Print Email Facebook Twitter Adaptive importance sampling for probabilistic validation of advanced driver assistance systems Title Adaptive importance sampling for probabilistic validation of advanced driver assistance systems Author Gietelink, O.J. de Schutter, B. Verhaegen, M. TNO Industrie en Techniek Publication year 2006 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. Subject TrafficAlgorithmsAutomobile simulatorsComputer simulationDriver trainingIterative methodsProbabilityAdaptive importance samplingDriver assistance systemsKernel density estimateRandomized algorithmsAutomobile drivers To reference this document use: http://resolver.tudelft.nl/uuid:a41e7437-fff8-4147-9c8e-e3a148619d6f TNO identifier 239617 ISBN 9781424402106 ISSN 0743-1619 Source Proceedings American Control Conference, 14-16 June 2006, Minneapolis, MN, USA, 2006, 4002-4007 Series Proceedings of the American Control Conference Article number No.: 1657344 Document type conference paper Files To receive the publication files, please send an e-mail request to TNO Library.