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25 A survey was developed to determine agency practices for automated pavement condition data collection. The survey was provided to all U.S. and Puerto Rican highway agencies and all Canadian provincial transportation agencies. The questionnaire focused on the following: â¢ Agency automated pavement condition data collection methods; â¢ Types of condition and distress collected; â¢ Data quality management plans; â¢ Data integration, storage, and retention requirements; â¢ Contracting processes; â¢ Costs associated with automated data collection; and â¢ Successes and challenges of automated pavement condition data collection. The intended recipients of the survey questionnaire were the pavement management engineers (or comparable position) of the U.S. and Puerto Rican highway agencies and Canadian provincial and territorial governments. The detailed survey questionnaire is provided in Appendix A, and agency responses are summarized in Appendix B. As of March 2018, 57 agencies (90%) responded to the survey, including 45 U.S. highway agencies and 11 Canadian provincial and territorial governments. The following sections provide a summary of the survey results. Pavement Data Collection Methods Agencies were asked a number of questions related to data collection methods, pavement con- dition types collected, and the frequency of data collection. Figure 12 illustrates agency methods for pavement condition data collection. Since the majority of agencies collect profile data using high-speed profilers to assess IRI, rutting, and faulting, the data collection methods shown in Figure 12 relate only to collection and evaluation of surface distress (e.g., cracking, patching, raveling). In total, 45 agencies indicated using automated data collection methods (fully auto- mated, 16 agencies; a combination of fully and semiautomated, 21 agencies), six agencies indicated using both manual and automated methods, and six agencies indicated using manual pavement condition surveys. In total, 51 (nearly 90%) of the responding agencies indicated using auto- mated pavement condition surveys. Figure 13 summarizes the number of agencies using automated methods for condition and distress assessment. In general, regardless of pavement type, about half of the agencies conduct only fully automated analysis, and about half of the agencies conduct a combination of both semi- and fully automated analysis. Agencies conducting only manual pavement condition surveys were asked to identify reasons for not adopting automated condition surveys. Of the six agencies conducting manual surveys, C H A P T E R 3 State of the Practice
26 Automated Pavement Condition Surveys Figure 12. Agency data collection methods (total responses = 57). 26 18 8 24 23 11 0 5 10 15 20 25 30 Asphalt (50 responses) JPCP (41 responses) CRCP (19 responses) N O . O F AG EN CI ES PAVEMENT TYPE Fully automated Semi- and Fully Automated Figure 13. Summary of automated distress collection method.
State of the Practice 27 five agencies indicated that equipment or vendor service costs and additional efforts are needed to assess the impact on pavement condition results as primary reasons for not moving to auto- mated condition surveys. Other responses included agency hesitancy to transition to automated methods (three agencies), issues with changing technologies (three agencies), concerns with the accuracy of automated data collection (two agencies), a need to develop decision trees and performance models based on automated data (one agency), and high-cost condition assess- ment not warranted on lower classification roadways (one agency). Agencies that use automated data collection surveys were asked to indicate whether the agency or a vendor conducts the data collection and data analysis. Figure 14 illustrates agencies that collect and conduct the data analysis, agencies that contract for collecting and conducting the data analysis, and agencies that conduct a combination of both. Of the agencies that conduct automated condition surveys, 16 indicated that the agency collects and analyzes the data, 16 agencies contract with a vendor for data collection and analysis, and 16 agencies indicated a combination of agency- and vendor-conducted data Figure 14. Agency versus vendor data collection and analysis (total responses = 54).
28 Automated Pavement Condition Surveys collection and data analysis (total of 48 responses). The following summarizes the agency- vendor combinations: â¢ Both the agency and the vendor collect and analyze the data (six agencies). â¢ A vendor collects the data, and the agency analyzes the data (five agencies). â¢ A vendor collects the data, and the agency and the vendor analyze the data (three agencies). â¢ The agency and a vendor collect the data, and the agency analyzes the data (two agencies). Finally, agencies were asked to identify the length of time automated condition surveys have been conducted by their agency (Figure 15). Although Figure 15 does not capture the progres- sion of implementation over time, it does illustrate that 22 agencies have used automated tech- nology for more than a decade, 16 agencies for 5 to 10 years, and nine agencies for 1 to 4 years; four agencies did not respond to this question. Pavement and Asset Data Types Collected Agencies use various automated methods for assessing pavement condition and distress. As noted previously, the majority of agencies have used automated methods to assess IRI, faulting, and rutting for decades. Agencies were asked to identify the analysis method (semiautomated, Figure 15. Length of time conducting automated pavement condition surveys (total responses = 47).
