Using Regression Analysis and Distribution Fitting to Analyze Pavement Sensing Patterns for Condition Assessments

Pavement condition assessment is essential for pavement asset management and it involves data collecting, pattern detecting, and condition monitoring processes. The paper presents an approach using regression analysis and probability distribution fitting to analyze pavement sensing patterns and signals collected on the I-10 corridors in Phoenix, Arizona. A vehicle is equipped with four sensors placed on the top of the control arms of the vehicle and one sensor is inside of the vehicle to gather the data for analysis. The result of the multiple regression analysis shows that the mean of sensors differ in a logarithmic scale at significance level 0.05, which suggests that all sensors should be included for pavement condition assessments. The distribution models are fitted using the acceleration vibration and can be used to determine the threshold values by computing a specified percentile, for example 99th percentile. The determination of thresholds varies based on the statistical analysis and the data falls in the remaining percent would indicate the pavement deterioration, which is called significant points in the paper. The ANOVA results show that there is an association between two variables (pavement temperatures and the number of significant points) at the significance level 0.05 which indicates the pavement temperature does play an important role in controlling pavement condition. Based on the Time-Series analysis and prediction, the pavements will be deteriorated if the maintenance and rehabilitation will not be scheduled. The paper concludes that using multiple regression analysis and distribution fitting method provides a promoting approach that can be used to help determine the level of different pavement conditions as well as predicting future performance.

• Record URL:
  https://annualmeeting.mytrb.org/OnlineProgram/Details/15859
• Supplemental Notes:
  • This paper was sponsored by TRB committee AED60 Standing Committee on Statistical Methods.
• Corporate Authors:

  Transportation Research Board

  ,    
• Authors:
  • Zhang, Dada
  • Ho, Chun-Hsing
  • Zhang, Fangfang
• Conference:
  • Transportation Research Board 100th Annual Meeting
  • Location: Washington DC, United States
  • Date: 2021-1-5 to 2021-1-29
• Date: 2021

Language

• English

Media Info

• Media Type: Digital/other
• Features: Figures; Maps; References; Tables;
• Pagination: 20p

Subject/Index Terms

• TRT Terms: Analysis of variance; Condition surveys; Data collection; Distributions (Statistics); Multiple regression analysis; Pavements; Sensors
• Geographic Terms: Phoenix (Arizona)
• Subject Areas: Highways; Maintenance and Preservation; Pavements;

Filing Info

• Accession Number: 01764954
• Record Type: Publication
• Report/Paper Numbers: TRBAM-21-04008
• Files: TRIS, TRB, ATRI
• Created Date: Feb 17 2021 7:23PM