Automated Data Collection and Quality Management for Pavement Condition Reporting (2022)

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90 Responding State Highway Agencies A P P E N D I X B Agency Survey Responses Response Agencies No. of Agencies No Alabama, Alaska, Arizona, Arkansas, Colorado, Connecticut, Delaware, Georgia, Hawaii, Idaho, Illinois, Indiana, Iowa, Kansas, Kentucky, Maine, Michigan, Minnesota, Mississippi, Montana, Nebraska, Nevada, New Jersey, New Mexico, New York, North Carolina, North Dakota, Ohio, Oklahoma, Oregon, Pennsylvania, Rhode Island, South Carolina, South Dakota, Tennessee, Texas, Utah, Vermont, Virginia, Washington, DC, Washington State, West Virginia, Wisconsin, and Wyoming 44 Yes California, Florida, New Hampshire, and Puerto Rico 4 No. responding agencies: 48. General Information 1. Have you significantly modified your pavement condition data quality management plan since receiving initial FHWA approval? • Alabama • Illinois • New Hampshire • South Carolina • Alaska • Indiana • New Jersey • South Dakota • Arizona • Iowa • New Mexico • Tennessee • Arkansas • Kansas • New York • Texas • California • Kentucky • North Carolina • Utah • Colorado • Maine • North Dakota • Vermont • Connecticut • Michigan • Ohio • Virginia • Delaware • Minnesota • Oklahoma • Washington, DC • Florida • Mississippi • Oregon • Washington State • Georgia • Montana • Pennsylvania • West Virginia • Hawaii • Nebraska • Puerto Rico • Wisconsin • Idaho • Nevada • Rhode Island • Wyoming Comments: – Caltrans: Updated in accordance with FHWA Guidelines for Development and Approval of State Data Quality Management Programs, 2018.

Agency Survey Responses 91   – Florida: Modified to include statistical validation when comparing field verification site data. A statistical evaluation is performed to verify data collection of vehicle-measured rut depth, percent cracking, and fault depth. Ten 0.03-mile subsections measured by the data collection vehicle are compared with the reference values for those subsections by using a two one-sided test of equivalence for paired samples (TOST-P). – New Hampshire: Updated to include outsourcing network data collection to a vendor. – Puerto Rico: Only performed one update. 2. Method for identifying pavement distress (excluding profile-based measures, i.e., IRI, faulting, rutting)? Response Agencies No. of Agencies Fully and semiautomated Alaska, California, Delaware, Hawaii, Michigan, Minnesota, Mississippi, Nebraska, New Jersey, New York, North Carolina, Oklahoma, Pennsylvania, Puerto Rico, Utah, Vermont, and Washington State 17 Fully automated Arizona, Connecticut, Idaho, Indiana, Maine, Montana, New Hampshire, New Mexico, North Dakota, Rhode Island, Tennessee, West Virginia, and Wyoming 13 Manual and fully automated Arkansas, Colorado, Florida, Kentucky, South Carolina, South Dakota, and Virginia 7 Semiautomated Alabama, Georgia, Iowa, Oregon, Texas, and Washington, DC 6 Manual and semiautomated Kansas, Illinois, and Wisconsin 3 Manual Nevada and Ohio 2 No. responding agencies: 48. Comments: – Maine: Collect all miles with automated vehicles and do extensive quality control and acceptance testing. All right-of-way (ROW) videos are reviewed to determine those few sections where the automated detection is not working well enough, at which manual efforts (e.g., drawing cracks, deleting cracks) are conducted. For the IRI-only sections, no images are collected, but quality control and acceptance is conducted on the data. When data are not acceptable, they are re-collected or delayed for the next cycle. – Michigan: Combination of fully automated, semiautomated, and manual (on the basis of different cracking types). – Puerto Rico: Combination of fully automated, semiautomated, and manual. 3. Pavement condition data collection is conducted by: Response Agencies No. of Agencies Vendor Alabama, Alaska, Arizona, California, Colorado, Delaware, Georgia, Hawaii, Illinois, Michigan, Mississippi, New Hampshire, New Mexico, New York, North Carolina, Oklahoma, Oregon, Rhode Island, Tennessee, Utah, Virginia, Washington, DC, West Virginia, and Wyoming 24 Agency Connecticut, Idaho, Kansas, Kentucky, Maine, Minnesota, Montana, Nebraska, Nevada, North Dakota, Ohio, South Dakota, Washington State, and Wisconsin 14 Both vendor and agency Arkansas, Florida, Indiana, Iowa, New Jersey, Pennsylvania, Puerto Rico, South Carolina, Texas, and Vermont 10 No. responding agencies: 48.

92 Automated Data Collection and Quality Management for Pavement Condition Reporting 4. Pavement condition data analysis/processing is conducted by: Response Agencies No. of Agencies Agency Connecticut, Idaho, Illinois, Kansas, Kentucky, Maine, Minnesota, Montana, Nebraska, Nevada, North Dakota, Ohio, Oklahoma, South Dakota, Texas, Utah, Washington State, and Wisconsin 18 Both vendor and agency Arizona, Arkansas, Florida, Georgia, Hawaii, Indiana, Iowa, Michigan, New Hampshire, New Jersey, New Mexico, North Carolina, Pennsylvania, Puerto Rico, South Carolina, Vermont, and Washington, DC 16 Vendor Alabama, Alaska, California, Colorado, Delaware, Michigan, Mississippi, New York, Oregon, Rhode Island, Tennessee, Virginia, West Virginia, and Wyoming 14 No. responding agencies: 48. 5. On average, how many roadway lane miles does your agency survey each year? Response (lane-mile) Agencies No. of Agencies ≤10,000 Alaska, Arkansas, Connecticut, Delaware, Hawaii, Maine, Michigan, Nevada, New Hampshire, North Dakota, Ohio, Oregon, Puerto Rico, Vermont, Washington, DC, Washington State, West Virginia, Wisconsin, and Wyoming 19 >10,000 and ≤20,000 Alabama, Arizona, Colorado, Idaho, Iowa, Minnesota, Mississippi, New Jersey, New Mexico, Oklahoma, South Dakota, Tennessee, and Utah 13 >20,000 and ≤30,000 Florida, Illinois, Indiana, Kansas, Montana, Pennsylvania, and Virginia 7 >30,000 California, Georgia, Kentucky, New York, North Carolina, South Carolina, and Texas 7 No. responding agencies: 46. 6. Please provide the estimated annual costs for the pavement condition survey (i.e., start-up to integration of results into the pavement management system). Response ($/lane mile) No. of Agencies ≤30 4 >30 to ≤60 12 >60 to ≤90 11 >90 to ≤120 5 >120 to ≤150 3 >150 to ≤180 1 >180 to ≤210 1 >300 4 No. responding agencies: 41.

