RST Software
Editorial Team
Ross Krawczyk
Reviewed by a tech expert

9 use cases of AI in urban mobility that can power smart cities in the not-so-distant future

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It feels like growth and movement are essential to life itself. Some forms of it are steadily expanding, others are constantly shifting their position in space for a variety of reasons. Modern cities, bustling with commotion, include both – their own growth and the movement of various elements within them. Urban mobility is you, basically, moving around town. AI has I in it. Does this mean it’s you and I looking at yet another area where humanity’s inching closer to a merger with a greater artificial intelligence entity? Only time will tell how all this will eventually play out, but in the meantime, let’sget back down to Earth to discuss AI in urban mobility and the ways in which it will affect various aspects of transportation in smart cities and beyond.

Speaking of the future and keeping up with the latest trends, it's fascinating to witness how rapidly technology is reshaping our movement. The emergence of AI has not only sparked curiosity but also presented us with incredible opportunities for advancements.

Its integration into urban mobility is set to revolutionize multiple aspects of transportation, making our city-wide journeys more efficient, sustainable, and enjoyable. By harnessing the power of AI algorithms, smart cities can create an ecosystem where transit seamlessly blends with cutting-edge technology.

Now swipe your card, scan the code, we're going on a ride!

What is urban mobility?

The notion of urban mobility refers to the movement of both people and goods within a city or urban environment. It encompasses various modes of transportation, such as cars, buses, trains, bicycles, and pedestrians. If you've ever used any of those, you're part of it. As cities and populations they host continue to grow, the efficient management of urban mobility becomes an increasingly pressing matter.

Urban areas are facing mobility challenges caused by factors such as traffic congestion, limited parking spaces, and inadequate public transportation systems. The application of artificial intelligence in smart cities may offer innovative solutions addressing these issues and improving the overall urban mobility experience.

Feel like this is a niche you may want to explore? Have a look at our guide to mobility as a service (MaaS) app development.

The role of urban mobility in smart cities of the future

We’ve already touched on how the way people move around cities is evolving in another post about shared mobility companies and their future. However, urban transportation is a topic worth revisiting, as it plays a pivotal role in shaping the future of our cities and the overall quality of life for their inhabitants, especially since they constitute about 57% of the world’s population, according to the United Nations, with trends pointing to a further rise.

This creates both transportational issues and a demand for efficient solutions to them.

In the coming years, we can anticipate the rise of autonomous vehicles, intelligent ride-sharing platforms, and predictive analytics that optimize public transport schedules based on demand patterns.

Artificial intelligence in smart cities will lead us into a new era of mobility, where advanced transportation systems become even more interconnected, constantly evolving, and adapting to our needs. It's an exciting time to witness the convergence of technology and urban mobility, as  the latter becomes not just a dull mean of getting from point A to point B, but an experience that ushers actual value into our daily lives.

If AI is going to help us transform, it will need to be fed information, and big data and smart cities go together like hot wings and coleslaw. An urban mobility network filled with all sorts of nodes will serve as a digital mine where extraction of precious intelligence takes place. Processing the ore in the form of raw data flowing in to make it educationally feasible for AI models is challenging but obviously not a showstopper.

In theory, AI leveling up our urban mobility experience sounds great, but what are some concrete examples of what the collected and processed information could be used for? I’m glad you asked, as I have a bunch of ‘em for you.

Use case #1: Intelligent public transport routing

Picture this: you're standing at a busy bus stop downtown. Thanks to AI, your daily commute just got a whole lot smoother. By tapping into real-time data and smart algorithms, cities are transforming public transport routing into a seamless experience. Buses can now dynamically adapt their routes based on demand and traffic conditions, so you can forget about waiting in frustration. With AI's predictive analytics and machine learning, your journey becomes more reliable, travel times shorten, and the overall user experience improves.

Use case #2: AI-powered traffic management, prediction, and congestion avoidance

Let's face it, being stuck in an unending traffic jam is pretty close to hell. But fear not, because artificial intelligence is stepping up to tackle this frustrating issue head-on. Using AI-powered traffic management, smart cities can get on top of keeping the streets flowing. By crunching massive amounts of real-time data, the algorithms will start accurately predicting congestion and identifying potential bottlenecks in advance. Armed with this knowledge, cities can optimize signal timings, reroute traffic, and suggest alternate routes to drivers, helping them avoid gridlock and arrive at their destinations without being massively annoyed.

