Date of Award
Doctor of Philosophy (PhD)
Computational Modeling & Simulation Engineering
Modeling and Simulation
Frederic D. McKenzie
Duc T. Nguyen
Many computer applications such as racing games and driving simulations frequently make use of 3D high-fidelity road network models for a variety of purposes. However, there are very few existing methods for automatic generation of 3D realistic road networks, especially for those in the real world. On the other hand, vast road network GIS data have been collected in the past and used by a wide range of applications, such as navigation and evaluation. A method that can automatically produce 3D high-fidelity road network models from 2D real road GIS data will significantly reduce both the labor and time needed to generate these models, and greatly benefit numerous applications involving road networks. Based on a set of selected civil engineering rules for road design, this dissertation research addresses this problem with a novel approach which transforms existing road GIS data that contain only 2D road centerline information into 3D road network models. The proposed method consists of several components, mainly including road GIS data preprocessing, 3D centerline modeling and 3D geometry modeling. During road data preprocessing, topology of the road network is extracted from raw road data as a graph composed of road nodes and road links; road link information is simplified and classified. In the 3D centerline modeling part, the missing height information of the road centerline is inferred based on 2D road GIS data, intersections are extracted from road nodes and the whole road network is represented as road intersections and road segments in parametric forms. Finally, the 3D road centerline models are converted into various 3D road geometry models consisting of triangles and textures in the 3D geometry modeling phase.
With this approach, basic road elements such as road segments, road intersections and traffic interchanges are generated automatically to compose sophisticated road networks. Results show that this approach provides a rapid and efficient 3D road modeling method for applications that have stringent requirements on high-fidelity road models.
"Automatic High-Fidelity 3D Road Network Modeling"
(2011). Doctor of Philosophy (PhD), Dissertation, Computational Modeling & Simulation Engineering, Old Dominion University, DOI: 10.25777/2zer-2787
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