Generating Test Cases for Autonomous Vehicles With Controllable Levels of Difficulty
Date
Authors
Wang, Ziyu
Ma, Jing
Lai, Edmund M-K
Supervisor
Item type
Journal Article
Degree name
Journal Title
Journal ISSN
Volume Title
Publisher
IEEE
Abstract
Autonomous 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.Description
Keywords
3509 Transportation, Logistics and Supply Chains, 46 Information and Computing Sciences, 40 Engineering, 35 Commerce, Management, Tourism and Services, Autonomous vehicles, test scenario generation, adversarial testing, Stackelberg game, controllable difficulty level
Source
IEEE Open Journal of Intelligent Transportation Systems, ISSN: 2687-7813 (Print); 2687-7813 (Online), IEEE, PP(99), 1-1. doi: 10.1109/ojits.2026.3692749
Publisher's version
Rights statement
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.