Resource Allocation Logic Framework to Meet Highway Asset Preservation (2012)

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44 C h a p t e r 6 After formulating the mathematical model for the resource allocation problem, the research team developed a tool to derive solutions using the logic model. The tool demonstrates the capa- bilities of the logic model, based on plausible assumptions and examples of data sets and input decisions in a hypothetical state DOT setting. The data sets, inputs, and decisions are based on actual case experience, scaled for clarity and simplicity in the demonstration. The Excel-based solution model and optimization approach is grounded on plausible asset inventories, average AAG performance/condition ratings, average AAG deterioration rates, and average AAG unit costs. The model is intended to provide a basis for testing the concept and for building a simple logic-based system, expanded to encompass a full asset inventory if desired. It can be easily adapted for whatever district/jurisdictional structure exists in the enterprise. 6.1 Logic Process The particular solution derived and described in this report is a computational process that can provide multiple input-output examples. Many process variations and outputs can be demonstrated—using varied assumptions, inputs, and priority and ranking approaches. The impact of policy guidelines, constraints on funding, performance/condition targets, and time- line goals can be seen and assessed easily. The many variations and output effects of adjusting inputs, assumptions, and priorities can be demonstrated in real time in working sessions using the Excel model that has been developed. The logic framework and computational model is described in this section based on one static input-output example. The team has provided summary tables from several alternative cases in Section 6.4. While the framework can be expanded to full-scale use, the example herein addresses a subset of asset types and districts—sufficient to demonstrate a range of quantities, priorities, preservation needs, and overall impact on total allocation. 6.2 Logic Framework and Demonstration Model The logic framework is structured to operate on specific AAGs for which inventories and performance/condition ratings can be reasonably determined and understood—and on basic jurisdictions (e.g., districts) within a state highway management enterprise. Inventories, performance/condition factors, computations, and results can be rolled up to AAG totals and to statewide results. Resource Allocation Logic Framework

resource allocation Logic Framework 45 The logic framework involves the following major components: • Adjustable Strategic Inputs. These are determined by policies, program objectives, overall performance/condition expectations, best practices, and available resources and constraints. • Data and Estimate Inputs. These reflect AAG inventory, actual performance/condition rat- ings, average unit cost experience, and jurisdictional or statewide asset deterioration factors. • Outputs/Results. These include unconstrained13 need, total annual allocation need, based on performance/condition targets and expected deterioration, funds availability-adjusted alloca- tions, and achievable improvement timelines to reach target ratings after funds availability adjustments. The output also shows the predicted performance/condition rating that can be achieved at the end of the allocation cycle (annual, in the example). • Computational Functions. This includes calculation of optimal results based on strategic input adjustments and on assessment of the sensitivities of various estimates and assumptions underlying the data inputs. Figure 6-1 is a high-level view of the Excel model for demonstration of the logic framework. In this figure and in subsequent figures in the report, user input cells are displayed with light gray shading, and cells containing computation results are shown in darker gray shading. In the companion demonstration model available on the NCHRP Project 14-21 web page at www.trb. org, the user input cells are shaded yellow and the computation results are shaded blue. It is important to note that the model was developed to demonstrate the full logic framework, but it is not intended to be prescriptive. Some key observations follow about the demonstration model presented in this report: 1. The allocation solution is primarily designed to address situations where (a) available pres- ervation funding is less than estimated or computed overall preservation needs and (b) asset performance or condition ratings for specific AAGs are below desired targets. Where the opposite is the case, we assume the allocation challenge is met by simply estimating the pres- ervation needs for each asset group and jurisdiction and funding the need—or possibly by re-assessing the rating targets and priorities for a more aggressive preservation program. 2. The allocation solution and model are not intended to have granularity below the District/ AAG level; rather the solution is intended to provide a logical total preservation funding Figure 6-1. Resource allocation model—an overview. 13 Total resources needed to restore the units of an AAG to ideal performance/condition rating (i.e., the rating of units at completion of preservation projects). This can be considered as-new or nearly as-new, depending on the standards set by the agency for preservation work.

46 resource allocation Logic Framework for highway asset preservation envelope for an AAG within a jurisdiction—either district or state. Neither selection of spe- cific projects nor preservation tactics are intended to derive from this logic model. These are considered technical decisions within the work planning process. The model gives emphasis to the computed total annual preservation needs of AAGs in each district based on inven- tory, existing shortfall to targeted performance/condition ratings, deterioration rates, unit costs, and desired timelines to achieve target ratings. In fact, annual preservation needs can be estimated and determined in many different ways and for different time periods, yet the basic optimization approach can still be applied. 3. The reader will see that the example model uses a hypothetical prioritization and ranking approach to modulate the limits to which allocations can be adjusted for each AAG and to solve for the optimum adjustments by (a) balancing the ratio of allocated amount versus expected deterioration for each asset type or (b) minimizing the impact on the desired time- line to achieve target ratings for each AAG. While these appear to be logical bases for adjust- ment, other logic can easily be built in and applied. 4. There are solution options for users to treat specific AAGs that lack key data or estimates to compute and optimize allocation needs in the way intended by the framework. These will pro- duce reasonable approximations of need and may suffice if the investment is relatively small. Users will also be able to experiment with reasonable estimates of the data and factors needed for those AAGs and determine that approximations are sufficient for allocation purposes. 5. The predicted end-of-cycle performance/condition rating results for each AAG (after funds- available adjustments), when compared with desired targets, is useful to assess the effects of funding shortfalls on preservation of the road network. This will help to calibrate stakeholder expectations and high-level decisionmaking on funding in subsequent cycles. The objective of the allocation model is to assist in allocation of needed and appropriate pres- ervation funding resources for each asset type and for each responsible district or jurisdiction. Planning, selection, and execution of specific preservation projects are subsequent activities performed by central or district authorities based on the allocations approved. The allocation model is not a work-planning or project-selection tool. 6.2.1 Basic Assumptions and Definitions for the Illustrative Allocation Model The basic assumptions and definitions for the example Resource Allocation case are laid out in the Excel workbook for ready reference and shown in Table 6-1. The definitions and 1 2 3 4 5 6 7 The Resource Allocation Logic Framework should be Run by clicking the "Run Model" button in the Run Model Worksheet. The Final Result can be exported to a new workbook by clicking the "Export Results" button The Resource Allocation Logic Framework can be used to allocate the available Preservation and Maintenance funds across different user defined Asset Activity-IDs The user can choose to allocate the resources for Non Bridge/Pavement assets as a percentage of funds allocated for Pavement Asset IDs Up to 15 Districts and 15 Asset Activity-IDs can be set by the user For full application of the Resource Allocation Logic Framework, the following data elements are needed for each of the Asset-Activity ID specified: (1) Asset Inventory Data (2) Condition Data (3) Deterioration Rates (4) Unit Costs (5) Historical Expenditures. Linear Optimization Program is used to allocate the resources to different asset types to minimize the deviation between the expected time to achieve rating and the desired time. The user can set policy objectives by setting relative weights/ranks for each asset type or the desired time to target rating For Region-wide Allocation, the user should treat the entire region as a "Single" District and provide the data inputs The user can identify which of the five data elements identified above are available. If either the Inventory, Condition Data, Deterioration Rates or Unit Costs are not input for a particular Asset-Activity ID, the allocation for the particular asset is determined by prorating historical allocations and cost escalation factors Table 6-1. Resource allocation case assumptions.

