Dissertation Defence: Modernizing Pavement Condition Assessment
July 22 at 9:00 am - 1:00 pm
Ali Faisal, supervised by Dr. Suliman Gargoum, will defend their dissertation titled “Modernizing Pavement Condition Assessment: A Unified Framework Integrating Light Detection and Ranging and Computer Vision to Overcome Index Fragmentation” in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Civil Engineering.
An abstract for Ali Faisal’s dissertation is included below.
Examinations are open to all members of the campus community as well as the general public. This examination will be offered in hybrid format. Registration is not required to attend in person, but please email suliman.gargoum@ubc.ca to receive the Zoom link for this exam.
Abstract
Pavement condition assessment remains fragmented across transportation agencies, with inconsistent definitions, thresholds, and rating scales that limit comparability and decision consistency. This dissertation develops and validates a unified framework that combines LiDAR-based deformation measurement and vision-based crack into a single standardized pavement condition index. The work progresses in four stages. First, a survey of 14 Canadian transportation agencies documents the current state of practice and confirms substantial index heterogeneity. Second, LiDAR methods are developed and validated for rutting, roughness (IRI), and pothole detection and quantification. These methods achieve practical agreement with references, including rut-depth deviation near 2.5mm at operating thresholds, IRI RMSE below 0.05 m/km, and pothole geometric error below 5.6%, while identifying practical minimum densities of approximately 230 ppsm for stable rutting/IRI and 205 ppsm for pothole reliability. Third, a top-down crack segmentation and metrology workflow is developed for near-nadir roadway imagery, achieving F1=0.871 and IoU=0.783 at the selected operating point and producing physically interpretable crack metrics (density, width, and coverage). Fourth, these deformation and cracking outputs are integrated through severity-transfer functions, calibrated weighting, and section-level fusion to produce a Unified Pavement Condition Index. The full implementation is demonstrated on a 1.5km segment of Highway 97 through downtown Kelowna (15 sections). The computed corridor condition is PCI(100) =83.4 (PCI(5) =1.66). Validation against independent windshield ratings shows meaningful agreement with expert judgment (Pearson r = 0.74, Spearman ρ = 0.81, MAE=0.30 on the 1–5 scale, ICC(2,1)=0.85), with all sections within ±1 condition class. The resulting framework provides a repeatable, implementable basis for standardized pavement condition assessment using complementary sensing technologies.
