Mobilising algorithms for smarter city living
More than half of us call cities home. Traffic challenges come hand-in-hand with urban expansion and rising population density, but do they have to? Smart cities are looking to algorithms to smooth the intersection of mankind and mobility on our streets with creative results.
Humanity is on the move
Urbanisation continues its sharp ascent and there are no signs of it slowing. Latest figures from the UN Department of Social and Economic Affairs project 68 per cent of the world’s population to be living in towns and cities by 2050, with over half of us already doing so. The faces of our cities are also changing. Nearly one in eight people currently live in 33 mega cities with more than ten million inhabitants and 43 of these metropolises are expected by 2030. This is a massive and rapid shift in global living patterns since the 1950s when urbanites comprised just 30 per cent of the total population.
Despite global variation in how these trends are playing out, we’re unified by the need to successfully manage urban growth. Rethinking our approach to mobility is one way we can improve the liveability and sustainability of cities. Traffic jams are a long-standing cliché of city life for good reason: transport data firm INRIX’s largest ever traffic congestion study shows they cost Los Angeles commuters more than 100 hours and the London economy GBP 9.5 billion in 2017. There are also social, health and environmental considerations. With pressure mounting to get smart, many cities are embracing the potential of algorithms to optimise the relationship between traffic and urban life.
Algorithms: an ancient approach to modern problem solving
Algorithms are everywhere. They underpin many aspects of modern life, from Google searches, automated stock market trading and the management of airport logistics to the matchmaking of organ donors and recipients or couples on dating sites. Today the term is strongly associated with computer science and high-profile cases such as the Cambridge Analytica data-mining scandal have made algorithms headline fodder in recent years. However, stripped back they are no more than a detailed step-by-step instruction set for solving a problem or completing a task and our usage of them dates back centuries.
What’s changed is the amount and type of data available. Big Data and the Internet of Things are now in common parlance. Not only are we humans producing a tidal wave of data but so too are our belongings. We’re at an interesting juncture with the mixture of increasing urbanisation, new data and the rapidly advancing information and communications technologies which helped give rise to it. Ride-sharing provides a concrete example of this: while carpooling has long been a thing, smart phones and ride-sharing applications have generated new insights into demand, usage patterns and user profiles.
Getting street smart both on- and off-road
Options for improving urban mobility go way beyond better or less cars. A great example is the Array of Things in Chicago – it’s an urban sensing project using data collection to positively impact liveability, including transforming statistics on traffic, air quality, sound and vibration into suggestions for healthy, safe and efficient walking routes. In Canada, the government has recently announced its Smart Cities Challenge aimed at improving the lives of their residents through innovation, data and connected technology. On a global scale, over 1000 cities applied for the Rockefeller Foundation`s 100 Resilient Cities project, intended to reduce the impact of shocks caused by disaster as well as everyday stresses such as over-taxed or inefficient public transport systems.
Algorithms form the basis for many solutions. New York, known for its queues of yellow cabs, could see congestion cuts thanks to Massachusetts Institute of Technology researchers whose dispatching algorithms could allow a 30 per cent reduction in the Manhattan taxi fleet. Computer scientists from the Nanyang Technological University in Singapore are using routing algorithms to reduce spontaneous traffic jams and waveform analysing algorithms to develop noise-cancelling windows. And, while the pros and cons of autonomous cars are currently hotly debated, their development utilises machine-learning algorithms.
Deciding on tomorrow’s roads today
The urban mobility options of tomorrow will be influenced by the possibilities cities begin exploring today. Professor Dr. Kay W. Axhausen from the Institute of Transport Planning and Systems at the ETH Zurich believes cities can benefit from eliminating the transgressions individual road users make that have a ripple effect on the transport system as a whole. “Some cities already partially implement such system optimisation, including Zurich’s traffic control system and San Francisco’s dynamic parking rate,” says Prof. Dr. Axhausen. “But rolled out on a large scale, it could mean cities where parking searches, undue congestion and bus bunching is a thing of the past. Less waiting times all around while the alternatives are improved.”
The future of mobility is one of the global megatrends that will impact the lives of future generations. And, with more people than ever before living in cities, it’s clear that sustainable development goes hand-in-hand with the successful management of urban growth. So, where will cities decide to hang their mobility investment hat? Given today’s intersection of data, technology and rapid urbanisation, it’s an exciting time to be rethinking the roads of tomorrow.
Over the next 20 years, more than 2 billion people will migrate to cities. With the growing number of urban dwellers come many challenges: congestion, pollution and a shortage of housing and recreation options, to name a few. So how will our transportation infrastructures keep up? Where will everybody live? Will there be enough jobs for everyone? In our ‘Future Cities’ series, we explore what type of innovations are helping cities to become more sustainable – and liveable.