Agency Survey Responses 93   7. Pavement condition survey storage requirements. Response Agencies (terabytes per year, if provided) No. of Agencies Drive storage Alabama (25), Alaska (1), Arizona (12), Arkansas, California (60), Colorado (9), Connecticut, Hawaii (10), Idaho (15), Illinois (25), Indiana, Iowa (2), Kansas (20), Maine (9), Michigan, Minnesota (20 + 20 backup), Mississippi (18), Montana (22), Nevada (1.5), New York (40), North Dakota (7), Ohio (0.01), Oklahoma (16), Pennsylvania (3.5), Puerto Rico (5), South Carolina (7.3), South Dakota (20), Vermont (1), Virginia (25), Washington, DC (5), Washington State (10), West Virginia (2), Wisconsin (35), and Wyoming (2.5) 34 Cloud storage Kentucky, New Hampshire, New Mexico, North Carolina, Oregon, Tennessee, and Utah 7 Both Florida, Georgia, Nebraska, New Jersey, Rhode Island, and Texas 6 No. responding agencies: 47. Comments: – Florida: Hybrid for now. Short-term on-site, but future will be cloud-based storage. Implementation has been hard considering cloud upload speeds are slow. Plans to be cloud-based by 2022. – Georgia: Combination of cloud and in-house drive storage. – Nebraska: Hard drives and the video logs are saved to the cloud. – New Jersey: Combination of drive (4 terabytes per year) and cloud storage. – Rhode Island: Drive storage for raw pavement distress data and cloud storage for pave- ment images. – Texas: Hard drives, data center, and cloud storage. 8. Acceptance sampling rate: __% of annual lane miles collected and estimated time to conduct data acceptance: __ annual personnel hours. Agency % of Annual Lane-miles Hours to Complete Agency % of Annual Lane-miles Hours to Complete Alabama 400 New Jersey 99 (HPMS) No response 5 (non-HPMS) 400 New Mexico 99.5 160 New York 10 500 North Carolina 5 1,000 North Dakota 2–5 320 Ohio Oklahoma 20 320 Puerto Rico 5 500 Rhode Island 270 frames for F- and t-test 250 South Carolina 95 1,750 South Dakota 100 50 Tennessee 2 40 Texas 6 1,500 Utah 10 Vermont 25 100 Virginia 100 Interstate and primary, 20 secondary 2,000 3 No response No response No response Alaska 150 Arizona 80 California 0.5 office, 1–5 field 5,500 Colorado 560 Connecticut 960 Florida 500 Georgia 640 Hawaii 200 Idaho 500 Illinois 2,400 Iowa 500 Kansas 70 Kentucky 360 Maine 2,500 Michigan Minnesota 200 5 <1 0.9 100 10 10 1 20 60–70 5 3 95 100 2 100 No response (continued on next page)

94 Automated Data Collection and Quality Management for Pavement Condition Reporting Reporting Results 9. Determined performance measures or indices include (select all that apply): Agency % of Annual Lane-miles Hours to Complete Agency % of Annual Lane-miles Hours to Complete Mississippi 800 Washington, DC 100 200 Montana 320 Washington State 90 4,000 Nebraska 2,500 West Virginia 0 0 Nevada 160 Wisconsin 11 400 New Hampshire 490 Wyoming 10–20 60 Pennsylvania 100 2 100 10 25 2.5 700 No. responding agencies: 44. Response Agencies No. of Agencies International Roughness Index (IRI) Alaska, California, Colorado, Connecticut, Florida, Georgia, Hawaii, Idaho, Illinois, Indiana, Iowa, Kansas, Kentucky, Maine, Minnesota, Mississippi, Montana, Nebraska, Nevada, New Hampshire, New Jersey, New Mexico, New York, North Carolina, North Dakota, Ohio, Oklahoma, Oregon, Pennsylvania, Puerto Rico, Rhode Island, South Carolina, South Dakota, Tennessee, Texas, Utah, Vermont, Washington, DC, Washington State, Wisconsin, and Wyoming 41 Average rut depth (in.) Alaska, California, Colorado, Connecticut, Florida, Georgia, Hawaii, Idaho, Illinois, Iowa, Kansas, Maine, Minnesota, Nebraska, Nevada, New Hampshire, New Jersey, New Mexico, New York, North Carolina, North Dakota, Ohio, Oklahoma, Oregon, Pennsylvania, Puerto Rico, South Carolina, South Dakota, Tennessee, Texas, Utah, Washington, DC, Washington State, Wisconsin, and Wyoming 35 Average faulting (in.) California, Colorado, Connecticut, Florida, Georgia, Hawaii, Idaho, Illinois, Indiana, Iowa, Kansas, Minnesota, Mississippi, Nebraska, Nevada, New Jersey, New Mexico, New York, North Carolina, North Dakota, Ohio, Oklahoma, Oregon, Pennsylvania, Puerto Rico, South Carolina, South Dakota, Tennessee, Texas, Utah, Washington, DC, Washington State, Wisconsin, and Wyoming 34 Percent cracking Alabama, Alaska, California, Colorado, Connecticut, Florida, Georgia, Hawaii, Idaho, Illinois, Indiana, Iowa, Kansas, Maine, Nebraska, New Hampshire, New Jersey (HPMS), New Mexico, New York, North Carolina, North Dakota, Oklahoma, Oregon, Puerto Rico, Rhode Island, South Carolina, South Dakota, Tennessee, Texas, Utah, Vermont, Washington, DC, Washington State, Wisconsin, and Wyoming 35 Asphalt pavement cracking (% area) California, Connecticut, Florida, Georgia, Idaho, Illinois, Indiana, Iowa, Maine, Nebraska, Nevada, New Jersey, New Mexico, New York, North Carolina, North Dakota, Ohio, Oklahoma, Oregon, Puerto Rico, South Carolina, South Dakota, Texas, Utah, Vermont, Washington, DC, Washington State, Wisconsin, and Wyoming 29 JPCP cracking (% slabs) Alabama, California, Colorado, Connecticut, Florida, Georgia, Hawaii, Idaho, Illinois, Iowa, Nebraska, Nevada, New Jersey, New Mexico, New York, North Carolina, North Dakota, Ohio, Oklahoma, Oregon, Pennsylvania, Puerto Rico, South Carolina, South Dakota, Texas, Utah, Washington, DC, Wisconsin, and Wyoming 29

Agency Survey Responses 95   Comments: – Alaska: Planning on developing patching and raveling indices. – California: Multiple cracked slabs for JPCP. – Connecticut: Working to develop a new pavement performance index to be based largely on remaining service life. – Indiana: Severity of wheel path and non–wheel path cracking, and edge and shoulder distresses (more than 80 fields). – Michigan: In-house cracking-severity index; but is in the process of researching alterna- tives for future use. – Minnesota: Concrete distress by percent slabs. Asphalt distress by percent section length. – Rhode Island: To determine agency-specific combined index, indices for alligator, block, longitudinal, and transverse cracking and for rutting, patching, and IRI are determined. – Vermont: Travel weighted average condition. Response Agencies No. of Agencies Non-load-related distress index Hawaii, Idaho, Maine, New Jersey (non-HPMS), North Carolina, North Dakota, Oregon, Utah, Virginia, and Washington, DC 10 Pavement Condition Index (PCI) Arizona, Connecticut, Hawaii, Kentucky, New Jersey (HPMS), North Carolina, Washington, DC, West Virginia, and Wisconsin 9 Remaining service life or interval Kansas, Maine, Minnesota, Nebraska, and Wisconsin 5 PSR New Jersey (HPMS), Maine, Minnesota, and Nebraska 4 Modified PCI Georgia, Vermont, and Washington, DC 3 No. responding agencies: 47. Agency-specific combined index Alabama, California, Connecticut, Florida, Hawaii, Idaho, Iowa, Kansas, Maine, Minnesota, Mississippi, Nebraska, Nevada, New Jersey (non- HPMS), New Mexico, Ohio, Oregon, Pennsylvania, Rhode Island, South Carolina, South Dakota, Tennessee, Texas, Utah, Virginia, and Washington State 26 Agency-specific cracking index California, Connecticut, Florida, Georgia, Hawaii, Illinois, Iowa, Maine, Michigan, Minnesota, New Mexico, New York, North Carolina, North Dakota, Oregon, South Carolina, South Dakota, Texas, Utah, Vermont, and Wyoming 21 Rutting index Connecticut, Florida, Hawaii, Idaho, Iowa, Kansas, Maine, Nebraska, New Mexico, New York, North Carolina, Ohio, Oregon, Rhode Island, South Dakota, Utah, Vermont, and Washington, DC 18 CRCP cracking (% area) California, Georgia, Hawaii, Illinois, Mississippi, New Jersey (HPMS), New Mexico, New York, North Carolina, North Dakota, Oklahoma, Oregon, South Carolina, South Dakota, Texas, and Washington, DC 16 Faulting index Florida, Hawaii, Idaho, Iowa, Kansas, Nebraska, New Jersey (non- HPMS), New Mexico, North Carolina, South Dakota, Utah, and Washington, DC 12 Load-related distress index Hawaii, Idaho, Maine, New Jersey (non-HPMS), North Carolina, North Dakota, Oregon, Utah, Virginia, and Washington, DC 10

