Sensor Modeling with a focus on noise modeling in the context of Self-Driving Vehicles using Neural Network
Examensarbete för masterexamen
Complex adaptive systems (MPCAS), MSc
Esmi Serkani, Siamak
System Simulation has become an indistinct part of developments in which there are complexity involved. In this thesis, modeling of one of the most applicable sensors in automotive industry is carried out by applying a machine learning method known as neural networks. This report outlines a method of employing a combination of neural network techniques to model system behaviour; an applicable method compatible with any type of data. By integrating this sensor model into simulation environment (OpenDaVINCI), simulation test which plays an important role in testing of selfdriving vehicles will become more realistic.
Building Futures , Grundläggande vetenskaper , Hållbar utveckling , Innovation och entreprenörskap (nyttiggörande) , Annan teknik , Building Futures , Basic Sciences , Sustainable Development , Innovation & Entrepreneurship , Other Engineering and Technologies