PAVEMENT MANAGEMENT OF SECONDARY ROADS IN IRELAND. Dr. Kieran J. Feighan

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1 PAVEMENT MANAGEMENT OF SECONDARY ROADS IN IRELAND Dr. Kieran J. Feighan PMS Pavement Management Services Ltd. 226 Harolds Cross Road Dublin 6W Ireland Abstract A pavement inspection methodology has been developed and improved for use specifically on the Irish non-national road network. The procedures were successfully used to survey almost 9000 kilometres of roadway throughout Ireland in a six week period in September and October 1996, with over 60 survey teams simultaneously carrying out the survey. Examination of the results to date indicate a high level of consistency and reproducibility in distress type and severity identification, and have identified the distress types where quantification of distress can be improved. The results from the survey will be used to quantify the lengths of roadway requiring various types of remedial work. 1. INTRODUCTION Ireland has a significantly different public road network compared with most other developed countries. The length of public road per 1000 population is almost 3 times the EU (European Union) average, at 27.2 kilometres per 1000 compared with the EU average of 9.25 kilometres per Of the other EU countries, Sweden and Finland are closest at and km per 1000 population. Most of the traffic is carried on a relatively small proportion of the network. The National Road Authority (NRA) has responsibility for this network, and has developed systems to manage the network. The data collection procedures on the national road network are almost totally automated, using ARAN, SCRIM and FWD equipment, and video cameras for visual distress identification. Management of the remainder of the network requires a different approach. Most of the roads carry low volumes of traffic, with many roads providing access to a few households. The cost of automated data collection as a proportion of the available maintenance budget is much too high to be economically viable. Accordingly, manual assessment procedures are the most cost-effective and appropriate. A windshield pavement inspection procedure, based on the U.S. Army Corps of Engineers Pavement Condition Index (PCI) methodology was developed and improved on over a 5 year period in Ireland. It differs from the original PCI procedure as it can be performed from a slowly-moving vehicle (c. 8 kilometres per hour), the entire length of the road section is assessed compared with the original PCI sampling procedure, and distress definitions appropriate to Irish conditions have been developed. Survey teams average 20 to 25 kilometres of surveying per day.

2 A major pavement condition study was undertaken on non-national roads in Ireland in A benchmark of existing condition in all local authorities was needed to quantify maintenance and cost requirements and to aid in allocation of central resources on a needs basis. Surveying of a total of over 9,000 kilometres (c. 10% of the total network length) was carried out simultaneously throughout the country over a 4 week period using 60 survey teams provided by the local authorities. Training courses and on-site training was carried out for all teams. Auditing of the results to ensure consistency was carried out by 5 independent survey teams on over 1000 kilometres of the surveyed roads. It is felt that there are many valuable lessons to be learnt from the Irish experience that may be useful for other jurisdictions where automated data collection is not viable from an economic or practical basis. Considerable work has been carried out to validate the windshield PCI, and to confirm that this PCI can be used to identify maintenance needs (strengthening, surface restoration, reconstruction etc.). Very useful information on the repeatability of the results, the scale of auditing required to ensure consistency, and the degree of difficulty in repeatability of identification and quantification of particular distress types is available from this large scale survey. 2. LOGISTICAL AND FINANCIAL BACKGROUND Ireland has a significantly different public road network compared with most other developed countries. The length of public road per 1000 population is almost 3 times the EU (European Union) average, at 27.2 kilometres per 1000 compared with the EU average of 9.25 kilometres per Of the other EU countries, Sweden and Finland are closest at and km per 1000 population, but they are still much lower than the Irish value. Most of the traffic is carried on a relatively small proportion of the network. The national road network of 5400 km is less than 6% of the total public road length, but carries 38% of the total traffic. The National Road Authority (NRA) has responsibility for this network throughout the country, and has developed systems to manage the network. The data collection procedures on the national road network are almost totally automated, using ARAN, SCRIM and FWD equipment, and video cameras for visual distress identification. In the current year, just over IR250 million (c. $410 million) is budgeted for expenditure on improvements and maintenance of the national road network. The remainder of the road network, c. 86,300 km, is funded through a combination of central government financing (through the Department of the Environment), and locally generated funding by local authorities. The local funding is generated primarily through commercial property taxes and charges for services provided. Administratively, Ireland is broken into 29 local authorities, each of which has primary responsibility for maintenance and upkeep of roads in their area. The proportion of central funding to local funding for roads varies from local authority to local authority; on average 60 to 65 percent of the direct funding comes from central government. Central funding for non-national roads has increased significantly in the past 2-3 years. In the current year, a total of IR173 million is being made available by the Department of the Environment, with another IR68 million of expenditure from local authority resources, yielding a total expenditure of around IR240 million (c. $385 million).

