Quantifying long-term rates of texture change on road networks

Abstract

John (2020) Quantifying long-term rates of texture change on road networks.

Toward the Determination of the Appropriate Capturing Resolution of Surface Textures in Relation to Pavement Friction

“…Then, in a second step, from these measured textures, different new resolutions are created by resampling. The friction of these resampled textures is calculated using the dynamic friction model (DFM [8][9][10][11][12][13]), a model already validated. In a third step, a comparison between calculated friction (with the DFM) and the experimentally measured friction on the set of pavement surfaces are conducted in order to determine which of the resolutions (obtained after resampling) allows the most accurate prediction.…”

“…The DFM or dynamic friction model is a friction model of a rubber pad/pavement based on the modeling of the contact of these two bodies [8][9][10][11][12][13]. This model considers the type of rubber, the roughness of the road, the level of wetting and the operating conditions (load, sliding speed, etc.).…”

“…(This adhesion friction coefficient corresponds to the optimum value which, inputted to the DMF, outputs the best prediction of the experimental friction.) [8][9][10][11][12][13].…”

Seasonal Signals Observed in Non-Contact Long-Term Road Texture Measurements

“…The southbound inside lane was considered more likely to have the heaviest traffic usage being the lane favoured by heavy goods vehicles (HGV). The mean average length of the inside southbound lane considered at each site was 800 m. The raw texture depth data captured by TRACS for these sites were preprocessed by the Highway Agency's machine preprocessor and stored as SMTD in the Highways Agency Pavement Management System (HAPMS) [30], for a 300 mm evaluation length at 10 m intervals, as previously described in [23]. SMTD is used in the UK for texture reporting and has previously been found to relate to mean profile depth (MPD) by the relationship [34]: The A1(M) varies along its route from one to four lanes.…”

“…The International Roughness Index (IRI) is widely used for this purpose, with acceptable IRI threshold levels specified on a country by country basis for new, reconstructed and rehabilitated roads [6]. Recent, research has also suggested that texture readings can enhance maintenance planning by estimating long-term "rates of change" from legacy data as a guide to predicting the future evolution of texture on pavement surfaces [23]. Several parameters related to vehicle type and traffic flow have been proven to have an effect on the state of texture evolution.…”