resource allocation Logic Framework 47 assumptions of the case inputs, computations, and output results are described in subsequent sections. The basic flow of the computational operations in the model can easily be followed, as users progress through the input tabs and computation tables and summaries. The basic flow of the computations is shown in Figure 6-2. The Excel demonstration model workbook incorporates multiple tabs as follows: Tab 1: 1-Resource Allocation Logic Framework (Introduction Page) Tab 2: 2-Overview Tab 3: 3-Basic Inputs Tab 4: 4-Strategy Inputs Tab 5: 5-Data Inputs Tab 6: 6-Needs Estimation Tab 7: 7-Run Model Tab 8: 8-Calculations Tabs 3, 4, and 5 contain the input and control operations; the rest of the tabs are information, displays of intermediate computations, and results. The results are displayed on Tab 7, which also contains the Run Solver and Export Data buttons. 6.2.2 Context and Inputs for the Illustrative Allocation Case The first step in using the Resource Allocation Logic Framework is to define the AAGs, units of measure, and availability of data or estimates needed for each AAG. The user can specifically identify if the following data elements are available for each AAG: • Asset Inventory Data • Condition Rating Data • Deterioration Rate • Unit Cost Data. Table 6-2 shows sample inputs for AAIDs, units of measure, and data/estimate availability. 1 2 3 4 5 6 7 The Resource Allocation Logic Framework should be Run by clicking the "Run Model" button in the Run Model Worksheet. The Final Result can be exported to a new workbook by clicking the "Export Results" button The Resource Allocation Logic Framework can be used to allocate the available Preservation and Maintenance funds across different user defined Asset Activity-IDs The user can choose to allocate the resources for Non Bridge/Pavement assets as a percentage of funds allocated for Pavement Asset IDs Up to 15 Districts and 15 Asset Activity-IDs can be set by the user For full application of the Resource Allocation Logic Framework, the following data elements are needed for each of the Asset-Activity ID specified: (1) Asset Inventory Data (2) Condition Data (3) Deterioration Rates (4) Unit Costs (5) Historical Expenditures. Linear Optimization Program is used to allocate the resources to different asset types to minimize the deviation between the expected time to achieve rating and the desired time. The user can set policy objectives by setting relative weights/ranks for each asset type or the desired time to target rating For Region-wide Allocation, the user should treat the entire region as a "Single" District and provide the data inputs The user can identify which of the five data elements identified above are available. If either the Inventory, Condition Data, Deterioration Rates or Unit Costs are not input for a particular Asset-Activity ID, the allocation for the particular asset is determined by prorating historical allocations and cost escalation factors Compute Total Annual Preservation Needs by AAG and by District Prorate Available Amounts to AAGs in Proportion to Needs Determine Total Preservation Funds to Allocate Optimize the Adjustments to Needs for Each AAG Compute Reductions or Adds (Delta) Made for Each AAG Compute Achievable Timelines to Target Ratings Allocate Optimized AAG Amounts to Districts Total Program Less: Constraints Mandates Commitments Priorities and Ranks: Program Objectives Needs Ratios Basic Logic Flow FIgure 6-2. Resource allocation model—logic flow.

48 resource allocation Logic Framework for highway asset preservation 6.2.3 Funding Constraint Inputs The key assumption here is that NSDOT14 has determined a total funding amount available for the entire Preservation Program (i.e., distinct from Maintenance, Expansion, Traffic), and that external constraints on the use of the funds can be quantified and summed up, including such items as pre-committed major projects, specific statewide campaigns, and major one-off projects. The research team recognizes that the amount of available funds can be a “moving target” as resource allocations are adjusted between programs and as revenue projections fluc- tuate. The allocation model will permit immediate recalculation of optimal allocations as such changes occur. The initial input for the NSDOT example case is shown in Table 6-3. For this example, the $66 million constraint reflects several hypothetical major projects in process that carry multiyear funding commitments, including this year: a $43 million bridge replacement/rehabilitation, two major repaving projects totaling $18 million, and a $5 million drainage ditch reconstruct campaign. These are assumed to span two districts in the example. 6.2.4 Allocation Method By default, the Resource Allocation Logic Framework assumes that the input data elements are available to apply a needs-based allocation process. However, in situations where some data elements (see Table 6-2) may not be available, or in situations where the agency routinely allo- cates funds for NBP AAGs as a percentage of pavement AAGs, the user has an option to allocate resources for some assets by setting the Use Percent Allocation for Some Assets flag to Yes, as shown in Table 6-4. The user can also set the relative rank of AAGs, by setting the Use Relative AAG Ranks flag to Yes. This establishes a scale of user-predefined limits on the extent of the adjustment that can be made to preservation needs of each AAG. 14 New State DOT, the case agency name used for the Excel model. Asset - Activity Group (AAG) Units of Measure Inventory Condition Rating Deterioration Rate Unit Cost Bridges Bridge Decks Yes Yes Yes Yes Pavements Lane Miles Yes Yes Yes Yes Signs # of Signs Yes Yes Yes Yes Highway Lighting # of Lights Yes Yes Yes Yes Guardrail Miles of Guardrail Yes Yes Yes Yes Weigh Stations # of Stations Yes Yes Yes Yes - - - - - - - - - - - - - - - - - - Are Data or Reasonable Estimates Available for the Solution Framework? (See note below table) NOTE: If any of the four data elements is not available for an AAG, the preservation needs for that particular AAG will be estimated based on (a) historical expenditures and escalation or (b) as a user-set percentage of the preservation needs of another AAG, such as pavements. Table 6-2. AAGs, units of measure, and data/estimate availability (Tab. 3-1).

