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Improved methodology for benefit estimation of highway pavement projects
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Research paper
Improved methodology for benefit estimation of highway pavement projects You Zhoua, Eric Jessupb,∗, Xiaodong Langa a b
School of Economic Sciences, Washington State University, PO Box 646210, Pullman, WA, 99164, USA Freight Policy Transportation Institute, Washington State University, PO Box 646210, Pullman, WA, 99164, USA
A R T I C LE I N FO
A B S T R A C T
Keywords: Pavement improvement Economic analysis User benefits
This paper offers an improved process for evaluating the benefits and economic tradeoffs associated with a variety of highway pavement projects at the Washington State Department of Transportation (WSDOT). It first analyzes the WSDOT current evaluation process and their utilization of the Highway Economic Requirement System (HERS-ST) developed by the Federal Highway Administration (FHWA). The assessment identifies some limitations. As a supplement, this study develops the HERS-ST Benefit Application Tool (HERS-ST-BAT) within Excel to improve the HERS-ST software and enhance the capabilities of evaluating highway project analyses. By combining HERS-ST-BAT and HERS-ST, the analyst is able to provide estimates for a variety of regional-level agency and user costs associated with pavement programs and more effectively consider different investment alternatives. Two separate pavement project case studies are selected to apply the HERS-ST-BAT. The results indicate that the improved process is generally applicable to various highway pavement projects. Other transportation agencies, especially for those without a statewide travel demand model, can incorporate this method for evaluating pavement improvement decisions.
JEL classification: R41 R42
1. Introduction Over the last several decades, the benefits of highway infrastructure have been justified in several aspects. From the micro-level perspective, the principal benefits of a highway project can include savings on travel time and vehicle operating costs, traffic accident rate reductions, and lower on-road emissions (Lawrence et al., 2015). From the macro-level view, it has the potential to create jobs and promote trade (Banister & Berechman, 2001). The U.S. government also commonly uses highway projects to fight against economic downturns (grants Overview. U., 2015). Given the limited infrastructure funding, there is a need for policymakers to be fully informed of the costs and benefits of highway projects. The Washington State Department of Transportation (WSDOT) currently utilizes the Federal Highway Administration (FHWA)-developed Highway Economic Requirements System, State Version (HERSST) model to quantify the benefits associated with new construction projects, as well as existing road improvement projects (FHWA. HERSST, 2005). The estimated benefits from these projects, such as reduced travel times and lower vehicle operating costs, can then be incorporated into the Computable General Equilibrium modeling system developed by REMI-TranSight to quantify broader regional economic impacts in state and local economies.
∗
The above method is not explicitly focused on estimating the benefits of pavement improvement projects; yet such projects do extend the use and longevity of existing infrastructure (Li, Luhr, Uhlmeyer, & Mahoney, 2015). Since many small-scale pavement projects fail to yield measurable reductions in travel time or other benefits, they could be prioritized below new infrastructure construction, thus placing pavement-related improvements at a disadvantage and ultimately resulting in dilapidated highway and bridge infrastructure (Kahn & Levinson, 2011). This further illustrates the need to have tools available to state DOTs for communicating why investment in maintenance and rehabilitation should be a priority in today's fiscally-constrained environment. This paper analyzes the current WSDOT's process for benefit estimation of highway projects and presents an improved method for pavement project evaluation. In particular, we developed the Excel-based HERS-ST Benefit Application Tool (HERS-ST-BAT) to supplement HERSST. It improves the existing process in three primary aspects: 1. Greater control of data inputs used by HERS-ST for simulations of pavement projects; 2. Ability to compare unimproved and improved scenarios at different time periods; 3. Modification of regional input parameters instead of utilizing
Corresponding author. E-mail addresses: [email protected] (Y. Zhou), [email protected] (E. Jessup), [email protected] (X. Lang).
https://doi.org/10.1016/j.retrec.2019.100739 Received 2 January 2019; Received in revised form 28 May 2019; Accepted 22 August 2019 0739-8859/ © 2019 Published by Elsevier Ltd.
