Abstract: 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.

Abstract: In example embodiments, techniques are provided for enabling use of an AI-generated TIN in generation of a 3D design model by defining site objects (e.g., pads) using multiple (e.g., three) phases (i.e. states). A conceptual phase may be associated with a conceptual data structure, a preliminary phase may be associated with the conceptual data structure and a preliminary data structure, a final phase may be associated with the conceptual data structure, the preliminary data structure, and a final data structure. If changes are made in the conceptual phase, for example, as a result of AI optimization, they may be propagated up to the preliminary data structure and final data structure via the vertical draping. Changes made in the preliminary phase or final phase may be propagated down to the conceptual data structure by treating boundaries and breaklines as spatial constraints.