Ask most people what stands between self-driving cars and everyday adoption, and the answer usually points at the technology: sensors, edge cases, regulation. What gets talked about far less is a much softer problem, and arguably a harder one to solve: whether people actually want to sit in one, and under what conditions they'd be willing to give up the wheel, or even give up owning a car at all.
That question is exactly where this research project starts. Rather than surveying the general population, a common approach in most existing acceptance studies, it zooms in on a specific group that rarely gets asked directly: students living in rural areas, where public transport tends to be sparse and a car is often less a convenience than a necessity. The guiding question was straightforward to state and considerably harder to answer: can autonomous vehicles actually solve this group's mobility needs more efficiently than what they already have?
Where the Acceptance Numbers Disagree
Before designing anything new, it's worth noting how mixed the existing research on this topic already is. A TÜV Rheinland survey of over 1,400 drivers found 76.3 percent broadly open to the technology. Continental's most recent mobility study found a majority in every surveyed country considers automated driving a sensible development in general, though actual willingness to use it varies sharply by region, notably higher in China and Japan than in most of Europe. A Bertelsmann Foundation study, meanwhile, found the opposite emphasis: more than two thirds of respondents distrustful of self-driving vehicles, with that distrust growing steadily with age, and fear of technical failure, hacking, and loss of control cited as the main reasons.
None of these studies agree cleanly with each other, which is itself a useful finding: acceptance of autonomous driving isn't one fixed number waiting to be measured, it depends heavily on who's being asked, and what specifically they're being asked about. That's the gap this project tries to fill for one particular group.
Listening First: Exploratory Interviews
The study followed a two-stage structure, first mapping the problem space through interviews, then developing and testing a solution based on what those interviews actually revealed. Rather than a quantitative survey chasing statistical breadth, the team ran qualitative, exploratory interviews with six students aged 22 to 26 (three women, three men), each already owning or having regular access to a car and driving trips of roughly 15 to 45 minutes several times a week. The interview guide opened with participants describing their current car use and general attitude toward mobility, before moving into specific frustrations and positive experiences during typical drives, and finally into existing knowledge of and attitudes toward autonomous vehicles and AI-driven features specifically.
Three hypotheses framed the later analysis: that having a personal car matters a great deal to this group, that routine commuting is either boring or a source of stress, and that respondents would be broadly open to autonomous vehicles. The interview results were then organized using the Customer Profile component of the Value Proposition Canvas, sorting findings into customer jobs, pains, and gains.
The core "job" that came up across every interview was, unsurprisingly, getting to university or work reliably and efficiently, while still leaving room for spontaneous plans and appointments. For non-dual students in particular, a second job stood out clearly: keeping mobility costs as low as possible on a limited budget. On the "pain" side, that same financial constraint dominated, making comfort or luxury features largely irrelevant to this group, while public transport, despite genuine environmental interest, was seen as too poorly connected in rural areas to be a real alternative to a personal car. Frustration caused by other drivers' behavior came up repeatedly too, as a shared irritation independent of the vehicle question entirely.
The "gains" side complicated the picture in an interesting way. The hypothesis that daily commutes are boring or stressful didn't hold up: most respondents genuinely enjoy driving, or at least don't see it negatively, particularly when they can drive alone with music on. Openness to autonomous vehicles was similarly only partially confirmed. While the majority said they'd be willing to try the technology, doubts about safety surfaced consistently, with one respondent asking, more or less verbatim, how a car would even be programmed to act ethically, a concern the researchers link back to generally limited background knowledge about the technology across the group. Opinions were split on whether the vehicle should have any kind of humanlike personality at all: some said that might build more trust, others said the opposite, preferring a car that's clearly identifiable as AI rather than something dressed up to feel human.
Building a Believable Future: Design Fiction
With the problem space mapped, the project moved into Design Fiction, an approach distinct from conventional Design Thinking in one key respect: rather than optimizing toward a marketable product, its goal is to make a speculative future scenario tangible enough to provoke genuine discussion about how a technology might reshape people's lives, without pretending to predict the future with any real precision.
To make that speculative future believable, the team built a full fictional context around it rather than presenting the concept in the abstract. South Korea was chosen as the setting, specifically the city of Gimcheon, precisely because it's unfamiliar to a German audience and carries strong existing associations with technological openness and progress, a useful blank canvas for a concept that would otherwise need a lot of persuading. Two types of artifacts were then built to introduce this world during testing: an objective artifact, a fictional press article styled after the magazine Zeit Campus, which introduced a fictional company called Navia and its autonomous ride-hailing service, laying out core features like a separable "Personal Space" seat and interest-based rider matching, along with concrete pricing (55 euros a month for students, 160 euros for the general public); and a subjective artifact, a staged recorded interview with a supposed exchange student describing his everyday use of Navia in Gimcheon, walking through the app's personal calendar, ride-matching, and booking features via Figma mockups shown alongside the recording.
