New Infrastructure of Mobility by Version 1

The new infrastructure of mobility

Openness, intelligence and trust in transport data

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The unseen network: data as transport’s most critical asset

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Building the new ecosystem and When vehicles talk, who gets to listen?

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Trust is infrastructure: power and the new governance for mobility

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AI-ready data: intelligence will depend on structure

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Ecosystem incentives: what’s in it for everyone?

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Situational intelligent awareness: the future ultimate digital twin

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A new social contract for data-driven mobility and About the Open Data Institute

About the authors

Synopsis

A new era beckons for the UK’s transport sector. This is one not defined solely by roads, rails, ports or regulation, but by two new critical components.

The first is the flow of data across an expanding ecosystem of stakeholders: regulators, operators, manufacturers, local authorities, technology platforms and citizens. And the second? Trust. Data will not flow without trust between all parties, whether they be regulators, operators, vehicle manufacturer, local authorities or the public.

But the real shift isn’t just technological; it’s social. It’s about whether we design data systems that serve the public good, that are open, trusted and interoperable. If not, we risk creating digital monopolies that shape mobility on opaque terms.

This report explores the rise of AI-ready transport data ecosystems: not closed pipelines, but open networks where data flows securely and equitably. Like the early railway era, the future of transport depends not just on innovation, but on open standards, shared governance and a new social contract for mobility.

The unseen network

Data as transport’s most critical asset

Transport is no longer defined only by the built world, whether that be roads, railways or bridges (or indeed things like timetables). Increasingly, it’s data — how we capture it, how we connect to it and who can act on it.

Data has become the invisible infrastructure of modern mobility. It now shapes everything from route planning to congestion management, from safety interventions to the real-time experience of a passenger unlocking a bike or planning that essential journey.

Data is critical because it’s no longer just a by-product of the transport system

Data is the system. It propels automation, informs policy, enables safety, and increasingly powers artificial intelligence.

To put this in some perspective, a single autonomous vehicle can generate over 1.2 TB of data per day 1 which is equivalent to around 500 high-definition movies. There are an estimated tens of millions of journeys made per day in the UK 2. If these were all by autonomous vehicle (and let’s assume the figure is 20 million car journeys per day), 24 exabytes of data would be generated every single day. And 24 exabytes to put it in context is equivalent of streaming every movie and TV show ever made, more than 300,000 times.

And we can safely assume that many organisations will be interested in that data (or a slice of it at least), not least the driver who is helping to generate it. That level of data generation is both a testament to the opportunity and a stark warning about the scale of challenge.

Like our water and energy networks, data infrastructure underpins how transport functions, evolves, and serves the public.

But, as highlighted in the introduction, there is a second, equally critical component: trust. Without trust in how data is collected, governed and shared, the system stalls. Public confidence weakens, innovation slows, and the full value of data remains largely inaccessible.

The architecture of any infrastructure is essential. During the railway boom of the Industrial Revolution, progress depended on a shared track gauge. Without it, networks could not interconnect. Today, the same principle applies to data. The UK must define open standards, shared governance and long-term stewardship, not leave that role to closed platforms or manufacturer-specific protocols.

This is a moment for public sector leadership. Transport data must not be treated as a commercial afterthought. It, and the trust needed to surround it, is critical national infrastructure and must be governed in the public interest.

Building the new ecosystem

With openness not ownership

Transport data ecosystems are emerging as one of the defining features of the future transport landscape. As mobility becomes more automated, connected and intelligent, the value of transport data increases, but only if the data ecosystem is accessible to all those who can create this value, rather than a privileged few.

When vehicles start to talk Who gets to listen?

Who gets to access this growing stream of information?

In many instances, it isn’t the public authorities who plan, regulate or serve. It is the global platforms and manufacturers, the companies integrating operating systems into vehicles or running the digital interfaces that sit between journeys and users. Google’s Android Automotive OS is becoming increasingly common in new vehicles. This creates seamless user experiences, but it also raises important questions about data access, control and transparency.

Are local authorities and transport agencies at risk of becoming data-poor in a data-rich world? If decisions on mobility, emissions, and investment are shaped by insights held within closed platforms, how can public trust or policy leadership be sustained?

We are reaching a tipping point. The ability to govern transport depends on the ability to see it. And that requires access to the data that vehicles and infrastructure are already sharing. What’s at stake is not just insight, but influence over how transport systems work, who they serve, and how public value is delivered.

Governments are beginning to respond. In the UK, the Department for Transport’s emerging strategies on decarbonisation, innovation and

network integration are laying the groundwork for smarter systems. Globally, countries like China are investing heavily in centralised, vertically integrated transport platforms. But the UK has a different opportunity to lead through openness. By fostering shared standards, interoperable systems and data governed in the public interest which can build transport ecosystems that are not only intelligent but inclusive.

The risk of proprietary silos is that they lock innovation behind commercial walls. The alternative is an ecosystem where data flows securely and fairly, and where the benefits of intelligent mobility are shared by all.

Openness, not ownership, must become the guiding principle

Trust is infrastructure

Power and the new governance for mobility

“By the end of 2023, there were around 16.6 billion IoT devices connected globally — nearly doubling estimates from just a few years earlier and continuing to expand rapidly in sectors such as smart transport and infrastructure.”