State of the Practice 29 automated, or manual) used for a variety of pavement distress types, the frequency of data collection, and the secondary assets assessed during the automated pavement condition survey. It should be noted that distress type definitions were not provided as part of the survey and are assumed to be based on individual agency standards. Pavement Condition Assessment Asphalt Pavement For asphalt pavements, agencies reported 41 condition and distress types evaluated using fully automated analysis, 26 using semiautomated analysis, and 26 using manual surveys. Table 11 summarizes asphalt pavement condition and distress types (with at least two responses) assessed using manual and fully and semiautomated analysis. As expected, fully automated analysis is used for determining IRI, rutting, and cross slope (55, 53, and 30 agencies, respectively). Fully automated analysis is used by most agencies (i.e., 75 percent or more when compared to semiautomated analysis) to assess longitudinal cracking (33 agencies); alligator cracking (29 agencies); texture (19 agencies); and bumps, sags, and depressions (eight agencies). Fully and semiautomated analyses are conducted on a number of distress types (i.e., neither analysis method is used predominately to evaluate distress type). More than twice as many agencies reported using fully automated analysis for assessing alligator, edge, transverse, and reflection cracking, lane/shoulder drop off, and shoving. However, the split between semi- and fully automated analyses for the remaining distress types is not as distinct. Agencies reported Condition Fully Automated Semiautomated Manual Total No. Responses Rutting 53 0 3 56 IRI 55 0 0 55 Transverse cracking 32 13 10 55 Alligator cracking 29 15 10 54 Longitudinal cracking 33 9 9 51 Potholes 14 13 9 36 Patching 10 15 11 36 Raveling 14 11 10 35 Block cracking 16 11 7 34 Edge cracking 19 10 4 33 Cross slope 30 0 1 31 Bleeding 10 9 9 28 Reflection cracking 16 7 4 27 Texture 19 1 2 22 Lane/shoulder drop off 9 3 5 17 Depression 8 2 3 13 Shoving 5 2 6 13 Bumps and sags 8 1 2 11 Corrugation 3 2 6 11 Weathering 0 3 7 10 Polished aggregate 1 3 4 8 Faulting (composite pavements) 4 0 0 4 Delamination 2 0 0 2 Wheel path cracking 1 1 0 2 Table 11. Condition and distress typesâasphalt pavements (total responses = 57).
30 Automated Pavement Condition Surveys nearly equal use of semi- and fully automated analyses for block cracking, potholes, raveling, bleeding, and corrugation. Jointed Plain Concrete Pavement Forty-four agencies indicated the use of JPCP on their highway network. In total, agencies reported assessing 23 fully automated condition and distress types and 22 semiautomated condition and distress types. Table 12 summarizes JPCP condition and distress types (with at least two responses) assessed using manual and fully and semiautomated analysis. As expected, fully automated analysis is used for determining IRI (44 agencies), faulting (37 agencies), cross slope (20 agencies), and texture (12 agencies). At least twice as many agencies report using semiautomated analysis for assessing spalling, corner cracking, durability, blowups, shattered areas (or slabs), polished aggregate, scaling, and broken slabs (or percent cracked slabs). The remaining distress types have less than half the agencies using either fully or semiautomated analyses for longitudinal and transverse cracking, patching, lane/shoulder drop off, joint seal damage, map cracking, and pumping. There is a wide range of agency criteria for identifying patching and raveling. Patching is generally measured by area; however, three of 12 agencies identify the number of patches (Table 13). Five of 12 agencies have a size criteria, most being a minimum value, with Oregon, Pennsylvania, and Texas having maximum values for patching. Lastly, eight of the 12 agencies also record patch severity. For raveling, eight of the 11 agencies report using area, with the others using linear feet, and 10 of the 11 agencies use severity levels (Table 14). The Saskatchewan Ministry of Highways and Infrastructure utilizes a fully automated method for collecting, identifying, and reporting raveling on dense-graded mixes. 3D lasers capture the road profile, which is sectioned into Condition Fully Automated Semiautomated Manual Total No. of Responses IRI 44 0 0 44 Faulting 37 3 2 42 Cross slope 20 1 1 22 Longitudinal cracking 20 13 7 40 Transverse cracking 16 17 6 39 Texture 12 1 2 15 Patching 8 14 7 29 Corner cracking 7 16 7 30 Spalling 7 15 8 30 Joint seal damage 6 7 7 20 Lane/shoulder drop off 6 4 5 15 Durability 4 9 6 19 Map cracking 4 7 2 13 Blowups 2 6 3 11 Pumping 2 3 6 11 Broken slabs/percent cracked slabs 1 3 0 4 Polished aggregate 1 3 3 7 Scaling 1 3 7 11 Shattered area/slabs 1 2 0 3 Shrinkage cracks 0 0 2 2 Table 12. Condition and distress typesâJPCP (total responses = 44).
