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This document is a synthesis of the information collected in 2003 on highway community prac- tice and research and development efforts in the automated collection and processing of pave- ment condition data typically used in network-level pavement management. The scope of the effort covered all phases of automated pavement condition data collection and processing for pavement surface distress, pavement ride quality, rut-depth measurements, and joint-faulting measurements. Included in the scope were the technologies employed, contracting issues, qual- ity assurance (QA) issues, 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 in automated data collection and processing. Although emphasis was on network-level pavement management, project-level or research-level work, such as the Long-Term Pavement Performance Program, was included where it was helpful in contributing to the knowledge base on the subject matter. To expedite the gathering of available information, a questionnaire was sent to all U.S. state transportation agencies, the FHWA, Canadian provinces, and the World Road Association (Per- manent Association of World Road Congresses). A total of 56 responses were received from 43 state highway agencies, 2 FHWA offices, 10 Canadian provinces or territories, and Trans- port Canada. Additional material was acquired through a literature search of North American and European resources, with more than 150 references retrieved through that process. It was discovered that essentially all North American highway agencies are collecting and using pavement condition data through some automated means. Almost all of those data are collected in a single pass by an integrated machine capable of capturing forward, lateral, and downward images as well as both longitudinal and transverse profiles. Virtually 100% of those responding to the questionnaire are using automated means to collect International Roughness Index (IRI) data on at least a portion of their systems. Most agencies collecting IRI data (52) also collect other data measured by electronic sensing devices (laser, acoustic, or infrared). Of these other sensor data, rut-depth measurements are by far the most popular (50 agencies) with joint-faulting measurements employed by some 30 agencies. Pavement surface images are collected through automated means by 30 agencies, whereas automated processing of pave- ment surface distresses from those images is employed by only 14 of those agencies. The oth- ers apply manual data reduction techniques to obtain surface distress data from the images. Thirty-three agencies use vendors to collect at least some of the automated data. In many of those cases, the vendor collects sensor data on longitudinal and transverse profiles while the agency collects pavement surface distress data through manual surveys. The most popular means of procuring contracted services is through a request for proposal, as used by 18 agen- cies. Seven agencies use a request for qualification approach, whereas eight use advertised con- tracts and a low-bidder approach. Several agencies use more than one approach to contracting. A typical contract is for 2 years, although some agencies use a 1-year period and one uses a 4-year period. Several provide for up to 5-year negotiated extensions of shorter-term original contracts. Six agencies have warranty provisions in their contracts, whereas only one requires a performance bond. A total of 22 agencies have QA provisions in their contracts and 12 have price adjustment clauses. Typical price adjustment clauses relate to delivery dates and accrue SUMMARY AUTOMATED PAVEMENT DISTRESS COLLECTION TECHNIQUES
in the form of penalties for late delivery. No agency mentioned a bonus for early delivery. Agencies reported a low estimated cost of $0.60 per km ($1 per mi) for agency-collected IRI data up to $106 per km ($170 per mi) for vendor collection and processing of images and sen- sor data in an urban environment. Roughly $30 per km ($50 per mi) is considered average for that same work. In special circumstances, such as urban areas or extremely remote locations, costs may be expected to vary widely from those cited here. Some agencies have done extensive work to develop very thorough QA requirements or practices. Some of the Canadian provinces have been exceptionally productive in this area and have established procedures that could well provide the foundation for national or inter- national approaches. However, in general, there is a need for additional development work in pavement data QA, for there is a scarcity of information on inherent variabilities of the processes involved. Further additional work appears needed on developing quality manage- ment programs for pavement data. One of the major benefits that agencies cited from automated collection of pavement con- dition data is in the area of safety. Many agencies noted the danger of having people on the roadway to collect data manually, whereas it can be collected safely and at traffic speeds with modern automated equipment. Others cited the efficiency of operation for automated proce- dures. Still others noted the benefit of having a permanent record of pavement condition; greater objectivity is obtained through automated means, and improved data consistency comes through automation. Not all agencies responded positively to automated procedures, as some believe that data quality is compromised. On the other hand, several mentioned an improved data quality through automation. It is suspected that the difference lies in the use of reliable and realistic QA procedures. Three case studies are included in the synthesis. The first is of the Maryland State Highway Administration, which does all automated pavement data collection and processing in-house. The second case is that of procedures followed by the Louisiana Department of Transportation and Development, where all data are collected and processed through contracts. The third case is of data collection and processing activities of the Mississippi Department of Transportation. Itsâ data collection and processing are done by a vendor, but with specific protocols provided by the agency. The issue of state of the art versus state of the practice for automated pavement condition data collection and processing is cause for concern. Although there seems to be little gap in roughness measurement, there is a significant one for both cracking and rut-depth measure- ment. For joint-faulting measurements, the automation issues are not well enough developed to determine either the state of the art or state of the practice. For cracking measurements, some agencies seem hesitant to invest in the new technologies until they have been more thor- oughly proven. For both rutting and joint-faulting measurements there is little consensus on what is really required to furnish quality data, therefore, additional protocol work seems needed. Research needs identified in this synthesis project include ⢠A study of automated data collection standards, ⢠A study of automated surface distress processing standards, ⢠Development of quality management programs for automated pavement data collec- tion and processing, ⢠Development of a âtoolboxâ for automated pavement data collection and processing, and ⢠Development of metadata standards for pavement condition data. 2