96 Automated Data Collection and Quality Management for Pavement Condition Reporting 10. To comply with MAP-21/FAST Act reporting, my agency (select all that apply): Response Agencies No. of Agencies Developed a DQMP Alabama, Alaska, Arizona, California, Colorado, Connecticut, Florida, Georgia, Hawaii, Idaho, Illinois, Iowa, Kansas, Kentucky, Maine, Minnesota, Mississippi, Montana, Nevada, New Hampshire, New Jersey, New Mexico, New York, North Carolina, North Dakota, Ohio, Oklahoma, Oregon, Pennsylvania, Puerto Rico, Rhode Island, South Carolina, South Dakota, Tennessee, Texas, Utah, Vermont, Washington, DC, West Virginia, Wisconsin, and Wyoming 41 Developed data quality control requirements and procedures Alaska, Arizona, California, Connecticut, Florida, Hawaii, Idaho, Iowa, Kansas, Kentucky, Mississippi, Montana, New Hampshire, New Jersey, New Mexico, New York, North Dakota, Ohio, Oregon, Puerto Rico, South Carolina, South Dakota, Tennessee, Texas, Utah, Washington, DC, Wisconsin, and Wyoming 28 Established control, verification, and/or blind site sections Alaska, Arizona, Connecticut, Florida, Hawaii, Illinois, Iowa, Kentucky, Maine, Michigan, Minnesota, Mississippi, Montana, New Hampshire, New Jersey (HPMS), New Mexico, New York, North Carolina, North Dakota, Ohio, Oregon, Puerto Rico, South Carolina, South Dakota, Tennessee, Texas, and Wisconsin 27 Established data acceptance requirements and procedures Alaska, Arizona, California, Connecticut, Florida, Hawaii, Illinois, Iowa, Kentucky, Maine, Mississippi, New Hampshire, New Jersey, New Mexico, New York, North Carolina, North Dakota, Ohio, Oregon, Puerto Rico, South Carolina, South Dakota, Tennessee, Utah, and Wisconsin 25 Established a process for data collection equipment calibration and certification Arizona, Connecticut, Florida, Hawaii, Illinois, Kentucky, Maine, Mississippi, Montana, New Hampshire, New Jersey (HPMS), New Mexico, New York, North Dakota, Ohio, Puerto Rico, South Carolina, South Dakota, Tennessee, Washington, DC, and Wisconsin 21 Added MAP- 21/FAST Act definitions Alabama, Colorado, Connecticut, Florida, Hawaii, Kansas, Maine, Michigan, Minnesota, New Jersey, New York, Ohio, Pennsylvania, South Carolina, South Dakota, Texas, Utah, Virginia, and Washington State 19 Added indices for MAP-21/FAST Act Alaska, California, Florida, Hawaii, Illinois, Iowa, Kansas, Maine, Nevada, New York, Ohio, South Carolina, South Dakota, Texas, Utah, Vermont, Washington, DC, and Wyoming 18 Implemented automated pavement condition surveys Arizona, Connecticut, Florida, Hawaii, Illinois, Kentucky, New Jersey, New Mexico, New York, Puerto Rico, South Carolina, South Dakota, Texas, Wisconsin, and Wyoming 15 Changed distress definitions Alaska, Hawaii, Idaho, New Hampshire, New Jersey (non-HPMS), New Mexico, New York, Oregon, Puerto Rico, and Vermont 10 Developed a rater certification program Connecticut, Hawaii, New Jersey (HPMS), New Mexico, Oregon, South Carolina, South Dakota, and Wisconsin 8 Changed indices calculation Hawaii, Iowa, Kansas, New Jersey (non-HPMS), New Mexico, New York, and Wyoming 7 Developed a rater training program Connecticut, New Jersey, New Mexico, North Carolina, Puerto Rico, and Wisconsin 6 No modifications were required Indiana, Michigan, and Nebraska 3 No. responding agencies: 44

Agency Survey Responses 97   Comments: – Arizona: All data collection and management is done with GIS. – Florida: Annual rater training for manual cracking for verification of HPMS and pave- ment data collection needs. – Maine: We had calibrations, processes, and procedures in place before MAP-21 but did formalize them and gather them all in one place for our DQMP. Calibration procedures had to be expanded. We keep a training log for all staff involved with data collection and processing. – Michigan: Data collection process met much of the MAP-21 requirements, but certain elements specifically related to such have been added. – New Jersey: Enhanced established equipment calibration and certification. – Rhode Island: Added blind sites to the already existing control sites as documented in the DQMP. – Wisconsin: Using automated distress routines as a starting point for distress surveys - all automated routines are manually reviewed. 11. Did your agency experience any challenges with MAP-21/FAST Act reporting requirements? Response Agencies No. of Agencies Establishing SHA performance targets Alabama, Arizona, California, Colorado, Connecticut, Iowa, Kansas, Kentucky, Maine, Michigan, New Mexico, Oklahoma, Pennsylvania, Puerto Rico, Rhode Island, South Dakota, Tennessee, Texas, Utah, Vermont, Washington, DC, and Wyoming 22 Determining baseline condition Arizona, Colorado, Iowa, Kansas, Maine, Montana, New Jersey (non- HPMS), New Mexico, New York, Puerto Rico, South Dakota, Tennessee, Texas, Utah, and Wyoming 15 Needing to adjust targets Colorado, Connecticut, Maine, Montana, Nebraska, New Mexico, Oklahoma, Puerto Rico, South Carolina, Tennessee, Texas, and Washington, DC 12 Establishing MPO performance targets Connecticut, Illinois, Iowa, Kentucky, Minnesota, New Jersey (HPMS), New Mexico, New York, Utah, Vermont, and Wyoming 11 No challenges Georgia, Idaho, Indiana, Mississippi, New Hampshire, North Carolina, North Dakota, Ohio, Virginia, Washington State, and Wisconsin 11 Insufficient data Colorado, Illinois, Michigan, Nevada, New York, Tennessee, Texas, Utah, and Washington, DC 9 Meeting targets Kansas, Maine, New Jersey (non-HPMS), New Mexico, Oklahoma, Puerto Rico, South Carolina, and Washington, DC 8 New interstate requirements Florida, Hawaii, Michigan, New Mexico, Oregon, Pennsylvania, and Puerto Rico 7 Extenuating circumstances Kentucky, Maine, and Michigan 3 No. responding agencies: 44. Comments: – Alaska: The DQMP requires more quality control and acceptance testing than we did pre- viously. It is good we are doing more now, but, given staffing levels, meeting the require- ments in that plan takes a significant amount of time. – Arizona: The single biggest improvement came from using GIS to manage the data. – Caltrans: Agency has its own performance targets. – Florida: Moving from manual distress ratings to new semi/automated distress measuring systems. – Michigan: Initially, insufficient data mostly for local NHS; only IRI had been collected prior to MAP-21 requirements.

