路面损坏状况指数PCI未确知聚类预测方法

Unascertained Clustering Prediction Method of the Pavement Surface Condition Index(PCI)

路面损坏状况指数PCI是沥青路面使用性能指数PQI分项指标之一,路面损坏状况的检测采用快速检测设备检测或人工方法调查,但沥青路面损坏分类和分项较多,无论采用何种方式检测均较为复杂。通过研究PCI与沥青路面使用性能指数PQI其他3个指标路面行驶质量指数RQI、路面车辙深度指数RDI、路面抗滑性能指数SRI的关系,采用未确知聚类预测方法发掘PCI与RQI、RDI、SRI之间的内部联系。通过预测路面破损状况指数PCI,可用于辨识并剔除公路技术状况评定中的不良数据,对于提高公路技术状况评定的工作效率具有重要意义。

Pavement surface condition index （PCI） is one of four individual indexes of the asphalt pavement performance index. Pavement surface condition index is detected by rapid detection device or artificial methods. However, both methods are complicated due to the multiple classifications of asphalt pavement damages. Through researching the relationship between Pavement Surface Condition Index （PCI） and other indexes of Pavement Qual- ity or Performance Index （PQI）：Riding Quality Index （PQI）, Rutting Depth Index （RDI）, Skidding Resistance Index （SRI） , the unascertained clustering prediction method is used to explore the internal link between SRI through PCI and RQI, RDI, SRI. The predicted Pavement surface condition index （PCI） can be utilized in identif- ying and eliminating the fault data in highway performance assessment, which has important significance in impro- ving the efficiency of the highway performance assessment.