Integrating Pavement Sensing Data for Pavement Condition Evaluation

Sensors

Andreas Loizos¹  Konstantinos Gkyrtis¹  Christina Plati¹ 

[1] Laboratory of Pavement Engineering, NTUA Campus, National Technical University of Athens (NTUA), 5, Iroon Polytechniou, GR-15773 Athens, Greece;

关键词: pavement profile;    deflectometric data;    geophysical inspections;    data integration;    pavement management;   

DOI  :  10.3390/s21093104

来源: DOAJ

【 摘 要 】

Highway pavements are usually monitored in terms of their surface performance assessment, since the major cause that triggers maintenance is reduced pavement serviceability due to surface distresses, excessive pavement unevenness and/or texture loss. A common way to detect pavement surface condition is by the use of vehicle-mounted laser sensors that can rapidly scan huge roadway networks at traffic speeds without the need for traffic interventions. However, excessive roughness might sometimes indicate structural issues within one or more pavement layers or even issues within the pavement foundation support. The stand-alone use of laser profilers cannot provide the related agencies with information on what leads to roughness issues. Contrariwise, the integration of multiple non-destructive data leads to a more representative assessment of pavement condition and enables a more rational pavement management and decision-making. This research deals with an integration approach that primarily combines pavement sensing profile and deflectometric data and further evaluates indications of increased pavement roughness. In particular, data including Falling Weight Deflectometer (FWD) and Road Surface Profiler (RSP) measurements are used in conjunction with additional geophysical inspection data from Ground Penetrating Radar (GPR). Based on pavement response modelling, a promising potential is shown that could proactively assist the related agencies in the framework of transport infrastructure health monitoring.

【 授权许可】

Unknown