3 The nature of this non-national road network is fundamentally different to the national road network. The network is classified into four groupings; regional, local primary, local secondary and local tertiary. Typical road widths by road classification are c. 6 metres for regional roads, c.4.5 metres on local primary roads, c.3.5 metres on local secondary roads and c.2.5 metres on local tertiary roads. A relatively small percentage of the regional road network would currently carry in excess of 300 commercial vehicles per day. Most of the roads carry low volumes of traffic, less than 100 commercial vehicles per day, with many roads providing cul-de-sac access to a few households. The cost of automated data collection as a proportion of the available maintenance budget on the non-national road network is much too high to be economically viable on a routine basis. In addition, a very high proportion of the roads are limited in width, have poor geometrics, poor surface condition and many are cul-de-sac roads. It has been found that the available automated equipment cannot perform satisfactorily on these roads from practical considerations of manoeuvrability, damage to equipment and road parameters outside of the range of measurement of the equipment. Accordingly, manual assessment procedures have been found to be the most cost-effective and appropriate. In January 1996 the Department of Environment invited proposals for the carrying out of a consultancy entitled "Condition of Road Pavement Study" on Non-National Roads in Ireland (Dept. of Environment, 1996). The purpose of the Non-National Road Condition Study was to determine the extent of the backlog of deficiencies on regional and county roads in county council areas, and to quantify the remedial works required to restore these roads to a satisfactory condition. The results of the study were to provide the following information; { The length and average width, by local authority, of regional and county roads requiring surface restoration, road reconstruction and restoration of skid resistance; { The accuracy of the lengths arrived at in the above for each county, at the 95% confidence level; and { The quantities, in sq. metres, of each type of remedial work for Regional and County roads for each local authority. In May, 1996, a consortium composed of Ove Arup and Partners Ireland, PMS Pavement Management Services Ltd. and Jennings & O'Donovan and Partners were awarded the contract to carry out the study over a nine month period. 3. DEVELOPMENT OF SURVEY TOOLS A visual inspection of the pavement condition, identifying pavement distress types, quantities and severities is an invaluable aid in the evaluation of a pavement's performance, and the causes of poor performance in either structural or functional modes. One of the most comprehensive visual inspection systems developed is the Pavement Condition Index (PCI) procedure, developed by the U.S. Army Corps of Engineers in the early 1970's and extensively refined and improved over the past 20 years (Shahin and Kohn, 1981). The system is built around the concept of the PAVEMENT CONDITION INDEX or PCI. A new pavement (theoretically distress-

