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Publication Number:  FHWA-HRT-13-038    Date:  November 2013
Publication Number: FHWA-HRT-13-038
Date: November 2013


Reformulated Pavement Remaining Service Life Framework



The prediction of future pavement preservation, repair, rehabilitation, and reconstruction requirements is the fundamental basis of engineering design and management of pavement structures. Pavement design methods are based on the provision of a pavement structure predicted to remain in acceptable condition under anticipated traffic loads and environmental conditions for a specified number of years. After construction, planning the timing of maintenance, preservation, resurfacing, rehabilitation, and reconstruction activities that take into account the material and structural as-constructed pavement characteristics become important. Life terminology has been developed and used in various ways to describe the expected period of time it will take for a pavement to reach an unacceptable condition state.

RSL is the time from the present (i.e., today) to when a pavement reaches an unacceptable condition requiring construction intervention. While some make the distinction that remaining life is the time until major rehabilitation and RSL is the time until a service threshold is reached, both types of events require some type of construction treatment to correct.

This report provides a framework to replace current pavement life terminology with one based on more exact construction event terms. The remainder of this chapter discusses pavement business decisions and the role that current RSL terminology serves in these decisions. This is followed by a discussion of issues with current RSL terminology.


Many decisions need to be made to effectively provide and manage a pavement network. A common method to classify these decisions into groups with common characteristics is through the notion of hierarchal levels within the business management process. The pavement management business processes impacted by these decisions are most often described as network-and project-level decisions.

The purposes and goals of network-level pavement management are normally related to the budget process.(2) Decisions at this level are made by higher-level management positions within an organization with resource allocation authority.

Network-level decisions have many strata starting at the local level and progressing to the national level. In local municipal agencies, network-level decisions start at the city or regional level depending on size and governmental organization. Decisions on pavement networks managed by State agencies can start at a district level but ultimately are made centrally. Primary results from network-level pavement/asset management decisions are the pavement infrastructure needs and necessary funding to effectively maintain and preserve them. At other network-level strata, decisions are made on which segments of the road network are scheduled for future construction interventions requiring project-level plans to be prepared.

Because of the economics of pavement condition field data collection, data requirements to support network-level business decisions must be more aggregated and contain fewer details as one progresses from local- to national-level network strata.

For pavement assets, decisions at the project level focus on providing the most cost effective, feasible, and original design, maintenance, rehabilitation, or reconstruction strategy possible for a selected section of pavement within the available funds and other constraints.(3) The data needs at the project level are the greatest since they result in engineering plans and specifications on treatment activities to be applied to individual projects.

Alternative contracting mechanisms such as design-build-operate and warranty construction are subsets of the more general project-level business decisions and could be classified as a contract administration level type of business decision. Because the acceptance conditions must be specified in the contract, data support for these project-level contracts have an additional burden of withstanding the test of potential contractual challenges.


Predicting the remaining life of a pavement is a fundamental aspect of pavement management planning. Knowing or estimating the future condition of pavement segments is the rational basis of all informed pavement infrastructure planning decisions. A goal of modern pavement management systems (PMSs) is to optimize agency resource expenditures while minimizing impacts on facility users and the ecosystem.

Pavement infrastructure budget optimization techniques require predicting the change in pavement condition within a defined set of timeframes. Those techniques then predict what is needed under the following action scenarios:

Table 1 presents a summary of the role of RSL models in business decisions at different levels of pavement management, contract construction, and pavement operation mechanisms.

Table 1. Role of RSL models in levels and types of pavement management business decisions.



Pavement RSL Model Role




Project design

treatment selection

Time until pavement structural and functional limit
thresholds are reached or exceeded; service life prediction of candidate treatments

Overlay thickness

Service life prediction of candidate overlay design

rehabilitation treatments

Time until pavement structural and functional limit
thresholds are reached or exceeded; service life prediction of candidate treatments

Noise mitigation
treatment selection

Prediction of increase in noise as a function of pavement age,
surface texture, traffic volumes, and vehicle speed

Friction mitigation
treatment selection

Prediction of changes in friction as a function of predicted
change in surface texture characteristics and age




Pavement network planning

Needed pavement
maintenance budget

Time until pavement functional limit threshold are reached
or exceeded; predicted pavement condition as a function of funding allocation

Needed pavement
rehabilitation budget

Time until pavement structural and functional limit
thresholds are reached or exceeded; changes in pavement condition for non-treated projects and rehabilitated projects

Needed pavement
reconstruction budget

Time until pavement structural and functional limit
thresholds are reached or exceeded; change in pavement condition for non-treated projects and reconstructed projects

optimization— allocation of resources to projects

Change in pavement condition for non-treated projects,
rehabilitated projects, and reconstructed projects

maintenance management

award fees/penalties

Structural and functional service life prediction as a function
of applied maintenance treatments


Acceptance by
public agency at end of contract; decisions based on contract terms

Time until pavement functional need thresholds are reached
or exceeded; predicted maintenance-free life; time until rehabilitation is required; predicted performance of pavement until rehabilitation required

construction contract

Acceptance by
public agency at end of contract; decisions based on contract terms

Time until pavement functional need thresholds are reached
or exceeded; predicted maintenance-free life; time until rehabilitation is required; predicted performance of pavement until rehabilitation required

As described in table 1, the central role of RSL models in all of these pavement management business decisions is predicting the change in pavement condition as a function of time, traffic loading, and environment. The basic difference in the RSL models used at the project, network, and contract administration levels are data requirements related to level of technical detail, extent, quality, precision, and accuracy of the model inputs. Project- and contract-level models require the greatest amount of input data to satisfy statistically based inferences. Ideally, models used at the project level are expected to be calibrated to local conditions and use better and more data. As a result, they are perceived to be more accurate than models used at network levels since actual engineering decisions are based on their results. Network-level decisions typically result in an allocation of resources, which must be subsequently programmed down to the project level. Since pavement network condition is only one input in this process, data requirements do not currently justify the intensity of project-level data collection.