State of the Practice 31 9.8 Ã 9.8-in. (250 Ã 250-mm) squares. For each square, the space between the road surface and a flat layer placed over the image is calculated as the air-void volume (Figure 16). The algorithm then builds a smooth 3D surface by filling in areas of worn asphalt and lost aggregates. The space between the smooth 3D surface and the existing road surface is calculated as the road porosity index. The raveling index is the difference between the air-void volume and the road porosity index. The extent of raveling is reported as the total percent area affected, and the severity is reported as the average raveling index. Continuously Reinforced Concrete Pavement Nineteen agencies indicated using CRCP on their highway network. In total, agencies reported assessing 18 condition and distress types using fully automated methods and 12 condition and distress types using semiautomated methods. Table 15 summarizes CRCP condition and distress types (with at least two responses) assessed using manual and fully and semiautomated analysis. As anticipated, fully automated analysis is used for determining IRI (19 agencies), cross slope (nine agencies), and texture (six agencies). In addition, the majority of agencies (five of six agencies) report using fully automated analysis for assessing lane/shoulder drop off. Agency Extent and Severity Alberta Indicator of presence (0 or 1), based on sudden texture reduction/change Arkansas Count, by severity level British Columbia Area, > 6 in. (152 mm) diameter, severity by depth of patch Delaware Area, by severity level Hawaii Area, by severity level Iowa > 1 ft2 (0.1 m2) to full lane width x 120 ft (37 m) in length Oregon > 1 ft2 (0.1 m2), excludes utility patches, < 0.5 mi (0.8 km), severity based on presence of distress Pennsylvania Total number and area, > 1 ft2 (0.1 m2), < 400 ft (122 m) in length, severity based on presence of distress Texas Area, < 500 ft (152 m) in length Saskatchewan Count and area of full-depth patching Washington State Area, severity based on type of patch New York Area, severity based on extent of patch area Table 13. Summary of agency practice for identifying patching (total responses = 12). Agency Extent Alberta Area, all reports as medium severity Arkansas Area, by severity level British Columbia Area, moderate or high severity Delaware Area, by severity level Iowa Area, by severity level New Mexico Linear feet, by severity level Oregon Linear feet, by severity level Texas Area, severity based on area Pennsylvania Linear feet, medium or high severity Saskatchewan Area, severity based on raveling index (fully automated method) Wyoming Area (fully automated method) Table 14. Summary of agency practice for identifying raveling (total responses = 11).
