ABSTRACT

Texture is required on pavements to provide safe and comfortable ride performance for users. This paper provides the first meaningful analysis of a long-term study of texture data obtained using TRACS (TRAffic Speed Condition Survey) at a site in the UK. TRACS data were collected annually, over a 2 km stretch of motorway from 1995 to 2019. A new data analysis approach utilising time series data with spectral analysis and spatial filtering procedures is presented. The results reveal that the approach enables legacy TRACS laser profile Sensor Measured Texture Depth (SMTD) data to be used to determine long term rates of change in road surface macrotexture. Thus, the technique has unlocked the potential for SMTD data collected annually for 7000 km of the Strategic Road Network in the UK, to inform road maintenance programmes by extrapolation. Additionally, results expose a systematic periodicity occurring each year within the SMTD data studied, corresponding to longitudinal oscillations with wavelengths between 33 and 62 m. The time-invariant periodicity of these oscillations suggests that it is ‘imprinted’ in the early life of the pavement. ‘Imprinting’ may theoretically arise with cyclic tyre loading applied by the suspension systems of heavy vehicles or during road construction.

摘要

人行道上需要纹理，以便为用户提供安全舒适的乘坐性能。本文首次对在英国的一个地点使用 TRACS（TRAffic Speed Condition Survey）获得的纹理数据进行了有意义的分析。从 1995 年到 2019 年，每年在 2 公里的高速公路上收集 TRACS 数据。提出了一种利用时间序列数据和光谱分析和空间过滤程序的新数据分析方法。结果表明，该方法使传统的 TRACS 激光轮廓传感器测量纹理深度 (SMTD) 数据能够用于确定路面宏观纹理的长期变化率。因此，该技术释放了每年为英国 7000 公里的战略道路网络收集的 SMTD 数据的潜力，以通过推断为道路维护计划提供信息。此外，结果揭示了每年在所研究的 SMTD 数据中发生的系统周期性，对应于波长在 33 和 62 m 之间的纵向振荡。这些振荡的不随时间变化的周期性表明它在路面的早期生命中“留下了印记”。从理论上讲，“印记”可能会在重型车辆的悬挂系统或道路施工期间施加的循环轮胎载荷中出现。