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Suggested Citation:"Bibliography." National Academies of Sciences, Engineering, and Medicine. 2004. Automated Pavement Distress Collection Techniques. Washington, DC: The National Academies Press. doi: 10.17226/23348.
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Page 62
Page 63
Suggested Citation:"Bibliography." National Academies of Sciences, Engineering, and Medicine. 2004. Automated Pavement Distress Collection Techniques. Washington, DC: The National Academies Press. doi: 10.17226/23348.
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Page 63

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62 ASTM D6433 Standard Practice for Roads and Parking Lots Pavement Condition Index Surveys, American Society for Testing and Materials, West Conshohocken, Pa., 1999. Cable, J.K., Clarifying the Quadrennial Needs Study Process, HR-363, Iowa Highway Research Board, Ames, Dec. 1993. Cheng, H.D., X. Jiang, J. Li, and C. Glazier, “Automated Real-Time Pavement Distress Analysis,” Transportation Research Record 1655, Transportation Research Board, National Research Council, Washington, D.C., 1999, pp. 55–64. Cline, G.D., M.Y. Shahin, and J.A., Burkholder, “Auto- mated Data Collection for Pavement Condition Index Sur- vey,” Presented at the 82nd Annual Meeting of the Trans- portation Research Board, Washington, D.C., Jan. 12–16, 2003. Condition of the Pavement—1998, Interstate and Primary Highways, Maintenance Division, Virginia Department of Transportation, Richmond, Va., 1998. 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Pujol, Jr., “An Adaptive Segmentation Technique for Automated Crack Detection,” Presented at the 78th Annual Meeting of the Transportation Research Board, Washington, D.C., Jan. 1999. Hedfi, A. and P. Stephanos, “Pavement Performance Model- ing: An Applied Approach at the State of Maryland,” Pre- sented at the Fifth International Conference on Managing Pavements, Seattle, Wash., Aug. 11–14, 2001. Howe, R. and G. Clemena, Feasibility of an Automated Pave- ment Distress Survey System Incorporating Digital Image Processing, VTRC Report No. 98-R1, Virginia Trans- portation Research Council, Charlottesville, Mar. 1998. Hummer, J.E., C.R. Scheffler, A.J. Khattak, and H.A. Karimi, “Choosing an Inventory Data Collection System,” Trans- portation Research Record 1690, Transportation Research Board, National Research Council, Washington, D.C., 1999, pp. 126–134. Jitprasithsiri, S., H. Lee, R.G. Sorcic, and R. Johnston, “Development of Digital Image-Processing Algorithm to Compute a Unified Crack Index for Salt Lake City,” Transportation Research Record 1526, Transportation Research Board, National Research Council, Washington, D.C., 1996, pp. 142–148. Ksaibati, K., R. McNamara, and J. Armaghani, “A Compari- son of Roughness Measurements from Laser and Ultrasonic Road Profilers,” Presented at the 78th Annual Meeting of the Transportation Research Board, Washington, D.C., Jan. 1999. Kulkarni, R., F. Finn, E. Alviti, J. Chuang, and J. Rubinstein, Development of a Pavement Management System, Report to the Kansas Department of Transportation, Woodward– Clyde Consultants, Topeka, 1983. Landers, S., Resurfacing Program Roadway Pavement Man- agement System Pavement Condition Data Primer, British Columbia Ministry of Transportation and Highways, Victoria, B.C., Canada, Feb. 2000. Lee, H., Standardization of Distress Measurements for the Network-Level Pavement Management System, ASTM STP, No. 1121, American Society for Testing and Materi- als, West Conshohocken, Pa., 1992, pp. 424–436. Lee, H. and K. Kang, “Development of Automated Pavement Distress Measurement System Following New AASHTO Provisional Protocol,” Presented at the 14th Annual RPUG (Road Properties Users Group) Meeting, Roanoke, Va., Oct. 2002. Lee, H. and H. Oshima, “New Automated Crack Imaging Procedure Using Spatial Autocorrelation Function,” Jour- nal of Transportation Engineering, Vol. 120, No. 2, Mar. 1994, pp. 206–228. Li, Y. and J. Delton, “Approaches to Evaluation of Profiler Accuracy,” Transportation Research Record 1860, Trans- portation Research Board, National Research Council, Washington, D.C., pp. 129–136. Luhr, D.R., “A Proposed Methodology to Quantify and Ver- ify Automated Crack Survey Measurements,” Presented at the 78th Annual Meeting of the Transportation Research Board, Washington, D.C., Jan. 1999. Maze, T., O.G. Smadi, and J. Resler, Feasibility of Using Automated Distress Data in the County Need Study, TR-418, Iowa Department of Transportation, Ames, Dec. 1998. McGhee, K.H., Development and Implementation of Pave- ment Condition Indices for the Virginia Department of Transportation, Phase I, Flexible Pavements, Maintenance Division, Virginia Department of Transportation, Rich- mond, Va., Sep. 2002. MHM Associates [Online]. Available: http://www. networksplus.net/rpug/vendors.html [2001, June 12]. BIBLIOGRAPHY