resource allocation Logic Framework 49 6.2.5 Strategic Inputs After setting the Allocation Method, the next step is to set the strategic inputs for allocating resources by each AAID. Table 6-5 shows the different input values to be provided by the user. The table receives important strategic inputs from the users of the allocation framework. These have significant effects on allocation outcomes, and equally important, they strongly affect the resulting predicted performance of AAGs at the end of the allocation cycle. Users can experiment with variations on these inputs to determine their leverage on outcomes. The inputs are as follows: • Ideal Rating. This represents the rating of a single inventory unit of an AAG that has been restored to new or as-new performance, presumably at completion of a preservation project. This rating, when considered hypothetically in comparison with the actual average ratings of an AAG, allows determination of total unconstrained preservation need for the AAG. The unconstrained need is typically a very large number that has little absolute meaning by itself, but it is of value in consid- ering cycle-to-cycle preservation strategies. When compared with unconstrained need calculated the same way from prior years, decisionmakers can assess whether overall AAGs are gaining or losing in health and performance. Over time, this information can be correlated with preserva- tion investments being made as a valuable guide for funding decisions going forward. • Target Rating. This indicates the average performance/condition rating of an AAG that the agency is committed to achieve. Combined with the average current rating of an AAG, unit costs, and inventory population, this drives the amount of investment needed to advance to the desired performance/condition level. When added to the investment needed to offset normal deterioration of an AAG inventory, this can represent a large preservation need, and in most cases, AAGs cannot achieve sufficient performance gains in a single cycle to meet such targets. This leads us to the next input. Table 6-3. Preservation and maintenance funds availability data (Tab. 4-1). Table 6-4. Allocation method and ranking (Tab. 4-2). Table 6-5. Strategic inputs for allocating preservation resources (Tab. 4-3). $281,000,000 $66,000,000 $215,000,000 Preservation funds to be allocated Total Preservation funds Adjustments for directed programs No Yes Use Relative AAG Ranks Use Percent Allocation for Some AAGs Asset - Activity Group (AAG) Units of Measure Ideal Rating Target Rating Time (Years) for Target Rating Relative AAG Rank Needs based Allocation % Allocation Basis Allocation Percentage Escalation in Expenditure** Bridges Bridge Decks 100% 80% 2 2 Yes No 10% 5% Pavements Lane Miles 100% 80% 2 1 Yes Yes 10% 5% Signs # of Signs 100% 100% 8 4 Yes No 2.5% 5% Highway Lighting # of Lights 100% 85% 4 6 Yes No 2.5% 5% Guardrail Miles of Guardrail 100% 80% 4 2 Yes No 2.5% 5% Weigh Stations # of Stations 100% 80% 4 5 Yes No 2.5% 5% - - - - - - * Used only when Percent Based Allocation Flag is set as "Yes" ** Used when Inventory, Condition, Deterioration Rate or Unit Cost data are not available

50 resource allocation Logic Framework for highway asset preservation • Target Time (in Years or Cycles) to Reach Target Rating. This value indicates the desired number of allocation cycles (years, in this case) to reach the targeted rating for an AAG, assuming that current average ratings are below the targets. This has a couple of functions in the model. First, the time target divides the “performance improvement” portion of the preservation need into a cycle-by-cycle amount. Second, it is an indicator of the strategic priority (or level of urgency) vested in each AAG by the user. And third, it forms the basis for an objective function that moderates funding-driven adjustments to each AAG, so that the difference can be minimized between the desired timelines and the timelines after adjustment. • Relative AAG Rank. This is a user input that can be 1-2-3-4-5-etc. or 1-1-2-3-4-4-etc. Com- bined with the “deviation limit” in Table 6-6, this ranking reflects the extent to which the user will allow each AAG to be “hit” by negative adjustments to preservation needs due to funding limits. It is another way that strategic inputs can influence the overall optimization. • Needs-Based Allocation. This column is set to identify the AAGs for which the allocation will be a needs-based computation. Note that the Data Availability flag described in Table 6-2 is set to Yes for the particular AAG if the Needs-Based Allocation flag is set to Yes. If an AAG is set to No in this column, the allocation needs will be computed as a ratio with respect to the AAG(s) flagged with Yes in the next column. • % Allocation Basis. This column designates the AAG or AAGs (example, pavement) that will provide the basis for percentage-based allocations, as preservation needs for the designated basis AAGs are determined. • Allocation Percentage. The user sets the percentage of the basis AAG to apply wherever needs-based allocation is set to No. • Escalation in Expenditure. If data is not available for the specific AAG, and percentage alloca- tion is not selected, the allocation is made based on historical expenditure for that AAG, plus the cost escalation factor entered in this column. 6.2.6 Setting Ranks Table 6-6 requires user inputs to modulate the optimization routine. The values will be used only if the Use Relative Asset/Activity Ranks flag is set to Yes. The user-set deviation limit is linked to the AAG ranking, as shown in the previous example. The deviation addressed here is the deviation from the adjustments made for each AAG when calculated preservation need is adjusted to match funding limits. For example, if an across- the-board adjustment of minus 10 percent is made due to funding limitations, that adjustment Relative AAG Rank Deviation Limit* 1 100% 2 110% 3 120% 4 130% 5 140% 6 150% 7 14 15 * Allowed Deviation from Pro - rata allocation adjustment Table 6-6. AAG rank and deviation limits (Tab. 4-4).

resource allocation Logic Framework 51 amount will float for each AAG, as the allocation is optimized for best overall performance gain. This table limits the adjustment “float” for the number 1-ranked AAG to a greater extent than for the number 6-ranked AAG. So the lower-ranked AAG is subject to a greater “hit” in some cases (though not every case), depending on how big the funding adjustment is and how much performance gain was targeted for that AAG. Users can experiment with these factors. The research team found the ranks and deviation limits do not have major impact except in extreme funding shortfall cases. 6.2.7 Foundational Data Inputs Upon setting the strategic inputs, the user needs to provide the AAG inventory, condi- tion, unit costs, and other essential data items. Given inventory data, and having determined strategic program objectives and the key standards, ratings, and timeline targets for perfor- mance, other essential data inputs are necessary to determine preservation needs including the following: • AAG Inventory Data. These are the AAG quantities in user-specified units of measure. • Current AAG Ratings. This is the average performance/condition rating of each AAG. • AAG Unit Costs. This is the average cost of restoring a single unit of an AAG to the ideal rating (completed preservation project). • AAG Deterioration Rate. This is the estimated percentage of assets of an asset type or group that is expected to deteriorate below an acceptable level of performance or safety during each cycle. • Historical Expenditure Data. This is the aggregated preservation expenditure for each AAG in prior periods. All of these performance factors can be measured, computed, or reasonably estimated15 for the purpose of the model—based on historical data, sample study, engineering analysis, or (if applied across the board) by professional opinion and consensus. The example inputs (current situation) for the NSDOT illustrative case are shown in Tables 6-7 through 6-11: The average unit cost estimates are based on analyses of known state DOT preservation program costs as well as fact sheets and a number of periodic DOT reports found in our data research—this data is scaled and adjusted for the example NSDOT case. Because of the relative size of the bridge and pavement allocations in typical preservation programs and because the nature of these two 15 Again, the inputs need not be highly precise, as long as they are reasonably sound estimates, consistently done and applied. The allocation model ultimately leads to an adjustment for available funding; reasonable allocation is the object, not estima- tion and commitment of funds for projects. Table 6-7. AAG inventory data (Tab. 5-1). Asset-Ac�vity Group (AAG) Units of Measure Total District 1 District 2 District 3 District 4 District 5 District 6 District 7 District 8 District 9 District 10 Bridges Bridge Decks 3,500 1,475 885 1,140 Pavements Lane Miles 20,750 8,190 5,850 6,710 Signs # of Signs 38,100 13,900 11,900 12,300 Highway Ligh�ng # of Lights 273,050 176,500 56,750 39,800 Guardrail Miles of Guardrail 36,580 16,380 8,590 11,610 Weigh Sta�ons # of Sta�ons 113 48 31 34 - - - - - - 216,493 84,006 71,594TOTAL Regions

