Pavement roughness index estimation and anomaly detection using smartphones

Qiqin Yu, Yihai Fang, Richard Wix

Research output: Contribution to journalReview ArticleResearchpeer-review

40 Citations (Scopus)

Abstract

The prevalence of smartphones among vehicle drivers presents exciting opportunities in assessing pavement roughness in a more efficient and cost-effective manner, compared with using conventional instruments. This paper describes the body of knowledge in smartphone-based roughness assessment, reports knowledge gaps and casts light on future research directions. First, a systematic literature search found 192 academic publications in relevant fields. These works were critically reviewed with regard to sensor selection, pre-processing methods, and assessment algorithms. Special attention was given to practical factors that are expected to affect the accuracy and robustness of smartphone-based methods, including data collection speed, vehicle type, smartphone specifications and mounting configuration. Findings from this research are expected to provide a thorough understanding of the potentials and limitations of smartphone-based roughness assessment methods and inform future research and practices in this domain.

Original languageEnglish
Article number104409
Number of pages20
JournalAutomation in Construction
Volume141
DOIs
Publication statusPublished - Sept 2022

Keywords

  • Algorithm
  • Pavement roughness
  • Roughness index
  • Smartphone
  • Surface distress

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