32 Automated Pavement Condition Surveys As with asphalt pavement and JPCP, there are a number of CRCP condition and distress types that are not distinct to the data analysis method. Semiautomated analysis is used for identifying polished aggregate (two agencies) and blowups (four agencies). In addition, semi- automated analysis is used more often than fully automated analysis for identifying map cracking (three versus one agency, respectively), patching (seven versus three agencies, respectively), and punchouts (eight versus five agencies, respectively). Finally, agencies report nearly the same number of occurrence of fully and semiautomated assessment of durability, spalling, transverse cracking, and longitudinal cracking. Data Collection Frequency Agencies were also asked to indicate the frequency of pavement condition data collection. Figure 17 summarizes data collection frequency for agencies by roadway category. For the United States and Puerto Rico, the majority of the agencies conduct pavement condition surveys annually for the Interstate and NHS roadways (44 and 40, respectively). Approximately one-third 9.8 x 9.8 in (250 x 250 mm) a. Example of raveling. b. 3D smoothed surface. c. Loss of stone from 3D image. Figure 16. Saskatchewan method for measuring raveling (Saskatchewan Ministry of Highways and Infrastructure 2017). CRCP Fully Automated Semiautomated Manual Survey Total No. of Responses IRI 19 0 0 19 Cross slope 9 0 0 9 Longitudinal cracking 8 7 2 17 Transverse cracking 6 6 1 13 Texture 6 0 1 7 Punchout 5 8 1 14 Lane/shoulder drop off 5 1 2 8 Spalling 3 4 1 8 Patching 3 7 2 12 Durability 3 3 2 8 Scaling 1 1 1 3 Map cracking 1 3 0 4 Polished aggregate 0 2 1 3 Blowups 0 4 2 6 Table 15. Condition and distress typesâCRCP (total responses = 19).
State of the Practice 33 of the agencies conduct pavement condition surveys on non-NHS roadways either annually or every 2 years. For Canadian agencies, the majority (six agencies) reported conducting pavement condition surveys annually on primary and secondary provincial highways, while five agencies reported conducting the surveys on a 2-year cycle. Secondary Assets Although pavement condition data have been collected for decades, there is increased agency interest to collect condition data for nonpavement assets. These secondary assets can be anything from guardrail and barriers to fencing to sound walls. Several agencies require the data collection vendor to collect condition data for these secondary assets; other agencies specify these as optional assets for data collection. Table 16 summarizes the agencies that collect secondary asset condition and which secondary assets are being collected. Contractual Requirements As previously described, 32 of the 57 (56%) responding agencies indicated using vendors for collecting or analyzing, or both, automated pavement condition data. Of the responding agencies, the predominant number of agencies (16 agencies) require the vendor to collect and analyze the data; six agencies conduct both vendor and agency data collection and analysis; five agencies require the vendor to collect the data, and then the agency analyzes the data; three agencies require the vendor to collect the data, and then the agency and vendor share in data analysis; and two agencies conduct both vendor and agency data collection, and the agency analyzes the data (Figure 18). 1 1 1 5 6 9 10 13 22 23 40 44 0 5 10 15 20 25 30 35 40 45 50 Interstate every 2 years Non-NHS every 4 years Off Highway System NHS every 3 or more years Canadian provincial highways every 2 years Canadian provincial highways annually NHS every 2 years Off Highway System NHS every 2 years Off Highway System NHS annually Non-NHS every 2 years Non-NHS annually NHS annually Interstate annually NO. OF AGENCIES Figure 17. Frequency of pavement condition survey (total responses = 56).
