Autonomous Emergency Braking (AEB) is a safety-critical Advanced Driver Assistance System now mandated for commercial vehicles in India.to reduce crash frequency and severity. This paper presents a structured, simulation-based V&V approach for camera-based AEB that integrates TTC braking evaluation, Forward Collision Warning assessment, and real-time object detection validation. High-fidelity tools Hexagon VTD & ROD, and MATLAB Roadrunner are employed to generate photorealistic, India-specific scenarios capable of modelling detailed road geometry, marked and unmarked lanes, mixed traffic behavior, and diverse environmental and weather conditions. Scenario-driven testing enables frame-accurate, end-to-end assessment of detection, decision-making, and actuation without requiring access to internal algorithms (black-box validation). Across representative scenarios, the test campaign achieved up to 90% accuracy in detecting relevant targets. This validation aligns with AIS & MoRTH guidance, and adheres to UN Regulation (UN R131), while incorporating applicable ISO 26262 functional safety principles. Requirement traceability matrices are used to evaluate system behavior under sensor degradation, misclassification, and other critical edge-case conditions prevalent in Indian driving environments. The proposed methodology enables consistent, repeatable, and regulation aligned validation of camera based AEB systems, supporting safer and more reliable commercial vehicle deployment in India.