52 resource allocation Logic Framework for highway asset preservation Asset-Ac�vity Group (AAG) Units of Measure Average District 1 District 2 District 3 District 4 District 5 District 6 District 7 District 8 District 9 District 10 Bridges Bridge Decks 77.2% 77.2% 76.2% 78.0% Pavements Lane Miles 75.9% 76.1% 75.8% 75.6% Signs # of Signs 92.6% 92.1% 92.9% 92.8% Highway Ligh�ng # of Lights 82.8% 83.0% 82.5% 82.0% Guardrail Miles of Guardrail 75.7% 75.0% 76.0% 76.5% Weigh Sta�ons # of Sta�ons 77.7% 78.0% 76.5% 78.5% - - - - - - - - - Regions Table 6-8. AAG current condition data (Tab. 5-2). Table 6-9. AAG unit cost data (Tab. 5-3). Table 6-10. AAG deterioration rates data (Tab. 5-4). Asset - Activity Group (AAG) Description Average District 1 District 2 District 3 District 4 District 5 District 6 District 7 District 8 District 9 District 10 Bridges Estimated average cost to improve typical bridge structure to meet Ideal standard 1,100,000 1,100,000 1,100,000 1,100,000 Pavements Estimated average cost to improve typical lane mile to meet Ideal standard 120,000 120,000 120,000 120,000 Signs Estimated average cost to improve typical sign to meet Ideal standard 2,000 2,000 2,000 2,000 Highway Lighting Estimated average cost to improve Highway Lighting to meet Ideal standard 250 250 250 250 Guardrail Estimated average cost to improve typical guardrail to meet Ideal standard 1,000 1,000 1,000 1,000 Weigh Stations Estimated average cost to improve typical weigh station to meet Ideal standard 50,000 50,000 50,000 50,000 - - - - - - Regions Asset-Ac�vity Group (AAG) Units of Measure Average District 1 District 2 District 3 District 4 District 5 District 6 District 7 District 8 District 9 District 10 Bridges Bridge Decks 1.5% 1.5% 1.5% 1.5% Pavements Lane Miles 5.0% 5.0% 5.0% 5.0% Signs # of Signs 10.0% 10.0% 10.0% 10.0% Highway Ligh�ng # of Lights 4.0% 4.0% 4.0% 4.0% Guardrail Miles of Guardrail 3.0% 3.0% 3.0% 3.0% Weigh Sta�ons # of Sta�ons 2.0% 2.0% 2.0% 2.0% - - - - - - - - - Regions

resource allocation Logic Framework 53 activities is very different from each other, the research team focused most heavily on realistic estimation of average unit costs and deterioration rates for these two asset groups: • Pavements. Numerous pavement deterioration studies gravitate around 18- to 20-year cycles for major overlay/repaving events, with average costs as low as $100,000 per lane mile; how- ever, costs can run in excess of $130,000 per lane mile, depending on the maintenance regi- men in effect. The research team assumed a typical routine maintenance program, with a 20-year cycle, suggesting a deterioration rate of about 5 percent on average. This means that preservation allocations would need to cover at least 5 percent of the inventory each year. • Bridges. Two state DOTs for which we found information appear to address about 1.5 percent of their bridge inventory with significant preservation projects each year. These include such projects as painting, deck rehabilitation, structural reinforcement, scour mitigation, and gen- eral rehabilitation of smaller bridge structures. These project costs appear to range between $500,000 and $1.6 million. Larger rehabilitation/replacement projects on major spans range up to $200 million and well beyond, in some cases. We assumed the major bridge replace- ment/rehabilitation projects on larger bridges would be treated as separate (usually multi- year commitments), and we treated them as commitments that are constraints to determine annual regular preservation funding to be allocated. Similar estimating can be done for other AAGs, based primarily on historical records of pres- ervation work done and costs. If this data cannot be sampled for analysis, preservation project estimate data might provide a basis for judgment. The research team adapted the example inventory and expenditure data in proportion to real-world cases. 6.2.8 Computation of Preservation Needs The first step in the computation process is determination of preservation needs for each AAG. The Bridge AAG computation is used to illustrate this process, shown in Table 6-12. The table shows the input factors linked from prior tabs and contains the calculation results, assuming the desired timelines to reach target ratings. Allocation need calculations in the demonstration model are as follows: UnconstrainedNeed Inventory Ideal Rating= [ ]× [ ]−[ ]( )×[ ] = Current Rating Average Unit Cost Inventory Deterioration Rate Average U[ ]×[ ]× nit Cost[ ] Table 6-11. AAG historical expenditure data (Tab. 5-5). Asset-Ac�vity Group (AAG) Units of Measure Total District 1 District 2 District 3 District 4 District 5 District 6 District 7 District 8 District 9 District 10 Bridges Bridge Decks 67,998,000 29,854,000 16,889,000 21,255,000 Pavements Lane Miles 138,419,000 50,802,000 42,724,000 44,893,000 Signs # of Signs 4,395,333 1,627,900 1,348,833 1,418,600 Highway Ligh�ng # of Lights 1,595,000 447,500 587,500 560,000 Guardrail Miles of Guardrail 1,269,000 442,000 274,000 553,000 Weigh Sta�ons # of Sta�ons 195,000 45,000 20,000 130,000 - - - - - - - - - 213,871,333 83,218,400 61,843,333 68,809,600 Regions * Note that the Historical Expenditure Data entered here is is used to determine the percentage alloca�on for assets other than Bridge and Pavement assets if percentage based alloca�on is used TOTAL

54 resource allocation Logic Framework for highway asset preservation Total Needed for Target Rating Inventory= [ ]× Target Rating Current Rating Average [ ]−[ ]( ) × Unit Cost[ ] Annual Allocation Needed Average Annual Det= erioration Total Needed for Target Ratin[ ]+ g Desired Time for Target Rating [ ]( ) ÷[ ] Table 6-13 shows total and district-based allocation needs by AAGs. The result of Annual Allo- cation Needed computation for the assets in the model example is shown in the Total column. Asset-Ac�vity Group #1 Bridges District 1 District 2 District 3 Bridge Decks 3,500 1,475 885 1,140 Current Ra�ng - 77.2% 76.2% 78.0% Ideal Ra�ng - 100.0% 100.0% 100.0% Target Ra�ng - 80% 80% 80% Average Unit Cost $ - 1,100,000 1,100,000 1,100,000 Deteriora�on Rate - 1.5% 1.5% 1.5% Unconstrained Need 877,503,000 369,930,000 231,693,000 275,880,000 Ave. Annual Deteriora�on 57,750,000 24,337,500 14,602,500 18,810,000 Total needed for Target Ra�ng 107,503,000 45,430,000 36,993,000 25,080,000 Desired Time for Target Ra�ng (Years) - 2 2 2 Annual Alloca�on needed to meet target Ra�ngs and �melines 111,501,500 47,052,500 33,099,000 31,350,000 Funds needed to improve average current ra�ng by 1% 38,500,000 16,225,000 9,735,000 12,540,000 Total Districts Asset-Ac�vity Group (AAG) Total District 1 District 2 District 3 Bridges 111,501,500 47,052,500 33,099,000 31,350,000 Pavements 176,121,000 68,304,600 49,842,000 57,974,400 Signs 8,327,150 3,054,525 2,591,225 2,681,400 Highway Ligh�ng 3,114,422 1,985,625 656,172 472,625 Guardrail 1,489,638 696,150 343,600 449,888 Weigh Sta�ons 144,938 60,000 44,563 40,375 - 0 - - - - 0 - - - - 0 - - - 300,698,647 121,153,400 86,576,559 92,968,688 Alloca�on Needs based on Asset Inventory, Current Ra�ng, Target Ra�ng and Timelines Table 6-12. Calculation of needs. Table 6-13. Allocation needs using inventory, current rating, target rating, and timelines.