Please cite this article as: You Zhou, Eric Jessup and Xiaodong Lang, Research in Transportation Economics, https://doi.org/10.1016/j.retrec.2019.100739
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the total economic value of the initial treatment cost in addition to the discounted future costs of maintenance and rehabilitation associated with the assets (Khurshid, Irfan, & Labi, 2009). The three life-cycle cost components are defined as agency costs, user costs, and external costs (Wilde). Benefit-cost analysis (BCA) is another widely used method for evaluation. Many agency and user benefits accrue from pavement improvement: early maintenance extends the life of the pavement and reduces the life-cycle cost; road condition improvements also result in user benefits such as higher customer satisfaction, user cost reduction, and increased safety (Khurshid et al., 2009). BCA captures these benefits and compares them with relavent costs. There are some variations from LCCA and BCA that have been developed to better facilitate pavement improvement decisions. For instance, user benefits could be alternatively viewed as consumer surplus, an economic concept defined by the difference between what road users in the aggregate would have been willing to pay and what they are actually asked to pay (Stevens, 2004). Some studies also incorporate uncertainty to account for the stochastic process of pavement deterioration (Gao & Zhang, 2008). Although there are several approaches most states would benefit by utilizing a consistent tool to calculate costs and benefits (Lee, 2000). In order to better understand how states are currently evaluating pavement projects, we conducted a comprehensive survey to all 50 state transportation agencies. The survey was divided into two parts. The first part included general questions about the pavement preservation program in each state such as the existence of the program and the age of the program. The second part of the survey mainly focused on their evaluation methods and specifically whether and how they are using HERS-ST software. According to the survey results, the majority of state DOTs do not track or quantify the benefits of pavement improvement. Two most common factors in improvement decision are the budget availability and existing pavement condition. In addition, we only foun four active users of the HERS-ST software (Washington, Oregon, Kentucky, and Iowa). The majority of these states are either unaware of this software or do not have the necessary resources to manage it. Some did report previously using HERS-ST, but they no longer utilize it for vavious reasons such as necessary data inaccessibility and time-consuming simulation processes. The survey results imply that there is a need to develop a more systematic and consistent method to quantify the benefits of pavement projects. Though not widely used in pavement projects, HERS-ST has the potential for such application. The next section analyzes how WSDOT is evaluating pavement projects with HERS-ST in detail and several limitations.
national averages. Once highway pavement is constructed, it starts to deteriorate over time, mainly due to traffic and environmental factors (Gillespie et al., 1993). If appropriate strategies are implemented at the right time, however, they can slow down the deterioration and extend the pavement service life (Li, Luhr, Russell, Rydholm, & Uhlmeyer, 2017). This research focuses on the strategies related to pavement type selection and treatment type selections. 1.1. Pavement type selection The pavement in Washington can be primarily categorized into two types: flexible and rigid. Flexible pavement is either surfaced with Bituminous Surface Treatment (also called chip seal) or Hot Mix Asphalt (HMA). Chip seal lasts 6–8 years and usually applies to low traffic volume roadways with less than 5000 vehicles per day (Average Pavement Life in, 2016). HMA is a high-quality pavement type and more durable than chip seal. On average, HMA pavement in Washington has a 15-year life. The rigid pavement type only refers to Portland Cement Concrete (PCC) at WSDOT, which is typically designed to last 30–50 years (Average Pavement Life in, 2016). The average unit price of PCC is two times higher than HMA (highway Constructio, 2016). HERS-ST-BAT selects pavement type between HMA and PCC. The performance of Washington's highways is monitored by the Washington State Pavement Management System (WSPMS). Typically, the data required by the WSPMS is gathered by performing a pavement condition survey which would evaluate roughness, rutting, faulting, and other distress (Li et al., 2015). The International Roughness Index (IRI) was developed to measure the roadway smoothness. It ranges from 0 to 999, in the unit of inches per mile (FHWA. HERS-ST, 2005). A lower number indicates smoother pavement. In WSDOT's IRI categories, a value below 170 suggests a roadway in good condition and a value above 220 represents a roadway in poor condition (pavement Roughness, 2016). Overall, 91% of Washington's highways are in good condition. WSDOT has used IRI to either ensure the quality of construction or determine a need for rehabilitation. Our analysis measures pavement condition with IRI. 1.2. Treatment type selection Various treatments can generally be classified into three groups: preservation, rehabilitation, and reconstruction (pavement Policy. Wa, 2015). If a preservation program