Use case #3: Smart parking management, planning and search algorithms

Trying to find a parking spot can be such a waste of time. To mitigate this many a driver's frustration, cities will be implementing smart parking management, utilizing real-time data to guide vehicles to available spaces. Imagine your smartphone showing you the nearest parking options, making finding a spot a breeze. With optimized space utilization, AI will also reduce congestion, thus improving urban mobility on multiple levels.

Use case #4: AI-powered urban planning

“Welcome to AI Ville, we hope you'll have a pleasant and optimal stay!”

Smart urban planning assumes artificial intelligence taking the lead in shaping the metropolises of the future. By taking advantage of complex algorithms, cities can optimize land use, infrastructure, and resource allocation. With smart city planning driven by AI, land development becomes more efficient and sustainable. To achieve this, artificial intelligence will analyze vast data sets, identify patterns and anticipate future needs, enabling informed decisions. From optimizing transportation networks to determining ideal locations for public amenities, AI guides the way for connected, resilient, and livable communities.

Now that we think about it, we’d be very interested to see how a major city planned by AI from the moment the first shovel hits the ground would look like. We wonder how far away it would be from, say, Brasilia, Dubai, or Egypt’s New Administrative Capital.

Use case #5: Improved rural mobility and rural public transport planning

With so much focus put on cities, we shouldn't disregard rural mobility either. Limited public transportation options faced by remote areas can be improved by AI analyzing travel patterns and population distribution to optimize routes. Looking forward, algorithms have a role to play in fostering inclusivity and growth by performing planning of network extensions to create better connectivity between larger and smaller population centers.

Use case #6: Improved road safety

Road safety is a top priority, and another area where AI can lend a helping hand  (when or if it ever develops one). By analyzing real-time data from cameras, sensors, and vehicles, it can detect hazards and provide instant alerts to drivers, thus preventing accidents. But it doesn't end there. AI can also examine historical collision data to improve road infrastructure, signage, and traffic management systems. With its predictive capabilities, cities can make data-driven decisions and implement targeted interventions to make roads safer for everyone.

Use case #7: Enhanced last-mile delivery services

The final stretch of the shipping process may be, in fact, the most challenging one. Rest easy, though, AI comes in to help get those packages dropped off on time and below the budget threshold. As algorithms optimize routes, considering real-time data and customer preferences, faster and accurate deliveries become a standard. This is already a transpiring reality in the freight forwarding businesswith self-driving trucks transforming logistics.

Use case #8: Electrification of urban transportation via smart navigation

In the pursuit of greener cities, AI-powered smart navigation takes the wheel in electrifying urban transportation. EVs, guided by intelligent algorithms, are smoothly gliding through city streets via optimized routes, taking charging station availability, battery range, and traffic conditions into account. With smart navigation fueling the electrification of urban transportation, cities can reduce emissions, improve air quality, and foster sustainable mobility. Fossil fuels are leaving the chat, a greener future enters it.

Use case #9: Micromobility infrastructure management and planning

Micromobility is reshaping urban transportation worldwide. With AI at the helm, its infrastructure management can undergo a further transformation. Artificial intelligence will analyze data on usage patterns, demand, and user behavior to optimize bike, scooter, and other vehicle infrastructure. This translates to strategically placed docking stations, popular route identification, and efficient vehicle distribution. The result of this is reduced congestion, better overall mobility, and lower carbon emissions. AI-powered micromobility infrastructure management propels us towards a future of seamless, eco-friendly short-distance travel while human entrepreneurs can focus on how to build a micromobility app that’s better than the previous one.

Develop the future with RST Software

We all can keep making more or less educated predictions, but the scale of the impact AI will eventually have is yet to be determined. It’s like the creators of the original internet at ARPA in the late 1960s, who couldn’t have guessed all the ways in which their modest, by today’s standards, network will grow and mold the world.

The ultimate role of AI in smart cities will be to transform all sorts of mobility services to better suit the needs of their inhabitants. Realistically, widespread adoption leading to a major global change is perhaps still at least a decade or two away. However, in case you’d like to jump in and flow with this exciting, whirling current which is only going to speed up, we’re here to assist you in all-things-tech on this journey.

Strongly rooted in location-based services (including geospatial data visualization services and custom digital maps development), we do everything from product design, to cross-platform mobile and web development, to building an MVP – RST Software has the expertise and experience to help you thrive in this emerging digital reality. Together, we can Pave New World.

Contact us if you have any ideas you’d like to bring to reality. We’re ready to have a conversation when you are.

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