The National Academies

ACRP Synthesis 11-03/Topic S09-09 [New]

Automated Pavement Condition Survey Practices at Airports
[ ACRP 11-03 (Synthesis of Information Related to Airport Practices) ]

  Project Data
Funds: $45,000
Staff Responsibility: Kerry L. Ahearn
Fiscal Year: 2020

Tentative Scope

Pavement condition data is a critical component of all pavement management systems. The accuracy and validity of pavement condition data is the basis for many activities conducted by airports and local agencies. Pavement condition data is used, for example, to support asset management, assess existing and future pavement condition, establish budget needs and evaluate budget impacts, and select projects for pavement maintenance and rehabilitation. Many federal transportation bills (National Performance Management Measures; Assessing Pavement Condition for the National Highway Performance Program and Bridge Condition for the National Highway Performance Program) are performance-based.  As such, agencies are increasingly required to report validated pavement conditions when requesting funding.  Pavement condition reporting in support of federal funding requests includes existing project data on rut depth, the International Roughness Index (IRI) and percent cracking for flexible pavements and faulting for jointed concrete pavements, and IRI and percent cracking for continuously reinforced concrete pavements.

ACRP Research Report 203, Collecting, Applying, and Maintaining Pavement Condition Data at Airports, was published in 2019. The report describes best practices in collecting and using airfield pavement condition data. As part of the pavement management process the data are used to determine the Pavement Condition Index (PCI), which in turn is used to inform and improve operations, maintenance, and capital improvement programs. The availability of guidance to help airports determine the best approaches to collect, apply, and maintain pavement condition data has not kept pace with rapid changes in the associated technology, and this report was developed to address the need for guidance on the strategies available for pavement condition data collection, use, and storage. Decision tools (decision trees and matrices) are used to present appropriate strategies. Many airports approach this topic differently, and with new technologies deployed, there will continue to be a broad range of practices. The guidelines presented will help those involved in airport pavement condition data to sort through associated decisions related to those practices.  NCHRP Synthesis 334, Automated Pavement Distress Collection Techniques, 2004, documents highway community practice and research and development efforts in the automated collection and processing of pavement condition data techniques typically used in network-level pavement management. The study covered all phases of automated pavement data collection and processing for pavement surface distress, pavement ride quality, rut-depth measurements, and joint-faulting measurements. Included in the scope were technologies employed (now potentially dated), contracting issues, quality assurance, costs and benefits of automated techniques, monitoring frequencies and sampling protocols in use, degree of adoption of national standards for data collection, and contrast between the state of the art and the state of the practice. Three case studies are included as examples of transportation agencies applying a variety of methods for pavement condition data collection and processing.  This synthesis uses both reports as bases and updates the technology that is and can be used to collect pavement condition information. 

Airport agencies have implemented automated pavement data collection for several years now. It is important to learn from their experience and the improvements in their process over time.  Uses of GIS and ADS-B are of increasing interest.  This concise synthesis of practice intends to document existing practices from a range of geographically and size diverse airports.  Compilation of practices and lessons learned will be very beneficial to airports that are just moving into automated pavement data collection or airports with limited experience and few staff. 

The objective of this synthesis is to document airport practices, challenges, and success in conducting automated pavement condition data collection surveys. The study is intended to showcase successful practices, integration of automated data collection into pavement management systems, and efforts needed for reporting pavement condition.  The intended audience for this compilation of practice is airport maintenance managers and engineering staff responsible for airfield pavement maintenance management systems.

Information to be described in a concise report to describe airport practices:
• FAA requirements
• Pavement distress types
• Technology based data collection methodologies
• Systems/platforms
• Post processing practices
• Quality management considerations
• Appendix materials that display helpful documents/checklists
• Further research to close knowledge gaps

Information will be collected through a literature review, a survey of state aeronautical agencies, airports (geographically and NPIAS category distributed), with selected follow up to document case examples highlighting effective practices including small airports with fewer resources.

