This paper presents a scenario generation framework that creates diverse,
parametrized, and safety-critical driving situations to validate the safety
features of autonomous vehicles in simulation [1]. By modeling factors such as road geometry, traffic participants,
environmental conditions, and perception uncertainties, the framework enables
repeatable and scalable testing of safety mechanisms, including emergency
braking, evasive maneuvers, and vulnerable road user protection. The framework
supports both regulatory and edge case scenarios, mapped to hazards and safety
goals derived from Hazard Analysis and Risk Assessment (HARA), ensuring
traceability to ISO 26262 functional safety requirements and performance
limitations. The output from these simulations provides quantitative safety
metrics such as time-to-collision, minimum distance, braking and steering
performance, and residual collision severity. These metrics enable the
systematic evaluation of evasive maneuvering as a safety feature, while
highlighting system limitations and edgecase vulnerabilities. Integration of
scenario-based simulation with safety engineering principles offers accelerated
validation cycles, improved test coverage at reduced cost, and stronger evidence
for regulatory and stakeholder confidence.