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Coordinating, Developing, and Delivering Highway Transportation Innovations

 
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Publication Number:  FHWA-HRT-17-049    Date:  October 2017
Publication Number: FHWA-HRT-17-049
Date: October 2017

 

Investigation of Increase in Roughness Due to Environmental Factors in Flexible Pavements Using Profile Data From Long-Term Pavement Performance Specific Pavement Studies 1 Experiment

CHAPTER 7. SUMMARY AND CONCLUSIONS

Eighteen SPS-1 projects were constructed for the LTPP SPS-1 experiment. The number of projects located on coarse- and fine-grained subgrade were 11 and 7, respectively. The distribution of the projects according to the environmental zones were: DNF—two projects, DF—two projects, WNF—eight projects, and WF—six projects. Data from 201 test sections were analyzed, with 125 of these test sections located on a coarse-grained subgrade and the other 76 sections located on a fine-grained subgrade. Because this was not a balanced experiment, some biases could be present when comparisons are performed between subgrade types and environmental zones.

The median ages of the test sections that were analyzed were 11.8 and 9.3 years for the sections on coarse- and fine-grained subgrade, respectively. The third quartile values for the age of the test sections were 13.7 and 12.2 years for the sections on coarse- and fine-grained subgrade, respectively.

CLIRI

In this project, the increase in roughness that occurred along the center of the lane was assumed to be due to environmental factors. A rate of change of CLIRI was computed for each test section using liner regression using the time-sequence CLIRI data. The following conclusions were drawn from the analysis of the data:

MIRI

The profile of the pavement can change due to environmental effects such as frost heave and swelling of the subgrade. Along the wheelpaths, the profile of the pavement can change due to traffic effects. Therefore, the changes in MIRI on a pavement can be due to both environmental and traffic effects. It is possible that the traffic may counteract the upward movements caused in the profile due to environmental effects by smoothing the profile. In addition to evaluating the changes in IRI along the center of the lane, the changes in MIRI were also studied in this project. A rate of change of MIRI was computed using liner regression analysis using the available time-sequence MIRI data at each test section, and the results were used for analysis. The following observations were noted from the analysis of the data:

Other Observations

Benefits of Collecting Profile Data Along the Center of the Lane

State transportation departments can obtain network-level profile data along the two wheelpaths of the travel lane and use MIRI values computed from the collected data to track the roughness of their highway network. Collecting profile data along the center of the lane could provide information on how the profile along the center of the lane, which is mainly influenced by environmental effects, would change over time. This information could be used to modify or improve the agency’s pavement design procedure to minimize large increases in IRI in areas where the combination of environmental and subgrade conditions caused such increases in the center lane. This information could also be used by the agency to build better models for predicting the change in IRI due to environmental conditions. If an agency collects network-level data using the services of a vendor, collection of the center of the lane profile data in addition to the wheelpath data would be expected to increase the cost minimally. If the agency used its own equipment to collect data, there would be a cost associated with upgrading existing equipment with an additional sensor to collect the profile data along the center of the lane. However, if the agency purchased new equipment, it could obtain equipment with an additional sensor that could collect data along the center of the lane at a small increase in cost.

 

 

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