resource allocation Logic Framework 55 It can be seen that the sum of the Annual Allocation Needed is $300,698,654, which exceeds the total available funding of $215,000,000. This sets the stage for the optimization process (described in the next section), which operates in this model to adjust the individual proration up or down for each of the AAGs or an optimal solution. Before moving on to the optimization process, we note that the model can demonstrate at least three alternative approaches to narrow the gap between available funds and annual need. These can be applied individually or in combination to yield higher or lower annual needs for an AAG. The alternatives include the following: • Small downward adjustments in target rating have a significant reduction effect on annual needs. • Extending desired timelines to reach targets also lowers annual needs results. • Any reduction in unit costs, possibly based on specific changes in preservation tactics or methods, can reduce annual needs for the specific AAG involved. 6.2.9 Optimization In this sample optimization approach, we pursued the following strategy: • At the highest level, we sought to meet both annual needs and desired time for target rating as closely as possible for the assets, given funding constraints (shortfall to needs). • We moderated the effect of the funding shortfall on specific asset groups by determining lim- its on upward and downward adjustments based on weighting and ranking factors. • The weighting and ranking factors are influenced by several user inputs as well as ratios between costs to cover deterioration versus annual needs for each asset type. The summary of the case example optimization results is shown in Table 6-14 and Figures 6-3 and 6-4. Table 6-14. Summary allocation results (Tab. 7-1). Asset-Activity Group (AAG) Total District 1 District 2 District 3 District 4 District 5 District 6 District 7 District 8 District 9 Bridges 65,688,599 27,719,921 19,499,531 18,469,147 - - - - - - Pavements 137,039,134 53,147,570 38,781,886 45,109,678 - - - - - - Signs 8,035,405 2,947,509 2,500,441 2,587,456 - - - - - - Highway Lighting 2,924,593 1,864,598 616,177 443,818 - - - - - - Guardrail 1,190,236 556,231 274,540 359,465 - - - - - - Weigh Stations 122,033 50,518 37,520 33,994 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 215,000,000 86,286,347 61,710,095 67,003,558 - - - - - - Table 7-1: Summary results - Allocation of Preservation Funds (continued on next page)

56 resource allocation Logic Framework for highway asset preservation Desired Time Estimated Time Difference (Desired - Target) Average Historical Allocation Difference (Current - Historical) Total Allocation less Deterioration Need Target Rating Current Rating Expected Rating Result Bridges 2 14 12.0 67,998,000 (2,309,401) 7,938,599 80.00% 77.21% 77.41% Pavements 2 14 12.0 138,419,000 (1,379,866) 12,539,134 80.00% 75.85% 76.36% Signs 8 20 12.0 4,395,333 3,640,072 415,405 100.00% 92.58% 93.12% Highway Lighting 4 16 12.0 1,595,000 1,329,593 194,093 85.00% 82.75% 83.03% Guardrail 4 16 12.0 1,269,000 (78,764) 92,836 80.00% 75.71% 75.96% Weigh Stations 4 16 12.0 195,000 (72,967) 9,033 80.00% 77.74% 77.90% - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 213,871,333 1,128,667 21,189,100 Asset-Activity Group (AAG) Asset-Activity Group (AAG) Difference between Desired and Estimated Time to reach Target Rating Difference between Current and Historical Allocation Table 6-14. (Continued). 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% g n i t a R AAG Target Rating Current Rating Expected Rating Result Figure 6-3. Comparison of target rating, current rating, and expected rating result.

resource allocation Logic Framework 57 Step 2. In 4-Strategy Inputs tab, Table 4-2 (in the model), set the Use Percent Allocation for Some Assets to No. No Ye s Us e Re lati ve AA G Ra nk s Us e Perc en t Al lo ca tion fo r So me AAG s 6.3 Setup of Additional Case Examples This section provides examples of how to set up key parameters in the Excel model for dif- ferent case studies. Case Example 1: Allocate the total funds for the AAGs based on needs. Step 1. In the 3-Basic Inputs tab, Table 3-1 (in the model), set the Data Availability flags to Yes for the AAGs. Asse t Ac ti vi ty Gr ou p ( AAG ) Un it s of Me as ur e I nv en tory Condi ti on Ra ti ng De te ri or at io n Ra te Unit Cost Br id ge s Br id ge De ck s Y es Ye s Y es Ye s Pa ve me nt s La ne M ile s Y es Ye s Y es Ye s Si gn s # of Si gn s Y es Ye s Y es Ye s Hi ghwa y Li ghti ng # of Li gh ts Ye s Y es Ye s Y es Gu ar dr ai l M ile s of Gu ar dr ai l Y es Ye s Y es Ye s We ig h St at io ns # of St at io ns Ye s Y es Ye s Y es Ar e Da ta or Re as on ab le Es ti ma te s Ava ila bl e fo r th e Sol ut io n Fr am ew or k? Figure 6-4. Comparison of desired time and estimated time to reach target rating. 0 5 10 15 20 25 s r a e Y AAG Desired Time Estimated Time