63 MINITAB Inc., Pennsylvania State University, University Park, Pa., 1972. NCHRP Research Results Digest 181: Video Image Pro- cessing for Evaluating Pavement Surface Distress, Trans- portation Research Board, Washington, D.C., 1991, 4 pp. Ott, R.L. and M. Longnecker, An Introduction to Statistical Methods and Data Analysis, 5th ed., Duxbury Press, Belmont, Calif., 2001, pp. 396–400; pp. 410–413. Pathway Services, Inc., Tulsa, Okla. [Online]. Available: http://www.networksplus.net/rpug/vendors.html [2001, June 12]. Pavement Condition Index (PCI) Guidance, Ser ESC63/103 of Feb. 16, 2000. Pavement Management Catalog, 2002 Edition, Federal High- way Administration, Washington, D.C., May 2002. “Pavement Management Information System (PMIS) Sum- mary Sheet,” Iowa Department of Transportation, Ames, Oct. 28, 1999. Pavement Management System Field Operations Manual, Bureau of Materials and Research, Kansas Department of Transportation, Topeka, Jan. 2002. Peterson, D.E., NCHRP Synthesis of Highway Practice 135: Pavement Management Practices, Transportation Research Board, National Research Council, Washington, D.C., 1987, 139 pp. Phoenix Scientific, Inc., San Marcos, Calif. [Online]. Avail- able: http://phnx-sci.com. Rada, G.R., C.L. Wu, G.E. Elkins, R.K. Bhandari, and W.Y. Bellinger, “Update of Long-Term Pavement Performance Manual Distress Data Variability, Bias and Precision,” Transportation Research Record 1643, Transportation Research Board, National Research Council, Washington, D.C., 1998, pp. 71–79. Shahin, M.Y., Pavement Management for Airports, Roads, and Parking Lots, Kluwer Academic Publishers, Norwell, Mass., 1998. Shahin, M. and S. Kohn, Pavement Maintenance Management for Roads and Parking Lots, Report CERL-TR-M-294, USACERL, U.S. Army Corps of Engineers, Vicksburg, Miss., Oct. 1981. Simpson, A.L., “Characterization of Transverse Profile,” Transportation Research Record 1655, Transportation Research Board, National Research Council, Washington, D.C., 1999, pp. 185–191. Standard Practice for Use of the Terms Precision and Bias in ASTM Test Methods, Annual Book of ASTM Standards, Vol. 14.02, Designation E 177-90a, American Society for Testing and Materials, West Conshohocken, Pa., 1998. Stephanos, P., P. Dorsey, and A. Hedfi, “Implementation of a New Pavement Management Planning Process at the Maryland State Highway Administration,” Presented at the 5th International Conference on Managing Pavements, Seattle, Wash., 2001. Transportation Management Technologies, LLC [Online]. Available: http://www.networksplus.net/rpug/vendors.html [2001, June 12]. URS Greiner Woodward Clyde, Pavement Performance Prediction Models, Interim Report prepared for Kansas Department of Transportation, Topeka, Jan. 21, 2000. Wang, K.C.P., “Designs and Implementations of Automated Systems for Pavement Distress Survey,” Journal of Infra- structure Systems, Vol. 6, No. 1, Mar. 2000, pp. 24–32. “WiseCrack,” Roadware Inc., South St. Paul, Minn. [Online]. Available: http://www.roadware.com/WiseCrax.htm [Oct. 2001].

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TRB’s National Cooperative Highway Research Program (NCHRP) Synthesis 334: Automated Pavement Distress Collection Techniques examines 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 scope of 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, 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.

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