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Approaches to Target Setting for PM3 MeasuresChapter 3. Challenges of Target SettingThis section will discuss some of the challenges that agencies often face when attempting to set targets. Target setting challenges are divided into two categories: technical and other challenges. Technical challenges are focused on the analytical aspects of setting targets such as measuring baseline performance and forecasting future performance. Other challenges are those that involve overcoming financial, organizational, and other challenges to setting targets. There are three technical methods that agencies can use in target setting. This section identifies the issues associated with them and in later sections demonstrate how they may be used by agencies. Technical ChallengesInconsistent Historical DataA major issue is establishing past trends is the existence of two different versions of the National Performance Management Research Data Set (NPMRDS) data. The NPMRDS is a National data set of average travel times on the National Highway System that was acquired by the FHWA for use in its performance measures and management activities. This data set also is available to State DOTs and MPOs to use for their performance management activities. FHWA acquired the first version of the NPMRDS data set for 2014, 2015, and 2016 using travel time data from the private vendor HERE. The second version of the NPMRDS data set was acquired for 2017 onwards using travel time data from the private vendor INRIX. This change in vendors for acquiring the NPMRDS data set in 2017 directly impacts the results for performance measures. Version one of the NPMRDS used point speeds, whereas version 2 adds path processing to improve the accuracy of the data. The results observed nationwide indicate that the performance of non-Interstate NHS vastly improved in 2017 compared to previous years. This can be attributed in part to the differences in data sources between version 1 and version 2 of the NPMRDS. Technical Method 1: Extrapolation of Past TrendsThe extrapolation of past trends is a commonly used method by State DOTs and local agencies because it is simple to implement. However, a major issue in establishing past trends is the limited data available for the agencies to use. The NPMRDS data is available to the agencies for only four years, and version 2, which is supplied by a different vendor than version 1, began in 2017. The results of measure calculations with version 2 have proved to be different than those developed with version 1, especially for non-Interstates. If only version 2 is used, projecting future performance based on past conditions creates huge challenges and errors when using such a limited data set, until sufficient data are accumulated under version 2 and future versions. However, a method exists for combining two travel time datasets that have been processed differently. Instead of using absolute numbers, the annual rate of change in a performance measure can be tracked using the older dataset and applied to measures developed with the newer dataset. The example presented later for the North Carolina Department of Transportation’s (NCDOT) target setting uses this approach. Regardless of the travel time dataset used, tracking trends—as well as any forecasts—for the factors influencing congestion and reliability should also be accomplished. Chief among these factors is how vehicle-miles traveled (VMT) has changed over time, and how it is expected to change in the future. Economic conditions can also be tracked, but even though these are likely to be strongly correlated with VMT, the lag between economic variables and VMT should be noted. Additionally, the agency should also consider internal factors that might affect congestion and reliability going forward. Historic and expected investments—or at least funding levels—for projects related to new physical capacity, transportation systems management and operations (TSMO), transit, and demand management should also be tracked and used to inform target setting. Technical Method 2: Identifying Vulnerable Portions of the NetworkOften, there are reporting segments on an agency’s transportation network that are “vulnerable” to failing to meet performance thresholds. For example, an Interstate reporting segment with a level of travel time reliability (LOTTR) of 1.49 meets the 1.50 threshold, but just barely. Similarly, the reporting segments with an LOTTR of 1.51 do not meet the 1.50 threshold. Because the definition of reliability depends on LOTTR metrics for four time periods, it is also useful to know how many of the time periods are vulnerable. These reporting segments that are “on the cusp” may be viewed as vulnerable links for the next performance period. Identifying these vulnerable portions of the network and accounting for them in target setting is a challenge for State DOTs and local agencies as it involves analysis techniques not commonly found in commercial tools. As with trend extrapolation, the agencies should consider and analyze VMT trends on the vulnerable segments, as well as if any capacity or operational improvement projects are being planned and take those into consideration while setting targets. Technical Method 3: Forecasting PerformanceAs opposed to the previous methods identified, forecasting performance represents a mid to long-term challenge that State DOTs and local agencies must confront in order to transition from a performance measurement to a performance management approach. While most travel demand models have been developed to forecast performance measures such as volume-to-capacity and vehicle-hours traveled, models to forecast travel time reliability are not yet in widespread use. A potential approach for forecasting mid and long-range reliability performance measures is to adapt the reliability forecasting methods and tools developed under the Strategic Highway Research Program 2 (SHRP 2), as listed below. While these tools were not explicitly designed to support target setting, they can be adapted for that use. Basically, these tools and methods can be used in the same way that average or typical conditions are forecasted with traditional tools, with the output now being reliability measures. A limitation of these tools and methods is that they were developed prior to the creation of the Third Performance Measure Rule (PM3) measures, so modification to the methods to produce them would be necessary.
For further information on forecasting approaches for target setting, please refer to FHWA-HOP-21-014, Approaches to Forecasting the PM3 Measures for Target Setting. Performance Management HorizonRelated to the challenge of forecasting performance, State DOTs and MPOs also must consider the relatively short performance management horizons (2 and 4 years) in conjunction with the timeline for project delivery. While transportation operational investments can be implemented more rapidly, transportation infrastructure investments take considerable time to identify, program, design, and construct—often longer than 2 to 4 years depending on the size and scope of the project. Thus, a challenge that agencies will face is ensuring that their desired targets and the timeline for achieving those targets are aligned with the timelines for delivering projects that advance performance to meet those specific target levels. Targets for the PM3 measures, as specified in the Final Rule, are relatively short term in nature (two-and four-year horizons). However, as the Response to Comments section of the PM3 Final Rule states:15
The FHWA strongly recommends that State DOTs and MPOs consider longer time horizons, which look beyond 4 years (i.e., multiple performance periods), for planning and programming of projects, so identification and selection of those projects is guided by the longer-term performance expectations. Therefore, it is critical that agencies consider their long-range performance targets when setting the 2- and 4-year targets.16 Operational improvement projects have been known to improve reliability, reduce delay, and potentially reduce emissions. However, the resulting improvements in performance are hard to quantify consistently for varying operational improvements and is usually dependent on the local conditions and the specific nature of the improvement being implemented. This adds to the challenges faced by agencies while aligning improvement projects that advance performance to meet those specific target levels. Other ChallengesFinancial ResourcesTargets will be affected by the financial resources that are available to an agency to improve the transportation system’s performance. For example, a region may have identified a corridor for a capacity expansion or transit investment to relieve congestion, but lacks the funds needed to make that investment—thus affecting its ability to improve performance and meet targets. Uncertainty in future funding levels and the scarcity of financial resources are enormous challenges in forecasting performance and thus setting targets. Conflicting Stakeholder PerspectivesIn addition to funding-related challenges, agencies also may face other challenges to improving performance and thus setting and meeting targets. For example, one group of stakeholders may desire greater transit investments as a method of relieving congestion while another group prefers a capacity expansion. Reconciling these differences are important for State DOTs and MPOs in their target setting approaches. 14 Highway Capacity Manual, Sixth Edition: A Guide for Multimodal Mobility Analysis, Transportation Research Board, 2021. [Return to note 14] 15 23 CFR 490. [Return to note 15] 16 82 FR 5970, 5989 (Jan. 18, 2017). [Return to note 16] |
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United States Department of Transportation - Federal Highway Administration |
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