58 resource allocation Logic Framework for highway asset preservation Step 3. In 5-Data Inputs tab, enter values in the five tables for ALL AAGs. Step 4. Run the optimization model by selecting the Run Model button in the 7-Run Model tab. Results will be seen in the 7-Run Model tab. Step 5. Press the Export Results button to save the output results in a new workbook. Save the new workbook for future reference (if needed). Case Example 2: Allocate the total funds based on needs for AAGs with data, but use his- torical expenditure information and escalation for AAGs with missing data. Step 1. In 3-Basic Inputs tab, Table 3-1 (in the model), set the Data Availability flags to Yes for the AAGs that need to be allocated using needs and set the data flag to No for assets that should be allocated based on historical expenditure and associated escalation rates. Setting No in any one of the four columns will allow historical data to be used for determining resources for the particular asset. In the example below, resources for highway lighting and weigh stations will be determined based on historical data, and the other allocations will be determined based on needs. Asse t Ac ti vi ty Gr ou p ( AAG ) Un it s of Me as ur e I nv en tory Condi ti on Ra ti ng De te ri or at io n Ra te Unit Cost Br id ge s Br id ge De ck s Y es Ye s Y es Ye s Pa ve me nt s La ne M ile s Y es Ye s Y es Ye s Si gn s # of Si gn s Y es Ye s Y es Ye s Hi ghwa y Li ghti ng # of Li gh ts Ye s N o Y es Ye s Gu ar dr ai l M ile s of Gu ar dr ai l Y es Ye s Y es Ye s We ig h St at io ns # of St at io ns Ye s Y es No Ye s Ar e Da ta or Re as on ab le Es ti ma te s Ava ila bl e fo r th e Sol ut io n Fr am ew or k? Step 2. In the 4-Strategy Inputs tab, Table 4-2 (in the model), set the Use Percent Allocation for Some Assets to No. Step 3. In the 4-Strategy Inputs tab, Table 4-3 (in the model), enter the escalation factor for the AAGs that do not have the necessary data (in this case, for Highway Lighting and Weigh Stations). Step 4. In the 5-Data Inputs tab, input values in the five tables for the assets for which a needs- based allocation is to be made. No Ye s Us e Re lati ve AA G Ra nk s Us e Perc en t Al lo ca tion fo r So me AAG s Asse t Ac ti vi ty Gr ou p (A AG ) Un it s of Me as ur e I de al Ra ti ng Targ et Ra ti ng Ti me (Y ea rs ) fo r Targ et Ra ti ng Re la ti ve AAG Ra nk N eed s ba se d A llo cati on % A llo ca ti on Ba si s A llo cati on Pe rc en ta ge Es ca la ti on in Ex pe ndi ture ** Br id ge s B ri dg e De ck s 100% 80% 2 2 Yes N o 10% 5% Pa ve me nt s L an e M ile s 100% 80% 2 1 Yes Y es 10% 5% Si gn s # of Si gn s 100% 100% 8 4 Yes N o 2.5% 5% Hi ghwa y Li ghti ng # of Li ghts 100% 85% 4 6 Yes N o 2.5% 5% Gu ar dr ai l M ile s of Gu ar dr ai l 100% 80% 4 2 Yes N o 2.5% 5% Weig h St at io ns # of St at io ns 100% 80% 4 5 Yes N o 2.5% 5% * Us ed onl y wh en Pe rc en t Ba se d Al lo ca ti on Fl ag is se t as "Y es " ** Us ed wh en In ve nt or y, C ond it io n, De te ri or at io n Ra te or Un it Cost dat a ar e no t av a il abl e

resource allocation Logic Framework 59 Step 5. Run the optimization model by selecting the Run Model button in the 7-Run Model tab. Results will be presented in the 7-Run Model tab. Step 6. Press the Export Results button to save the output results in a new workbook. Save the new workbook for future reference (if needed). Case Example 3: Allocate the funds based on needs for some AAGs and percentage-based for other AAGs. For example, use needs-based allocation for Bridges, Pavements, Highway Lighting, and Weigh Stations and use percentage-based allocation for Signs and Guardrail (based on percentage of Pavements allocation). Step 1. In the 3-Basic Inputs tab, Table 3-1 (in the model), set the Data Availability flags to Yes for the AAGs with needs to be allocated using needs (Bridge, Pavement, Highway Lighting, and Weigh Stations). As se t Ac ti vi ty Gr ou p ( AAG ) Un it s of Me as ur e I nv en tory Condi ti on Ra ti ng De te ri or at io n Ra te Un it Cost Br id ge s Br id ge De ck s Y es Ye s Y es Ye s Pa ve me nt s La ne M ile s Y es Ye s Y es Ye s Si gn s # of Si gn s N o N o N o N o Hi ghwa y Li ghti ng # of Li ghts Ye s Y es Ye s Y es Gu ar dr ai l M ile s of Gu ar dr ai l Y es No Ye s N o Weig h St at io ns # of St at io ns Ye s Y es Ye s Y es Ar e Da ta or Re as on ab le Es ti ma te s Ava ila bl e fo r th e So lu ti on Fr am ew or k? Step 2. In the 4-Strategy Inputs tab, Table 4-2 (in the model), set the Use Percent Allocation for Some Assets to Yes. Ye s Ye s Us e Re lati ve AAG Ra nk s Us e Perc en t A llo ca tion fo r So me AAG s Step 3. In the 4-Strategy Inputs tab, Table 4-3 (in the model), set the Needs-Based Allocation flag to Yes for Bridges, Pavements, Highway Lighting, and Weigh Stations and set the Needs- Based Allocation flag to No for Signs and Guardrail. Set the Percentage Allocation Basis flag to Yes for Pavements (to allocate as a percentage of Pavements), and input the allocation percent- age (as a percentage of Pavement funds) in the Allocation Percentage column. A sse t Ac ti vi ty Gr ou p (A AG ) Unit s of Me as ur e I de al Ra ti ng Targ et Ra ti ng Ti me (Yea rs ) fo r Ta rg et Ra ti ng Re la ti ve Asse t Acti vi ty Ra nk N eed s ba se d Al lo ca ti on % Al lo ca ti on Ba si s Al lo ca ti on Pe rc en tage Es ca la ti on in Ex pe ndi tu re ** Br id ge s B ri dg e De ck s 100% 80% 2 2 Ye s N o 10% 5% Pa ve me nt s L an e Mi le s 100% 80% 2 1 Ye s Y es 10% 5% Si gn s # of Si gn s 100% 100% 8 4 No No 2.5% 5% Hi ghwa y Li ghti ng # of Li ghts 100% 85% 4 6 Ye s N o 2.5% 5% Gu ar dr ai l M ile s of Gu ar dr ai l 100% 80% 4 2 No No 2.5% 5% We ig h Stat io ns # of Stat io ns 100% 80% 4 5 Ye s N o 2.5% 5%