4 free) has a PCI of 100. For each distress measured, there are deduct values depending upon the nature of the distress, its severity and quantity. The deduct values are summed, adjusted to take into account the total number of distresses identified, and then subtracted from 100 to give the PCI index for the pavement. The power of the PCI inspection system revolves around the provision of a defined index between 0 and 100 that all pavements must lie between. In addition, all of the detailed distress by distress data is available on a section and sample unit basis so that the engineering manager is not reliant upon the PCI alone when deciding what maintenance action to pursue for a specific section. This combination of disaggregate data (the individual distress types) and an aggregated close-ended index for comparison purposes (the PCI) is what makes the PCI inspection methodology particularly appropriate for the current project. A rough breakdown of pavement classification by PCI is PCI Range Pavement Condition 85 to 100 Very Good 65 to 85 Good 50 to 65 Fair 35 to 50 Poor 20 to 35 Very Poor > 20 Failed This section PCI can then be used to compare sections with one another, to monitor pavement performance over time for that section, and to show a picture of the entire network condition by examining the number of sections in each PCI range. In addition, relationships between PCI and cost can be established, making budget estimation and prediction more accurate and easier to perform. 4. PCI WINDSHIELD SURVEY FOR IRISH NON-NATIONAL ROADS Manual condition inspection, where the pavement is examined by eye, and the distress quantities measured by hand, is the most accurate and complete form of visual inspection. It also requires the least amount of additional equipment. However, there are situations where it is uneconomical to perform a detailed manual distress survey on pavement sections. This is particularly the case on lower class roads, where the available budget per kilometre is at a low level, and the costs of data collection per kilometre become excessively high as a percentage of the available budget. A system whereby greater lengths of road can be surveyed in a given time period is obviously attractive for these road classes. Additionally, there is a safety aspect involved in the manual survey procedure, with personnel being physically located on the carriageway and shoulder surface. A windshield survey, where the pavement condition is identified from a slowly moving (5-15 km/h) vehicle, provides the ability to cover much larger distances. The inevitable tradeoff is in the quality and detail of the distress data gathered. As the speed of the vehicle increases, the types of distress, and the minimum severity of distress, that can be identified decreases. In addition, there is no physical measurement of the extent of the distress, with "ballpark" estimates being required.

5 Given these problems, the identification of an acceptable speed/accuracy tradeoff is essential. A windshield survey methodology for use on county and regional roads was developed in Ireland through research carried out at University College Galway (Brennan et al, 1994). The system was designed to complement the manual survey carried out under the PCI inspection system, and correlations were developed between the PCI obtained from the windshield survey, and the PCI obtained from a detailed manual survey over the same road sections (US Army Corps of Engineers, 1984). The windshield inspection methodology was originally developed based on very detailed inspection of almost 100 kilometres of non-national roads in County Galway. It has been successfully used on well over 1000 kilometres of local authority roads in four local authorities in the last three years, and substantial additional work has been performed to further refine the features of the system to make it as simple, reliable and accurate as possible. In addition, the windshield survey methodology has been used by PMS Pavement Management Services Ltd. to carry out surveys for engineering consultants and local authorities on over 200 kilometres of road to assess current conditions and decide on maintenance requirements and costings based on the output from the system. 5. DATA COLLECTION FOR THE WINDSHIELD PCI SURVEY Of the original 19 distresses specified under the manual PCI methodology, 10 distresses have been retained as they are by far the most common distresses encountered on Irish non-national roads (Feighan, 1991). The distresses are grouped into three categories as follows: Surface Defects Cracking Pavement Deformation In addition, a further pavement distress, Road Disintegration, has been defined to cover conditions where the pavement has completely failed. A detailed pavement inspection manual has been produced specifically for Irish road conditions, with descriptions of each distress type, how to distinguish between severity levels, and full colour photographs for every distress type/severity combination. The final edition of the manual was produced after consultations and site visits with engineering personnel from the Department of the Environment, and a representative group from the City and County Engineers Association (PMS Pavement Management Services Ltd, 1996). 6. CALCULATION OF PAVEMENT CONDITION INDEX (PCI) Deduct curves from the manual PCI system have been adopted, as the curves have been developed, refined and validated based on engineering experiences worldwide over the last 20 years. In particular, there has been a high level of satisfaction in the Irish local authorities that have implemented the PCI system with the relative rankings of roads based on the PCI deduct curves. For each pavement distress type/severity combination identified by the pavement inspectors in a sample unit, a deduct value is calculated from the appropriate deduct curve, based on the quantity

