Sensor Modeling with a focus on noise modeling in the context of Self-Driving Vehicles using Neural Network

Typ
Examensarbete för masterexamen
Master Thesis
Program
Complex adaptive systems (MPCAS), MSc
Publicerad
2016
Författare
Esmi Serkani, Siamak
Modellbyggare
Tidskriftstitel
ISSN
Volymtitel
Utgivare
Sammanfattning
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.
Beskrivning
Ämne/nyckelord
Building Futures , Grundläggande vetenskaper , Hållbar utveckling , Innovation och entreprenörskap (nyttiggörande) , Annan teknik , Building Futures , Basic Sciences , Sustainable Development , Innovation & Entrepreneurship , Other Engineering and Technologies
Citation
Arkitekt (konstruktör)
Geografisk plats
Byggnad (typ)
Byggår
Modelltyp
Skala
Teknik / material
Index