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This scientific publication focuses on the efficient application of boundaryvalue analysis in the testing of corner cases for kinematic-basedsafety-critical driving scenarios within the domain of autonomous driving.Corner cases, which represent infrequent and crucial situations, presentnotable obstacles to the reliability and safety of autonomous driving systems.This paper emphasizes the significance of employing boundary value analysis, asystematic technique for identifying critical boundaries and values, to achievecomprehensive testing coverage. By identifying and testing extreme and boundaryconditions, such as minimum distances, this publication aims to improve theperformance and robustness of autonomous driving systems in safety-criticalscenarios. The insights and methodologies presented in this paper can serve asa guide for researchers, developers, and regulators in effectively addressingthe challenges posed by corner cases and ensuring the reliability and safety ofautonomous driving systems under real-world driving conditions.

Exploring the Boundaries: Thorough Software Testing for Safety-Critical Driving Scenarios Based on Kinematics in the Context of Autonomous Driving