98 Automated Data Collection and Quality Management for Pavement Condition Reporting Response Agencies No. of Agencies No reporting challenges Alabama, Alaska, Arizona, Georgia, Hawaii, Illinois, Indiana, Mississippi, Montana, Nebraska, New Hampshire, New Jersey, North Carolina, North Dakota, Oklahoma, Puerto Rico, Rhode Island, South Carolina, Texas, Utah, Virginia, Washington, DC, and Washington State 23 Determining percent cracking California, Colorado, Florida, Kansas, Maine, Michigan, Minnesota, Nevada, New Mexico, New York, Ohio, Pennsylvania, South Dakota, Tennessee, and Vermont 15 Reporting percent cracking Colorado, Kansas, Maine, Minnesota, New Mexico, and Vermont 6 Reporting faulting Connecticut, Michigan, Minnesota, and New York 4 Reporting IRI New Mexico and New York 2 Determining PSR (if applicable) Maine and Wyoming 2 Reporting rutting None. 0 No. responding agencies: 44 – Nevada: Time/effort for collecting new data specific to HPMS (crack percent). – New Jersey: Disconnect between agency performance measures and NHS performance measures. – Oregon: Federal performance measures and State performance measures are significantly different with regard to percent good and percent poor. – Rhode Island: Modeling based on FHWA method of evaluating pavement condition when modeling is done in pavement management software based on state agency method of evaluating pavement condition. 12. Did your agency have any challenges with HPMS reporting requirements? Comments: – Caltrans: Agency definition of wheel path cracking is somewhat different from HPMS definition of fatigue cracking. Cracking percent determination method is also different. Limitations of current automated pavement condition survey technology. CRCP spall and other surface distresses are difficult for current automated pavement condition survey technology to accurately identify. – Connecticut: Faulting metric might be missing this year due to challenges, but we do not have many lane miles of JPCP, so it is almost negligible to our reporting. – Idaho: We had data loss at end of collection window that resulted in substantial missing information. – Iowa: HPMS requirements are different from our internal reporting metrics. Correlation between the HPMS metrics and internal agency metrics is a little tricky. – Kentucky: Reporting requirements and additional workload are not useful for pavement management. – Maine: When HPMS changed the wheel path width to 1 meter, it caused a lot challenges, including discontinuity with 14+ years of historical cracking index data. – Minnesota: On asphalt, our standard method is percent length, not percent area, for dis- tress amounts. We needed to reprocess data for HPMS. – Nevada: Cost and time requirement. – New York: Challenge in determining our baseline data when it came to percent cracking and faulting due to qualitative versus quantitative cracking values and changes in how the faulting data values are calculated. Also, IRI data were challenging to collect in urban areas due to speed requirements to collect IRI data accurately. – Oregon: Level of detail required by MAP-21 (0.1 mi) and reporting around bridges are challenges.

Agency Survey Responses 99   Response Agencies No. of Agencies Upper Management Alabama, Alaska, Arizona, California, Colorado, Connecticut, Florida, Georgia, Hawaii, Idaho, Illinois, Kansas, Kentucky, Maine, Minnesota, Mississippi, Montana, Nebraska, Nevada, New Hampshire, New Jersey, New Mexico, New York, North Carolina, North Dakota, Ohio, Oklahoma, Oregon, Pennsylvania, South Carolina, South Dakota, Tennessee, Texas, Utah, Virginia, Washington, DC, Washington State, Wisconsin, and Wyoming 39 Asset Management Alabama, Alaska, Arizona, California, Colorado, Connecticut, Georgia, Hawaii, Idaho, Illinois, Indiana, Kentucky, Maine, Michigan, Minnesota, Montana, Nebraska, Nevada, New Hampshire, New Jersey (HPMS), New Mexico, New York, North Carolina, North Dakota, Ohio, Oklahoma, Oregon, Pennsylvania, Puerto Rico, South Carolina, South Dakota, Tennessee, Texas, Utah, Virginia, Washington, DC, Washington State, Wisconsin, and Wyoming 39 Districts Alabama, Arizona, California, Colorado, Connecticut, Florida, Georgia, Hawaii, Idaho, Illinois, Indiana, Iowa, Kansas, Kentucky, Maine, Michigan, Minnesota, Mississippi, Montana, Nebraska, New Hampshire, New Jersey (HPMS), New Mexico, New York, North Dakota, Ohio, Oklahoma, Oregon, Pennsylvania, South Carolina, South Dakota, Tennessee, Texas, Utah, Virginia, Washington State, Wisconsin, and Wyoming 38 Pavement Design Arizona, California, Colorado, Connecticut, Georgia, Hawaii, Indiana, Iowa, Kansas, Kentucky, Maine, Michigan, Minnesota, Montana, Nebraska, Nevada, New Hampshire, New Jersey, New Mexico, New York, North Carolina, North Dakota, Ohio, Oregon, Pennsylvania, Puerto Rico, South Carolina, South Dakota, Tennessee, Texas, Utah, Washington State, Wisconsin, and Wyoming 34 Maintenance Alabama, California, Colorado, Connecticut, Florida, Georgia, Hawaii, Idaho, Kentucky, Maine, Minnesota, Mississippi, Montana, Nebraska, New Hampshire, New Jersey (HPMS), New York, North Carolina, North Dakota, Ohio, Oregon, Pennsylvania, South Carolina, South Dakota, Tennessee, Texas, Utah, Virginia, Washington, DC, Washington State, Wisconsin, and Wyoming 32 Transportation Planning Arizona, Hawaii, Illinois, Kansas, Kentucky, Maine, Michigan, Minnesota, Montana, Nebraska, Nevada, New Hampshire, New Jersey (HPMS), New Mexico, New York, North Dakota, Ohio, Oklahoma, Oregon, South Carolina, South Dakota, Texas, Utah, Washington, DC, Washington State, Wisconsin, and Wyoming 27 Materials Alabama, Arizona, California, Colorado, Florida, Hawaii, Idaho, Iowa, Kansas, Maine, Minnesota, Nebraska, Nevada, New Hampshire, New York, North Carolina, North Dakota, Ohio, Oregon, South Carolina, South Dakota, Tennessee, Texas, Wisconsin, and Wyoming 25 Budget California, Florida, Hawaii, Illinois, Kentucky, Minnesota, New Jersey (non-HPMS), New York, North Carolina, Ohio, Oregon, South Carolina, South Dakota, Texas, Utah, Virginia, Washington, DC, Washington State, and Wyoming 19 Construction California, Hawaii, Kansas, Minnesota, New Hampshire, New York, North Dakota, Ohio, Pennsylvania, South Carolina, South Dakota, Texas, Washington, DC, Wisconsin, and Wyoming 15 No. responding agencies: 44. – Wisconsin: Due to the COVID-19 pandemic, pavement data collection was delayed in 2020, which added challenge to performing the required 100% NHS/HPMS surveys, but able to meet the reporting deadlines. – Wyoming: Reporting construction locations. 13. Pavement condition survey results are provided to the following offices (select all that apply):

