Europe stands at the edge of a transport revolution that feels both familiar and alien. Cars that can steer themselves, once the stuff of science fiction, are inching toward everyday streets and city centers. But turning a clever prototype into an everyday habit—to get people to trust, regulators to align, and industries to retool—requires more than slick hardware and clever software. It demands a map of plausible futures, a sense of scale, and a plan for the bumps along the way. This is the heartbeat of a study from the European Commission’s Joint Research Centre (JRC), a team that stitched together literature, expert voices, and a diffusion model to sketch how passenger automated vehicles (AVs) might diffuse across EU27 plus the UK by 2050. The authors carry the names Duboz, Raileanu, Krause, Norman-López, Weitzel, and Ciuffo, all affiliated with the JRC’s dispersed network in Belgium, Italy, Spain, and beyond.
What makes this work stand out is not a single prediction but a multilayered forecast designed for policy and industry planning. The researchers acknowledge the uncertainty baked into high-automation deployment: regulatory fragmentation, consumer trust, vehicle costs, and the sheer pace of software and sensor advances all tug in different directions. So they build a framework that can bend with the wind, offering slow, baseline, and fast uptake scenarios. They also translate adoption into value-added for Europe’s economy, a reminder that the road to autonomous mobility is as much about factories and code as it is about dashboards and test tracks.
The study is a product of the European Commission’s Joint Research Centre (JRC), with collaborators across several member states. The authors, including Louison Duboz, Ioan Cristinel Raileanu, Jette Krause, Ana Norman-López, Matthias Weitzel, and Biagio Ciuffo, lay out a careful, policy-conscious portrait of a future that could reshape jobs, factories, and cities across Europe. It’s a document aimed less at predicting a single moment and more at diagnosing a spectrum of plausible paths—and, crucially, at showing what kind of policy and investment could tilt those paths toward safety, accessibility, and growth.
A framework for European AV futures
The backbone of the paper is a methodological scaffold that blends what the literature says with what practitioners observe on the ground. First comes a systematic literature review, pulling from peer-reviewed work and grey literature alike to gather evidence about when different automation levels might enter the market, how much they might cost, and how hardware and software share the bill. This step is essential because, in a field as fast-moving and uncertain as automated driving, raw projections can drift away from reality if not anchored to a broad evidence base.
Next, the authors deploy the Bass model of technology diffusion to translate those inputs into uptake trajectories. The Bass model—long a staple in forecasting the spread of innovations—rests on a simple idea: new technologies spread when early adopters spark imitation by others, all within a finite market. The model uses three parameters: p, the innovation coefficient representing spontaneous adoption; q, the imitation coefficient representing social influence; and N, the market potential. Put simply, it’s a way to turn assumptions about market size and curiosity into a curve of how quickly different automation levels might become common in new car registrations. In this study, p is fixed at a small, steady value, while q and N are tuned to align with literature anchors and expert input, producing baseline trajectories that can be shifted toward slower or faster futures as needed.
But numbers alone don’t tell the whole story, especially in a field as policy-sensitive as AVs. To ground the diffusion curves in reality, the researchers conducted expert interviews with seven professionals spanning startups, supplier networks, transport operators, and research bodies. The aim wasn’t to chase a single consensus but to test whether the baseline trajectory looked plausible and to understand where bottlenecks—cost, regulation, or public acceptance—might tighten the screws. The result is a refined set of trajectories that capture a spectrum of possible outcomes: a slow path where regulatory and market friction persists, a baseline path with steady momentum, and a fast path where policy alignment and cost reductions unlock rapid uptake.
Pricing automation: value added and costs
If the diffusion curves are the map, the value-added calculations are the fuel. The study asks a practical question: what is the economic ripple of rolling out AVs across Europe? The authors calculate value added (VA) from the production of additional hardware and software components tied to automation, subject to a learning-curve rule: for every doubling of production, costs fall by about 20 percent. They also apply a 50 percent markup to reflect the extra work of safety-critical software, validation, and integration, plus the reality that the EU would likely be producing much of the components domestically or within a tightly balanced trade framework.
The assumptions about costs, and how quickly they fall, matter as much as the uptake curves. The paper anchors the baseline to a point where an automation level reaches a 10 percent market share and then tracks how costs drop as volumes grow. The authors also allocate the cost split between hardware and software, drawing on limited but telling sources that suggest higher automation levels demand more software and sensing capabilities, whereas earlier levels lean more on hardware. In the scenario where automation climbs fastest, the resulting VA is substantial but highly sensitive to the pace of uptake and the distribution of costs between hardware and software.
The authors’ VA results invite a sober read. In the baseline path, total VA from 2020 to 2050 hovers around 1.5 trillion euros. In the slow scenario, it drops to about 0.95 trillion euros, while in the fast uptake scenario, VA could reach roughly 2.6 trillion euros. The spread is not a forecast of GDP; it’s a measure of the additional activity created by the production, design, and software development tied to AVs. It’s also a reminder that automation can boost value chains and job-creating activities even as it cannibalizes some traditional driving-related work. The study is careful to note that these are production-side gains—the ultimate macro effects on employment and output would require a broader macroeconomic model to quantify fully.
