Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Pavement roughness index estimation and anomaly detection using smartphones
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.
Graphical abstract Display Omitted
Highlights 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.
Pavement roughness index estimation and anomaly detection using smartphones
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.
Graphical abstract Display Omitted
Highlights 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.
Pavement roughness index estimation and anomaly detection using smartphones
Yu, Qiqin (Autor:in) / Fang, Yihai (Autor:in) / Wix, Richard (Autor:in)
03.06.2022
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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