6 of distress present. The deduct curves are significantly different from distress to distress, reflecting the implications for present and future road conditions of the particular distress type. Load-related distresses, such as alligator cracking and rutting, have much steeper deduct curves (i.e. a given quantity of a load-related distress will result in a higher deduct value than the same quantity of a non-load related distress such as bleeding). The individual deduct values are totalled, adjusted to account for the interaction of multiple distresses, and subtracted from the "perfect" PCI of 100 to give the actual PCI of the sample unit inspected. The deduct value computation and correction is performed by computer software; the pavement distress data are entered (distress type, severity and quantity for each distress type/severity combination) and the software performs all of the remaining calculations. As the estimation of quantity of the distress defects is based totally on visual assessment in the windshield survey, it was found that it was convenient to give the pavement inspector the alternatives of quantifying the defects by either ranges of magnitude (<1, 1-5, 5-10, or metres or sq. m), or by estimated percent area of the distress. This has worked out well in practice, with good levels of repeatability in surveying sections with different teams of inspectors (Feighan, 1997). 7. TRAINING OF THE LOCAL AUTHORITY STAFF Each local authority provided survey teams, usually based on one team for every 3 engineering areas in the local authority. No previous experience of carrying out road condition surveys was required. The personnel provided varied from county to county, and included area engineers, engineering technicians, student engineers and technicians, and retired local authority engineers. Training of the personnel was carried out in two stages. Stage one involved a one day training course at three central locations on successive days. Each course started with an introductory outline of the purpose of the survey by Department of the Environment personnel. The remainder of the course included an outline of the survey methodology, explanation and illustration of all distress types, a guide to the practical aspects of carrying out the survey including measurement and recording of distresses, and a demonstration of the use of the data entry software. Copies of the distress manual and survey forms had been circulated to all local authority staff in the week prior to the training courses to allow for familiarisation. In the afternoon of each course, a site visit to a nearby road was undertaken. Distress identification and quantification was demonstrated on site by various personnel from the consultants offices, and a demonstration of how to fill out the survey forms correctly was included. The second stage of training involved a visit from the relevant consultant's project engineer to each local authority to supervise the local authority staff in carrying out surveys on their own roads. Care was taken to ensure that no roads designated for inclusion in the study were included in this training phase. When the project engineer was satisfied that each local authority survey team had reached a satisfactory level of competence and consistency in distress identification, quantification and recording, they were allowed to proceed with carrying out the road survey. Typically, this second stage of training required one full day in each local

7 authority, but some local authorities required supplementary visits before a satisfactory level was reached. 8. ROAD SCHEDULE A full road schedule, listing all of the road sections in each local authority using a standardised road numbering system, was supplied by each local authority. Table 1 shows the total lengths of road, in kilometres by road classification. For each road section, information was typically provided on the road number, road name, engineering administrative area, descriptions of the start and end of the section, and the length and average width of the road. The road classification is included in the road number, allowing retrieval of related road sections. Table 1: Total Road Length by Road Classification Regional Local Primary Local Secondary Local Tertiary Total 11,327 23,612 31,725 19,643 86, SELECTION OF SAMPLE ROAD SECTIONS A random sample of road sections was selected from each road schedule. A sampling rate of 11 percent was used for the Class A (Regional and Local Primary) road sections, and 8 percent was used for the Class B (Local Secondary and Local Tertiary) road sections, with the sample being drawn from within every engineering area in the local authority. The sampling rate was chosen to give the desired confidence level of 95 percent in the out-turn lengths, as specified in the consultancy brief. The sample size was calculated based on simple one-stage cluster sampling statistics (Levy and Lemeshow, 1991). The list of selected road sections in each engineering area of the local authority was sent to the local authority. The local authority then produced maps showing the locations of all chosen road sections, with copies being provided to the consultants and the Dept. of the Environment. After the survey training was successfully completed, the local authority staff carried out the survey on the chosen road sections. The distress data for each road section were collected for each 100 metre length of pavement. It is necessary to maintain the speed of the survey vehicle between 3 and 15 km/h (2 and 8 mph) depending on the condition of the pavement. The higher end of the speed range is suitable where visibility is clear, and there are very few distresses present. As the condition of the road deteriorates, the survey speed must be reduced. Typical daily output of road surveyed was 20 to 25 kilometres per day. The total lengths, surveyed in each local authority, by road classification is shown in Table 2. Typically, this survey phase was carried out over a period of 4 to 6 weeks in September and October, Table 2: Total Road Length Surveyed by Road Classification (km)

