By Jade Neville

As someone who’s worked in the UK parking sector for a number of years, I’ve seen firsthand how much of our urban infrastructure still struggles with what should be a relatively simple question: Where can I park?

If you’ve spent any time driving in busy cities — whether it’s London, New York, Manchester or San Francisco — you know the answer isn’t straightforward. In the UK, drivers spend around 44 hours every year just looking for parking, according to a 2017 study by the transportation analytics company INRIX. Over a lifetime, that adds up to 106 days stuck behind the wheel in search of a space. In the U.S., it’s a similar story: INRIX found in another 2017 study that American drivers waste 17 hours a year (and $73 billion nationally) doing the same thing.

These aren’t just personal frustrations. This wasted time creates broader impacts: lost productivity, increased emissions, unnecessary fuel use, and reduced access to local businesses. That’s why I believe we need to stop thinking about parking as just enforcement and start treating it as an essential part of the mobility conversation.

AI and ANPR: evolving beyond enforcement

In the UK, we’ve seen a major shift in how we use automatic number plate recognition (ANPR) and artificial intelligence (AI) in parking. Historically, ANPR was all about enforcement — tracking overstays, issuing fines, and making sure rules were followed. But today, it’s evolving into something much smarter.

AI now allows us to make sense of vast amounts of parking and traffic data. In my work with local authorities, I’ve seen how intelligent systems can now predict peak times, identify trends, and even adapt in real time to changing conditions. For example, advanced ANPR combined with AI algorithms can distinguish between a delivery van briefly stopping for a drop-off and a vehicle improperly parked, enabling more proportionate, evidence-based management.

At the technical level, this is powered by deep learning models trained on large image datasets, using tools like convolutional neural networks (CNNs) and optical character recognition (OCR). But what really excites me isn’t the tech. It’s the outcomes: smoother streets, cleaner air, and fewer frustrated drivers.

Lessons from the UK: data with direction 

One thing I’ve learned is that data is only valuable if it’s used strategically. In UK cities, we’ve moved beyond just capturing license plates. We’re now integrating real-time parking data with air quality monitoring and electric vehicle charging strategies.

We’ve piloted dynamic curbside management systems where parking rules change based on demand or vehicle type, giving priority to electric vehicles, delivery vehicles, or short-term stays. In one project, we saw a measurable drop in search times and a noticeable increase in compliance simply by aligning pricing and availability with real-time behavior.

It’s not perfect — and it never will be — but these tools help us manage complexity rather than just react to it. That’s a big difference.

What U.S. cities can take from this approach

From what I’ve seen in cities like San Francisco and Los Angeles, many of the same ideas are being tested and scaled. A standout example is SFpark, a pilot program launched by the San Francisco Municipal Transportation Agency (SFMTA) that used smart parking meters and sensors to adjust parking prices based on demand. Relying on dynamic pricing and real-time availability data, SFpark cut search times of drivers looking for parking spaces by 43% and reduced vehicle emissions by 30%, according to a 2014 report by the SFMTA. These are exactly the kinds of results we should all be aiming for.

There’s also growing interest in using ANPR for more than enforcement. In some U.S. cities, it’s being integrated into broader systems for freight management, access control in restricted zones, and even personalized parking recommendations for drivers. That sort of intelligent, joined-up thinking is where this technology really shines.

Innovation requires responsibility

Of course, with great data comes great responsibility. Both in the UK and U.S., we’re grappling with legitimate concerns around privacy, bias in AI algorithms, and the ethical use of public space data. These concerns are valid and should be addressed head-on — not just in policy, but in how we design and deploy technology.

I believe it’s possible to innovate responsibly. In my own work, that means designing systems that are transparent, explainable, and fair. We work hard to eliminate bias from AI models, audit our outcomes, and comply with strict data protection regulations like the UK’s GDPR, which is a comprehensive privacy law designed to protect individuals’ personal data and give them greater control over how it is used. That’s not a barrier to progress: It’s the foundation for it.

Why it all matters

The future of parking isn’t just about tech. It’s about people. It’s about giving time back to drivers, reducing stress on communities, and helping our cities function more smoothly and sustainably. Whether you’re in Boston or Birmingham, the challenge is remarkably similar.

My message to U.S. parking professionals is this: We’re all facing the same core questions. How do we make space work better? How do we reduce friction? And how do we bring the public with us?

I don’t have all the answers, but I’ve seen how AI and ANPR, when thoughtfully applied, can be part of a better future for urban mobility. Not just smarter enforcement, but smarter cities.

Let’s keep the conversation going. 

JADE NEVILLE is the sales operations and marketing manager for Trellint, a co-founder of Women in Parking UK, and a former president of the British Parking Association. She can be reached at [email protected].