AI adoption speeds up safety and sustainability in urban transport

With an explosion of use cases, enthusiastic large-scale adoptions, and a global market valuation that’s set to multiply nearly eight times in just ten years to hit $23 billion, AI in transportation is making its mark in the early years of this decade. We examine the drivers for this upsurge in AI adoption activity by urban planners and their backers, with three recent examples from around the world.

Smart mobility is central to the smart city living experience

The UN is confident that cities are responsible for at least 75% of all global CO2 emissions, with buildings and transport being among the largest contributors. This makes them the proverbial eye of the storm and the necessary focus for rapid decarbonisation efforts. 

However, delivering more efficient and sustainable transportation options at the mass-transit and individual journey levels is not only essential for lowering citywide emissions, it also goes to the heart of the much-promised “smart city living” experience. To live up to that promise, every city resident and visitor needs to have access to modes of transport that are safe, clean, affordable, efficient and easy to access. 

The focus on smart mobility systems is accelerating globally because delivering them can unlock vast gains in decarbonisation, citizen productivity and satisfaction, public health and safety, while also saving city authorities funds in the long run. On the flip side, the prospect of a “business as usual” approach to public transport presents a vision of increasingly unfair, inefficient systems running on often crumbling infrastructure, which is the current reality even in advanced economies ranging from the UK to the US, and all across the world.

AI provides the vision,
and the path ahead

Overhauling something as complex and wide-reaching as cities’ public transport systems, not to mention their roads, bike lanes, walkways, ferries, bridges and other transit routes, is a vast undertaking, especially since changes must be made even as the public uses them every day. 

AI is increasingly being seen as essential for helping urban planners to make the right decisions for the future of city transport. Through advanced data collection, analysis and predictive modelling, AI platforms can provide 

an accurate understanding of how transport systems are being used. This leads to more effective decision-making on everything from simple capacity tweaks (“Where should this new car park be built?”), to the optimal design and delivery of wholly new modes of transportation (“How can we integrate autonomous shuttles into the city centre?”).

With the right AI solutions, urban planners can achieve a holistic overview of what their city needs right now, what it will need in the future, and how best to get there.

3 Real-world AI adoptions in global cities show progress in mindsets and on the ground

Chilean capital Santiago already has one of the biggest electric bus networks in the world outside of China, with nearly 2,000 e-buses in the fleet. Currently, Directorio de Transporte Público Metropolitano is working with Optibus to introduce an AI system that will further improve the planning, scheduling, route-mapping and predictive maintenance of what is already one of the most advanced bus fleets in Latin America. This will be essential in driving decarbonisation in Santiago and paving the way for the city’s goal of running a 100% electric bus fleet by 2040.

Palermo, Italian island Sicily’s capital city, has engaged Milestone Systems for a citywide safety, sustainability, and mobility project. Milestone’s AI system provides Palermo’s planners with a comprehensive overview of the city’s traffic, monitoring road usage routes and driving habits of thousands of vehicles every moment of every day. The system is fed data from the existing city traffic cameras (keeping down costs since they don’t need to be replaced), in combination with IoT sensors that monitor weather and air quality factors. Together, this overview will present Palermo’s planners with optimal solutions for the detection and prevention of traffic incidents, slowdown causes, and the design of new road configurations that integrate into the city’s future public transportation plans.

Dubai’s Roads and Transport Authority (RTA) is partnering with the Dubai Taxi Corporation (DTC) to integrate advanced AI technology into DTC’s Control Centre. This AI-powered Control Centre is already capable of directing and supporting 5,200 taxis and their drivers simultaneously, 24/7, directing them to high-demand areas of the city, monitoring their activities and providing more efficient routes in real time. This should allow DTC drivers to operate more sustainably while boosting customer safety and satisfaction levels.  

Mapping the road ahead for net-zero city transportation

In each of these examples, alongside innumerable other AI adoptions occurring in cities worldwide, the benefits of bringing together comprehensive data collection/management/analysis with predictive modelling is clear. Since every facet of a city’s infrastructure and systems are interconnected, it takes more than human intelligence to plot a path for optimal changes that need to take place as new technologies offer better, greener transportation options. AI is fast becoming an integral part of urban design and planning as it gives that crucial current overview and predictive power that allows for true smart mobility visions to take shape.