100 Automated Data Collection and Quality Management for Pavement Condition Reporting Response Agencies No. of Agencies Yes (can provide a link or file) California, Colorado, Connecticut, Florida, Hawaii, Illinois, Kentucky, Maine, Minnesota, Mississippi, Nebraska, Nevada, New Hampshire, New Mexico, New York, Oregon, Puerto Rico, South Dakota, Tennessee, Texas, Utah, Vermont, Virginia, Wisconsin, and Wyoming 26 Yes (internal only) Alabama, Idaho, Kansas, Michigan, Montana, New Jersey (HPMS), North Carolina, Ohio, Oklahoma, Rhode Island, Washington, DC, and Washington State 11 No Alaska, Arizona, Georgia, Indiana, Iowa, North Dakota, Pennsylvania, and South Carolina 9 No. responding agencies: 45. California: https://dot.ca.gov/programs/maintenance/pavement/pavement‐ management Connecticut: https://portal.ct.gov/‐/media/DOT/documents/dpavement/ Connecticut‐DOT‐Annual‐Pavement‐Report_2019.pdf Florida: http://infonet.dot.state.fl.us/PavementManagement/sas/cntyform.htm Hawaii: https://histategis.maps.arcgis.com/apps/MapSeries/index.html?appid= 39e4d804242740a89d3fd0bc76d8d7de Illinois: https://idot.illinois.gov/Assets/uploads/files/Transportation‐System/ Reports/OP&P/Travel‐Stats/FY2019_CRS%20Summary%20Report.pdf Maine: https://www.maine.gov/mdot/about/assets/search/ Comments: – Alaska: Pavement condition information shared through ArcGIS Online with everyone, but just report our survey results specifically to a few groups. – Caltrans: HPMS. – Connecticut: Surveys are conducted by the Planning Bureau and passed to pavement management in CSV format; also provide ROW and LCMS [Laser Crack Measurement System] pavement images. – Florida: Pavement management. – Indiana: The data are available to the whole agency with tools that are created and video log provided. – Michigan: Research efforts related to pavement design and asset management; also, to certain construction warranty monitoring efforts. – Minnesota: We publish an annual report and post it on our website along with pavement condition maps so they are available to anyone. However, we make presentations to upper management, planners, and districts each year. – Mississippi: Upon request to anyone within the agency, universities for research, and pri- vate consultants. – New York: Design. – North Carolina: Division offices. – Puerto Rico: Highway Systems Office. – Rhode Island: Performance measures. – South Dakota: State legislature. – Tennessee: We publish annual pavement condition report online. – Vermont: Pavement conditions (map and data) are freely available to everyone through a public-facing GIS web application. 14. Does your agency develop a pavement condition status report?

Agency Survey Responses 101   Automated Pavement Condition Surveys 15. Number of years agency has been conducting automated pavement condition surveys: Response (years) Agencies No. of Agencies <5 Arizona, Florida, New Hampshire, New Jersey (HPMS), Puerto Rico, South Carolina, South Dakota, Texas, Wisconsin, and Wyoming 10 5–10 Alaska, California, Georgia, Hawaii, Kansas, Kentucky, New Jersey (non-HPMS), North Carolina, Ohio, and Tennessee 10 >10 Alabama, Colorado, Connecticut, Idaho, Illinois, Indiana, Iowa, Maine, Michigan, Minnesota, Mississippi, Montana, Nebraska, New Mexico, New York, North Dakota, Oklahoma, Oregon, Pennsylvania, Utah, Vermont, Virginia, Washington, DC, and Washington State 24 No. responding agencies: 44. Minnesota: http://www.dot.state.mn.us/materials/pvmtmgmt.html Mississippi: https://path.mdot.ms.gov/pavement_condition Nevada: https://www.dot.nv.gov/home/showpublisheddocument?id=17163 New Hampshire: https://www.nh.gov/dot/org/commissioner/amps/documents/2019‐ paving‐annualreport.pdf New Jersey: https://www.nj.gov/transportation/about/publicat/lmreports/ New Mexico: https://dot.state.nm.us/content/dam/nmdot/CPI/NMDOT_TAMP.pdf New York: https://www.dot.ny.gov/divisions/engineering/technical‐services/ pavement‐management Oregon: https://www.oregon.gov/odot/Construction/Documents/Pavement/ 2020_condition_report_maps.pdf Puerto Rico: https://cmapr.sharepoint.com/:b:/s/18286/ESAqy3C026tHrQbR0x_ CR8YB7XSLmrwyP4hS2h5X6oTttg?e=GFptrx South Dakota: https://apps.sd.gov/hr53needsbook/ Tennessee: https://www.tn.gov/tdot/maintenance/pavement‐office/pavement‐ management.html Texas: https://progress.pathwayservices.com/texas.html Utah: https://sites.google.com/utah.gov/pavementmanagement/ statewide‐condition?authuser=0 Vermont: https://vtransparency.vermont.gov/pages/pavement Virginia: https://www.virginiadot.org/info/state_of_the_pavement.asp Wisconsin: https://wisconsindot.gov/Pages/about‐wisdot/performance/mapss/ goalpreservation.aspx 16. Number of data collection vehicles used for the annual pavement condition survey. Agency No. Vehicles Agency No. Vehicles Alabama 1 Montana 2 Alaska 2 Nebraska 2 Arizona 1–3 New Hampshire 1 Colorado 1–2 vendors New Jersey (non- HPMS) 2 (continued on next page)

102 Automated Data Collection and Quality Management for Pavement Condition Reporting Agency No. Vehicles Agency No. Vehicles Connecticut 2 New York 4 Florida 1 (plans to use 4 in 2022) North Dakota 1 Hawaii 2 Ohio 2 Idaho 1 Pennsylvania 3 or 4 Illinois 3–4 South Carolina 3 agency, 1 to 5 vendor Indiana 2–4 South Dakota 1 Iowa 2–4 Tennessee 3–5 Kansas 2 Texas 10 Kentucky 3 Vermont 1 vendor, 1 agency Maine 2 Virginia 6–8 Michigan 1–2 vendors Washington State 1 Minnesota 1 for state/HPMS data, 2 for county Wisconsin 2 Mississippi 4 Wyoming 2 vendors No. responding agencies: 34. 17. Implementation of automated pavement surveys required my agency to (select all that apply): Response Agencies No. of Agencies Assess data quality issues Alabama, Colorado, Florida, Hawaii, Idaho, Illinois, Iowa, Kansas, Kentucky, Michigan, Minnesota, Mississippi, Montana, New Hampshire, New Jersey (non-HPMS), New Mexico, New York, Pennsylvania, Puerto Rico, South Dakota, Texas, Utah, Wisconsin, and Wyoming 24 Modify distress definitions Alabama, Florida, Georgia, Hawaii, Idaho, Iowa, Kansas, Kentucky, Maine, Michigan, Minnesota, New Mexico, New York, Oregon, Pennsylvania, South Dakota, Texas, Vermont, and Washington, DC 19 Modify index/rating calculations Alabama, Florida, Georgia, Hawaii, Kansas, Kentucky, Maine, Mississippi, Montana, New Jersey (non-HPMS), New Mexico, New York, North Dakota, Oregon, Puerto Rico, Texas, Utah, Vermont, and Washington, DC 19 Add index/rating calculations Alabama, Alaska, Florida, Georgia, Hawaii, Illinois, Kentucky, Maine, Michigan, Mississippi, New Mexico, New York, Pennsylvania, South Dakota, and Texas 15 Add distress definitions Alaska, Florida, Hawaii, Idaho, Maine, Michigan, Mississippi, New Mexico, New York, Pennsylvania, Puerto Rico, South Dakota, Tennessee, and Wyoming 14 Develop correlation with manual surveys Alabama, Colorado, Florida, Georgia, Kentucky, Maine, New Jersey (non-HPMS), New Mexico, New York, South Carolina, Utah, Wisconsin, and Wyoming 13 Modify decision trees Alaska, Florida, Georgia, Idaho, Kentucky, Maine, Mississippi, New Mexico, North Dakota, Pennsylvania, Wisconsin, and Wyoming 12 Add decision trees (branches) Alaska, Florida, Idaho, Kentucky, Mississippi, New Mexico, Puerto Rico, and Wisconsin 8 No modifications needed Connecticut, Indiana, Nebraska, North Carolina, Ohio, Oklahoma, Virginia, and Washington State 8 Modify historical manual surveys Kentucky, Maine, Mississippi, and New York 4 No. responding agencies: 41. Comments: – Alaska: Developing distress indices since we added patching/raveling data to our collec- tion and have implemented an overall level of service calculation. – Arizona: Retire all historical distress data as they became irrelevant/incomplete for comparison.