34 Automated Pavement Condition Surveys Agency Secondary Assets Alberta Shoulder condition. British Columbia Bridges (> 164 ft [50 m]), steel mesh bridge decks, railway crossings, construction zone, storm water drainage, utilities, and rumble strips in lane. California Bridge, shoulder pavement type, metal beam guard rail, median barrier type, attenuator type, highway lighting, traffic signals, flashing beacons, traffic operations elements, vehicle detection system, traffic census count stations, ramp metering station, fence type, sound walls, curbs and dikes, and sidewalks. Illinois Ability to perform sign, signal, guardrail, or other highway asset surveys/inventory, and to measure offsets and dimensions of highway asset inventory. Iowa Pavement texture and roadway geometry. New York Signs, guardrail, sidewalk, ramps compliant with the Americans with Disabilities Act, catch basins, drainage ditches, noise walls, rumble strips, signals, bridge deck, paved shoulders, retaining walls, medians, and on-route parking. North Carolina Traffic signals, signs, guardrail, guardrail terminals, pavement markings, unpaved shoulders, and presence of rumble strips. Vermont Raveling, HPMS items (median width and type, shoulder width and type, curve classification, grade classification, and cracking). Virginia Bridge begin and end location. Lane-shoulder drop-off, highway asset inventory data collection (e.g., signals, guardrail, pavement markings, signs), ramps and loops (image, sensor data, and distress), HPMS data items, and ground penetrating radar. Wyoming Volume of material for rut fill, and areas of raveling and weathering using laser sensors. Table 16. Secondary asset collection (total responses = 10). 16 6 5 3 2 0 2 4 6 8 10 12 14 16 18 Vendor collects & analyzes data Both agency and vendor collect & analyze data Vendor collects & agency analyzes data Vendor collects & agency and vendor analyze data Agency and vendor collect data & agency analyzes data N O . O F AG EN CI ES Figure 18. Vendor or agency data collection and analysis (total responses = 32). Proposer Selection Process Five agencies provided requests for proposals as part of the follow-up questions. The follow- ing provides a summary of the proposer selection process for each agency. British Columbia Ministry of Transportation and Infrastructure The British Columbia Ministry of Transportation and Infrastructureâs (MoTIâs) request for proposal includes a project scope to collect pavement condition data on 11,184 mi (18,000 km)
State of the Practice 35 over a 2-year period (with an option for a 2-year extension) (British Columbia Ministry of Transportation and Infrastructure 2015) (see Table 17). The contract price is based on per lane-mile (lane-kilometer) for data collection on highways and side roads, with a separate rate for mobilization to complete additional work as requested. Proposer selection is based on score, and price is determined by the following: S Min M P = Ã where, S = score, Min = lowest priced proposal, M = total points available for price, and P = price on this proposal. California DOT (Caltrans) The Caltrans contract for pavement condition survey includes data collection for approxi- mately 52,000 lane-miles (ln-mi) (83,686 lane-kilometers [ln-km]) of the Caltrans highway network, 10,000 ln-mi (16,093 ln-km) of ramps and connectors, 6,000 ln-mi (9,656 ln-km) of non-Caltrans highway network, and 15,000 centerline mi (24,140 km) of asset extraction on the Caltrans highway network (Caltrans 2017). Proposers must have conducted statewide pavement condition work for at least three distinct states in the United States or in any other country (Caltrans 2017). Proposers are required to attend a mandatory proposer instruction conference and obtain locations for field collection and analysis. Field collection and analysis is to be conducted on eight pavement sections within 50 miles of the Sacramento area, with the results included in the proposal. Caltrans also provides proposers access to agency measurements on two additional pavement segments for reference and calibration purposes. Proposals are ranked according to the consensus of the Caltrans Evaluation Committee and include the technical proposal (50 points); field collection and analysis evaluation (50 points); the analysis tool (20 points); organization, clarity, and the viewing tool (20 points); and cost proposal (60 points), for a total possible score of 200 points. The technical proposal criteria are shown in Table 18. Criteria Description Weight Company knowledge and experience Past experience with this type of work and references 10 Project team Team member experience, project manager clearly identified 5 Methodology Describe approach to meet or exceed requirements, include description of survey equipment, data collection and processing, QC, schedule, and deliverables 40 Resolution of key issues Identify key issues and challenges and how they will be managed (e.g., inclement weather, failing blind site testing) 5 Survey price (Year 1 and 2) 20 Survey price (optional Years 3 and 4) 20 Grand Total 100 Table 17. Proposal selection criteria and weight values (British Columbia Ministry of Transportation and Infrastructure 2015).
