Abstract

Road pavement is expected to withstand enormous traffic loads for long time but sooner or later the deterioration reaches levels when its optimal to apply treatment. While easy to measure roughness or rutting in normal traffic speed, defects are in most countries still collected by means of time-consuming visual inspection in low traffic speeds or expensive and difficult- to-use equipment. Also, most visual inspection systems only operate with aggregated inspection data. That makes data-collection expensive and defects-based decision-making inefficient. In Estonia, defects inventory system utilizes high quality panoramic and orthogonal images to enable data collection in traffic speeds and detailed mapping of pavement defects in 10 classes. Defects mapped in full detail means, that location, shape and size of each defect is known and classified data can be effectively used twice in pavement maintenance planning: for section selection planning in road network level when aggregated and for work method selection in design process when analyzed in detail. Combined with measured lidar-based point-cloud data, detailed 3d-basemap saves both road-owner's and road designer’s valuable time in design phase. In period of 2016-2020, around 35000km of state roads were analyzed with one of the most efficient road defects inventory systems in the world. Also, around 25000 km of municipal and forest roads have been captured with same technology covering several pavement types from bicycle paths to multilane streets and motorways. Current presentation discusses outcomes of Estonian defects inventory study in 2020.

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