Title :
Adaptive importance sampling for probabilistic validation of advanced driver assistance systems
Author :
Gietelink, Olaf ; De Schutter, Bart ; Verhaegen, Michel
Author_Institution :
TNO Sci. & Ind., Helmond
Abstract :
We present an approach for validation of advanced driver assistance systems, based on randomized algorithms. The new method consists of an iterative randomized simulation using adaptive importance sampling. The randomized algorithm is more efficient than conventional simulation techniques. The importance sampling pdf is estimated by a kernel density estimate, based on the results from the previous iteration. The concept is illustrated with a simple adaptive cruise control problem
Keywords :
adaptive control; importance sampling; iterative methods; position control; randomised algorithms; road vehicles; adaptive importance sampling; advanced driver assistance systems; iterative randomized simulation; kernel density estimate; probabilistic validation; randomized algorithms; simple adaptive cruise control problem; Adaptive control; Control systems; Iterative algorithms; Iterative methods; Monte Carlo methods; Programmable control; Safety; Testing; Vehicle detection; Vehicle driving;
Conference_Titel :
American Control Conference, 2006
Conference_Location :
Minneapolis, MN
Print_ISBN :
1-4244-0209-3
Electronic_ISBN :
1-4244-0209-3
DOI :
10.1109/ACC.2006.1657344
