Integrate and store 3D roads and terrain for navigation purposes

Student report (2023)

Authors

D. MOUZAKIDIS Architecture and the Built Environment
Puti Puti Nabila Riyadi Architecture and the Built Environment
G.K. Nestoras Architecture and the Built Environment
L. Xu Architecture and the Built Environment
N. Liu Architecture and the Built Environment
S. Köbben Architecture and the Built Environment

Contributors

G.A.K. Arroyo Ohori Urban Data Science - Architecture and the Built Environment (supervisor 1)
S. Vitalis Urban Data Science - Architecture and the Built Environment (supervisor 1)
J.E. Stoter Urban Data Science - Architecture and the Built Environment (supervisor 1)
Faculty
Architecture and the Built Environment
Copyright: © 2023 DIMITRIOS MOUZAKIDIS, Puti Puti Nabila Riyadi, Konstantinos Nestoras, Leon Xu, Na Liu, Stein Köbben
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Published Date

16-11-2023

Language

English

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Faculty

Architecture and the Built Environment

Abstract

Modern navigation heavily relies on Global Navigation Satellite Systems (GNSS) and digitized road network databases, but faces limitations in GNSS-denied areas and complex 2D road netowrks. This project addresses these challenges by developing a methodology to create and store a comprehensive 3D road and terrain dataset for enhanced navigation. In collaboration with TomTom, a company that aims to fulfill software requirements, making significant advancements in geolocation technology and societal contributions. The main research question of the project is: ”How can we create a 3D map of roads using information about the center of the road and elevation data?”. The approach to answer this question involves extracting 2D road polygons from centerline data based on width of the roads, the direction and the amount of lanes of them. These 2D polygons undergo enrichment with elevation data, with techniques like filtering, segmentation, and primitive extraction ensuring alignment with the digital terrain model. The methodology encompasses data acquistion, creation of polygons using the centerlines dataset, 2D-to-3D polygon conversion, elevation integration and data storage in CityJSON format.