Understanding Safety-Critical Systems in Self-Driving Cars
In self-driving cars, safety-critical systems are components whose failure could lead to loss of life, injury, or significant property damage. These systems must operate reliably under all conditions, integrating with prerequisites like model-predictive-control-mpc for trajectory planning and end-to-end-learning-approaches for perception and decision-making.
The core principles—redundancy, fail-safes, and adherence to standards like ISO 26262—ensure that vehicles can detect faults, mitigate risks, and maintain control even when primary systems fail.
Consider a basic example: During highway driving, if the primary sensor suite (LiDAR and cameras) malfunctions due to weather, redundant systems like radar or ultrasonic sensors kick in to prevent collisions.
Building from basics, redundancy duplicates critical functions to avoid single points of failure, while fail-safes provide emergency responses to halt unsafe operations.