Wang, ZiyuMa, JingLai, Edmund M-K2026-05-272026-05-272026-05-12IEEE Open Journal of Intelligent Transportation Systems, ISSN: 2687-7813 (Print); 2687-7813 (Online), IEEE, PP(99), 1-1. doi: 10.1109/ojits.2026.36927492687-78132687-7813http://hdl.handle.net/10292/21252Autonomous vehicle (AV) safety validation increasingly relies on scenario-based testing. However, existing approaches to test scenario generation do not provide mechanisms to systematically regulate scenario difficulty. To address this critical limitation, this paper introduces a novel game-theoretic framework for adversarial safety validation. The interaction between the AV-under-test and a strategically obstructing rear vehicle is modelled as a Stackelberg game. The level of adversarial intensity, which reflects the level of difficulty, of a scenario can be controlled by a single tunable parameter called aggressiveness at both the action level and the interaction level. The efficacy of this approach is studied through the highway lane-changing operational design domain. Simulation experiments demonstrate that increasing aggressiveness reduces the success rate of lane-changing and prolongs maneuver duration for the successful attempts. These results confirm that this parameter can effectively and systematically control the difficulty level of test scenarios, providing a valuable tool for rigorous and reproducible AV safety validation.CC-BY. Open Access. IEEE is not the copyright holder of this material. Please follow the instructions via https://creativecommons.org/licenses/by/4.0/ to obtain full-text articles and stipulations in the API documentation.https://creativecommons.org/licenses/by/4.0/3509 Transportation, Logistics and Supply Chains46 Information and Computing Sciences40 Engineering35 Commerce, Management, Tourism and ServicesAutonomous vehiclestest scenario generationadversarial testingStackelberg gamecontrollable difficulty levelJournal ArticleOpenAccess10.1109/ojits.2026.3692749