Why Safety Verification Matters in Autonomous Vehicles
In self-driving cars, safety verification ensures that vehicles can operate reliably in unpredictable environments, preventing accidents and building public trust. Unlike traditional cars controlled by humans, autonomous vehicles (AVs) rely on algorithms like model-predictive control (MPC) to make real-time decisions. Verification methods confirm these systems handle edge cases, such as sudden pedestrian crossings or adverse weather.
Key challenges include:
- Complexity of Scenarios: AVs must respond to millions of possible driving situations.
- Non-Determinism: Sensors and AI can produce varying outputs under similar conditions.
- Ethical Implications: Decisions in unavoidable collisions must prioritize safety.
For example, the 2018 Uber AV accident highlighted the need for robust verification, where a pedestrian was not detected in time due to unverified sensor fusion.