, the world’s most concentrated populations will occupy city environments where a digital blanket of sensors, devices and cloud-connected data are brought together to enhance the living experience for all.

Smart concepts encompass key elements of what enable effective city ecosystems – from traffic control and environmental protection to management of energy, sanitation, healthcare, security and buildings. These models help us to envisage how cities might evolve over the next 10-15 years. Here we explore three 2030 scenarios showing how data, artificial intelligence (AI) and clean energy might deliver interconnected and seamless mobility in healthy, clean, smart and liveable cities. 

Scenario 1: Data in the city

Transport for London (TfL) runs Greater London’s multi-modal transport network using a fully integrated AI-based Travel and Transport Management System (TTMS). Vast amounts of data are processed using human expertise, AI-based transport infrastructure planning and traffic management algorithms, and predictive analysis – drawing on sensors in roads, pavements and public transport access points. These are supplemented by video interpretation from 60,000 CCTV cameras, which re-established London as the world’s most watched city, surpassing Beijing. Traffic and pedestrian flows have grown exponentially, transport’s environmental impacts have declined dramatically and globally in 2030 with London  ranked first on mobility.

A single control centre automatically manages and matches services to demand – combining autonomous buses and surface and subway trains, and road and rail signalling. Live predictive analytics allows greater use of road and track space. Autonomous boats ply their trade on the Thames from Putney in the west to Woolwich Royal Arsenal in the east. An automated fail-safe mode restricts public access to capacity-sensitive areas like underground stations and riverboat piers.

Manual drive cars of all fuel types are still visible but only autonomous electrically powered vehicles are permitted in the city centre Congestion Charge area. A toll fee is automatically charged against the vehicle’s account information held in a blockchain-based payment system. 

In the late 2010s traffic controllers still manually changed timings at three-quarters of London’s traffic signals to reduce queues. Now the process is automated. A constant flow of data between autonomous vehicles (their current location, destination, purpose of the journey) and the central system is used to re-route traffic around congested areas. The system gives priority to public transport and emergency services. The system’s associated app provides pedestrians’ personal digital assistant with navigational information. 

Embedded road sensors monitor surface and sub-surface conditions. Traffic type and flows are constantly monitored against the TTMS’ comprehensive historic road status database – proactively undertaking maintenance. This reduces requirements for lengthier and more extensive subsequent repairs, minimising traffic disruption by accurately re-routing transport resources during repairs, maintenance and emergency situations and predicting the implications.

For the first time since the horse and cart, London is (for the most part) moving freely again thanks to its fully integrated TTMS. Not only is London moving, but other major cities around the world are seeking London’s expertise, creating an unexpected revenue for TfL.

Scenario 2: Artificial Intelligence

It’s New Year’s Eve 2029 and several hundred thousand people gather in Times Square, New York, to see in 2030. The all-encompassing role of smart, autonomous self-managing vehicles is in full evidence across the city. As of tomorrow, only autonomous vehicles will be allowed on the streets except in a few designated zones and drive parks where enthusiasts will be able to take the controls. Vehicle ownership is almost obsolete as most new vehicles are effectively self-owning. 

These independent taxis earn a fare for each ride and share revenues with those who manufacture, service and refuel them. The cars work in self-managing self-insuring networks – covering each other in the event of increasingly rare incidents. Autonomous technology grows ever smarter and accidents only tend to arise when human-driven vehicles are in collision with autonomous cars. 

Revellers at the New Year’s Eve celebrations can rest assured that a smart-cab or personal drone will reach them within five minutes. Autonomous ambulances patrol the city with in-vehicle robots providing immediate first aid and carrying out more complex tasks under the guidance of remote doctors observing via video. Personal drones are used to extract the injured parties from their location and transport them to the ambulance. Autonomous food trucks serve revellers in public areas with drones delivering the food to the individual wherever they stand without having to navigate through the crowd. Single user Droneloos can also be summoned on demand – dropping into the midst of the crowd to enable those caught short to relieve themselves in privacy. 

Autonomous vehicles have changed city life, cutting congestion, reducing pollution, providing services on demand, and freeing up car parking for new uses and pop-up activities.

Scenario 3:?Energy

Martina and her friends have a meeting at the library after school. Even in 2030, homework is still an everyday occurrence here in Paris. Taking a driverless car from school to the library – a standard transportation option for schoolchildren – the girls walk in through the grand entranceway of the library. 

