In English

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

SIAMAK ESMI
Göteborg : Chalmers tekniska högskola, 2016. 60 s.
[Examensarbete på avancerad nivå]

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.

Nyckelord: System identification, neural network, proximity sensor, noise, selfdriving



Publikationen registrerades 2017-02-22. Den ändrades senast 2017-02-22

CPL ID: 248287

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