Applying Transportation Asset Management to Traffic Signals: A Primer

Chapter 6. Maximizing Performance—Lifecycle Planning

Planning for the lifecycle of assets is a foundational principle of asset management. The FHWA encourages transportation agencies to develop and adopt asset management plans that enable them to meet the challenges of preserving their assets while optimizing their performance over asset lifecycles. The maintenance approach for each asset type may differ, depending on its risks and effect on the transportation network. Effective asset management planning is proactive. Rather than waiting for an asset to fail, requiring replacement or costly repairs, preventive maintenance and other proactive interventions may keep costs low and support better system operation (reduce delays).

FHWA TAMP Element: Lifecycle Planning, Risk Management (23 CFR 515.7(b)-(c))

Lifecycle planning is a critical component of asset management, but is most effective when part of a robust asset management program. Lifecycle planning is one of the emerging themes in traffic signals asset management. Lifecycle planning is a requirement for TAMPs. All major asset classes should have a lifecycle plan addressing future changes in demand, information on current and future environmental conditions, the management/maintenance of the asset, and other factors that could impact whole of life costs of assets.

Every asset will eventually reach a point of failure, and this timeframe is often referred to as the life expectancy (National Academies 2012). Each asset may experience a different rate of deterioration. Figure 6 illustrates various deterioration rates.

A line graph showing various deterioration curves of condition over time.

Figure 6. Graph. Asset deterioration curves.
(Source: FHWA.)

Assets (especially electronic assets) can fail at any time (sometimes unexpectedly). As an asset gets closer to the end of its life, the risk of failure increases. This increased risk creates uncertainty in decisionmaking and lifecycle planning.

Several key concepts that inform asset specific decisionmaking are as follows:

Maintenance Management—How maintenance decisions are made within an agency. The maintenance management approach influences the method to estimate the lifecycle cost of managing an asset over its whole life.
Work Types—The action taken as a result of a life-cycle planning approach. FHWA uses work type categories of initial construction, maintenance, preservation, rehabilitation, and reconstruction.
Lifecycle Planning—The overall process to estimate the cost of managing an asset class, or asset subgroup over its whole life with consideration for minimizing cost while preserving or improving the condition.

Maintenance Management Approaches

With traffic signals, an agency may consider a range of maintenance management approaches, including the common approaches listed in table 7.

Table 7. Maintenance management approaches for traffic signals.
Approach	Description	Outcome
Condition-Based Maintenance Management	Maintenance activities are scheduled based on regularly monitored performance. Typically, used on assets with long asset lifecycles.	Approaches can lead to asset preservation.
Interval-Based Maintenance Management	Maintenance activities are scheduled at specific time intervals based on an analysis of asset performance. Used on assets with either short or long lifecycles.	Approaches can lead to asset preservation approaches.
Reactive Maintenance Management	Maintenance activities are performed in response to reported asset failures or events, such as a vehicle collision or component failure.	Requires repair/replacement to return service.

Each approach listed in table 7 can be appropriate for certain assets. The following sections describe the approaches and their application.

Condition-Based Maintenance Management

Condition-based maintenance management involves regular monitoring of an asset to assess the point at which repair or replacement is required, as shown in figure 7. The cost to undertake inspections can be high and should be balanced with the associated risk of failure.

A line graph showing condition of an asset over time with condition-based maintenance.

Figure 7. Graph. Condition-based maintenance management.
(Source: FHWA.)

For traffic signals, traffic signal poles should be inspected regularly because they are major supporting structures. Virginia DOT conducts a combination of maintenance management approaches for its traffic signals, including condition-based maintenance for its traffic signal structures.

Interval-Based Maintenance Management

Interval-based maintenance is commonly used for traffic signal assets, and it is a good starting point for planning and predicting needed repair or replacement. Once an asset reaches a specified age it is either repaired or replaced. The age at which an asset must be repaired or replaced varies (sometimes considerably) but this proactive approach reduces the likelihood of asset failure. Interval-based maintenance uses information on the age of the asset to assess the time to repair/replace. A decision on the best way to predict service life depends on the information available, knowledge of the product, and the time available to decide. This information may come from various sources, including the manufacturer, industry best practices, and the agency’s own research. Interval-based preventive maintenance (figure 8) creates an opportunity for operations checks for traffic signals. Technicians may check the pedestrian timing as they check the pedestrian push buttons. They often check signal timing parameters, such as gap times and min and max green. In-pavement loop detectors are usually checked as well.

