ISSUES OF LIABILITY FOR ROAD ACCIDENTS INVOLVING SELF-DRIVING VEHICLES EQUIPPED WITH ARTIFICIAL INTELLIGENCE TECHNOLOGIES

• Normanov Okhunjon

  University of Public Safety, Uzbekistan

Objective: This study investigates the emerging legal and regulatory challenges posed by the integration of self-driving vehicles (SDVs) equipped with artificial intelligence (AI) into public transportation systems, with a specific focus on criminal liability in the context of road traffic accidents (RTAs) in Uzbekistan. Method: Employing a qualitative legal-analytical method, the research critically examines national legislation, international conventions, and comparative case studies to identify conceptual and procedural gaps in attributing liability. Results: The analysis reveals that existing Uzbek criminal law is insufficient to address the complexities of SDV-related RTAs, particularly in determining fault, establishing causation, and assigning liability among stakeholders such as developers, manufacturers, owners, and infrastructure managers. The study underscores the critical role of black box data and technical standards in guiding legal assessments. Novelty: The research offers a comprehensive multi-layered liability framework and recommends specific amendments to the Criminal Code and traffic laws, proposing legal definitions and mechanisms aligned with international norms. This contribution provides a foundational model for Uzbekistan to proactively adapt its legal system to accommodate the technological realities of autonomous mobility.

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