The historic library building is retrofitted with the smart technologies of 2030 without sacrificing the charm of the 1970s façade. Old buildings are precious in the city – the cost to upgrade them is offset by the carbon neutrality of new transportation solutions. The building is old, net zero, and smart. When someone is dropped off at the entrance, it lets the autonomous cars know which library patrons are ready to leave, or sends them to another passenger nearby.

As the girls complete their work they are earning social credits that will provide more free rides in the future; doing homework and other good deeds are a currency children use to get around town. Mobility had become a service as basic as electricity and the internet – and, completely clean, safe and renewable. Electric transportation options are around every corner in the form of public mass transport (self-driving buses and trains), drone taxis and self-driving EV cars. The scaling of apps and technology to intuitively offer ‘Mobility as a Service’ (MaaS) across the city mean private cars and driving have become obsolete. Smart technologies are so advanced that users rarely need to request rides; they are predictively hailed by internet-connected things (their watch, phone, home, desk).

From the library, the autonomous car drives the girls to their various homes, lessons or practices. The parents’ digital assistants communicated with the city’s main ‘brain’ to agree different drop-off locations for their children with no wasted trips. The smart city offers a lot for families. Parents are no longer caught in gridlock on long commutes to the suburbs, since efficient city planning allows large numbers of residents to live in urban places comfortably and abundantly.

Planning for the future of cities

The 2030 scenarios described here are vibrant high-tech places with transportation strategies that ensure a high quality of life. In this future, data is wealth, and physical infrastructure is a tool to extract benefits for the greater good.

The smart city movement has the potential to transform the organisation of people and physical objects in a way that transcends urban development as we know it. The shift to smart infrastructure is not simply fashionable or aspirational. In many ways, it appears to be a critical enabler of the future sustainability of cities. It can be argued that the future of human life on the planet rests on a smooth transition to cities that are more efficient, less wasteful, and more conscious of the impacts of the individual upon the greater good. 

To achieve this vision, society must harness the impressive and increasing potential of the collective data drawn from large groups of people living together in cities. Who owns the data? Who decides how it will be used? Where does the greater good overshadow individual free will, and vice versa? These are questions that city planners and residents will need to discuss to ensure that future cities are wise and human, not just smart.

Smart parking = No parking?

Will parking soon be obsolete? In 10-15 years, the idea of a stationary vehicle may be an anachronism. In future smart cities, self-driving cars will be enabled by data to orchestrate smooth mobility, with almost no stopping required, other than to let passengers on and off. Self-driving cars are but one element in a larger wave of change sweeping us toward this vision; another is the erosion of car ownership.

The success of enterprises like Lyft and Ola Car have popularised mass ride sharing, and it is imaginable that in a smart city environment, such programmes could become the norm. The environmental and economic benefits, like cleaner air, and less traffic, might encourage more pedestrian areas and the creation of green spaces – improving public health. Most of all, the ability to creatively reclaim spaces that are now devoted to parked cars could enhance the quality of life in cities, a key consideration in terms of the legacy for future generations.

The authors

The authors are futurists with Fast Future who specialise in studying and advising on the impacts of emerging change. Fast Future also publishes books from future thinkers around the world exploring how developments such as AI, robotics and disruptive thinking could impact individuals, society and business and create new trillion-dollar sectors. Fast Future has a particular focus on ensuring these advances are harnessed to unleash individual potential and enable a very human future.

www.fastfuture.com

• Rohit Talwar is a global futurist, keynote speaker, author and chief executive of Fast Future, where he helps clients develop and deliver transformative visions of the future. He is the editor and contributing author for The Future of Business, editor of Technology vs. Humanity, and co-editor of a forthcoming book on Unleashing Human Potential: The Future of AI in Business.
• Steve Wells is the chief operating officer of Fast Future and an experienced strategist, futures analyst and partnership working practitioner. He is a co-editor of The Future of Business, Technology vs. Humanity, and a forthcoming book on Unleashing Human Potential: The Future of AI in Business.
• April Koury is a foresight researcher, writer, and publishing director at Fast Future. She is a contributor to The Future of Business, and a co-editor of Technology vs. Humanity and a forthcoming book on 50:50–Scenarios for the Next 50 Years.
• Alexandra Whittington is the foresight director, futurist and writer at Fast Future, and a faculty member on the Futures programme at the University of Houston. She is a contributor to The Future of Business and a co-editor for forthcoming books on Unleashing Human Potential: The Future of AI in Business and 50:50–Scenarios for the Next 50 Years.
• Maria Romero is a futurist and foresight researcher with Fast Future. A recent graduate from the University of Houston Master in Foresight, she has worked on projects for consultants, NGOs, for-profit organisations, and government clients. She is currently working on a study of AI in business.