A line graph showing condition of an asset over time with interval-based maintenance.

Figure 8. Graph. Interval-based maintenance management.
(Source: FHWA.)

Condition-Based Lifecycle Management—Virginia DOT

Virginia DOT classifies its traffic signals into two components: the traffic signal structure (what it defines as an ancillary structure) and the traffic signal head (the electrical and technical components). For the traffic signal structure, Virginia DOT assesses the condition of the superstructure (span wire and/or cantilever) and the substructure (foundation). The condition ratings used for ancillary assets are divided into five categories: good, fair, poor, critical, and failed condition. At the time of each inspection, an inspector assigns condition ratings to describe the major structural components of the asset. Condition ratings are based on criteria similar to those defined by FHWA for bridge inspection. Signals are inspected for condition every four years. Figure 9 shows the condition of Virginia DOT’s ancillary structures for three of the five rating categories.

A stacked bar chart showing conditions ratings of Virginia Department of Transportation’s ancillary structures for the good, fair and poor categories.

Figure 9. Graph. Virginia Department of Transportation condition of ancillary structures.
(Source: Virginia Department of Transportation, 2018.)

For traffic signal heads, the agency follows an interval-based approach. Information (based on industry standards and field subject matter expert observations) on the age, expected useful life, and recommended cycles of preventive maintenance and replacement for traffic signals is used to develop a maintenance management model that generates needs information. Investment activities for traffic signals include repair and replacement to restore a damaged or deteriorated asset to standard design, functionality, and capability.

Reactive Maintenance Management

When the information on an asset is limited, the risk of failure is low, or the cost to collect data (including condition) is high, then a reactive approach to repair and replacement may be appropriate. Although reacting to asset failure has the benefit of maximizing the life of the asset, from a risk perspective, this approach should consider the time required to repair the system and the impact of that down time. When deciding to take a reactive approach (figure 10), agencies should consider that traffic signal failures can introduce major safety and operational issues (i.e., signal goes into flash mode or goes dark) or less critical failures (i.e., system communications fails but has minimal impact on actual operations). A failure can be identified in a number of ways, commonly including through sensor detection or public complaints.

A line graph showing condition of an asset over time with reactive maintenance.

Figure 10. Graph. Reactive maintenance management.
(Source: FHWA.)

Predicting Performance of Traffic Signal Assets—Austroads

The Technical Supplement to the Austroads Guide to Asset Management provides a list of common approaches to predicting the service life of assets including:

Manufacturers’ performance data.
Professional judgment of agency staff.
Literature reporting service life experienced by others.
Documented road agency experience: for example, historical databases or other records of asset performance and service life.
Lifecycle cost analyses to compare the performance and costs of alternative components.
Predictive models or management information systems to support the management of these assets.

This guide also provides an overview of likely failure modes, methods for predicting service life and the data required for monitoring. The performance prediction for traffic signals is provided in table 8.

Table 8. Predicting performance of traffic signal assets.
Asset	Asset Lifecycle (Physical) Performance “Failure” Mode(s)	Predictability of Physical Service Life of Asset	Data Required for Monitoring
Traffic signals Traffic sensing loops Traffic signal controllers	Lamp failure (end of globe life). System failure due to damage/deterioration of controller. Reduced conspicuity due to dirty lends. Damage from vehicle crash or vandalism. Technical obsolescence.	Professional judgment based upon local experience, manufacturers’ data on life of components and monitoring.	Operation. Power supply. Power usage. Condition and cleanliness.

Reliability-Centered Maintenance

Given the three maintenance management approaches previously discussed, agencies must decide which one is best for them. A reliability-centered maintenance (RCM) approach can be beneficial here. RCM is the application of engineering principles to manage the consequences of failure. The RCM process also invokes engineering reasoning to establish the appropriate maintenance tasks for a given asset. It can be used to select the preferred maintenance management approach for an asset. An example of this is shown in figure 11.

Figure 11. Flowchart. Maintenance Approach Decision Tree.
(Source: FHWA, 2019.)

