Self-Driving Vehicles: Benefits, Safety Challenges, and the Critical Role of SIL/HIL Simulation-Based Verification and Validation

Abstract

Autonomous vehicles are a key technology for future transport, where machine learning, multi-modal sensing and real-time control are combined to perform driving with minimal human involvement. For the safe deployment of the technology, new verification and validation approaches are needed that address faults and hazards arising from errors and from shortfalls in functionality․ SIL, and HIL Testing is an important part of the AV development process because it provides a means of scalable, repeatable, and complete safety assurance. They are also used because they can provide scenario testing far beyond what is possible with road testing. SIL and HIL Testing can be used to meet functional safety and safety of intended functionality standards. In addition to their technical abilities, AVs can deliver many social benefits, which can be unlocked by deploying them responsibly with safety evidence, governance frameworks, and policies for equitable access and mobility for all road users. Complementary safety standards and inclusive deployment strategies, combined with advanced simulation-based validation, could make autonomous vehicle technology a foundational enabler of safer, more inclusive transportation systems accessible on a global scale.