The Structural Unworkability of Level 5 Autonomy and a Human-Centered AV Policy Framework

The Structural Unworkability of Level 5 Autonomy and a Human-Centered AV Policy Framework Civilization Physics —— AI Governance Series This paper examines the structural limits of pursuing Level 5 autonomous driving under current ethical, legal, and physical conditions, arguing that fully driverless vehicles are not merely technologically premature but systemically misaligned with real-world governance requirements. Drawing on recent high-profile robotaxi incidents and regulatory failures, the analysis shows that the Level 5 paradigm embeds contradictory expectations: near-zero tolerance for machine error, unclear legal responsibility in the absence of a human driver, and the assumption that bounded AI systems can reliably operate in open, adversarial, and unpredictable environments. These tensions reveal a feedback failure between technology deployment, public trust, and institutional accountability Rather than treating recent autonomous vehicle failures as isolated software defects, the paper frames them as structural signals. Incidents involving stalled vehicles during infrastructure failures, interference with emergency responders, and delayed medical transport expose a core mismatch between closed-loop autonomous decision systems and the demands of human-centered public space. The pursuit of unrestricted autonomy amplifies risk precisely because it removes human judgment at the moments where ambiguity, moral weight, and contextual improvisation are highest. Under the current paradigm, legitimacy in autonomous vehicle deployment has been implicitly tied to the promise of technical perfection. This standard proves unattainable in practice and destabilizing in governance. When failures occur, public backlash escalates rapidly, regulators react episodically, and companies oscillate between overconfidence and retreat. The result is a brittle deployment model that lacks durable feedback loops capable of correcting course without crisis. The paper identifies several interlocking structural failures that render Level 5 autonomy unworkable as a near-term objective: Ethical asymmetry — machine error is treated as morally intolerable despite far higher tolerated human error rates. Liability vacuum — the absence of a human driver fractures traditional accountability and delays compensation. Open-world mismatch — AI systems optimized for bounded domains fail under rare, emergent, or infrastructure-level disruptions. Binary autonomy logic — the exclusion of human oversight removes the only reliable fallback for long-tail uncertainty. Governance lag — deployment outpaces regulatory frameworks capable of enforcing safety, transparency, and responsibility. Building on this diagnosis, the paper proposes a human-centered policy framework that reorients autonomous vehicle governance around augmented autonomy rather than full replacement. The framework emphasizes retaining human-in-the-loop oversight, instituting specialized accident adjudication mechanisms, mandating robust corporate liability coverage, enforcing staged and auditable deployment, and developing certification regimes for both autonomous systems and their human supervisors. Together, these measures restore feedback channels between technology, institutions, and public safety without abandoning innovation. The analysis situates autonomous vehicles within a broader pattern of system design failures where performance claims outrun governance capacity. Its core contribution lies in reframing the debate away from timelines and capability hype toward structural alignment. Autonomy succeeds when embedded within accountable human systems; it fails when treated as a self-sufficient substitute for judgment, responsibility, and institutional memory. The paper concludes that Level 5 autonomy remains a long-term aspiration rather than a viable policy target. Sustainable progress requires accepting bounded autonomy, preserving human agency at critical decision points, and designing regulatory structures that can hear, process, and respond to failure before it becomes systemic. Without this recalibration, autonomous vehicle programs risk repeating the same cycle of overreach, backlash, and retrenchment that has already begun to define the field. Keywords: Autonomous Vehicles · Level 5 Autonomy · Human-in-the-Loop · AI Governance · Liability Frameworks · Public Safety · Staged Deployment · Structural Risk · Transportation Policy · Civilization Physics