36 Automated Pavement Condition Surveys Criteria for field collection and analysis sections are summarized in Table 19. Proposer- determined pavement distress values are compared to Caltrans-measured values and assessed based on pass/fail criteria. A pavement section is considered acceptable if all distresses meet the pass criteria. Proposers are awarded points based on the number of passing sections (Table 20). Criteria for the analysis tool evaluation include whether or not it is user-friendly and capable of determining image-based cracking (20 points). Evaluation criteria include the following (Caltrans 2017): â¢ Images must be clear to identify and quantify cracking on each element. â¢ Images must be easy to manipulate and move. Criteria Weight Max. Consensus Ranking Total Possible Points Equipment used for data collection 1.0 4.0 4.0 QC approach and experience 1.5 4.0 6.0 Key personnel qualifications and experience 0.5 4.0 2.0 Data hosting and access approach and experience 0.5 4.0 2.0 Schedule, contingency plans 0.5 4.0 2.0 Experience with other state DOT networks 0.5 4.0 2.0 Linear reference system (LRS) approach and experience 1.5 4.0 6.0 Methodology and experience measuring image-based cracking 1.5 4.0 6.0 Data delivery logistics and punctuality 1.5 4.0 6.0 Customer satisfaction and advantages for choosing firm 0.5 4.0 2.0 Pavement condition reporting and approach 1.5 4.0 6.0 Asset reporting and approach 1.5 4.0 6.0 Total 50.0 Table 18. Caltrans evaluation criteria (adapted from Caltrans 2017). Criteria Measure Pass/Fail IRI (in./mi) Average value over 0.1-mi (0.16-km) Proposer- reported values will be acceptable. Rut depth Percent wheel path length > 0.1 in. (2.5 mm) MPD Percent wheel path length > 0.02 in. (0.6 mm) Faulting Percent length > 1 joint with > 0.15 in. (3.8 mm) Asphalt pavement distress1 Alligator A cracking2 Percent wheel path length Â± 10% Alligator B cracking3 Percent wheel path length Â± 10% Concrete pavement distress Longitudinal cracking Percent slabs Â± 10% Transverse cracking Percent slabs Â± 10% Corner cracking Percent slabs Â± 10% 1st stage cracking4 Percent slabs Â± 10% 3rd stage cracking5 Percent slabs Â± 10% 1 Summarized over an element length of 26.4 ft (8 m). 2 Single or double unconnected crack. 3 Interconnected or interlaced cracks (generally less than 1 ft [305 mm]) on each side. 4 Nonintersecting cracks (excludes corner cracking) dividing slab into 2 or 3 large pieces. 5 At least two cracks (longitudinal and transverse) dividing the slab into at least 3 pieces. Table 19. Caltrans field collection and analysis evaluation criteria (adapted from Caltrans 2017).
State of the Practice 37 â¢ Images must be continuously stitched and each image geo-referenced or location stamped. â¢ Cracks must be measurable by count or length and automatically recorded. â¢ Tools must be available to aggregate and report the element pavement condition data based on 0.1-mi (0.16-km) segments. The organization, clarity, and viewing tool criteria include organization and clarity of demonstration and viewing tool capabilities and user friendliness. Consensus ranking is based on a 0- to 4-point scale, with 0 indicating that the tool does not meet requirements and four indicating that the tool exceeds requirements. The lowest-cost proposal will be awarded the maximum number of points (60 points), and other proposerâs price score is based on the following: Other Proposerâs Cost Points = Lowest Proposerâs Cost Other Proposerâs Cost Maximum Cost PointsÃ Illinois DOT The pavement condition rating survey for the Illinois DOT includes data collection on approximately 16,000 centerline miles (25,750 km) of NHS, National Highway Freight Network, and HPMS sections (Illinois DOT 2017). The contract term is 4 years, with two 2-year renewal options. The proposer selection includes a point ranking system and price evaluation (Table 21). The point ranking system is conducted before the price evaluation, and only proposers meeting the minimum required points are considered for price opening or for award. No. of Sections Meeting Pass Criteria 0 1 2 3 4 5 6 7 8 Total Points 0 5 10 15 20 25 30 40 50 Table 20. Caltrans pavement section evaluation pass points (adapted from Caltrans 2017). Criteria Description Minimum Required Points Total Possible Points Experience â¢ Capability to use the collected data to document pavement condition â¢ Capability to provide point cloud or similar data set for asset inventory â¢ Number of years of experience â¢ Knowledge, experience, and ability of staff to perform tasks â¢ Past performance 140 280 Capability â¢ Ability to provide all services â¢ Ability to collect data and images â¢ Financial capacity and equipment to perform the work â¢ QA/QC plan 140 280 Resources â¢ Office location â¢ Organizational chart â¢ Financial capacity to carry out scope of services (submit 3-year financial data) 60 120 References â¢ Established private firms or government agencies (four required) â¢ Indications of past contracts with other state agencies 10 20 Grand total 350 700 Table 21. Illinois DOT selection criteria (adapted from Illinois DOT 2017).