The RCM process has been used in defense, airline, and mining industries to improve the reliability and cost effectiveness of maintenance activities. RCM is relevant to these industries because of the use of complex electronic and communication equipment that needs to work in an integrated manner.

The following discussion draws from an Austroads report, Reliability-Centered Maintenance Strategy and Framework for Management of Intelligent Transport System Assets (Austroads 2016), which further defines RCM and identifies key success factors, benefits, and acceptance of RCM approaches.

The basic steps of RCM involve a set of questions as follows:

Under what circumstance can an asset fail that may lead to major economic, environmental, operational, and safety costs?
What are the root causes of the failure?
Can the failure be viably managed through proactive maintenance? If yes, it is best to minimize the possibility of the failure through proactive maintenance techniques, including on-condition maintenance and preventive maintenance.
If proactive maintenance is neither technically nor financially feasible then identify the best alternative maintenance task, which could be a combination of tasks including the following:
1. Unscheduled maintenance.
2. Equipment redesign.
3. Failure-finding tasks.
4. Modifications to operating procedures.
5. No scheduled maintenance (i.e., make no effort to anticipate).

As part of Austroads’ RCM study noted above, a number of traffic signal assets were considered as case studies. A group of practitioners went through the RCM process for these assets. Table 9 illustrates some of the key findings, specifically in this case, for inductive loop vehicle detectors (as part of a traffic signal).

Table 9. Austroads reliability-centered maintenance process.
Item	Description
Component	Inductive loop vehicle detectors.
Function	To accurately detect and count vehicles as inputs to traffic signal control.
Functional failure	The sensors are unable to detect vehicles. The sensors are sending inaccurate readings.
Most prominent failure mode	Pavement cracks or erodes to expose loop cables. Loop lifts up out of pavement and loop frequency changes, therefore loop cannot detect vehicles. Loops exposed or poorly terminated due to incorrect installation.
Failure effect	Vehicles are undercounted or overcounted, resulting in suboptimal signal control leading to longer delays at intersections. Turning vehicles not detected and turning arrow not activated, resulting in long wait and increased risk-taking by vehicles.
Determine criticality: Failure consequence	Not severe to severe, depending on location.
Determine criticality: Likelihood	Most likely.
Determine criticality: Criticality	Critical (yellow).
List possible task (if applicable)—On-condition maintenance task	Conduct on-condition survey and document level of pavement wear. Inspect condition of surrounding pavement for water ingress, pooling water, and exposed loops. Repair pavement as required.
List possible task (if applicable)—Scheduled restoration/replacement task	Restoration as part of pavement rehabilitation.
List possible task (if applicable)—Change operating procedure	Activate ‘fail safe’ mode whereby detector is left on if terminal fault is found in the loop/leads to over-counting, but at least signals change (turning arrow).
List possible task (if applicable)—Charge in commissioning (installation to site)	Revise installation process to ensure loops are correctly installed, with no part of the loop protruding from the pavement. Inspect commissioning immediately after installation, and periodically thereafter. Document handover between installation contractor and service operation, including inspections. Document correct termination techniques and ensure proper training of technicians.
List possible task (if applicable)—Equipment redesign	Interrogate SCATS (or other traffic signal management system) counts for irregularities and reoccurring zero counts to identify failed loops. Consider video-based detection.
List possible task (if applicable)—Call-out maintenance	Conduct call-out repairs as currently practiced.
Remarks	All of the above tasks should be implemented.

Obsolescence

Technology assets (including traffic signals) can become obsolete even if the asset is in good physical condition and functioning as designed. With rapidly changing technology and expectations of the traveling public, technological demands of the transportation system may exceed the asset’s capacity to provide the necessary service.

For advanced technology that is commonly found in traffic signals assets, obsolescence is a challenge. For example, an asset can become obsolete if:

It needs to be replaced due to other projects (e.g., road widening).
The software or the product is no longer supported by suppliers, and software upgrades or replacement parts are unavailable.
The cost to repair becomes greater than the cost for replacement (and often improved) products.
The software is no longer compatible with new systems.
New, adopted concepts cannot be supported (such as ATSPM or transit signal priority).