When the promise of fully automated pavement data collection technology is finally reached, project- and network-level decisionmaking can converge to use a common set of RSL model inputs. The basis of the decisions made at the network planning level will then converge with information used at the project implementation level. Since simplified models are currently used for network-level planning, the assumptions made during the optimization process on the type of future treatments to apply to each pavement segment may not match the actual pavement treatments designed using detailed project-level data. Until the disparity between assumptions used in network-level budget optimization algorithms are matched to the resulting project-level treatment decisions, true network budget optimization is not assured. While this vision of merging network- and project-level pavement management modeling may be somewhat optimistic at this point in time, efforts to reduce network-level data collection costs while providing more information are continuing to be pursued.


While the prediction of time until a corrective or preventative construction treatment should be applied is an established critical component at all levels of pavement management decisions, many issues exist in the current RSL terminology and resulting numerics, which confuse, confound, and complicate proper interpretation, interagency data exchange, and use.

One common RSL definition is the time until the next rehabilitation or reconstruction event. Rehabilitation and reconstruction are two very different events in terms of pavement condition at the time of construction and construction costs. The rule of thumb is that rehabilitation treatments should be applied before a pavement has suffered too much structural damage. Otherwise, the rehabilitated pavement structure will not last very long. Reconstruction treatments are generally warranted after a pavement has reached an advanced degree of deterioration. Typically, during the planning process, an agency decides to apply a rehabilitation treatment to extend the time until reconstruction is required. Attempting to interpret combined RSL estimates from mixed rehabilitation and reconstruction units can cause confusion for decisionmakers.

Another common RSL definition is the time until a condition index threshold limit is reached. This approach shares the same issues as rehabilitation and reconstruction RSL units but also introduces other service and safety condition indices, which further complicate the meaning of RSL. Setting threshold limits for pavement conditions that are not based on human subjective ratings, such as cracking, can be complicated to justify. Moreover, interpretation of a single RSL number gets even more complicated when it is based on multiple condition states. For example, if RSL for roughness is 2 years, RSL for cracking is 5 years, RSL for friction is 7 years, and RSL for rutting is 20 years, expressing that the current pavement RSL equals 2 years can lead to imperfect construction decisions since the construction treatment selected to correct roughness may not necessarily address the more serious cracking issue expected to occur soon after the roughness threshold is reached. Since there are many construction treatments that can be used to correct excessive pavement roughness that can be classified as pavement preservation, this approach adds maintenance-type activities to RSL units.

Another intriguing aspect of RSL based on threshold limits is negative RSL. When a Pavement Condition Index (PCI) limit is reached, from a numerical standpoint, the years it remains in service after this time could be considered a negative service life, which is counterintuitive. One approach is to set negative values to zero, thus not allowing a negative RSL value to be provided by the process. Another approach is to consider negative RSL as overdue needs, in which case, the number of years overdue can be considered as additional information to decisionmakers if they know the basis of the condition in need of attention.

Another approach to RSL is based on agency management rules on the time between applications of corrective pavement construction treatments. For example, a State highway agency (SHA) with a relatively small number of interstate highway lane-miles may decide, based on past performance, to apply a resurfacing, rehabilitation, or reconstruction treatment every 8 years to each construction segment unit on the system to keep their highest level functional class pavements in the best condition. The RSL becomes the difference in time between the construction frequency established and how long it has been since the last treatment was applied. While this approach simplifies the decisionmaking and project selection process, it does not typically result in the most cost effective solution.

One unintentional consequence of using current RSL terminology, which is defined as the time to reconstruction or major rehabilitation, is that it tends to promote worst-first approaches to correcting pavement deficiencies. By expressing pavement condition in terms of RSL, laymen and politicians expect that pavements in the worst condition get treated first. Construction treatments on pavements in the worst condition tend to cost the most. Applying a life extending corrective rehabilitation treatment before the pavement condition gets too bad tends to cost less than reconstruction treatments. Optimum allocation of annual pavement resurfacing, rehabilitation, and reconstruction budgets will be a mixture of pavements with differing remaining lives and not based solely on a worst-first approach.


The framework presented in this report is intended to provide a common definition that may be referred to by anyone attempting to evaluate the remaining life or service life of a pavement structure. Chapters 2 and 3 discuss the updated vocabulary as well as the framework associated with RSL development and construction needs assessment. The remaining chapters cover each step of the process including construction triggers, threshold limits, performance curves, inputs, strategy selection, assessments, and updates. The final chapter summarizes the major findings.