3D Roadway Model Anomaly Detection with Template Drops
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Solution Overview
Problem
Detecting anomalies and changes in 3D roadway models is difficult due to their long linear aspect and obscured layers, making manual review slow and error-prone.
Innovation Solution
Anomaly and change detection software extracts template drops along a horizontal alignment, constructs a graph to analyze geometric properties, and flags inconsistencies or gaps, displaying results in a user interface.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual review of 3D roadway models is performed, then users can visually inspect the model, but the process is slow and error-prone due to the long linear aspect and obscured layers
Solution Approach 1:
The patent replaces manual visual inspection with automated computer-based detection algorithms. The system automatically extracts template drops, constructs graphs of geometric relationships, and identifies anomalies without human intervention, thereby eliminating the time loss associated with manual review while maintaining detection accuracy through computational methods
Solution Approach 2:
The patent creates a 2D representation (template drop) of each cross-section of the 3D roadway model at regular intervals. This 2D copy simplifies the complex 3D data into an ordered list that can be easily processed and reviewed, allowing automated detection while preserving all geometric information needed for anomaly identification
2Ease of operation
If 3D roadway models are viewed in 3D view, then the model structure is visible, but layers obscure each other making anomaly detection difficult
Solution Approach 1:
The patent segments the continuous 3D roadway model into discrete cross-sectional slices (template drops) at regular intervals along the horizontal alignment. This segmentation separates the overlapping layers into individual 2D representations, making each layer visible and detectable without obstruction from other layers, thereby resolving the visibility problem in 3D views
Solution Approach 2:
The patent transforms the 3D roadway model into a series of 2D cross-sectional views (template drops) arranged in an ordered list. This dimensional transformation from 3D to 2D eliminates the obscuration problem by viewing each layer from a perpendicular perspective, making all layers simultaneously visible and detectable without mutual obstruction
3Productivity
If automated detection algorithms are applied, then review speed increases, but the system must handle complex geometric relationships and potential false positives
Solution Approach 1:
The patent introduces a graph data structure as an intermediary between the template drops and the anomaly detection logic. The graph represents geometric relationships (adjacency, continuity, overlap) between consecutive template drops, simplifying the detection of anomalies by reducing complex spatial relationships to graph theory problems that can be solved efficiently with standard algorithms
Solution Approach 2:
The patent transforms the continuous 3D model into discrete parameters (template drops) with specific geometric properties (horizontal position, vertical position, dimensions). By changing the representation from continuous geometry to discrete parameterized sections, the system can efficiently process and compare features using simple geometric comparisons, thereby increasing productivity while managing complexity through parameterization
Data Source
AI summary
In example embodiments, anomaly and change detection software of a cloud-based design review service is provided for detecting anomalies and/or changes in 3D roadway models. The software analyzes the constituent meshes of the 3D roadway model that represent components and extracts template drops at locations along a horizontal alignment to produce an ordered list of template drops. The software then looks to differences in depths, widths, cross slopes and/or other geometric properties manifest in individual template drops, or between preceding/subsequent template drops of the ordered list, to detect anomalies and/or changes. Indications of the components associated with the detected anomalies and/or changes are displayed in a visualization of the 3D roadway model in a user interface.