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Development and evaluation of relationships between surface condition rating and objective pavement condition parameters
International Journal of Pavement Engineering ( IF 3.8 ) Pub Date : 2021-03-12 , DOI: 10.1080/10298436.2021.1894421
Tamina Tasmin 1 , David Richards 1 , Hussein Dia 1 , James Wang 1
Affiliation  

ABSTRACT

Highway authorities make efforts to relate visual ratings with directly measured pavement condition data to reduce or remove the necessity of manual pavement condition surveys that involve subjectivity and potential safety risk of assessors. This research develops a set of relationships between pavement surface condition rating and objective pavement condition parameters to assist road asset managers in triggering periodic bituminous resurfacing programs at the network level. These condition parameters include cracking (% area affected), rutting (mm), texture loss (% of left wheel path texture), and roughness (m/km). In the literature, deterministic and probabilistic modelling approaches are used to predict visual surface inspection rating (SIR) from directly measured pavement distresses. The Factorial ANOVA results that are typically used have inferred that cracking and rutting interact with each other significantly for the asphalt surfaced road network. However, the percentages of variation explained by the linear regression models that predict SIR from cracking/rutting are low (24–31%). Alternatively, developed ordinal logistic models for predicting the probability of a road section being in any particular surface condition, with any quantified cracking/rutting data, prove to be statistically better with overall success rates of 46% and 51% for sprayed sealed and asphalt surfaced network, respectively.



中文翻译:

开发和评估表面状况等级与客观路面状况参数之间的关系

摘要

公路当局努力将视觉评级与直接测量的路面状况数据联系起来,以减少或消除涉及评估人员主观性和潜在安全风险的人工路面状况调查的必要性。本研究开发了一组路面状况等级和客观路面状况参数之间的关系,以帮助道路资产管理者在网络级别触发定期沥青路面重铺计划。这些条件参数包括开裂(受影响面积百分比)、车辙(mm)、纹理损失(左轮路径纹理的百分比)和粗糙度(m/km)。在文献中,确定性和概率建模方法用于从直接测量的路面破损中预测视觉表面检测等级 (SIR)。通常使用的阶乘方差分析结果推断,沥青路面道路网络的开裂和车辙相互作用显着。然而,预测 SIR 开裂/车辙的线性回归模型解释的变异百分比很低(24-31%)。或者,开发的序数逻辑模型用于预测路段处于任何特定表面条件的概率,以及任何量化的开裂/车辙数据,证明在统计上更好,喷涂密封和沥青表面的总体成功率为 46% 和 51%网络,分别。由预测 SIR 开裂/车辙的线性回归模型解释的变异百分比很低(24-31%)。或者,开发的序数逻辑模型用于预测路段处于任何特定表面条件的概率,以及任何量化的开裂/车辙数据,证明在统计上更好,喷涂密封和沥青表面的总体成功率为 46% 和 51%网络,分别。由预测 SIR 开裂/车辙的线性回归模型解释的变异百分比很低(24-31%)。或者,开发的序数逻辑模型用于预测路段处于任何特定表面条件的概率,以及任何量化的开裂/车辙数据,证明在统计上更好,喷涂密封和沥青表面的总体成功率为 46% 和 51%网络,分别。

更新日期:2021-03-12
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