Partial Information Sources

ACRP Research Report 203, Collecting, Applying, and Maintaining Pavement Condition Data at Airports, 2019.  http://www.trb.org/Publications/Blurbs/179612.aspx

NCHRP Synthesis Report 334, Automated Pavement Distress Collection Techniques, 2004.  http://www.trb.org/Publications/Blurbs/155178.aspx
Airfield Pavement Management Framework using a Multi-Objective Decision Making Process. [Project].  Office of the Assistant Secretary for Research and Technology. Start date: 1 Sep. 2018.

Peshkin, David; Dzwilewski, Peter-Paul F; Potvin, Kyle M; Gauthier, Katherine; Wade, Monty; Risner, Eric; Robinson, Ryan; Snyder, Chris; Cardwell, Marianne; Feighan, Kieran. Guidelines for Collecting, Applying, and Maintaining Pavement Condition Data at Airports. ACRP Research Report, Issue 203, 2019, 123p

Tingle, Jeb S; Norwood, Gregory J; Cotter, Brian. Use of Continuous Friction Measurement Equipment to Predict Runway Condition Rating on Unpaved Runways. Transportation Research Record: Journal of the Transportation Research Board, Issue 2626, 2017, pp 58–65

Buttlar, William G; Alavi, Amir; Brown, Henry; Sills, Henry; Mesa, Amanda; Okenfuss, Elizabeth. Pavement Roughness Measurement Using Android Smartphones: Case Study of Missouri Roads and Airports.  University of Missouri, Columbia; Applied Research Associates; Missouri Department of Transportation; Federal Highway Administration, 2018, 124p

Airfield and Highway Pavements 2017: Airfield Pavement Technology and Safety. International Conference on Highway Pavements and Airfield Technology 2017, American Society of Civil Engineers, 2017, 259p

Zhan, You; Li, Qiang Joshua; Yang, Guangwei; Wang, Kelvin C  P. Performance Monitoring of Pavement Surface Characteristics with 3D Surface Data. International Conference on Highway Pavements and Airfield Technology 2017, American Society of Civil Engineers, 2017, pp 195-206

Mazari, Mehran; Beltran, Jorge; Tirado, Cesar; Lemos, Luis; Nazarian, Soheil. Evaluating Stiffness Parameters of Unbound Geomaterial Layers Using Intelligent Compaction, Plate Load Test, and Light Weight Deflectometer. International Conference on Highway Pavements and Airfield Technology 2017, American Society of Civil Engineers, 2017, pp 186-194

Villarreal, Jose; Hossain, M. Condition Evaluation of General Aviation Airport Runway Pavements. Airfield and Highway Pavements 2015, American Society of Civil Engineers, 2015, pp 572-580

Karim, Fareed M A. The airfield pavement condition index (PCI) evaluation by visual inspection method. Journal of Airport Management, Volume 8, Issue 3, 2014, pp 275-285

Li, Qiang (Joshua); Wang, Kelvin C P; Yang, Guangwei; Li, Lin. One-mm 3D Laser Imaging Survey for Comprehensive Runway Evaluation. 2014 FAA Worldwide Airport Technology Transfer Conference, Federal Aviation Administration, 2014, 13p

Lima, D., Santos, B., & Almeida, P. (2019). Methodology to assess airport pavement condition using GPS, laser, video image and GIS. Paper presented at the Pavement and Asset Management - Proceedings of the World Conference on Pavement and Asset Management, WCPAM 2017.

Rodriguez, D. D., & Edwards, L. (2017). Implementing the traffic speed deflectometer for airfield runway assessment. Paper presented at the Bearing Capacity of Roads, Railways and Airfields - Proceedings of the 10th International Conference on the Bearing Capacity of Roads, Railways and Airfields, BCRRA 2017.

Drenth, K., Ju, F. H., & Tan, J. Y. (2016). Structured management of airfield pavements using effective tools. Paper presented at the 8th International Conference on Maintenance and Rehabilitation of Pavements, MAIREPAV 2016.

Topic Panel


TRB Staff
Gail R. Staba


1st Meeting 
Workplan Delivered 
Comments Due (Email) 
Draft Report Delivered 
2nd Panel Meeting 

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