The challenge with obsolescence is that it is hard, if not impossible, to predict. It can shorten the expected life of an asset and mean that it needs replacement before it reaches the point of failure. Sometimes, upgrades in the asset or even software can have a net benefit to the mobility and reliability of the transportation system in addition to cost savings, even if the current setup is meeting the demands of the system. Agencies are starting to identify strategies and steps to better plan for obsolescence, which typically follows a risk-based approach:

Asset Lifecycle—Determine how long the asset should be sustained and operated, considering any major mid-life upgrades or replacements.
Identify Components Most Likely to Become Obsolescent—Breakdown the asset into its lowest maintainable units, or components. Most obsolescence issues are experienced at the component level.
Develop Criteria to Assess Obsolescence Risk—Identify various factors the agency can use to determine the probability of an obsolescence issue and/or the operational impact, if the component were to become obsolete. This might include number of manufacturers, access to software upgrades, and ease of replacement.
Assess the Risk of Becoming Obsolete—For each component, based on the criteria developed, assign a score (such as low, medium, or high) for both probability and impact and calculate an overall obsolescence risk score.
Mitigation Strategies—For those components identified as high obsolescence risk, determine appropriate mitigation strategies, such as design considerations, planned system upgrades, and partnership agreements with suppliers.

Lifecycle Planning

As defined in 23 CFR § 515.5:

Lifecycle planning means a process to estimate the cost of managing an asset class, or asset sub-group over its whole life with consideration for minimizing cost while preserving or improving the condition.

The process of lifecycle planning considers a range of different maintenance management approaches to deliver the most cost effective solution throughout the life of the asset. Lifecycle planning identifies the cost and outcome associated with a range of maintenance management approaches. This information then is combined with:

Existing condition information.
A deterioration rate for assets that assesses how quickly the condition of an asset falls from one condition level to another. In an age-based model, this will purely be the time to move from one condition level to the next.
An analysis period that is usually at least as long as the time from asset creation through to asset rehabilitation or replacement.

The FHWA publication Using a Lifecycle Planning Process to Support Asset Management (FHWA 2017) addresses developing an initial lifecycle planning process that satisfies the requirements of 23 CFR part 515.

Lifecycle Planning Model—Caltrans

The Caltrans TAMP has four primary asset classes: pavement, bridge, drainage, and Transportation Management Systems (TMS). California TMS assets include (but are not limited to): traffic signals, closed circuit televisions, changeable message signs, traffic monitoring detection stations, and freeway ramp meters. As shown in figure 12, California’s lifecycle planning model for its assets is based on the costs and service life of different types of treatments (currently, for TMS assets, the “Fair” state is not yet applicable). This lifecycle planning model is founded on the principle of deterioration. Deterioration is the physical degradation of an asset because of a combination of factors, including age, construction materials, environment, accidental damage, and traffic load. A set of deterioration rates are determined for each asset type to account for expected future conditions.

Caltrans currently uses a TMS Inventory Database populated by district personnel to track all statewide TMS assets. This database provides information on system type, location, and installation date. Caltrans is developing strategies to better monitor the condition of the TMS network, such as strengthening collaboration with maintenance staff, which will enable a more responsive and efficient replacement process.

A diagram showing the lifecycle of an asset. From right to left there is good, fair and poor categories.

Figure 12. Diagram. Caltrans physical asset model for lifecycle assessment.
(Source: Caltrans, 2018.)

Lifecycle Planning for Traffic Signals—Minnesota DOT

Minnesota DOT included the following example of traffic signal lifecycle planning within its 2019 TAMP, shown in table 10. The traffic signal lifecycle analysis included four strategies:

Strategy A: Included only reactive maintenance, with estimated maintenance costs.
Strategy B: Consisted of three periodic inspections/preventive maintenance tasks, one each for operational, electrical, and electronic and were anticipated to reduce reactive maintenance costs by five percent.
Strategy C: Consisted of replacing the electronics and the LED indications proactively on a periodic basis.
Strategy D: Consisted of periodic structural inspection, which was anticipated to increase the expected life of the entire signal system from 30 years to 40 years.