8 Regional Local Primary Local Secondary Local Tertiary Total 1,229 2,826 2,430 1,462 7, DATA ENTRY When the local authority survey was complete, the survey data were entered on the computer using customised software prepared by the consultants. When the data files were validated, the Pavement Condition Index (PCI) calculations were carried out using software prepared by the consultants. When all of the files for each local authority were ready, they were loaded into a Microsoft Access database. The process of uploading the data was extremely straightforward, and customised queries of the data table were then defined with Microsoft Access to produce the tables and data required for the data analysis. A random selection of the roads surveyed by the local authorities were independently surveyed by the consultant's survey teams and the results used as an audit of the primary results. A ten percent sample of the road sections surveyed by the local authorities was chosen in each local authority, with roads being chosen in all engineering areas, and on all road classes. The audit survey was completed virtually in parallel with the local authority survey. This minimal time difference was important to reduce the possibility of maintenance work altering the types and quantities of distress present. 11. DATA ANALYSIS Ultimately, the main product of the study will be the lengths of roadway requiring various remedial works. Specifically, the categories are surface restoration, road reconstruction and restoration of skid resistance. Surface restoration was defined to include improvement of drainage, pothole patching, restoration of road width and strengthening of road edges as well as localised surface dressing of the repaired areas. Road reconstruction was defined to include reconstruction of existing road pavements, overlaying of existing road pavements with bound or unbound materials surface dressed, and raising of road levels to prevent flooding with provision of drainage. A fourth category, Routine Maintenance, has been defined to include road section lengths not requiring any of the three remedial work types defined above. Road sections in this category would be in very good existing condition. The PCI rating of each sample unit, along with specific distress types, will be used to allocate each sample unit to a particular remedial works category. This allocation mechanism has not been finalised at the time of writing, and is not described. 12. DESCRIPTION OF DISTRESS PATTERNS NATIONALLY An analysis of the detailed distress data was carried out on the local authority and consultant audit survey results to determine the most commonly occurring distresses, the distresses with the highest average deduct values, and the distresses that have the largest average density of occurrence (expressed as the average percentage of the overall surface area within sample units where the

9 distress is recorded). The results, summarised at national level, are shown in Tables 3 and 4. Table 3: Local Authority Results by Distress/Severity Distress Severity Percent. Occur. Deduct Value Density Bleeding Medium Ravelling Low Ravelling Medium Ravelling High Potholes Low Potholes Medium Potholes High Patching Low Patching Medium Patching High Rutting Low Rutting Medium Rutting High Depressions Low Depressions Medium Depressions High Bumps Medium Bumps High Alligator Cr. Low Alligator Cr. Medium Alligator Cr. High Edge Cr. Medium Edge Cr. High Other Cr. Low Other Cr. Medium Other Cr. High Road Disintegr. High Table 4: Audit Results by Distress/Severity Distress Severity Percent. Occur. Deduct Value Density Bleeding Medium Ravelling Low Ravelling Medium Ravelling High Potholes Low Potholes Medium Potholes High Patching Low

