CVMar 4, 2022

Computer-Aided Road Inspection: Systems and Algorithms

arXiv:2203.02355v19 citationsh-index: 17
Originality Synthesis-oriented
AI Analysis

This work tackles the problem of inefficient and subjective manual road inspection for transportation authorities and public safety, but it appears incremental as it reviews existing systems and algorithms.

The chapter addresses the need for automated road inspection by comparing common road damage types and discussing 2-D/3-D imaging systems and state-of-the-art machine vision algorithms for detection, but does not report specific results or numbers.

Road damage is an inconvenience and a safety hazard, severely affecting vehicle condition, driving comfort, and traffic safety. The traditional manual visual road inspection process is pricey, dangerous, exhausting, and cumbersome. Also, manual road inspection results are qualitative and subjective, as they depend entirely on the inspector's personal experience. Therefore, there is an ever-increasing need for automated road inspection systems. This chapter first compares the five most common road damage types. Then, 2-D/3-D road imaging systems are discussed. Finally, state-of-the-art machine vision and intelligence-based road damage detection algorithms are introduced.

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Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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