Pavement Management Systems Peer Exchange Program
Findings and Observations
Although the topics raised during the Peer Exchange were specific to these participants, they are equally relevant to many other state highway agencies with initiatives underway to enhance their existing pavement management program. Whether an agency is looking to implement new pavement management software or improve the reliability of its data collection procedures, or whether an agency is looking to increase the use of pavement management information in its decision process or incorporate pavement preventive maintenance treatments into its pavement management software, the findings from the Peer Exchange provide an opportunity to learn more about how these issues are being addressed successfully by Mn/DOT and UDOT. This section of the report summarizes the findings and observations in a number of areas that were raised during the Peer Exchange.
Data Collection Activities
Mn/DOT has been collecting pavement distress and roughness data for approximately 40 years. The condition data are collected and analyzed each year; the results are loaded into TIS and extracted into the HPMA data tables for use in the pavement management analysis. The availability of the data in TIS assures easy access to the condition data for individuals in both the central office and the regional offices.
Pavement condition information is collected using one of two state-owned Pathway Services Digital Inspection Vehicles. The equipment is used to collect roughness, rutting, cracking, and faulting as well as digital images of the pavement surface. Table 2 summarizes the data collection protocols used by Mn/DOT. The equipment is replaced about every five years.
|Roughness & Rutting||
|Cracking & Faulting||
Pavement condition data is used to calculate three condition indexes: a surface rating (SR) that ranges from 0 to 4 based on the amount of cracking, rutting, faulting, and other distress present; a ride quality index (RQI) that converts an International Roughness Index (IRI) to a 0 to 5 scale, and a Pavement Quality Index (PQI) that is calculated from the SR and RQI. MnDOT calculates remaining service life (RSL) values by estimating the number of years until the RQI reaches a value of 2.5, which signifies the point at which major rehabilitation is required. Project and treatment selection are heavily weighted in terms of the RQI, and performance targets for this index have been established. The current RQI targets to achieve by the year 2014 are listed in table 3.
|Condition Category||Principal Arterials||Non-Principal Arterials|
|Very Good (4.1-5.0)
|70% or more||65% or more|
Very Poor (0.0-1.0)
|2% or less||3% or less|
Condition data are reported in a number of different formats. For example, a trifold fact sheet is produced annually showing the number of miles of each type of pavement and the average condition for the network by various groupings. An Executive Summary is produced for District Engineers to summarize their network conditions and to indicate whether or not their performance targets have been met. Map displays are also produced and provided to the Districts.
Mn/DOT is fairly unique in that the State provides data collection to counties on a contract basis. The counties are charged a flat rate of $37/mile to collect condition information on their road network. At the county's request, Mn/DOT will collect the same condition information collected on the state system for the county highways and present the information in a spreadsheet. The Division of State Aid for Local Government pays for the collection of the county data on the County State Aid Highway (CSAH) system. Mn/DOT contracts directly with the counties for testing their non-CSAH routes or when they want additional testing in a year when testing the CSAH system is not scheduled.
At the present time, pavement condition data for the state highway system is collected by individuals from both the central office and the Regions. Asset Management staff are responsible for collecting ride and rutting information on hot-mix asphalt (HMA) pavements and ride and faulting on portland cement concrete (PCC) pavement. This information is collected annually using an International Cybernetics Corporation (ICC) van, with one lane in each direction surveyed on interstate pavements and one lane in one direction on the rest of the state routes. In addition, the Asset Management team is responsible for collecting the photo log and for conducting any structural or skid testing that needs to be done at specific locations. Approximately 1800 miles of structural testing is conducted each year using a Jils falling weight deflectometer (FWD), which results in nearly a 3-year cycle for HMA interstate pavements, a 4- year cycle for other HMA routes, and a 5-year interval for PCC pavements. Approximately one test is made in each mile of the road network. Skid resistance is tested each year with half the system tested on odd years and half of even years. In addition to testing state routes, the Department also tests any nearby forest routes and state airports that request skid testing. Currently, the FWD and skid resistance data have limited use in project and treatment selection but eventually they would like to correlate test results to a structural number to help determine the remaining life of a pavement.
In addition to the information collected by the Asset Management section, the Region Pavement Management Engineers collect pavement distress data annually through windshield surveys. Each Region receives $5,000 for collecting the information and any additional costs are funded out of the Region budget. The first tenth mile (500 feet) of each mile in the outer travel lane is inspected. A summary of the type of distress information collected is presented in table 4.
Pavement condition information is reported in terms of nine indexes, each on a 0 to 100 scale with 100 representing a road in excellent condition. For asphalt-surfaced pavements, conditions are reported in terms of ride index, rut index, crack index (for environmental cracking), and wheel-path cracking. PCC surface indexes include a ride index, a faulting index, a concrete cracking index (for shattered slabs and corner breaks), and a joint spalling index. An Overall Condition Index (OCI) is calculated for all surfaces by taking the average of the four indexes for each surface type.