Agency Survey Responses 103   Response Agencies No. of Agencies Coordination of data collection activities Florida, Hawaii, Iowa, Mississippi, Montana, New Mexico, New York, Pennsylvania, Puerto Rico, South Carolina, South Dakota, Texas, Utah, and Washington, DC 14 Validation/ verification of data quality Alabama, Alaska, Arizona, California, Florida, Georgia, Hawaii, Idaho, Illinois, Iowa, Kentucky, Maine, Michigan, Minnesota, Mississippi, Nebraska, New Hampshire, New Jersey (non-HPMS), New Mexico, New York, Oregon, Pennsylvania, Puerto Rico, South Carolina, South Dakota, Tennessee, Texas, Utah, Vermont, and Wisconsin 30 Consistency of results Arizona, Florida, Hawaii, Iowa, Kansas, Kentucky, Michigan, Minnesota, Montana, New Jersey (non-HPMS), New Mexico, New York, North Carolina, Oregon, Puerto Rico, South Carolina, South Dakota, Tennessee, Texas, Washington, DC, Wisconsin, and Wyoming 22 Significant difference compared to manual surveys Alabama, Florida, Georgia, Idaho, Iowa, Kansas, Kentucky, Maine, Minnesota, Mississippi, New Jersey (non-HPMS), New Mexico, New York, Pennsylvania, South Carolina, Texas, Utah, Wisconsin, and Wyoming 19 Integrating results into the pavement management system California, Florida, Georgia, Hawaii, Idaho, Illinois, Kansas, Kentucky, Maine, Mississippi, Nebraska, New Mexico, New York, Pennsylvania, South Carolina, South Dakota, Washington, DC, and Wyoming 18 Training staff on data analysis California, Florida, Hawaii, Illinois, Iowa, Maine, Mississippi, Nebraska, New Hampshire, New Jersey (non-HPMS), New Mexico, New York, Pennsylvania, South Dakota, Texas, Utah, and Wisconsin 17 Training staff on data collection Florida, Hawaii, Idaho, Kentucky, Maine, Michigan, Montana, Nebraska, New Mexico, New York, South Dakota, and Texas 12 No challenges Connecticut, Indiana, New Jersey (HPMS), North Dakota, Oklahoma, Virginia, and Washington State 7 Reduced data quality Michigan and North Carolina 2 No. responding agencies: 42. – California: Automated Pavement Condition Survey Manual for data collection. – Connecticut: Been using automated surveys for over 25 years. – Indiana: Been doing this for a long time and adjust our methods annually for the better- ment of data. – Kentucky: Develop workflow for processing and reporting raw data from collection vehicles. – Maine: Change was made around 2002. Decision trees reviewed each year and every few years compare automated cracking results (mainly the calculation of cracking index values) with engineering judgment. With MAP-21, looking more at the raw cracking data (length and width). – Michigan: Currently researching alternative crack-surveying quantification methods, the impetus for which has been the introduction of more fully automated (including 3D) survey technology within the collection vendor community. Traditional crack/severity- level method is old, in need of updating and is cumbersome to execute relative to the technology readily available from the vendor pool. – Wisconsin: Using automated distress routines as a starting point for pavement condition surveys—all automated routines are manually reviewed. 18. Challenges while transitioning to automated condition surveys (select all that apply):

104 Automated Data Collection and Quality Management for Pavement Condition Reporting Response Agencies No. of Agencies Correct crack detection Alabama, Alaska, California, Colorado, Florida, Georgia, Indiana, Iowa, Kansas, Kentucky, Maine, Michigan, Minnesota, Mississippi, Montana, New Hampshire, New Mexico, New York, North Dakota, Oklahoma, Puerto Rico, South Carolina, Tennessee, Texas, Utah, Wisconsin, and Wyoming 27 Adjusting algorithms to meet requirements Arizona, California, Florida, Idaho, Illinois, Iowa, Kansas, Maine, Michigan, Montana, New York, North Dakota, Oklahoma, Puerto Rico, South Carolina, Texas, and Wisconsin 17 Cracking data collection and reporting Alabama, California, Colorado, Florida, Illinois, Indiana, Iowa, Kansas, Michigan, Montana, New Mexico, New York, South Dakota, Tennessee, Texas, Utah, and Wisconsin 17 Missing data California, Colorado, Florida, Georgia, Idaho, Iowa, Kentucky, Maine, Nebraska, New Hampshire, New Jersey (non-HPMS), New Mexico, New York, Utah, and Vermont 15 Correct condition data by surface type Arizona, California, Colorado, Hawaii, Illinois, Iowa, Kentucky, Mississippi, New Mexico, New York, Oregon, South Carolina, and Wyoming 13 Poor pavement image quality California, Colorado, Florida, Indiana, Iowa, New Jersey (non-HPMS), New Mexico, Ohio, Oklahoma, Virginia, and Washington, DC 11 Incorrect location California, Colorado, Florida, Minnesota, New Jersey (non-HPMS), New York, Pennsylvania, Texas, Virginia, and Wyoming 10 Meeting control and verification site requirements Arizona, Connecticut, Florida, Iowa, Maine, Mississippi, New Jersey (non-HPMS), New Mexico, New York, and Wisconsin 10 Faulting data collection and reporting California, Connecticut, Florida, Idaho, Indiana, Iowa, Minnesota, and South Carolina 8 Data out of range Colorado, Idaho, Kentucky, New Hampshire, New Mexico, Tennessee, and Utah 7 IRI data collection and reporting Alaska, Indiana, New Mexico, New York, and South Carolina 5 Meeting random sample requirements Iowa, New Mexico, New York, and South Carolina 4 Rutting data collection and reporting New Mexico, Tennessee, Texas, and Wisconsin 4 No challenges North Carolina and Washington State 2 Correct format New Jersey (HPMS) 1 No. responding agencies: 44. Comments: – Arizona: Historical manually collected data did not correlate to the automated data. – Connecticut: Been conducting automated condition surveys for over 25 years. – Florida: Currently evaluating consistency of automated data results from year to year. – Michigan: See comments under Question 17. – Mississippi: Storage problems. – Ohio: No indication from business process owner to move away from manual pavement condition rating process. – Virginia: Automated distress surveys have been conducted for more than 15 years. – Wisconsin: Using automated distress routines as a starting point for distress surveys—all automated routines are manually reviewed. 19. Challenges with data and image quality control and acceptance (select all that apply):

