基于等维灰数递补模型的路面性能预测方法

1)长安大学公路学院,陕西西安 710064; 2)广东华路交通科技有限公司,广东广州 510420

道路工程; 灰色GM(1, 1)模型; 等维灰数递补模型; 路面使用性能; 性能预测; 精度

Prediction method of pavement performance based on same dimension gray recurrence dynamic model
ZHAO Jing1, WU Wangjie1, WANG Xuancang1, LI Shanqiang1, 2, FANG Naren1, and DENG Ruixiang1

1)School of Highway, Chang'an University, Xi'an 710064, Shaanxi Province, P.R.China2)Guangdong Hua Lu Transportation Technology Co.Ltd., Guangzhou 510420, Guangdong Province, P.R.China

road engineering; grey GM(1, 1)model; same dimension gray recurrence dynamic model; pavement usage performance; performance prediction; precision

DOI: 10.3724/SP.J.1249.2019.06628

备注

为了准确掌握沥青路面使用性能指标的变化趋势,以车辙指数(rutting depth index, RDI)为例提出了能够有效动态使用新数据的等维灰数递补模型.利用该模型对路面状况指数(pavement condition index, PCI)、行驶质量指数(riding quality index, RQI)和横向力指数(skidding resistance index, SRI)等指标进行了预测. 结果表明,使用等维灰数递补模型对RDI、PCI、RQI和SRI预测在第3步时,最小误差概率均为1,后验方差比分别为0.1117、0.0654、0.2018和0.1130. 证明了随着步数的增加,其预测结果精度越高、误差越小,表明该方法能够准确地预测路面性能.

In order to accurately grasp the change trend of asphalt pavement performance index, taking the rutting depth index(RDI)as an example, we establish a gray recurrence dynamic model with equivalent dimension which can use the new data effectively and dynamically. The model is used to predict the indexes such as pavement condition index(PCI), driving quality index(RQI)and skidding resistance index(SRI). The results show that in step 3, the minimum error probabilities of RDI, PCI, RQI and SRI are all 1, and the posterior prescription variance ratios are: 0.111 7, 1, 0.065 4, 1, 0.201 8,and 0.113 0, respectively. It is proved that with the increase of recursive steps, the accuracy of the prediction result of the model becomes higher, and the error becomes less, which shows that the method can accurately predict the road performance.

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