My completed PhD research focuses on the assessment of pavement surfaces using computer vision and machine learning techniques. This research highlights and addresses the real-world challenges of automating pavement defect detection by evaluating the capabilities and limitations of deep learning and computer vision-based techniques. By developing object detection models for identifying pavement defects, this work explores the potential for effective automation in pavement assessment tasks and examines the barriers to achieving full automation in pavement inspections.