applies the right treatment to the right place at the right time, it can delay the need for rehabilitation and reconstruction, for which the unit costs are substantially higher (Li et al., 2017). When pavement performance has been poor, preservation is less cost-effective, and the other two strategies are required to restore roads. Pavement rehabilitation keeps an existing pavement structure unchanged. It extends pavement service life and/or increases roadway capacity by adding or replacing pavement materials. The overlay is a common rehabilitation method, which lays either HMA or PCC over the remaining structure of the existing pavement (pavement Policy. Wa, 2015). In contrast, the reconstruction method completely removes and replaces the existing pavement structure with the new one. Given that it is a complete replacement, the unit construction cost of reconstruction is high and typically four times more than that of rehabilitation for asphalt pavement in Washington (8). This study focuses on overlay and reconstruction treatments.
2. Evaluation of Wsdot benefit estimation process There are two separate groups within the WSDOT that evaluate pavement project benefits: the pavement management group and the economic analysis group. Both have their own methods which allow them to develop results which meet their particular needs. The pavement management analysis group's benefit evaluation method concentrates on Life-Cycle Cost Analysis (LCCA). It primarily calculates the present value of agency cost which includes the initial construction cost and discounted future costs of maintenance and rehabilitation. However, it excludes some unneglectable user cost types such as travel time costs, vehicle operating costs, accident costs, and emissions costs. The only user cost included is the user delay cost during the construction period. In addition, such analysis focuses only on the improved highway segment and does not show regional estimates of agency and user costs and economic indicators, such as employment and income, for state and local planners. The WSDOT economic analysis team currently incorporates the estimated change in user costs from highway improvements run in HERS-
1.3. Current methods for pavement project evaluation There are several approaches commonly utilized for pavement project evaluation. The most common approach is Life-Cycle Cost Analysis (LCCA). LCCA for highway assets is a process that evaluates 2
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HERS-ST: original Highway Performance Monitoring System (HPMS) file, revised HPMS file, and improvement file. The original HPMS file is the HPMS data file directly obtained from WSDOT. Both revised HPMS file and improvement file are derived from the original HPMS file by HERS-ST-BAT (Fig. 2).
ST into the REMI-TranSight model. This is the process to quantify the regional economic benefits associated with a variety of transportation projects. There are several ways that the utilization of HERS-ST could be improved upon to aid in future estimation techniques. First, pavement and treatment type selections, which are integral components in the analysis of pavement management, are absent in the economic analysis process. These two selections largely determine the pavement condition and life after implementing a pavement project. Omitting either can result in less accurate estimates. Since there is no such functionality within HERS-ST to address pavement and treatment types for estimations in the first year of analysis, necessary inputs incorporating pavement and treatment type selections have to be prepared before running HERS-ST. Second, user cost changes might not be measurable immediately after a pavement improvement project is completed. In this case, it is meaningful to compare the improved and unimproved scenarios over a more extended period. If roadway deteriorations are not remedied, the difference of user costs between improved and unimproved scenarios could be much larger as time goes on, which is not taken into account in the current HERS-ST analysis. In addition, due to budget constraints, the necessary funding for a pavement project might not be available during the initial or current period. Therefore, it would be desirable to broaden the analysis to account for timing variations of improvements. While HERS-ST does offer this flexibility for its users, additional data files are required, which presents a usage barrier for those who are not familiar with the software. Third, the HERS-ST system utilizes nationally-averaged parameters for estimation. Given that many pavement improvement projects are only for less than ten-mile roadway sections, having the ability to modify parameters to the state or local level can greatly benefit the accuracy of cost estimates from HERS-ST. Two examples of relevant parameters are state-specific fuel tax and value of travel time for estimating vehicle operating costs and travel time costs, respectively. Fourth, economic impact analysis requires inputs, such as changes in transportation costs from transportation improvement, to produce accurate results on regional economic impacts such as changes in employment and income. The HERS-ST software could provide some simple summaries on cost changes to feed into the economic impact analysis. An in-depth cost analysis and comparison with data summaries would be more insightful and aid in the interpretation of estimation results.
