The core of the problem lies in what Hölzer terms the speed offset problem. Some driver assistance systems allow users to exceed detected speed limits by a predefined margin—a +10 km/h offset applied to a 100 km/h limit produces a target speed of 110 km/h. On the surface, this looks like a trivial configuration option. In reality, it embeds discretionary law-breaking into the behaviour of a machine, creating a deep normative tension between legal compliance and traffic safety. An automated vehicle that brakes hard in response to a frequently ignored speed limit sign, for example, may provoke rear-end collisions from human drivers who never anticipated such scrupulous behaviour.

The paradox has deep roots in traffic safety research. Speed is undeniably a decisive factor in crash outcomes: kinetic energy transferred to the human body is the primary killer, which is why the 2020 Global Ministerial Conference on Road Safety called for default 30 km/h limits in urban areas to protect pedestrians and cyclists. Yet research also shows that compliance with speed limits collapses when drivers perceive those limits as unreasonable—outdated, inconsistent, or poorly justified. Wide urban boulevards that resemble highways, empty rural stretches, and long downhill segments all invite systematic speeding. Violations, in other words, are often not isolated acts of recklessness but predictable responses to specific road environments, and to informal norms that govern how traffic actually flows.

Those informal norms are not universal. Drawing on David Zaidel’s concept of a culture of driving, Hölzer shows that each driver’s behaviour both shapes and is shaped by the social environment of other road users. Empirical studies suggest wide cross-national variation: in one comparative analysis of five nations, most drivers exceeded speed limits in Italy, Japan, and the United States, while rates were much lower in China and moderate in Germany. Cultural differences extend beyond speed to the very grammar of traffic. In southern Europe, drivers tend to merge by accelerating into gaps and trusting others to yield; in central and northern Europe, they typically wait for explicit feedback such as eye contact or a visible reduction in speed. The same manoeuvre that signals competence in one culture can look reckless in another.

This diversity creates a philosophical trap. If cultures disagree about what safe or competent driving means, can automated vehicles be designed to universal ethical standards? Hölzer’s answer is a careful yes, but with a crucial distinction. Acknowledging that cultures differ in their informal driving norms does not entail moral relativism. The variation, he argues, occurs primarily at the level of surface practices rather than fundamental moral principles: different conventions can be understood as differing implementations of shared values such as harm prevention and efficient coordination. The universal commitment therefore shifts from prescribing one substantive answer to navigating moral uncertainty—weighing alternative principles according to their plausibility, as philosophers Vivek Bhargava and Tae Wan Kim have proposed for programmers facing situations where all the facts are known but morality’s demands remain unclear.

Crucially, Hölzer insists that cultural sensitivity must be principled, not merely pragmatic. Adapting a car’s behaviour to local norms because it boosts market success or user acceptance confers no moral legitimacy. Nor can the mere fact that humans routinely treat speed limits as guidelines justify programming machines to do the same—that would be a classic is-ought fallacy. There is also a corrosive risk: when law-breaking is embedded in a vehicle’s design, its official character can function as a false authority on what counts as a proper speed, eroding the social credibility of limits themselves. Cultural practices deserve prima facie respect, but that respect is defeasible. A community that collectively normalises dangerous speeding has not thereby made it ethical, and the company deploying the system remains an outsider with a duty not to facilitate avoidable harm.

To translate this into practice, the paper proposes three ethical guardrails for speed offsets. First, a speed offset is morally permissible only when it increases overall safety—the aggregate frequency and severity of incidents across all road users. The evidence here is genuinely uncertain: moderate offsets might increase acceptance of driver assistance packages, whose wider use could save lives, but no studies have yet tested whether speed offsets actually have this effect, and the safety statistics for assistance bundles are complicated by features like autonomous emergency braking that operate independently. Second, an offset must not increase overall safety at the expense of particular groups. Aggregate metrics can mask a net safety gain that comes with sharply increased risk for pedestrians or cyclists, so fairness stands as a separate constraint—supported, Hölzer notes, by distribution-sensitive utilitarianism, deontology, and Rawlsian frameworks alike. In practice this means offsets belong on highways where traffic flow systematically exceeds limits, while school zones and playgrounds should see them minimised or prohibited outright, potentially enforced through geofencing.

The third guardrail is provisionality: the legitimacy of a speed offset must be temporary and revisable. Automated vehicles will operate in mixed traffic for the foreseeable future, and adapting to prevailing flow may be necessary—but the relationship runs both ways. As automated vehicles spread, their consistent behaviour could gradually reform unsafe driving habits through what Zaidel called a snowball effect, transforming traffic culture step by step. A calibrated offset of +5 km/h remains preferable to a human culture that routinely tolerates +10. But if machines adapt too readily to unsafe norms, they may amplify them instead. Provisionality guards against this normalisation dynamic by tying the offset’s moral permissibility continuously to the empirical conditions that justify it, and by demanding governance structures in which manufacturers supply data, regulators set binding constraints, and local communities contest implementations through transparent, evidence-based procedures—with the burden of proof on those who wish to keep the offsets.

Putting the framework into practice will require data on driving scenarios, cultural characteristics, safety gains, and the redistribution of risk among road users. One promising tool is shadow mode, in which an automated driving function runs virtually alongside a human driver, logging sensor data and hypothetical actions without intervening—allowing developers to learn local traffic norms without exposing anyone to additional risk, though the extensive sensor recording involved raises serious questions of consent and data governance. Legal questions loom just as large: most jurisdictions do not recognise maintaining traffic flow as a defence for speeding, and an embedded offset amounts to what Hölzer calls a rule violation by design, straining liability frameworks built around human fault. The speed offset problem, in the end, is more than a technical puzzle about cruise control settings. It is a lens through which the deeper moral and cultural tensions of automation become visible—proof that even the smallest configuration option in a self-driving car can carry the full weight of an ethical argument about whose norms the machine should follow, and who pays when it does.

Subject of Research: Ethics of speed limit deviations and cultural sensitivity in automated vehicle design

Article Title: The speed offset problem: a case for principled cultural sensitivity in automated vehicle design

Article References: Hölzer, J. (2026). The speed offset problem: a case for principled cultural sensitivity in automated vehicle design. AI & SOCIETY. https://doi.org/10.1007/s00146-026-03222-3

Image Credits: AI Generated

DOI: 10.1007/s00146-026-03222-3

Keywords: automated vehicles, speed offsets, traffic safety, Vision Zero, driving culture, ethics, moral relativism, intelligent speed assistance, mixed traffic, algorithmic fairness, regulation, AI & Society