Agency Survey Responses 105   Comments: – Alaska: Per the DQMP, “typical” IRI values and left/right IRI values do not differ by more than 50. There are many locations, for example, due to unstable permafrost/poor curb/ gutter, and this leads to time being spent investigating the reasons they are outliers. – California: For variable slab length, accurate determination of faulting values can be challenging. – Connecticut: Measuring faulting is relatively new and was added in 2015. Will establish validation testing against “ground truth” measurements this year. – Florida: Faulting data are dependent on joint identification. – Ohio: Very few issues. Poor downward pavement image quality one year and not detected during routine weekly processing but only identified after collection was over. This only happened one year and learned how to detect and avoid almost immediately. – Oklahoma: Incorrect image location. – Oregon: Semiautomated rated distresses such as patching and raveling is the biggest challenge. – Virginia: There has been occasional incorrect location because of linear referencing system issues, and occasional poor pavement image quality. These are not widespread or major issues. 20. Advantages of automated pavement condition surveys (select all that apply): Response Agencies No. of Agencies Ability to collect sensor and distress with a single device Arizona, California, Colorado, Florida, Georgia, Hawaii, Idaho, Indiana, Iowa, Kansas, Maine, Mississippi, Montana, Nebraska, New Hampshire, New Jersey (HPMS), New Mexico, New York, North Carolina, North Dakota, Oklahoma, Pennsylvania, Puerto Rico, South Carolina, South Dakota, Texas, Utah, Virginia, Washington State, and Wyoming 30 Ability to easily track, review, and reproduce historical data and images Alaska, Arizona, California, Connecticut, Florida, Georgia, Hawaii, Idaho, Iowa, Kansas, Maine, Mississippi, Montana, Nebraska, New Hampshire, New Jersey (HPMS), New Mexico, New York, North Dakota, Ohio, Oregon, Pennsylvania, Puerto Rico, Tennessee, Texas, Utah, Washington, DC, and Washington State 28 100% roadway coverage Alaska, Arizona, California, Colorado, Florida, Georgia, Hawaii, Idaho, Iowa, Kansas, Maine, Minnesota, Mississippi, Montana, New Hampshire, New Mexico, New York, North Dakota, Ohio, Oklahoma, Pennsylvania, South Dakota, Tennessee, Utah, Vermont, Virginia, and Wyoming 27 Improved accuracy of distress identification Alaska, Arizona, California, Colorado, Connecticut, Florida, Georgia, Hawaii, Idaho, Illinois, Mississippi, Montana, New Jersey, New Mexico, New York, Oklahoma, Pennsylvania, South Carolina, South Dakota, Tennessee, Utah, Vermont, Virginia, Washington, DC, Washington State, and Wyoming 26 Ability to collect data compatible with HPMS and MAP-21 Alabama, Alaska, Arizona, California, Colorado, Connecticut, Florida, Georgia, Hawaii, Idaho, Illinois, Indiana, Iowa, Kansas, Kentucky, Maine, Minnesota, Mississippi, Nebraska, New Hampshire, New Jersey, New Mexico, New York, North Carolina, North Dakota, Ohio, Pennsylvania, Puerto Rico, South Dakota, Texas, Utah, Vermont, Virginia, Washington, DC, and Wyoming 35 Increased rater safety Alabama, Arizona, California, Colorado, Connecticut, Florida, Georgia, Hawaii, Idaho, Illinois, Iowa, Kansas, Kentucky, Maine, Mississippi, Montana, Nebraska, New Hampshire, New Mexico, New York, North Dakota, Ohio, Oregon, Pennsylvania, South Carolina, South Dakota, Tennessee, Texas, Utah, Vermont, and Virginia 31 (continued on next page)

106 Automated Data Collection and Quality Management for Pavement Condition Reporting Response Agencies No. of Agencies Direct correlation with historical data Alabama, Arizona, California, Florida, Hawaii, Idaho, Illinois, Iowa, Kansas, Kentucky, Mississippi, New Jersey (non-HPMS), New York, South Carolina, Texas, Vermont, Washington, DC, and Wyoming 18 Increased collection costs Alaska, Colorado, Florida, Georgia, Hawaii, Indiana, Iowa, Kentucky, New Hampshire, New Mexico, New York, Oregon, Puerto Rico, South Carolina, Utah, Washington, DC, and Wyoming 17 Year-to-year variability of results Alabama, California, Colorado, Florida, Indiana, Iowa, Kansas, Mississippi, New Mexico, New York, Pennsylvania, Puerto Rico, South Carolina, and Texas 14 Increased processing costs Alaska, Florida, Hawaii, Iowa, Kentucky, Minnesota, New Jersey (non- HPMS), New Mexico, New York, North Carolina, Puerto Rico, Washington State, and Wyoming 13 Additional costs and personnel associated with equipment or vendor procurement California, Florida, Hawaii, Kentucky, Montana, New Jersey (HPMS), New Mexico, Oregon, Puerto Rico, Texas, Vermont, and Virginia 12 Well-defined data collection methods Alaska, Arizona, California, Colorado, Connecticut, Georgia, Hawaii, Idaho, Illinois, Maine, Mississippi, Montana, New Hampshire, New Jersey (non-HPMS), New Mexico, New York, North Carolina, North Dakota, Ohio, Oklahoma, Pennsylvania, South Carolina, Utah, Vermont, Virginia, Washington, DC, and Washington State 27 Enhanced timeliness of data collection Arizona, California, Colorado, Connecticut, Georgia, Hawaii, Idaho, Iowa, Mississippi, Nebraska, New Hampshire, New Jersey (HPMS), New Mexico, New York, North Dakota, Ohio, Oklahoma, Pennsylvania, South Carolina, South Dakota, Tennessee, Utah, Virginia, Washington, DC, and Wyoming 25 Enhanced timeliness of data processing Arizona, California, Colorado, Connecticut, Georgia, Hawaii, Idaho, Michigan, Mississippi, Nebraska, New Hampshire, New Jersey (HPMS), New Mexico, New York, North Carolina, North Dakota, Ohio, Oklahoma, Pennsylvania, Puerto Rico, South Carolina, South Dakota, Utah, Virginia, and Wyoming 25 Access to ancillary data collection Alaska, Arizona, California, Colorado, Florida, Georgia, Hawaii, Idaho, Iowa, Kansas, Kentucky, Michigan, Mississippi, New Mexico, New York, Ohio, Pennsylvania, Utah, and Virginia 19 No. responding agencies: 43. Response Agencies No. of Agencies Comments: – Arizona: Ease of use within GIS. – Michigan: Looking forward to more full-automation of crack type/severity surveying from 3D that can possibly provide more consistency throughout an annual data set and across years. – Ohio: Also provides frequent update of ROW imagery, macrotexture data, network local- ized roughness assessments, and many other transportation asset management benefits. – Tennessee: Improved data quality control and acceptance. – Wisconsin: Automated routines provide accurate results only for limited distress types— automated routines provide efficiency only for identifying certain distresses. 21. Disadvantages of automated pavement condition surveys (select all that apply):