3.2.1. Original HPMS file The HPMS file reflects the current-year highway conditions calibrated for the HERS model run. Throughout this paper, the current year (YR0) refers to the year that the analysis starts. The original HPMS file is used for the unimproved scenario in which no improvement is implemented, and roads will deteriorate over time during the entire analysis period (Fig. 2). 3.2.2. Revised HPMS file The HERS-ST software provides the current-year cost estimates solely based on the information in the loaded HPMS file. If estimates are needed for any improvement implemented and completed during the YR0, however, a user must modify the original HPMS file with some project-specific information before the file is loaded into HERS-ST. One of the main functions of HERS-ST-BAT is to help facilitate this process. The HERS-ST-BAT only requires a user to enter the necessary project-specific information once: the project location, treatment type, pavement type, post-improvement pavement condition (optional), and project timing (Fig. 1 (b) and (c)). It then processes all this information and automatically modifies the original HPMS file for running HERSST. The pavement condition, measured by IRI, is the main variable that affects user costs in HERS-ST. Treatment type choices determine the IRI immediately after improvement. Therefore, it is an essential variable to specify in comparing improvement scenarios. The HERS-ST-BAT provides two main choices for treatment types: Overlay and Reconstruction. By selecting either, the values of pavement conditions within the improved highway segment will be modified in the HPMS file correspondingly. If the “Overlay” option is selected, the post-improvement IRI value will be set as 60; if the “Reconstruction” option is selected, the value will be set as 45. Both numbers are provided by WSDOT's pavement group. It is possible that a user would have a more accurate post-improvement IRI value than the one provided above. The HERS-ST-BAT allows the user the flexibility to specify a different value to override the default one. The pavement type selection is another critical pavement design procedure. Within the HERS-ST-BAT, users choose between HMA and PCC, which determines the material applied to a pavement project. For example, if a user selects the “HMA” for pavement type and “Overlay” for treatment type, the project will lay HMA over an existing pavement structure.
3. Hers-St Benefit Application Tool To address these identified issues in the last section, this analysis offers an improved capability utilizing an Excel module, called as the HERS-ST Benefit Application Tool (HERS-ST-BAT), to supplement HERS-ST for benefit estimation process of pavement projects (Fig. 1). This project-level tool mainly has three functions (Lawrence et al., 2015): economic parameter adjustment (Banister & Berechman, 2001), HERS-ST input preparation, and (grants Overview. U., 2015) HERS-ST output summary.
3.2.3. Improvement file An agency could be interested in the appropriate timing of the improvement and weighing alternative investment choices now or at different times in the future. In HERS-ST-BAT, a user can choose for the improvement to be undertaken during the first, second, or third funding period, while YR0 is always chosen to compare with the unimproved baseline scenario (Fig. 1 (c)). In accordance with the HERS-ST default setting, there are four funding periods after YR0 and each funding period lasts five years. That is, if YR0 represents 2015, then the first funding period (FP1) spans from 2016 to 2020; the second funding period (FP2) from 2021 to 2025; the third funding period (FP3) from 2026 to 2030; the fourth funding period (FP4) from 2031 to 2035. In total, this represents a 20-year analysis period. The simulation is always conducted for the current year and all four funding periods in order to evaluate the impact of improvements over the 20-year period for all the scenarios. The difference in the scenarios is the timing for making such improvements. The scenario of improvement during the fourth funding period is intentionally left out of
3.1. Economic parameter adjustment In this analysis, we have adjusted parameters related to vehicle operating and travel time costs, by vehicle types, whose data is immediately available. They are modified to reflect the situation in Washington State in 2015 as accurately as possible. A complete list of editable parameters can be found in the HERS-ST Technical Report. If the resources of time, labor, and data are available, all editable parameters could be updated for the most accurate estimation results. 3.2. HERS-ST input preparation The analysis for various scenarios requires three types of files for 3
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Fig. 1. HERS-ST-BAT interface.