That combination matters more than it might sound: the objective artifact establishes the concept neutrally, while the more personal, narrative artifact is specifically designed to provoke a stronger emotional reaction, whether that's enthusiasm or skepticism, giving researchers a clearer read on how the concept actually lands rather than just whether people find it plausible on paper.
The Prototype: Navia
Based on everything gathered during the brain dump phase that followed the interviews, the team settled on a concrete prototype: an autonomous taxi service intended for both cities and rural regions, positioned as an affordable complement to public transport rather than a replacement for it, aimed primarily at commuters and students. Users would book rides through an app similar to existing ride-on-demand services, with both single bookings and a subscription model available for regular use. A defining feature was the optional "Personal Space," a way to physically separate a rider's seat from others in the vehicle when privacy or quiet was wanted.
What the User Tests Revealed
When the prototype and its artifacts were presented back to a new round of test participants, the Design Fiction scenario proved convincing: everyone accepted the premise, even when a few noted, with a shrug, that they'd never actually heard of the fictional car brand before. That believability let the researchers test their prototype-stage hypotheses directly against real reactions, and the results were considerably more nuanced than a simple thumbs up or down.
Students were skeptical about the concept succeeding in Germany specifically, largely because they doubted broader, especially older, generations would be as technologically receptive as the fictional Korean setting implied. The personal calendar and Personal Space features landed well in concept, but less well in practice: participants worried a separated seat might feel less like privacy and more like being "locked in," and the calendar feature felt like a poor match for the irregular schedules most students actually keep, since it would require remembering to cancel bookings in the app rather than just skipping a ride. Personalized rider matching based on shared interests, meanwhile, turned out to be the least compelling feature of the three. Interest was more situational than expected, useful on a longer, boring trip, less so on a whim, and several participants pushed back on the whole premise, saying they'd rather talk to someone with different interests than someone chosen to match their own. What people did consistently ask for instead were simpler, more practical filters: smoking preference, pets, and music taste.
Price came up as the single biggest lever on actual willingness to switch away from a personal car, and even then, only cautiously. Most participants said they could imagine using the service at least occasionally, but very few were willing to give up their own car entirely, even while acknowledging the environmental upside of the concept. Interestingly, time savings, not comfort, was the stated reason autonomous vehicles were preferred over public transport at all, a distinction that says something specific about what this group actually values in a mobility solution.
What It Means Beyond Gimcheon
These findings line up with, and add useful specificity to, the broader research already summarized in the paper's early sections, including a 2021 Aral study on car-buying trends that found similar openness toward self-driving vehicles among younger demographics. But they also complicate the more optimistic acceptance numbers cited elsewhere: openness to trying a technology and willingness to actually restructure daily life around it, especially by giving up a personal car, are clearly two very different things. That gap tracks closely with Continental's own findings, where Germany showed the lowest confidence among surveyed countries, just 35 percent, that autonomous driving would be commonplace within a decade.
Price sensitivity specifically echoes findings from both the Boston Consulting Group and a University of Alabama study on college students' attitudes toward shared autonomous mobility, both of which found genuine interest in the underlying technology, but real willingness to share rides only once pricing dropped roughly 50 percent below conventional ride-hailing services like Uber. None of this is a knock against the concept itself so much as a reminder of where the actual bottleneck sits: not in convincing people the technology could work, but in building enough trust, and enough of a price advantage, that giving up a personal car stops feeling like a downgrade.
The Bigger Takeaway
What this study adds to the broader conversation around autonomous driving isn't a verdict on the technology, it's a reminder that acceptance is rarely one uniform number, and that Experience Design work gets meaningfully sharper once it stops asking "would people use this" in the abstract and starts asking a specific group, with specific constraints, what would actually have to be true for that yes to hold. For rural students, that turned out to mean less about futuristic features like AI-matched rides or in-app calendars, and considerably more about the basics: a fair price, a believable safety story, and a service that fits around a schedule that rarely looks the same two days in a row. Future work using the same fictional groundwork with other target groups, car-less rural students or long-distance commuters in particular, could well surface an even stronger case for the concept than the one found here.