Precision Inverse Modeling of Highway Pavements Based on Standardized Alignment

Abstract

Reconstruction and expansion, as well as asset management, of highways necessitate the development of a current and highly precise 3D pavement model. Current inverse modeling methods with point clouds are laborious, time-consuming, and limited in precision. This article introduces an alternative framework for parametric inverse procedural modeling of highway pavement with standardized alignments seamlessly integrated with off-the-shelf modeling software. It comprises three key steps. (1) Extraction of highway pavement boundaries and lane markings: Initially, we combine grid-based and model-driven methods, followed by line structure-based clustering, to accurately generate road centerlines and layouts. (2) Road centerline generation: The centerline, derived from lane markings, informs highway alignments and parameters based on geometric characteristics such as curvature and slope. We utilize cost functions to facilitate this process. (3) Novel inverse procedural assembly: This innovative step integrates off-the-shelf modeling software. This approach involves extracting vector lines from point clouds and applying constraints at pivotal points on highway pavement cross-sections. Our focus is on refined component-level modeling, allowing for the assembly of diverse highway elements. This method significantly reduces human intervention and achieves high precision. In tests on two highway datasets from Sichuan Province, China, our method achieved excellent results. It attained an average correctness of 98.63% and completeness of 99.66% within a 10 cm error margin. A comparison with the intersection point method indicated minimal errors, with maximum values below 1.2%. The resultant 3D highway pavement model is modular and highly accurate at the centimeter level.

Keywords

• Geometric design standards
• highway alignments
• inverse procedural modeling
• mobile laser scanners (MLS) point clouds