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maintenance cost whose unit is dollars per mile. All values in HERS-ST are constant dollars based on 2004. The HERS-ST-BAT converts per-unit costs to dollars for comparison purpose. Based on each funding period's total costs, HERS-ST-BAT shows the percentage change in each cost category between no-improvement and improvement scenarios for the entire county, in order to more clearly see the potential benefits of undertaking the improvement project. 3.4. Advantages of HERS-ST-BAT over HERS-ST The selection of pavement and treatment types is one of the most common challenges to pavement management practitioners, confronting state and local highway planners One of the primary challenges with utilizing the HERS-ST system is the inability to incorporate and modify data to reflect local or state conditions. HERS-ST-BAT enables such functionality through comparing HMA and PCC as pavement alternatives and overlay and reconstruction as treatment alternatives and incorporating local data. This is achieved by revising IRI values in the original HPMS file. The HERS-ST software also doesn't have the ability to analyze any pavement improvement if it is implemented during the current year. HERS-ST-BAT allows for these types of comparisons through the functional relationship between pavement and treatment types. For example, an analysis of capacity improvement can be added into HERSST-BAT through revising the number of lanes, width of existing lanes, or peak capacity in the original HPMS. Similarly, a new construction of a high-occupancy vehicle lane (HOV) can be handled by adding the type of HOV and maximum number of HOV lanes. Given state budget constraints, some improvements may not be feasible during the current year but rather considered for other funding periods. Such functionality is difficulty to simulate within HERS-ST. In HERS-ST-BAT, as described in the earlier section, this file can be easily produced in the user-friendly interface. A transportation agency may also have a difficulty to find the best location among several candidates for a specific pavement improvement project. HERS-ST either has no function to do this analysis if the project occurs during the current year or is inconvenient if during other funding periods. HERS-ST-BAT offers increased flexibility in order to address these types of problems. In both cases, one simply enters the beginning and ending milepost points for each location candidate. Corresponding HPMS data can be automatically produced and then input into HERS-ST for comparing purpose.
Fig. 2. Roles of three files in the simulation process.
the option. We investigate the impact of an improvement on various costs over time. Since the fourth funding period is the last funding period, there are no future costs for this scenario. Thus, we only focus on improvements during YR0, FP1, FP2, and FP3, though costs over a 20-year period are always estimated. By applying this option, the HERS-ST-BAT can produce a so-called “improvement file,” which is compatible with HERS-ST. HERS-ST uses this “improvement file” and the original HPMS file together for scenarios where any improvement is postponed. One drawback to applying this particular functionality is that the “improvement file” only contains information about treatment type, not pavement type. HERS-ST assumes that an overlay treatment is always performed with flexible pavements and a reconstruction treatment always applies the pavement type that the existing roads have. As a consequence, the results would be the same if a pavement improvement uses different pavement types but the same treatment type and is implemented after YR0. In contrast, the analysis for the YR0 improvement scenario has no such limitation because pavement type can be directly modified in the revised HPMS file before it is loaded into HERS-ST.