IoT Analytics, State of IoT Report

The future of transport is not only about automation, intelligence or decarbonisation. It is also about power and trust. Who owns the systems? Who governs the data? And who decides how mobility works in a world increasingly shaped by platforms, algorithms and real-time surveillance?

Trust is not an add-on in a digital transport system.

Trust is the infrastructure that allows data to flow — and there is going to be a lot of data flowing. Without trust, ecosystems stall. Data becomes siloed, underused or withheld entirely, and the promise of intelligent, responsive mobility remains unfulfilled. As transport data ecosystems expand, uninterrupted data flow becomes ever more important. What used to be simple, bilateral exchanges are now complex networks of stakeholders from manufacturers and platform providers to local authorities, regulators and citizens. Traditional governance models such as contracts and compliance frameworks do not scale to real-time, multi-party environments.

At the same time, platforms are beginning to shape the transport experience more than public institutions. Navigation, ticketing, vehicle software and service coordination are increasingly embedded in digital systems that are privately owned. What happens when platforms, not governments, set the defaults for how people move? What happens when a vehicle’s operating system decides what data is shared, with whom and under what terms?

This also has implications for the public. If citizens become more aware of how their movements and behaviours are tracked and monetised, they may begin to resist. What if they withhold their data, or demand ownership of it? What happens if consent is withdrawn?

So, what is the alternative?

Proposals are emerging to rebalance control. The Open Data Institute has developed practical frameworks for data institutions — legal and technical structures for stewarding data on behalf of others. “Data spaces” are also gaining traction, offering shared environments for secure, purpose-led data exchange. At Version 1, we are also exploring “data clean rooms,” secure digital environments with tightly governed access.

There are other approaches like mobility data unions, data cooperatives and citizen data institutions which imagine individuals collectively managing and negotiating the use of their data, much like labour unions once did for workers’ rights. These models aim to restore public agency in how data is used, for what purpose, and by whom.

There is growing momentum for citizen representation in transport data governance, not just consultation, but formal inclusion in decision-making. That may be uncomfortable for some. It challenges the assumptions underpinning much of our digital infrastructure. But it is also necessary.

If mobility becomes more intelligent, then its governance must become more democratic. Trust and power are now at the centre of future mobility. The question is no longer just technical. It is civic.

AI-ready data

Intelligence will depend on structure

Artificial intelligence (AI) is already beginning to shape how transport systems are managed, maintained and experienced. But AI is only as good as the data it is built on. Intelligent transport systems will not emerge from raw data alone. AI will require data that is structured, standardised and shareable. Data that is ready for machines to reason with and for people to trust.

What does it take to make transport data AI-ready?

High-quality, real-time data is essential, whether it comes from vehicles, drones, road, rail or port-side assets, other infrastructure or users. That data needs to be expressed through common schemas, accessed via open APIs, and backed by clear provenance and rights models. Without this structure, even the most advanced algorithms will struggle to produce consistent, transparent or explainable outputs.

The Open Data Institute recently published “A Framework for AI-Ready Data3 “, defining criteria UK organisations can adopt to ensure data is technically optimised, standardscompliant, legally sound and responsibly collected. This provides a clear, operational pathway for transport agencies seeking to prepare data for intelligent uses.

What could this lead to?

The potential benefits are well understood. Predictive maintenance can reduce downtime and costs. Adaptive traffic management can respond dynamically to congestion or disruption. Personalised journey planners can account for accessibility needs, environmental preferences or modal flexibility. But risks must be taken seriously. If AI systems are trained on biased data, or operate in opaque ways, public trust can quickly erode as well as take some time to regain. The ethics of AI in transport are not a future problem, they are a current design challenge. Transparency, auditability and public engagement must be built in from the outset.

Being AI-ready is not simply a technical question. It is a strategic one. The way we prepare data today will determine how fairly and effectively our transport systems behave tomorrow.

Data ecosystems are only as strong as the willingness of their participants to contribute. That willingness depends on trust, but also on something more fundamental: benefit. If data sharing is to be effective at scale, everyone needs to see a clear answer to the question, “What’s in it for me?”

Too often, conversations around data default to monetisation. But successful transport ecosystems must move beyond simply assigning price to data. The most resilient models create mutual value that is not just financial, but operational, civic and reputational.

A well-known example is Transport for London’s open data programme 4. By making real-time data openly available, covering everything from service updates to live bus arrivals, TfL catalysed the development of over 600 travel apps. These apps, built by the private sector, now support millions of daily journeys as well as contributing millions of pounds to the economy. The public benefitted through better services, and private developers gained market opportunities, all without duplicating infrastructure. The net result is improved user experience, reduced information costs and stronger alignment between public goals and private innovation.

Better data can lead to better services. Public authorities gain insights that inform

planning, optimise networks and improve outcomes for citizens. Operators gain access to richer, real-time information that helps them deliver more efficiently. And the private sector benefits from collaboration on open standards, common APIs and co-developed innovation (rather than duplicating effort or building in isolation).