Table 10. Minnesota Department of Transportation traffic signal lifecycle planning scenarios.
Treatments	Typical Costs	Strategy A Reactive Maintenance	Strategy B Preventive Maintenance	Strategy C Equipment Replacements	Strategy G Structural Inspection
Reactive Maintenance	$399	Annual	Annual	Annual	Annual
Operations Check	$74	None	Annual	None	None
Electrician Preventive Maintenance	$124	None	Every 3 years	None	None
Electronic Preventive Maintenance	$132	None	Every 2 years	None	None
Replace LED Indications	$20,000	None	None	Every 10 years	None
Replace Electronics	$30,000	None	None	Every 15 years	None
Structural Inspections	$1,000	None	None	None	Every 5 years
Expected Life	N/A	30 years	30 years	30 years	40 years
MNDOT EUAC Per Signal	N/A	$8,885	Add $23	Add $1,908	Sub $1,523

The agency’s analysis indicated that the added inspections/preventive maintenance tasks cost more than they saved. Even if the inspections/preventive maintenance and replacement tasks had eliminated all reactive maintenance costs, it would still cost more than it saved. Although the inspections/preventive maintenance tasks of the middle scenario did not demonstrate benefit from a lifecycle cost point of view, the agency considers these efforts beneficial for operational and liability reasons. Conducting structural inspections lowered the equivalent uniform annual cost, saving more than it cost, by lengthening the time between total rebuilds of the signal system.

Building Information Modeling as a Tool to Inform Lifecycle Planning

One factor that can affect maintenance and operations of traffic signal assets during the lifecycle is how they are inventoried, particularly in capturing key attributes such as location data. Most agencies manage the inventory of signalized intersections or signal sites but not the individual components at the signal site (e.g., signal head, poles, and cabinet equipment). Critical data about traffic signal assets and components such as manufacturer details; type of device; warranty period of installed device; and maintenance recommendations, schedule, and activities are typically not captured after installation, but this information is important for operations, periodic maintenance and proactive workplanning.

Issues such as those stated above can be addressed by incorporating Building Information Modeling (BIM) processes, policies, tools and standards. BIM integrates many technologies and practices that bring digital tools and a data-centric approach for improving lifecycle delivery and management of highway assets. However, the approach for deploying BIM has been typically siloed, either within an organization’s subunits or at the project level. Many State DOTs recognize the benefits associated with the bigger picture of BIM as a data-centric approach both for project delivery and asset management practices. BIM centers on the idea that data itself is an asset and that there are efficiencies to be gained when business silos are broken down so that data is accessible throughout a project and asset lifecycle.

Examples of BIM include:

Contractors installing the traffic signal assets/infrastructure can be required to submit information about the installed (as-built or as-rehabilitated) assets in a prescribed format (typically a spatial data file with relevant attributes). These are referred to as “Employer Information Requirements” (EIR) in the BIM world and can be set up as a legal/contractual requirement. The data requirements can vary depending on the type of signal work (new installation, modification, rehabilitation, component replacement, in-house maintenance). In addition to contractors, the requirements can also be established for in-house maintenance crew.
Tools such as mobile apps for traffic signal data collection can be deployed for meeting the EIR requirements at each stage of the lifecycle, especially when contractors or maintenance crews are changing any aspect of the installed infrastructure.
Requirements used to build the computer-aided design (CAD)/BIM data model created with CAD or BIM standards during the design phase. To meet the EIRs, the as-designed models can be updated after construction to create the asset as-builts. Across the various design stages, construction and operation/maintenance stages—interoperability or exchange of these data models would ensure that information is constantly added to create and update the data model. In fact, information about the timing and cost of the installations for each asset should be captured in the model. Software systems used during design, construction and operation/maintenance phases should be able to accept models in open standards.
Policies and processes should be in place to ensure that employees understand what data needs to be captured when and how.

Key Actions

Agencies can adopt or improve upon several key actions when working toward maximizing performance through lifecycle planning for traffic signals.

Understand the Outcome from Alternative Maintenance Management Approaches

Understand the outcomes of different maintenance management approaches to be able to demonstrate cost effective practices and inform investment strategy decisionmaking.

Key Steps:

Understand the available maintenance management approaches (condition-based, interval-based, reactive) for each asset/component.
Assess the lifecycle cost of different maintenance management approaches.
Consider the risk that obsolescence introduces to different approaches.
Use analysis to inform investment decisions (see subsequent section).
Implement and continually revisit the selected management approaches. Consider how detailed asset information (e.g., age, condition, cost) may help influence lifecycle planning decisions and consider changes to asset inventory collection if appropriate.

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