In the past, UDOT has had difficulty matching the survey data with field locations, which is one of the reasons they are moving forward with a contract to have a vendor collect pavement condition information using automated equipment. The DOT issued the RFP for data collection services and was in the process of selecting a vendor at the time of the Peer Exchange. UDOT plans to issue a 1-year contract to the vendor with an option for four additional single-year extensions. Under the automated data collection contract, the vendor will collect ride, rutting, faulting, and distress data as well as conduct the photo log. The cost of collecting the data using automated means is expected to be equivalent to the amount being spent by the Department internally, so no additional funding was needed for this change.
The pavement condition information is loaded into the pavement management software and reported to the Regions each fall in a number of different formats. In addition to reporting current and projected conditions, the Pavement Management team provides the Regions with section-by-section treatment recommendations and costs based on the results of an optimization analysis.
Links to Maintenance and Operations
With the increased emphasis on pavement preservation activities in state highway agencies, it is becoming increasingly important for Pavement Management personnel to interface with Maintenance and Operations personnel to coordinate maintenance and rehabilitation activities. In Utah, this interface is strengthened by the fact that the Deputy Engineer for Maintenance formerly served as the Pavement Management Engineer for the State. Therefore, he has a good understanding of the pavement management system and the types of information it uses to make project and treatment recommendations.
UDOT currently utilizes its maintenance management system (MMS) and its Maintenance Management Quality Assurance program (MMQA+) to assist in setting maintenance budgets that are linked to resource requirements and performance targets, although new software is being implemented. MMQA+ uses a sampling approach (a 100 percent sample in most cases), to determine a level of maintenance (LOM) for reporting the performance of UDOT's roadway appurtenances (such as signs, guardrail, and markings) and the effectiveness of maintenance activities (such as snow removal, litter control, and mowing). The results of the surveys are reported in terms of current LOM (as a letter grade) and funding needed to achieve the targeted LOM is estimated. The availability of this type of information allows UDOT to quickly respond to questions about the impact on performance associated with proposed budget cuts. This concept is illustrated in figure 1. As shown in the figure, the budget requirements associated with a high LOM (e.g., A or B) are higher than the cost of maintaining a low LOM (e.g., D or F). Depending on the type and number of assets, the difference in costs associated with different levels of service can vary greatly (represented by the steepness of the cost slope shown in figure 1). Agencies typically try to maintain a higher level of service on high-volume facilities than low-volume facilities and on assets related to safety (such as regulatory signs) over activities associated with aesthetics (such as mowing).
Figure 1. Example of the link between level of maintenance provided and budget needs.
The LOM for pavement activities is linked to the pavement management system through the OCI, which is calculated based on the results of the pavement condition surveys. The OCI will be the pavement performance measure used in the new maintenance management software program selected to replace the MMS and MMQA+ software. The new software, which was developed by AgileAssets and is being referred to at UDOT as the Operations Management System (OMS), has several modules that link LOM to budgeting and resource requirements. UDOT is currently planning to implement AgileAssets' pavements module as a replacement for UDOT's Plan For Every Section database, to further strengthen the link between pavement maintenance and pavement management. The pavements module will store information on inventory and service-level activities so it can be accessed by field personnel or by pavement management for use in performance modeling or treatment selection recommendations. UDOT envisions having both the maintenance component and the pavements component of the OMS fully operational by the end of 2008.
Mn/DOT does not have as strong a link to maintenance, largely because its work management system reports work activities in units that do not easily link with pavement management sections. However, this is not a huge issue since most preventive maintenance is conducted under contract (rather than with in-house forces) and records of contract maintenance activities are available in the Districts. Mn/DOT does not store its maintenance activities in the pavement management database, but relies on an analysis of pavement deterioration models for each section in the database to identify where maintenance improvements have been made. Mn/DOT's pavement management software has a tool that allows the Pavement Management Engineer to quickly review the historical deterioration trends of each section in the database to determine if any anomalies appear. These anomalies (such as an unexplained increase in condition) are reviewed with District personnel and are typically found to be explained by some type of maintenance activity.
An initiative is currently underway within Mn/DOT to demonstrate the effectiveness of maintenance activities. Using pavement management data, Mn/DOT has determined that smoothness isn't a good measure for documenting these benefits. However, Mn/DOT is considering the use of other performance measures, such as a cracking index, as a way to demonstrate maintenance effectiveness.
A previous initiative involved demonstrating to maintenance personnel that the automated data collection equipment was capable of measuring pavement condition information in sufficient detail to identify where maintenance activities had been performed. The Pavement Management Unit demonstrated its ability to identify concentrated areas of roughness and locations suitable for wedge paving (forcing fine material into depressions with a blade). The results of these activities significantly raised the level of confidence that Maintenance and Operations personnel had in the data collected by pavement management.