Shared value can also take the form of new business models, created by improving transparency, interoperability or service integration. From Mobility as a Service (MaaS) platforms to dynamic pricing tools, collaborative access to structured, high-quality data can enable services no one party could build alone.

But collaboration is not automatic. Incentives must be designed. Policy and procurement levers can be used to encourage openness. Recognition, access to pilots or preferred status in public contracts can reward those who contribute meaningfully to ecosystem growth.

Balancing public interest with private innovation is not a contradiction. It is the foundation of a healthy transport data ecosystem. The challenge now is to ensure that incentives are visible, shared and structured for the long term.

600+

By making real-time data openly available, covering everything from service updates to live bus arrivals, TfL catalysed the development of over 600 travel apps. 5

Situational intelligent awareness

The future ultimate digital twin

What if the transport system didn’t just react, but anticipated?

What if passengers didn’t wait for updates, but were informed before disruption happened? And what if every mode of transport - road, rail, air to micro-mobility - operated in concert, responding to shared signals in real time?

This is the promise of a fully connected, datadriven transport ecosystem and one that delivers situational intelligence as a live service, not a retrospective analysis.

At the heart of this vision lies the next generation of digital twins. These are not static simulations or dashboards, but dynamic, eventdriven systems that mirror the real-world state of transport networks with near-zero latency. They draw from vehicles, infrastructure,

services and users, interpreting billions of data points into actionable insights for both passengers and operators.

For control centres, this means unprecedented visibility. Live events such as congestion, breakdowns, signal failures or weather impacts can be analysed and responded to instantly, not after the fact. For planners, it opens the potential for predictive routing, demand-responsive services, and proactive safety management.

But the real shift is one of perspective. In a truly intelligent system, the user becomes the focal point. Journeys adapt in real time based on user needs, not just network capacity. Accessibility, reliability, personal safety, and even carbon impact can be considered on a per-passenger basis. The network learns, improves and prioritises accordingly.

Achieving this requires more than good technology. It requires joined-up data, AIready infrastructure, and governance models

that allow for interoperability between systems, agencies and providers. It also requires public confidence in how data is collected, interpreted and used to make policy decisions.

Situational intelligence is not just a tool for efficiency. It is the foundation for a new kind of responsiveness, where public transport systems don’t just serve users, they understand them and adapt in real time to serve us all better.

01 User becomes the focal point

02 Journeys adapt in real time

03 Network learns and improves

A new social contract For data-driven mobility

We are at a crossroads. One path leads to openness, inclusion and innovation built in the public interest.

The other risks increasing centralisation, control, and fragmented ownership of the very data that will shape how we move, how cities grow, and how equity is delivered in our transport systems.

The UK has a unique opportunity to lead. With a tradition of public service, a vibrant technology ecosystem and an increasingly joined-up approach to innovation and infrastructure, we can shape AI-ready transport ecosystems that are:

Trusted by default where privacy, consent and integrity are built in from the outset

Intelligent by design using high-quality, interoperable data to deliver real-time services and long-term planning

Equitable by intent where the benefits of digital mobility reach all citizens, not just those who own the platforms

But this future will not build itself. It requires intentional design and sustains public leadership. It’s imperative that we:

Invest in public data infrastructure as seriously as we do in physical networks

Mandate openness and interoperability as conditions for funding and innovation

Develop governance models that reflect public values, not just market logic

The transport sector is undergoing a profound transformation and one driven not only by new technology, but by an increased understanding of what public infrastructure means in the digital age. Data, trust, and AI-readiness are now the foundations of success.

This is a moment to act. Let’s create ecosystems that serve everyone, with openness as a principle, intelligence as a tool, and equity as a promise.

The UK has a unique opportunity to lead and shape AI-ready transport ecosystems

The Open Data Institute (ODI) is a not-for-profit company founded in 2012.

We build an open, trustworthy data ecosystem, collaborating with businesses, governments and civil society. Through training, consultancy and research, we equip leaders, shape policy, and drive global data-enabled initiatives.

Version 1 is a leading global transformation leader that partners with public and private sector organisations to drive mission-critical change through innovative technology solutions.

With deep expertise across cloud, data, AI, and enterprise applications, we deliver modern, sustainable services that improve business performance and public service outcomes.

1. Oxbotica and Cisco to Solve Autonomous Vehicle Data Challenge with Pioneering OpenRoaming

2. Road traffic statistics - Summary statistics

3. https://theodi.org/insights/reports/a-framework-for-ai-ready-data

4&5. Transport For London’s Open Data ‘Adds £130m A Year To Economy’

Authors

Dr David Tarrant

Head of Data Literacy and Principal Technical Consultant, Open Data Institute

David is responsible for the strategic direction of data literacy, including leading research and delivering data literacy products at scale at the ODI. He brings over 20 years’ experience in fostering trusted data ecosystems across the public and private sectors, with particular expertise in supporting education programmes that help organisations - including those in the transport sector - build stronger data cultures.

John Taylor

Digital Advisor, Version 1

John has over 30 years’ experience working across the public and private sector. In the 8 years at Version 1 he has helped customers drive tangible outcomes and benefits from the use of technology to solve real business problems.