10 Patching Medium Patching High Rutting Low Rutting Medium Rutting High Depressions Low Depressions Medium Depressions High Bumps Medium Bumps High Alligator Cr. Low Alligator Cr. Medium Alligator Cr. High Edge Cr. Medium Edge Cr. High Other Cr. Low Other Cr. Medium Other Cr. High Road Disintegr. High In examining the percent occurrences, it should be emphasised that it is frequently the case that different severity levels of the same distress can occur within a sample unit. Hence, it is not valid to simply add up the percent occurrences of all severity levels for a particular distress, and use this number as the overall percent occurrence. For this reason, attention is focussed on the relative levels of occurrence of each distress type/severity level combination. The most commonly occurring distress type/severity combinations based on the local authority survey are Bleeding, Patching (Medium), Ravelling (Low), Rutting (Low), Edge Cracking (High), Patching (High), Ravelling (Medium), Patching (Low), Ravelling (High), Edge Cracking (Medium) and Potholes (Low). The audit results show a reasonably similar ranking of occurrence, namely Ravelling (Low), Bleeding, Patching (Low), Rutting (Low), Edge Cracking (High), Patching (Medium), Potholes (Low). Examining the average deduct values for the distresses when they occur, it is clear that the structural distresses dominate both the local authority and audit surveys. In ranking the results based on the local authority data, the order is Road Disintegration, Rutting (High), Alligator Cracking (High), Rutting (Medium), Potholes (High), Patching (High), Bumps (High), Alligator Cracking (Medium), Rutting (Low), Potholes (Medium) and Other Cracking (High). The audit results show similar trends with the ranking order being Road Disintegration, Potholes (High), Rutting (High), Rutting (Medium), Bumps (High), Alligator Cracking (Medium), Alligator Cracking (High), Patching (High), Rutting (Low) and Potholes (Medium). The non-structural distresses, such as Bleeding and Ravelling, although occurring very frequently, do not have very high average deduct

11 values when they do occur. Clearly, if sample units end up with low PCI values, they are very likely to have significant structural problems based on these results. Finally, a ranking based on the average density of occurrence shows that for the local authority data, the ranking order is Road Disintegration, Ravelling (High), Ravelling (Medium), Ravelling (Low), Bleeding, Patching (High), Alligator Cracking (High), Rutting (High), Rutting (Medium), Rutting (Low), Alligator Cracking (Medium), Alligator Cracking (Low). The ranking based on the audit results is Road Disintegration, Ravelling (Medium), Ravelling (Low), Ravelling (High), Bleeding, Alligator Cracking (Medium), Patching (High), Patching (Medium), Rutting (Low), Patching (Low), Alligator Cracking (High). Clearly, from both surveys, the distress types with the largest densities are Road Disintegration, Ravelling, Bleeding, Patching and Alligator Cracking. The most significant discrepancy between the two sets of results is in the quantities of rutting present, with the local authority survey consistently indicating much more rutting present than the audit survey. This is not surprising, as quantifying the amount of rutting present visually is the most difficult part of a driven survey. Overall, the distress comparisons showed that there was very good consistency in distress identification between the local authority and audit results. There was also typically good consistency in severity level identification, with the most significant difference in ravelling where the local authorities tended to identify a significant percentage of medium severity Ravelling as high severity, and a significant percentage of low severity Ravelling as medium severity. There were also similar problems of over-rating in Patching, and, to a lesser extent in Rutting. In terms of quantification of the distress amount present, again there was typically good consistency between the local authority and audit surveys. The main differences were in Ravelling (High), Patching (High), Rutting (Low, Medium and High), Alligator Cracking (High) and Edge Cracking (High). 13. ADJUSTMENT OF DATA BASED ON AUDIT RESULTS When the audit results were compared with the local authority results, it was found that there were very significant differences in average PCI between the two surveys in some local authorities. Nationally, there was also a significant difference between the audit results and the local authority results, with the audit results having higher PCI average values. Only the sections surveyed in the audit were then extracted from the local authority database to allow a direct comparison, sample unit by sample unit, between the two surveys. Again, it was found that the local authority surveys typically had significantly lower PCI values (worse condition ratings) than the audit results. In these circumstances, there were only two options available; discard the suspect local authority data and re-survey, or adjust the local authority data based on the audit results. Re-surveying was not a feasible option in the timeframe required, and it was felt that a rational adjustment process could be used to adjust the results. Relatively little advice was identified in the statistical literature to advise on rational and defensible methodologies for adjusting the data when significant differences are noted.