38 Automated Pavement Condition Surveys Pricing is based on a per lane-mile (kilometer) cost for data collection, highway asset col- lection, and point cloud hardware; software; and warranty for 16 workstations. The total price points are determined by the following: Total Price Points = Maximum Price Points Lowest Price Offerorâs Price The values from the point ranking system and price evaluation are summed for a maximum of 1,000 points. New Mexico DOT The New Mexico DOT contract includes annual pavement condition data collection on 6,800 mi (10,944 km) of NHS routes and biannually on 11,800 mi (18,990 km) of non-NHS routes. The contract covers a 4-year data collection cycle with no time extensions. The proposer selection is based on a point evaluation system and cost. The criteria for the point evaluation system are shown in Table 22. The proposer cost estimate is based on cost per lane-mile (kilometer), total cost for data collection and interpretation, and final reporting. Once all proposals have been reviewed for compliance with mandatory specifications (includes items shown in Table 22 and completed campaign contribution disclosure form, New Mexico employeeâs health coverage form, pay equity reporting requirements, and resident business and resident veteranâs preference) and scored by the evaluation committee, the proposal that is most advantageous to the DOT is recommended for award (New Mexico DOT 2017). Virginia DOT The Virginia DOT requests annual pavement condition data collection on 2,500 mi (4,023 km) of interstate, 10,600 mi (17,059 km) of primary highways, and 11,200 mi (18,024 km) of selected asphalt-surfaced secondary roads, and in any given year, 45,000 mi (72,420 km) of the secondary network. Potential proposers are required to attend a mandatory preproposal conference to present questions and clarify solicitation requirements. The contract includes a 1-year term, with the potential of four successive 1-year renewal periods. The proposer evaluation criteria are summarized in Table 23. The proposer selection is based on two or more offerors deemed qualified and best suited to perform the work based on the submitted proposal and Virginia DOT evaluation. Price is Criteria Description Total Possible Points Company experience â¢ Summary of company history â¢ Document extent of knowledge, experience, and expertise â¢ Description of proposed tools and techniques 25 Personnel experience and qualifications â¢ Description of education, knowledge, and relevant experience â¢ Certifications or other professional credentials 25 Project plan â¢ Narrative description of the scope of work â¢ Approach to accomplish the scope of work â¢ Project schedule and timeline of deliverables â¢ Description of QC measures 25 Past performance â¢ Information that demonstrates the ability to provide sufficient professional competence, meet time schedules, accommodate cost considerations, and project administration requirements 25 Table 22. New Mexico DOT selection criteria (adapted from New Mexico DOT 2017).
State of the Practice 39 a consideration in the evaluation process, but not necessarily the sole determining factor in proposer selection (Virginia DOT 2015). Negotiations are conducted with each offeror, and the agency selects and awards the contract to the offeror, in the agencyâs opinion, who âhas made the best proposalâ (Virginia DOT 2015). If the agency determines that only one offeror is fully qualified or more highly qualified than the other submitters, then the agency can negotiate and award the contract to that offeror. Low-Speed Provisions For profile data, there is a low-speed limit for inertial profilers. At very slow speeds, the vertical acceleration is too small for meaningful results (Sayers and Karamihas 1998). Sayers and Karamihas (1998) suggest a minimum data collection speed no lower than 16 mph (25 km/h). Several agencies include provisions requiring a minimum speed of the DCV. Typically, provisions specify when IRI data should be removed and not reported to the agency. The following points provide a summary of agency provisions for collecting IRI at low speeds. â¢ The Saskatchewan Ministry of Highways and Infrastructure (MHI) requires data collection to be conducted at speeds above 16 mph (25 km/h) (Saskatchewan Ministry of Highways and Infrastructure 2017). â¢ Illinois DOT requires data collection to include an automatic low-speed cutoff and requires the proposer, at the approval of the agency, to provide a minimum speed (as slow as possible and still within the operating parameters) of data collection (Illinois DOT nd). â¢ North Carolina and Virginia DOT require data collection to be conducted above 15 mph (24 km/h). If