Probabilistic Validation of Advanced Driver Assistance Systems
Abstract
We present a methodological approach for validation of advanced driver assistance systems, based on randomized algorithms. The new methodology is more efficient than conventional validation by simulations and field tests, especially with increasing system complexity. The methodology consists of first specifying the perturbation set and performance criteria. Then a minimum required number of samples and a relevant sampling space is selected. Next an iterative randomized simulation is executed, followed by validation with hardware tests. The concept is illustrated with a simple adaptive cruise control problem.