12 There were three options examined for adjusting the local authority data. First, differences between the audit results and the matched local authority results could be identified by distress type/severity. These differences could be used to adjust all of the local authority data, and new PCI values could then be calculated. This approach has the advantage of adjusting at the most detailed level of data, but has several disadvantages including lack of data for some types of distress/severity combinations, differences between survey teams in a given local authority, difficulty in adjustment of data where misidentification of severity level rather than discrepancies in quantification of the data was the underlying problem, and the scale of the adjustment factors that would need to be deduced (31 local authority areas x 29 distress type/severity combinations x 4 road classifications. A second approach examined was to adjust the PCI ratings of each sample unit based on the difference between the audit and local authority PCI results. This has the advantages of being simple to implement, and having relatively large sample sizes in each road classification producing the correction factors. It has the disadvantages that the correction method does not allow correction of percent structural distress or percent surface distress parameters in each sample unit, even though these are being used for remedial works assignment. Furthermore, the best way to apply the correction method is unclear; if the average difference in PCI between the Audit and Match data is subtracted from all sample units, all results are skewed downwards, with no sample units being left in the routine maintenance (PCI > 90) category. If a ratio of Audit to Match data is applied to all sample unit results, the adjustments have much greater effect on high PCI values compared to low PCI values, and it also possible to end up with PCI values of greater than 100. The third approach examined, and ultimately adopted, was to assign each sample unit in the audit, matched and overall local authority survey into the appropriate remedial works category. The proportion of overall sample units in each remedial works category for each local authority was then calculated for the three samples. The proportion in each remedial works category from the local authority survey was then adjusted based on the difference between the audit proportion and the matched local authority proportion. The approach has the advantages that it is straightforward and simple to implement, it produces an overall adjustment of the out-turn results, it reduces significantly the variability in the out-turn results, and the reasonableness of the results can be checked immediately. A number of different adjustment methods were examined and investigated using variations on the approach outlined, and a procedure that significantly reduced the standard deviation among the local authority results, while yielding consistent and reasonable results nationally and at local authority level was adopted. The results obtained underline the importance of independently auditing the results from a pavement condition study to determine the accuracy of the collected data. REFERENCES Department of the Environment, Consultancy Brief - Non-National Roads Pavement Condition Study. Dublin.

13 Shahin and Kohn, Pavement Maintenance Management for Roads and Parking Lots. Technical Report M-294, U.S. Army Corps of Engineers Construction Engineering Research Laboratory, Champaign, Illinois. Brennan, Mulry and Feighan, A Windshield Survey Method for Pavement Condition Assessment. 2nd International Symposium on Highway Surfacing, University of Ulster at Jordanstown, Northern Ireland. U.S. Army Corps of Engineers Construction Engineering Research Laboratory, Asphalt Surfaced Roads and Parking Lots - Pavement Condition Index Field Manual. Champaign, Illinois. Feighan, An Application of Pavement Management Systems in Longford, Transactions of The Institution of Engineers of Ireland, Dublin, Vol. 115, PMS Pavement Management Services Ltd., Non-National Roads Pavement Condition Study, Windshield Distress Catalogue. Dublin. Feighan, Non-National Roads Pavement Condition Study - Methodology and Results. Proceedings, Institute of Asphalt Technology Seminar on Innovations in Road Maintenance, Ireland. Levy and Lemeshow, Sampling of Populations: Methods and Applications, Wiley-Interscience Publication, New York Keywords: Visual Condition, PCI, Windshield Survey, Statistical Analysis, Low Volume Roads