unavoidable, the proposer must provide a method for removing slow-speed sections from the average IRI calculations; however, no more than 10% of the readings within a homogeneous section shall be rejected for low speeds or any other reason. If extended sections of roadway cannot be tested above the specified speed limit, then the proposer should attempt to change the time of testing to allow data collection at the proper speed, and if this is not possible, the data should be flagged as invalid (North Carolina DOT 2015, Virginia DOT 2015). Multiple Data Collection Vehicles The entire automated condition survey process involves several steps, from data collection and processing through quality checks and the final data submittal. Depending on the size of Criteria Description Total Possible Points Technical approach â¢ Equipment, plans, operating procedures, etc. â¢ Schedule â¢ Approach for performing work Not specified Experience in similar works â¢ Specific experience and qualifications of firm and subcontractors Not specified Key personnel qualifications â¢ Key personnel experience and qualifications â¢ Staff rÃ©sumÃ©s Not specified Capability of large- scale data collection â¢ Written narrative demonstrating firmâs capability of large-scale data collection and ability to meet schedules Not specified Small business subcontracting plan â¢ Summary of planned use of Virginia Department of Small Business and Supplier Diversity 20 Price â¢ Pricing schedule Not specified Total 100 Table 23. Virginia DOT selection criteria (adapted from Virginia DOT 2015).
40 Automated Pavement Condition Surveys the network, this process can be very time-intensive. On larger networks, the use of several DCVs can and has been performed to decrease the time spent collecting data. However, this requires specifications to ensure that all DCVs are operating in the same manner and that data collected by one vehicle can be directly compared with data from the other vehicles. North Carolina and Virginia DOTs require multiple vehicle variability in IRI and rut depth measurements to be 5% or less (North Carolina DOT 2015, Virginia DOT 2015). Texas DOT requires that all DCVs and equipment employ identical hardware and software and that all pro- file equipment has been certified through the Texas Transportation Institute (Texas DOT 2017). Liquidated Damages Two agencies include liquidated damage clauses into the collection contracts. Oftentimes, liquidated damages are enforced to ensure proposer performance or to deter late submittal of deliverables. For example, the Illinois DOT contract language includes a provision for timely data and image submittal. A late-delivery reduction in per-mile cost may be assessed at 5% for 1 to 15 days late, 7% for 16 to 30 days late, and 10% for more than 31 days late. Texas DOT requires proposers to complete data collection within 180 days and assess, at the discretion of the agency, up to 10% of the cost if delivery is more than 20 working days late. In addition, Texas DOT includes language for proposer performance. Examples of unsatis- factory performance include the following (and may result in a negative proposer performance report or termination of the purchase order, or both): â¢ One instance of the proposer failing to notify the Texas DOT contract manager about equipment problems, calibration issues, equipment failures, and the ensuing solution within the agreed time; â¢ One instance of collecting data without passing the verification section; â¢ One instance of operating with an expired inertial profilerâs certification; â¢ One instance of operating equipment in an unsafe manner; and â¢ One instance of not reporting traffic violations. Exceptional performance determination includes, but is not limited to the following: â¢ Deliverables made early on Texas DOT member request. â¢ Product upgrade substitution suggested and accepted at no additional cost to Texas DOT. â¢ Proposer commended for exceptional customer service, exceptional service provided. Other North Carolina DOT requests proposers to suggest methods to assess shoulder condition and to determine pavement width and lane-shoulder drop-off condition (North Carolina DOT 2015). â¢ Shoulder condition. Assess shoulder width, material type, etc., and subjectively rate pavement shoulders to satisfy HPMS requirements. â¢ Pavement width. Determine the actual paved width of the highway pavement, from edge of pavement to edge of pavement, a representative lane width from centerline to centerline of the lane markers of the driving lane, and paved and unpaved shoulder width. â¢ Lane-shoulder drop-off condition. Report âyesâ or ânoâ rating based on a drop-off of 2 in. (51 mm) or greater.