3.3. HERS-ST output analysis 4. Case studies Another primary function of the HERS-ST-BAT is to analyze outputs from HERS-ST (Fig. 1 (d)). The analysis only concentrates on those outputs related to agency and user costs. HERS-ST only provides the cost estimates in the last year of each funding period. For example, the current year is set as 2015 and each of four funding periods lasts five years based on the default setting. A user can obtain cost estimates in 2015, 2020, 2025, 2030, and 2035 for YR0, FP1, FP2, FP3, and FP4, respectively. HERS-ST-BAT calculates a cumulative present value by first converting these five single-year values into present values with an appropriate discount rate and then summing them up. This cumulative present value is used to compare different scenarios. Several highway improvement scenarios can be compared with the baseline case, which allows the roads to deteriorate over time in accordance with no improvement. For each scenario, there are six types of costs shown in the summary statistics: travel time cost (TTC), vehicle operating cost (VOC), crash cost, total user cost, maintenance cost, and emission cost. The total user costs are the sum of TTC, VOC, and crash costs. The estimated pavement maintenance costs are based on the difference between a constant pavement condition, which is defined by HERS-ST, and an actual pavement condition, which is estimated by the HERS-ST built-in pavement deterioration model. All these costs are in terms of dollars per 1000 VMT, except
In order to test the validity of HERS-ST-BAT and the improved method, two past WSDOT projects were selected as case studies (Lawrence et al., 2015): a concrete pavement rehabilitation project on I-5 northbound and (Banister & Berechman, 2001) a replace/rehabilitation concrete project on I-90 westbound (Fig. 3). The selection criteria were primarily based on recent highway projects that WSDOT had evaluated and for which necessary data inputs were available. The WSDOT's pavement group conducted the original life-cycle cost analysis for pavement strategy selection. It focused on agency costs and only estimated user delay costs during construction periods. All costs have been constant dollar values, based on 2015 and 2013 for the project (Lawrence et al., 2015) and (Banister & Berechman, 2001), respectively. The analysis starting year is 2015 for both projects. Therefore, 2015 HPMS files are used for consistency. The improvement costs in the original analysis were constrained to the improved highway segments. It might have been more insightful to investigate the regional user costs for government agencies. In WSDOT's economic analysis group, the percentage change of county-level costs is always calculated and fed into the REMI-TranSight Model for economic forecasting. This section revisits these two projects and provides estimates for user and maintenance costs at the county level. 5
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agency and user costs that these projects have estimated by the original LCCA. Rather, it aims to offer a more comprehensive view of those projects by supplementing the original cost estimations with the county-level user and maintenance costs. The general analysis procedure in this case study section follows the steps below: 1. Obtain the original 2015 county-level HPMS file; 2. Import the original file into HERS-ST-BAT and input the project information into the tool to create the revised HPMS file and improvement files; 3. Import these three types of files into HERS-ST to run simulations for unimproved scenario and improvements during YR0, FP1, FP2, and FP3; 4. Retrieve the HERS-ST results and convert original units to milliondollar increments; 5. Incorporate initial construction costs and user delay costs during construction into various HERS-ST costs from step 4 to see how total costs evolve over time under unimproved scenario and each pavement improvement strategy; 6. Calculate the cumulative present value of each cost type for each scenario of each pavement improvement strategy for comparison. Step 5 creates figures to visualize the cost trends. Step 6 produces tables to compare different scenarios and strategies. 