60 resource allocation Logic Framework for highway asset preservation Step 4. In the 5-Data Inputs tab, input values in the five tables for the assets for which Needs- Based Allocation is to be made. Step 5. Run the optimization model by selecting the Run Model button in 7-Run Model tab. Results will be presented in the 7-Run Model tab. Step 6. Press the Export Results button to save the output results in a new workbook. Save the new workbook for future reference (if needed). 6.4 Results from Sample Runs 6.4.1 Scenario 1: Base Case (Fully Needs-Based Allocation) As se t Ac ti vi ty Gr ou p ( AAG ) To ta l D is tr ic t 1 D is tr ic t 2 D is tr ic t 3 D is tr ic t 4 D is tr ic t 5 D is tr ic t 6 D is tr ic t 7 D is tr ic t 8 D is tr ic t 9 Br id ge s 65 , 688 ,5 99 27 ,7 19 , 921 19 , 499 ,5 31 18 ,4 69 , 147 Pa ve me nt s 13 7, 039 ,1 34 53 ,1 47 , 570 38 , 781 ,8 86 45 ,1 09 , 678 Si gn s 8, 035 ,4 05 2, 94 7, 509 2, 500 ,4 41 2, 58 7, 456 Hi gh wa y Li gh ti ng 2, 924 ,5 93 1, 86 4, 598 616 ,1 77 44 3, 818 Gu ar dr ai l 1, 190 ,2 36 55 6, 231 274 ,5 40 35 9, 465 Weig h St at io ns 122 ,0 33 50 , 518 37 ,5 20 33 , 994 21 5, 000 ,0 00 86 ,2 86 , 347 61 , 710 ,0 95 67 ,0 03 , 558 De si re d Ti me Es ti mate d Ti me Di ff er en ce (D es ir ed Ta rg et ) Av er ag e Hi stor ic al Al lo ca ti on Di ff er en ce (C u rre nt Hi st or ic al ) To ta l Al lo ca ti on le ss De te ri or at io n N eed Targ et Ra ti ng Cu rre nt Ra ti ng Ex pe ct ed Ra ti ng Re su lt Br id ge s 2 14 12 .0 67 ,9 98 , 000 (2 ,3 09 ,4 01 ) 7, 93 8, 599 80 . 00% 77 .2 1% 77. 41 % Pa ve me nt s 2 14 12 .0 13 8, 41 9, 000 (1 ,3 79 ,8 66 ) 12 ,5 39 , 134 80 . 00% 75 .8 5% 76. 36 % Si gn s 8 20 12 .0 4, 39 5, 333 3, 640 ,0 72 41 5, 405 10 0. 00 % 9 2. 58 % 93. 12 % Hi gh wa y Li gh ti ng 4 16 12 .0 1, 59 5, 000 1, 329 ,5 93 19 4, 093 85 . 00% 82 .7 5% 83. 03 % Gu ar dr ai l 4 16 12 .0 1, 26 9, 000 (7 8, 76 4) 92 , 836 80 . 00% 75 .7 1% 75. 96 % Weig h Sta ti on s 4 16 12 .0 19 5, 000 (7 2, 96 7) 9, 033 80 . 00% 77 .7 4% 77. 90 % 21 3, 87 1, 333 1, 128 ,6 67 21 ,1 89 , 100 Tabl e 7 1: Su mm ar y re su lt s Al lo cati on of Pr es er va ti on Fu nd s As se t Ac ti vi ty Gr ou p ( AAG ) As se t Ac ti vi ty Gr ou p ( AAG ) Di ffe re nc e be tw ee n De si re d an d Es ti ma te d Ti me to re ac h Ta rg et Ra ti ng Di ffe re nc e be twee n Cu rr en t an d Hi st or ic al Al lo cati on Note : Th e Tota l Allocation less Deterioratio n Nee d column indicate s an excess amount over th e amoun t needed to cover deterioratio n costs. This is th e amount that is use d for ne t improvemen t in condition/performance rating.

resource allocation Logic Framework 61 6.4.2 Scenario 2: Constrained Case (Fully Needs-Based Allocation) This is the same as the base case, but the Adjustments to Directed Program in Tab 4-1 is increased to 91,000 from 66,000 (in base case). This results in a deficiency of funds as compared with the annual deterioration. As se t Ac ti vi ty Gr ou p ( AAG ) To ta l D is tr ic t 1 D is tr ic t 2 D is tr ic t 3 D is tr ic t 4 D is tr ic t 5 D is tr ic t 6 D is tr ic t 7 D is tr ic t 8 D is tr ic t 9 Br id ge s 56 , 614 ,4 63 23 ,8 90 , 728 16 , 805 ,8 91 15 ,9 17 , 843 Pa ve me nt s 12 2, 051 ,9 59 47 ,3 35 , 129 34 , 540 ,5 36 40 ,1 76 , 294 Si gn s 7, 470 ,1 68 2, 74 0, 171 2, 324 ,5 51 2, 40 5, 446 Hi gh wa y Li gh ti ng 2, 676 ,8 10 1, 70 6, 622 563 ,9 72 40 6, 216 Gu ar dr ai l 1, 075 ,8 22 50 2, 762 248 ,1 49 32 4, 910 Weig h St at io ns 110 ,7 78 45 , 859 34 ,0 60 30 , 859 19 0, 000 ,0 00 76 ,2 21 , 271 54 , 517 ,1 60 59 ,2 61 , 569 De si re d Ti me Es ti mate d Ti me Di ff er en ce (D es ir ed Ta rg et ) Av er ag e Hi stor ic al Al lo ca ti on Di ff er en ce (C u rre nt Hi st or ic al ) To ta l Al lo ca ti on le ss De te ri or at io n N eed Targ et Ra ti ng Cu rre nt Ra ti ng Ex pe ct ed Ra ti ng Re su lt Br id ge s 2 NA 67 ,9 98 , 000 (1 1, 3 83, 53 7) (1 ,1 35 ,5 37 ) 80 . 00% 77 .2 1% 77. 18 % Pa ve me nt s 2 NA 13 8, 41 9, 000 (1 6, 3 67, 04 1) (2 ,4 48 ,0 41 ) 80 . 00% 75 .8 5% 75. 76 % Si gn s 8 NA 4, 39 5, 333 3, 074 ,8 35 (1 49 , 832 ) 10 0. 00 % 9 2. 58 % 92. 38 % Hi gh wa y Li gh ti ng 4 NA 1, 59 5, 000 1, 081 ,8 10 (5 3, 69 0) 85 . 00% 82 .7 5% 82. 67 % Gu ar dr ai l 4 NA 1, 26 9, 000 (1 93 ,1 78 ) ( 21 ,5 78 ) 80 . 00% 75 .7 1% 75. 65 % Weig h St at io ns 4 NA 19 5, 000 (8 4, 22 2) (2 ,2 22 ) 80 . 00% 77 .7 4% 77. 70 % 21 3, 87 1, 333 (2 3, 8 71, 33 3) (3 ,8 10 ,9 00 ) Tabl e 7 1: Su mm ar y re su lt s Al lo cati on of Pr es er va ti on Fu nd s As se t Ac ti vi ty Gr ou p ( AAG ) As se t Ac ti vi ty Gr ou p ( AAG ) Di ffe re nc e be tw ee n De si re d an d Es ti ma te d Ti me to re ac h Ta rg et Ra ti ng Di ffe re nc e be twee n Cu rr en t an d Hi st or ic al Al lo cati on Note : Th e Tota l Allocation less Deterioratio n Nee d column indicate s an excess amount over th e amoun t needed to cover deterioratio n costs. This is th e amount that is use d for ne t improvemen t in condition/performance rating. Result Observation: This run demonstrates the impact of changing the total funds avail- able for preservation. As a result of increasing the Adjustments to Directed Program, the funds available for allocation reduce from $215 million in baseline to $190 million. As a result of the reduction, the total fund available for preservation is less than the total needs to cover deterio- ration costs (as indicated by negative numbers in the Total Allocation less Deterioration Need

