Investigation of seasonal variations of Beijing pavement condition data using unevenly spaced dynamic panel data model

Abstract

Beijing municipal highway administration started to collect pavement condition data on its major expressways since 2006. It is advised in the Chinese practice standard that data collection shall be conducted on annual basis. However, pavement data are usually collected at different seasons of the year, which may cause significant seasonal variations in the observed condition. Moreover, for some reasons, data are missing for some of the pavement sections at certain years, which could bring up difficulties in performance model estimation and inference. These concerns have been simply neglected in past practice. This study proposed an unevenly spaced dynamic panel data model to investigate the seasonal patterns of a performance indicator called Ride Quality Index (RQI). A quasi-differencing approach was adopted for the estimation. Data collected from the 5th Ring Road of Beijing were used in the case study. It was found that RQI data collected during the fall season are expected to be lower than that collected during the spring or summer seasons. Findings from this research would be helpful to pavement engineers in using unevenly spaced pavement condition data for future condition estimation.

Keywords:

• Pavement performance
• panel data
• seasonal
• time series
• unevenly spaced

Additional information

Funding

The authors would like to acknowledge the financial support for this study provided by the National Natural Science Foundation of China [grant no.51478021], National Social Science Foundation of China [Youth Program, Grant No.16CGL001], 2015 Key Project of Beijing Natural Science Foundation and Key Technology Project of Beijing Municipal Commission of Education [Grant No. KZ201510005002], Beijing Excellent Talent Program [Grant No. 2015000020124G035], and China Postdoctoral Science Foundation Funded Project [Project No. 2016M592696].