4.1. Case study 1: I-5 northbound project For this project, the WSDOT pavement group conducted the original LCCA in 2015 to compare PCC pavement reconstruction with HMA pavement overlay. The original analysis only evaluated 4.3 out of the 8.87-mile construction for 50 years. The present value of total costs for PCC reconstruction and HMA overlay were estimated at $130,600,000 and $28,058,000, respectively. It included the agency costs with initial construction costs, subsequent maintenance, and rehabilitation costs and user delay costs during initial construction, maintenance, and rehabilitation periods. Given the estimates, WSDOT pavement selection committee chose HMA pavement overlay as the rehabilitation strategy. To supplement the above analysis, we used the 2015 King County HPMS file, which contains information for the 407 miles of national and state highways within the county. Importing it into the HERS-ST-BAT and HERS-ST allowed supplemental evaluation and analysis and illustrated the application of the tool. Two points need to be clarified before proceeding. First, HERS-ST outputs are constant dollar values based on 2004, while original LCCA costs are based on 2015. We converted the LCCA costs to be based on 2004 with FHWA National Highway Construction Cost Index (NHCCI) and Consumer Price Index (CPI). Second, any subsequent maintenance and rehabilitation costs provided in the original LCCA were not included in the calculation of total costs in this analysis. The future NHCCI and CPI do not exist, so it is difficult to convert these costs. Moreover, the HERS-ST annual maintenance costs, which are estimated costs to maintain roads in good condition, has been added to the total costs. The exclusion of similar costs from the original analysis avoids potential double-counting. By combining HERS-ST outputs and original LCCA estimates, we calculate the total costs in the current or last year of each baseline funding period for each pavement strategy by summing up total travel time costs, total vehicle operating costs, crash costs, HERS-ST-defined maintenance costs, emission costs, initial construction costs, and user delay costs in the original LCCA. We present how total costs will change over time for the baseline, HMA overlay implemented during YR0 (i.e., the initial year 2015), and PCC reconstruction implemented during YR0 (Fig. 4 (a)). In general, the total costs of all scenarios will keep increasing. Due to high initial construction costs and associated user delay costs, the total costs of the
Fig. 3. Locations for I-5 northbound project in King County, WA and I-90 westbound project in Kittitas County, WA.
Although results are shown at the county level, other projects in this county during the same period are not considered in the analysis. If those projects were incorporated, it would be impossible to focus on the effects of the project being studied. In other words, we assumed that the project being studied was the only project within the county during the analysis period. Since HERS-ST assumes no construction time, we were unable to estimate any user costs during the construction period with the methods proposed in this paper, except those from WSDOT pavement group's original LCCA. Also, the effects of pavement improvement can be observed immediately. For the present value calculation, a 4% discount rate was selected in accordance with the WSDOT pavement policy (12). It should be noted that this section is not challenging the accuracy of 6
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Fig. 4. Scenario analysis results of implementing pavement improvements across different timings for I-5 northbound project in King County.
projects in the county during the analysis period. In the last year of the funding period that PCC reconstruction was implemented, the total costs of PCC reconstruction strategies were higher than baseline and HMA overlay but then became lowest after that. The total costs of HMA overlay strategies are always lower than the baseline. Also, the longer the project is delayed, the fewer benefits there are within a certain number of funding periods. For example, comparing the strategies of implementing HMA overlay during FP2 and FP3: the total cost savings of FP2 HMA overlay are $51 million, while the total cost savings of FP3 HMA overlay are $44 million. Based on the HERS-ST results, the present cost values in the current year and the last year of each funding period for different scenarios can be calculated with the 4% discount rate. Except for initial construction costs and associated user delay costs, there are five single-year values (2015, 2020, 2025, 2030, and 2035) for each cost type in each scenario. The cumulative present value is obtained by adding these five values (Table 1). With this value, the percentage change in each type of costs
