Sensor data fusion for automated driving

Toward robust perception in adverse weather conditions

Doctoral thesis (2022)

Authors

J.F.M. Domhof Intelligent Vehicles - Mechanical, Maritime and Materials Engineering
Research Group
Intelligent Vehicles (Mechanical, Maritime and Materials Engineering) (TU Delft)
Copyright: © 2022 J.F.M. Domhof
DOI
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https://doi.org/10.4233/uuid:ee7b5513-3917-44d0-9307-7689be201153
Object tracking Sensor data fusion Adverse weather
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Published Date

2022

Language

English

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Faculty

Mechanical, Maritime and Materials Engineering

Department

Cognitive Robotics

Research Group

Intelligent Vehicles

Abstract

The aim of the thesis is to develop methods and algorithms for the development of a robust perception system that is capable of dealing with adverse weather conditions. Robust environmental perception is important in order to guarantee safety for the automated vehicle and the road users in the neighborhood. To create a robust perception system, a sensor setup should be selected with multiple sensing modalities. Commonly used sensing modalities in the field of intelligent vehicles are lidar, camera and radar sensors. This thesis addresses three subjects that are important for robust perception, namely sensor selection, extrinsic calibration and object tracking....