62 resource allocation Logic Framework for highway asset preservation column). A value of NA (Not Applicable) in the Estimated Time columns indicates that with current funding levels, the target rating cannot be achieved. 6.4.3 Scenario 3: Percentage-Based Allocation This is the same as the base case, but it uses percentage-based allocation for Signs and Guard- rails. The allocation for Signs and Guardrail is based on a percentage of Pavements preservation funds. The allocation percentages are set by the user to be 2.5 percent. As se t Ac ti vi ty Gr ou p ( AAG ) To ta l D is tr ic t 1 D is tr ic t 2 D is tr ic t 3 D is tr ic t 4 D is tr ic t 5 D is tr ic t 6 D is tr ic t 7 D is tr ic t 8 D is tr ic t 9 Br id ge s 66 , 574 ,0 56 28 ,0 93 , 575 19 , 762 ,3 77 18 ,7 18 , 104 Pa ve me nt s 13 8, 437 ,8 60 53 ,6 90 , 035 39 , 177 ,7 23 45 ,5 70 , 102 Si gn s 3, 460 ,9 47 1, 26 9, 528 1, 076 ,9 70 1, 11 4, 449 Hi gh wa y Li gh ti ng 2, 943 ,2 89 1, 87 6, 518 620 ,1 16 44 6, 655 Gu ar dr ai l 3, 460 ,9 47 1, 61 7, 399 798 ,3 02 1, 04 5, 245 Weig h St at io ns 122 ,9 03 50 , 878 37 ,7 88 34 , 237 21 5, 000 ,0 00 86 ,5 97 , 932 61 , 473 ,2 77 66 ,9 28 , 791 De si re d Ti me Es ti mate d Ti me Di ff er en ce (D es ir ed Ta rg et ) Av er ag e Hi stor ic al Al lo ca ti on Di ff er en ce (C u rre nt Hi st or ic al ) To ta l Al lo ca ti on le ss De te ri or at io n N eed Targ et Ra ti ng Cu rre nt Ra ti ng Ex pe ct ed Ra ti ng Re su lt Br id ge s 2 13 10 .6 67 ,9 98 , 000 (1 ,4 23 ,9 44 ) 8, 82 4, 056 80 . 00% 77 .2 1% 77. 44 % Pa ve me nt s 2 13 10 .6 13 8, 41 9, 000 18 ,8 60 13 ,9 37 , 860 80 . 00% 75 .8 5% 76. 41 % Si gn s 8 NA 4, 39 5, 333 (9 34 ,3 87 ) ( 4, 15 9, 05 3) 10 0. 00 % 9 2. 58 % 87. 12 % Hi gh wa y Li gh ti ng 4 15 10 .6 1, 59 5, 000 1, 348 ,2 89 21 2, 789 85 . 00% 82 .7 5% 83. 06 % Gu ar dr ai l 4 1 (3 .4 ) 1 ,2 69 , 000 2, 191 ,9 47 2, 36 3, 547 80 . 00% 75 .7 1% 82. 17 % Weig h St at io ns 4 15 10 .6 19 5, 000 (7 2, 09 7) 9, 903 80 . 00% 77 .7 4% 77. 91 % 21 3, 87 1, 333 1, 128 ,6 67 21 ,1 89 , 100 Tabl e 7 1: Su mm ar y re su lt s Al lo cati on of Pr es er va ti on Fu nd s As se t Ac ti vi ty Gr ou p ( AAG ) As se t Ac ti vi ty Gr ou p ( AAG ) Di ffe re nc e be tw ee n De si re d an d Es ti ma te d Ti me to re ac h Ta rg et Ra ti ng Di ffe re nc e be twee n Cu rr en t an d Hi st or ic al Al lo cati on Note : Th e Tota l Allocation less Deterioratio n Nee d column indicate s an excess amount over th e amoun t needed to cover deterioratio n costs. This is th e amount that is use d for ne t improvemen t in condition/performance rating. Result Observation: This run demonstrates the impact of using percentage allocation for a few assets instead of fully optimized allocation. As a result of using percentage-based allocation

resource allocation Logic Framework 63 for Signs and Guardrail, the allocation for guardrail increases more than the baseline (optimal) allocation whereas the allocation for Signs ends up being less than the optimal allocation. 6.4.4 Scenario 4: Change in Desired Time to Reach Target Rating This is the same as the base case, except the desired time to reach target rating for Signs is reduced to 4 years from 8 years (in the base case). As se t Ac ti vi ty Gr ou p ( AAG ) To ta l D is tr ic t 1 D is tr ic t 2 D is tr ic t 3 D is tr ic t 4 D is tr ic t 5 D is tr ic t 6 D is tr ic t 7 D is tr ic t 8 D is tr ic t 9 Br id ge s 65 , 633 ,3 19 27 ,6 96 , 594 19 , 483 ,1 21 18 ,4 53 , 604 Pa ve me nt s 13 6, 952 ,0 30 53 ,1 13 , 789 38 , 757 ,2 35 45 ,0 81 , 005 Si gn s 8, 179 ,5 95 3, 01 4, 100 2, 537 ,3 20 2, 62 8, 176 Hi gh wa y Li gh ti ng 2, 923 ,4 09 1, 86 3, 843 615 ,9 28 44 3, 638 Gu ar dr ai l 1, 189 ,6 70 55 5, 966 274 ,4 09 35 9, 294 Weig h St at io ns 121 ,9 78 50 , 495 37 ,5 03 33 , 979 21 5, 000 ,0 00 86 ,2 94 , 787 61 , 705 ,5 16 66 ,9 99 , 696 De si re d Ti me Es ti mate d Ti me Di ff er en ce (D es ir ed Ta rg et ) Av er ag e Hi stor ic al Al lo ca ti on Di ff er en ce (C u rre nt Hi st or ic al ) To ta l Al lo ca ti on le ss De te ri or at io n N eed Targ et Ra ti ng Cu rre nt Ra ti ng Ex pe ct ed Ra ti ng Re su lt Br id ge s 2 14 12 .1 67 ,9 98 , 000 (2 ,3 64 ,6 81 ) 7, 88 3, 319 80 . 00% 77 .2 1% 77. 41 % Pa ve me nt s 2 14 12 .1 13 8, 41 9, 000 (1 ,4 66 ,9 70 ) 12 ,4 52 , 030 80 . 00% 75 .8 5% 76. 35 % Si gn s 4 16 12 .1 4, 39 5, 333 3, 784 ,2 62 55 9, 595 10 0. 00 % 9 2. 58 % 93. 31 % Hi gh wa y Li gh ti ng 4 16 12 .1 1, 59 5, 000 1, 328 ,4 09 19 2, 909 85 . 00% 82 .7 5% 83. 03 % Gu ar dr ai l 4 16 12 .1 1, 26 9, 000 (7 9, 33 0) 92 , 270 80 . 00% 75 .7 1% 75. 96 % Weig h Sta ti on s 4 16 12 .1 19 5, 000 (7 3, 02 2) 8, 978 80 . 00% 77 .7 4% 77. 90 % 21 3, 87 1, 333 1, 128 ,6 67 21 ,1 89 , 100 Tabl e 7 1: Su mm ar y re su lt s Al lo cati on of Pr es er va ti on Fu nd s As se t Ac ti vi ty Gr ou p ( AAG ) As se t Ac ti vi ty Gr ou p ( AAG ) Di ffe re nc e be tw ee n De si re d an d Es ti ma te d Ti me to re ac h Ta rg et Ra ti ng Di ffe re nc e be twee n Cu rr en t an d Hi st or ic al Al lo cati on Note : Th e Tota l Allocation less Deterioratio n Nee d column indicate s an excess amount over th e amoun t needed to cover deterioratio n costs. This is th e amount that is use d for ne t improvemen t in condition/performance rating. Result Observation: This run demonstrates the impact of changing the Target Years. As a result of decreasing the number of years to reach target rating for signs (from 8 to 4 years), the optimal allocation for signs increases from $8,085,405 in baseline to $8,179,595. This results in a corresponding decrease in allocation for other assets.