What the trajectories look like in Europe
The paper doesn’t pretend to know the exact calendar for every level of automation. Instead, it anchors Level 3, Level 4, and Level 5 to plausible “market availability” targets and then patches those targets into the Bass diffusion framework. In the baseline scenario, Level 3 is expected to reach about 1 percent of new registrations around 2025, Level 4 around 2035, and Level 5 perhaps in the 2040s, depending on how quickly the regulatory environment and consumer confidence catch up with technology. The slow scenario pushes those milestones later, while the fast scenario compresses them, with Level 4 potentially appearing by 2030 and Level 5 in the 2035–2040 window if policy and markets cooperate.
The authors also revise some trajectories based on expert feedback. Level 2, once treated as a transitional step, is given a larger market potential in the revised baseline, reflecting its role as a data-gathering, safety-building bridge that can support higher levels later. The updated curves show Level 2 persisting longer in the slow path and sometimes fading earlier in the fast path as Level 3–5 uptake accelerates. Importantly, these revisions keep the model faithful to the literature while opening space for variations driven by policy, industry structure, and consumer experience.
Visualizations in the study’s figures are not guarantees but snapshots of plausible futures. They illustrate how modest shifts in the adoption parameters—slightly higher imitation, a different market potential, or a tweak to the timing of market entry—can tilt the entire curve. The lesson is practical: the future isn’t a single date on a calendar; it’s a family of curves that respond to policy signals, investment, and the pace of real-world testing and trust-building.
Implications for people, policy, and the road ahead
On the human side, the promise of AVs is compelling and double-edged. Safer roads, more mobility for people who can’t drive, and the liberation of time from the drudgery of commuting sit alongside questions about who benefits as jobs shift. The study hints at these shifts without pretending to settle them: automation could spawn new roles in software, data analytics, robotics, and systems integration while reducing demand for traditional driving tasks. How those forces play out will depend heavily on policy choices—training programs, wage protections, and how mobility services are priced and regulated.
Regulation is the silent throttle here. Europe’s progress toward a harmonized framework for automated driving—the kind of regulatory backbone that can scale across 27 member states and the UK—has started, but deployment remains uneven. The paper notes that type-approval rules were a landmark step, yet the actual road to market requires national and regional alignment, interoperable infrastructure, and clear liability rules. The 2024 High Level Dialogue on Cooperative, Connected and Automated Mobility signaled political intent, but the real test will be turning that intent into concrete, day-to-day rules that don’t suffocate innovation or leave safety to chance.
Economically, the study’s verdict is nuanced. There is a positive value-added implication in every scenario, but the magnitude hinges on uptake speed, the cost split between hardware and software, and the availability of domestic European production. The authors stress that VA is not a standalone dividend for European households; there are broader effects on energy demand, congestion, and time savings that would materialize through a connected mobility system and productivity gains. In other words, automation’s economic story is not a single line but a web of interactions—policy incentives, consumer trust, urban design, and the resilience of supply chains all braided together.
A cautious roadmap for policymakers and industry
The paper’s lasting contribution is methodological: a disciplined way to explore uncertain futures without pretending one timeline rules them all. By combining a literature-led baseline with expert validation and diffusion modelling, the authors offer a set of trajectories that policymakers and industry can test against real-world developments. They also lay out a practical approach to translating uptake into economic meaning, connecting the diffusion curves to value-added calculations and macroeconomic implications to be explored in a larger European model (the JRC-GEM-E3) that can translate these micro decisions into GDP, employment, and sectoral impacts.
Despite its rigor, the authors don’t claim to have solved the riddle of AV deployment. They acknowledge limitations of the Bass model—static coefficients, the absence of dramatic policy shifts, and the simplification of multi-country dynamics. The study’s strength is in being explicit about uncertainties and in offering a modular, iterative framework: as new data comes in, the trajectories can be recalibrated, and policy levers can be adjusted accordingly. For policymakers, that’s a powerful reminder that the road to automated mobility is not a single green light but a sequence of calibrated decisions that accumulate over decades.
In the end, the authors show how European science is attempting to channel disruptive technology into a policy-ready, citizen-centered path. The study, authored by researchers at the European Commission’s Joint Research Centre, including Louison Duboz, Ioan Cristinel Raileanu, Jette Krause, Ana Norman-López, Matthias Weitzel, and Biagio Ciuffo, imagines a Europe where automation does not merely automate driving but reshapes industry, cities, and daily life. The roadmap is not a prophecy; it is a toolkit—one that invites governments, companies, and citizens to engage with the questions automation raises, and to shape a future that keeps people safe, equitable, and connected while letting European ingenuity flourish.
