Ground-to-Aerial Image Matching for Vehicle Localization

Doctoral thesis (2024)

Authors

Z. Xia Intelligent Vehicles - Mechanical, Maritime and Materials Engineering

Contributors

J.F.P. Kooij Intelligent Vehicles - Mechanical, Maritime and Materials Engineering (supervisor)
D. Gavrila Intelligent Vehicles - Mechanical, Maritime and Materials Engineering (supervisor)
Research Group
Intelligent Vehicles (Mechanical, Maritime and Materials Engineering) (TU Delft)
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Published Date

2024

Language

English

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Faculty

Mechanical, Maritime and Materials Engineering

Department

Cognitive Robotics

Research Group

Intelligent Vehicles

Abstract

Automated driving has immense potential for improving road safety. Over the past decades, extensive research has been conducted in this field. Although the technological capability for highly automated driving exists today, its widespread application is not yet present. One major limiting factor of current automated driving solutions is that vehicle localization heavily relies on high-definition maps (HD maps), which are highly expensive to construct and maintain. This dissertation focuses on developing a more scalable solution for vehicle localization. It explores a novel technique that estimates the ego vehicle’s pose (location and orientation) by matching ground-level images captured by the vehicle’s onboard camera to publicly available geo-referenced aerial imagery...

Files

Phd_thesis_20241114.pdf
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