Research on Safety Testing Method for Autonomous Driving Based on Visual System in Complex Urban Road Conditions - Guo, Zhanwei; Wen, Yufeng (Innovative Applications of AI, 2025)
With the rapid development of autonomous driving technology, its safety issues have increasingly attracted attention. Through in-depth analysis of autonomous driving technology, this paper focuses on combing the role of the Vision System in the autonomous driving system architecture, and points out its key position in information perception, environmental modeling, and decision planning. The existing safety test methods are systematically evaluated, and their limitations in adapting to rapidly changing driving environments are identified. Aiming at the specific needs of the visual system, a new safety test method framework is proposed, covering Data Preparation, Testing Process, Evaluation Metrics and other aspects. It provides a new theoretical basis and practical guidance for autonomous driving safety testing assisted by the visual system, and promotes the further development of this field.