Agency Survey Responses 107   Comments: – Idaho: Staff training and retention. – Mississippi: Changing vendors and software. – New Jersey: Additional data storage requirements. – New York: Additional costs associated with the storage of the data. Some of this is a result of agency policy and decisions not to store in the cloud or use off-site storage. With more advanced cameras and improved equipment, it directly affects the storage capacity requirements. – Wisconsin: Automated surveys provide accurate results only for limited distress types/ severities. Automated routines used as a starting point for certain distresses and auto- mated results are subject to manual quality control and review. Response Agencies No. of Agencies Additional costs for modifying performance models California, Colorado, Illinois, Kansas, Kentucky, Maine, Michigan, Montana, New Mexico, Oklahoma, South Carolina, and Texas 12 Dependence on a single vendor Florida, Illinois, Iowa, Kansas, Maine, Michigan, Mississippi, New York, Puerto Rico, Tennessee, and Utah 11 Technology evolution, forcing early equipment replacement Florida, Maine, Michigan, Nebraska, New Hampshire, New Mexico, North Dakota, Oregon, South Carolina, and Tennessee 10 Difficulties with operational changes Arizona, California, Florida, Idaho, Michigan, New York, Ohio, South Carolina, and Texas 9 Additional costs and personnel for calibration, validation, and verification California, Florida, Hawaii, Illinois, Iowa, Michigan, Montana, New Mexico, and Oregon 9 Additional costs for modifying pavement management software Colorado, Kansas, Maine, Michigan, New Jersey (HPMS), New York, Texas, and Wyoming 8 Additional costs for modifying distress manual California, Illinois, Michigan, New Mexico, New York, Oklahoma, and South Carolina 7 Additional costs for modifying distress ratings California, Iowa, Maine, Michigan, and New York 5 Breakdowns and long repair delays Montana, Nebraska, New Mexico, and Washington, DC 4 Additional costs for modifying decision trees Kentucky and Michigan 2 No. responding agencies: 41.

108 Automated Data Collection and Quality Management for Pavement Condition Reporting In Closing 22. Do you have any other suggestions or comments related to automated pavement condition survey technology, data quality management, or reporting requirements? Response Agencies No. of Agencies Yes Arizona, California, Florida, Indiana, Kansas, Michigan, Minnesota, New Jersey (non-HPMS), Ohio, South Dakota, Utah, and Wisconsin 12 No Alabama, Alaska, Colorado, Connecticut, Georgia, Hawaii, Idaho, Illinois, Iowa, Kentucky, Maine, Mississippi, Montana, Nebraska, Nevada, New Hampshire, New Jersey (HPMS), New Mexico, New York, North Carolina, North Dakota, Oklahoma, Oregon, Pennsylvania, Puerto Rico, South Carolina, Tennessee, Texas, Vermont, Virginia, Washington, DC, Washington State, and Wyoming 33 No. responding agencies: 45. Comments: – Arizona: We saw measurable improvements with GIS managing and disseminating infor- mation (data to reports) became web maps and dashboards. – California: In general, automated pavement condition surveys speed up data collection, improve worker’s safety, and improve data quality. Currently, technological limitations and accurate cracking determination remains a major challenge. Efforts underway with TPF-299/399 to standardize 2D/3D pavement image data format will help improve data analysis and quality control and acceptance efforts. This should be a high priority to speed up nationwide adoption of this data standard. – Florida: Promoting a universal data format can be used nationally and will not require vendor licensing. – Indiana: There is a lot to know and learn and be aware of and simply asking the right questions is a great start. – Kansas: I find we often use the same words and requirements when discussing with other state pavement management personnel but implement them in different ways. Even though we have standards, these data are not standardized in my opinion. – Minnesota: The biggest issue we have had with the automated system is determining what is a crack versus what is a joint on concrete pavement. This not only affects the distress index but also the average faulting. – New Jersey: Moved to automated surveys for consistency and repeatability. – Ohio: We are looking to purchase a vehicle-based LiDAR system to add to our vehicles as now it seems costs are reasonable, data storage and analysis are now less of an issue, and ROI looks to be quite high. – South Dakota: Need to continue to develop standards to keep pace with current and future technology. – Utah: Automated data were much more consistent year to year than manual data. – Wisconsin: 100 percent NHS/HPMS distress surveys are a challenge based on the level of manual survey and quality control required for acceptable level of accuracy in reporting.

Agency Survey Responses 109   23. The synthesis will also include case examples highlighting agency practices related to pave- ment condition data collection technology, data quality management, and reporting require- ments. Agencies will be provided the opportunity to review the case example write-up for accuracy. Would your agency be interested in participating in a case example? 24. If available, please include any additional documentation (internal or available via the web) related to implementation of automated pavement condition surveys and reporting of results (e.g., agency, FHWA, HPMS). Response Agencies No. of Agencies Yes Arizona, Connecticut, Florida, Idaho, Illinois, Kansas, Maine, Mississippi, New Hampshire, New Jersey, New Mexico, New York, North Dakota, Ohio, Oregon, Tennessee, Texas, Utah, Vermont, Virginia, and Wyoming 21 No Alabama, Alaska, California, Colorado, Georgia, Hawaii, Indiana, Iowa, Kentucky, Michigan, Minnesota, Montana, Nebraska, Nevada, North Carolina, Oklahoma, Pennsylvania, Puerto Rico, South Carolina, South Dakota, Washington, DC, Washington State, and Wisconsin 23 No. responding agencies: 44. Response Agencies No. of Agencies Yes (can provide a link) Arizona, Hawaii, Illinois, and Utah 4 Yes (can provide a file) Colorado, Connecticut, and Tennessee 3 No Alabama, Alaska, California, Florida, Georgia, Idaho, Indiana, Iowa, Kansas, Kentucky, Maine, Michigan, Minnesota, Mississippi, Montana, Nebraska, Nevada, New Hampshire, New Jersey, New Mexico, New York, North Carolina, North Dakota, Ohio, Oklahoma, Oregon, Pennsylvania, Puerto Rico, South Carolina, South Dakota, Texas, Vermont, Virginia, Washington, DC, Washington State, Wisconsin, and Wyoming 37 No. responding agencies: 44.

Abbreviations and acronyms used without denitions in TRB publications: A4A Airlines for America AAAE American Association of Airport Executives AASHO American Association of State Highway Officials AASHTO American Association of State Highway and Transportation Officials ACI–NA Airports Council International–North America ACRP Airport Cooperative Research Program ADA Americans with Disabilities Act APTA American Public Transportation Association ASCE American Society of Civil Engineers ASME American Society of Mechanical Engineers ASTM American Society for Testing and Materials ATA American Trucking Associations CTAA Community Transportation Association of America CTBSSP Commercial Truck and Bus Safety Synthesis Program DHS Department of Homeland Security DOE Department of Energy EPA Environmental Protection Agency FAA Federal Aviation Administration FAST Fixing America’s Surface Transportation Act (2015) FHWA Federal Highway Administration FMCSA Federal Motor Carrier Safety Administration FRA Federal Railroad Administration FTA Federal Transit Administration GHSA Governors Highway Safety Association HMCRP Hazardous Materials Cooperative Research Program IEEE Institute of Electrical and Electronics Engineers ISTEA Intermodal Surface Transportation Efficiency Act of 1991 ITE Institute of Transportation Engineers MAP-21 Moving Ahead for Progress in the 21st Century Act (2012) NASA National Aeronautics and Space Administration NASAO National Association of State Aviation Officials NCFRP National Cooperative Freight Research Program NCHRP National Cooperative Highway Research Program NHTSA National Highway Traffic Safety Administration NTSB National Transportation Safety Board PHMSA Pipeline and Hazardous Materials Safety Administration RITA Research and Innovative Technology Administration SAE Society of Automotive Engineers SAFETEA-LU Safe, Accountable, Flexible, Efficient Transportation Equity Act: A Legacy for Users (2005) TCRP Transit Cooperative Research Program TDC Transit Development Corporation TEA-21 Transportation Equity Act for the 21st Century (1998) TRB Transportation Research Board TSA Transportation Security Administration U.S. DOT United States Department of Transportation