Modeling the dynamic performance of transportation infrastructure using panel data model in state-space specifications  

作　　者：Bingye Han Zengming Du Lei Dai Jianming Ling Fulu Wei 

机构地区：[1]School of Civil and Transportation Engineering,Beijing University of Civil Engineering and Architecture,Beijing 100044,China [2]Jiangsu Technology Industrialization and Research Center of Ecological Road Engineering,Suzhou 215011,China [3]Key Laboratory of Infrastructure Durability and Operation Safety in Airfield of CAAC,Shanghai 201804,China [4]Foshan Construction&Development Group Co.,Ltd.,Foshan 528000,China [5]Key Laboratory of Road and Traffic Engineering of Ministry of Education,Tongji University,Shanghai 200092,China [6]China Construction Eighth Engineering Division Co.,Ltd.,Shanghai 200082,China [7]Lyles School of Civil Engineering,Purdue University,West Lafayette,IN 47907,USA

出　　处：《Journal of Traffic and Transportation Engineering(English Edition)》2023年第3期441-453,共13页交通运输工程学报（英文版）

基　　金：The authors disclosed receipt of the following financial support for the research,authorship,and/or publication of this article.This research is supported by the National Key R&D Program of China(2022YFB2601900);the R&D Program of Beijing Municipal Education Commission(KM202310016010);Jiangsu Technology Industrialization and Research Center of Ecological Road Engineering,Suzhou University of Science and Technology(GCZX2203);Key Laboratory of Infrastructure Durability and Operation Safety in Airfield of CAAC(MK202202);National Natural Science Foundation of China(No.5197082697);Natural Science Foundation of Beijing(No.Z21013).

摘　　要：In this study,different modeling approaches used in panel data for performance forecast of transportation infrastructure are firstly reviewed,and the panel data models(PDMs)are highlighted for longitudinal data sets.The state-space specification of PDMs are proposed as a framework to formulate dynamic performance models for transportation facilities and panel data sets are used for estimation.The models could simultaneously capture the heterogeneity and update forecast through inspections.PDMs are applied to tackle the cross-section heterogeneity of longitudinal data,and PDMs in state-space forms are used to achieve the goal of updating performance forecast with new coming data.To illustrate the methodology,three classes of dynamic PDMs are presented in four examples to compare with two classes of static PDMs for a group of composite pavement sections in an airport in east China.Estimation results obtained by ordinary least square(OLS)estimator and system generalized method of moments(SGMM)are compared for two dynamic instances.The results show that the average root mean square errors of dynamic specifications are all significantly lower than those of static counterparts as prediction continues over time.There is no significant difference of prediction accuracy between state-space model and curve shifting model over a short time.In addition,SGMM does not obtain higher prediction accuracy than OLS in this case.Finally,it is recommended to specify the inspection intervals as several constants with integer multiples.

关 键 词：Infrastructure performance MODELING Dynamic models State-space models Pavement condition index Ordinary least square Generalized method of moments 

分 类 号：U418.6[交通运输工程—道路与铁道工程]