Pavement roughness index estimation and anomaly detection using smartphones

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. [Display omitted] •Smartphone-based roughness assessment shows potential to supplement conventional methods.•A systematic performance evaluation of smartphone-based systems is lacking.•Systems that consider both acceleration and vision signals should be explored.•More features from the signal's temporal and spatial domains should be incorporated.