YR0 PCC reconstruction scenario in 2015 were even higher than the baseline costs. In contrast, the 2015 total costs of the YR0 HMA overlay scenario were still lower than the baseline costs. After 2015, the total costs of both strategies will be lower than the baseline. Moreover, PCC reconstruction values are always the lowest, even though the differences are small. The benefit of an improvement strategy can be defined by cost savings, which are the differences of summed total costs over all periods between the baseline and improvement strategies. Therefore, the benefit of HMA overlay improvement made in YR0 is $143 million in cost savings while PCC reconstruction has saved $113 million. If the improvement for some reason cannot be implemented during YR0, HERS-ST-BAT allows for the scenario that the improvement is postponed until FP1, FP2, or FP3. We compare these three scenarios (Fig. 4 (b), (c), (d)). Again, it consistently shows an increase in total costs. Before an improvement implementation, costs are the same as the baseline. This is because we assumed that there were no other ongoing 7
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Table 1 Cumulative present values of costs and its change from baseline to improvement strategies on I-5 NB. Improvement Strategy
TTC
Baseline HMA_OL_YR0 HMA_OL_FP1 HMA_OL_FP2 HMA_OL_FP3 PCC_RCTR_YR0 PCC_RCTR_FP1 PCC_RCTR_FP2 PCC_RCTR_FP3
9730.75 9729.27 9765.71 9756.83 9747.03 9728.31 9771.51 9761.58 9750.38
VOC
(−.015%) (.359%) (.268%) (.167%) (−.025%) (.419%) (.317%) (.202%)
8620.15 8516.68 8533.86 8552.88 8575.96 8506.74 8521.95 8543.66 8568.38
Crash
(−1.200%) (−1.001%) (−.780%) (−.513%) (−1.316%) (−1.139%) (−.887%) (−.601%)
2693.07 2693.06 2695.47 2694.45 2693.65 2693.00 2695.33 2694.92 2693.94
(−.000%) (.089%) (.051%) (.022%) (−.003%) (.084%) (.069%) (.032%)
Total User
Maintenance
Emission
Total Costs
21044.31 20938.85 20995.04 21004.16 21016.64 20928.32 20988.75 21000.17 21013.04
4.83 4.61 4.63 4.66 4.71 4.60 4.60 4.65 4.70
197.09 197.08 197.32 197.22 197.16 197.08 197.36 197.24 197.17
21246.23 21158.30 21214.75 21223.80 21236.27 21193.79 21254.51 21265.84 21278.70
(−.501%) (−.234%) (−.191%) (−.132%) (−.551%) (−.264%) (−.210%) (−.149%)
(−4.478%) (−4.216%) (−3.420%) (−2.427%) (−4.832%) (−4.691%) (−3.803%) (−2.742%)
(−.003%) (.120%) (.066%) (.035%) (−.004%) (.138%) (.077%) (.042%)
(−.414%) (−.148%) (−.106%) (−.047%) (−.247%) (.039%) (.092%) (.153%)
Note. 1. Baseline is the unimproved scenario; “HMA_OL_YR0” or “PCC_RCTR_YR0” indicates the strategy that the HMA Overlay or PCC Reconstruction is implemented during the current year; “HMA_OL_FPx” or “PCC_RCTR_FPx” indicates the strategy that the HMA Overlay or PCC Reconstruction is implemented during the x funding period. 2. “TTC” and “VOC” denote travel time costs and vehicle operating costs, respectively; total user costs are the sum of TTC, VOC, and Crash costs; total costs are the sum of total user costs, maintenance costs from HERS-ST, emission costs, initial construction costs ($9.93 million for HMA and $11.33 million for PCC), and user delay costs ($7.83 million for HMA and $52.46 million for PCC) during the construction. 3. The cumulative present value, in the unit of million dollars, is the sum of 5 single-year present values. Each of these five values represents the costs in the last year of each funding period. 4. Each percentage value in parentheses is the percentage change of cumulative present value of corresponding cost type for corresponding improvement strategies.
post-improvement IRI would be assumed to be the same if the treatment types are the same for two strategies. That is, pavement type will not affect post-improvement IRI. Given that total user costs and maintenance costs are mainly influenced by pavement condition, the difference in pavement type plays only a minor role in determining total cost difference. The savings for the strategy of HMA overlay implemented during YR0 are $94 million, while they are $87 million for PCC overlay during YR0. Due to the high initial construction costs and associated user delay costs, the 2015 total costs of HMA overlay and PCC overlay are $1.063 and $1.068 billion, respectively. Both are higher than 2015 baseline total costs ($1.058 billion). Therefore, the 2015 cost savings of both HMA overlay and PCC overlay from the baseline are negative. For this I-90 project, we only compare the timing of HMA overlay strategies (Fig. 5 (b), (c), and (d)). The results for any improvement after YR0 was obtained from HERS-ST with the improvement file. As mentioned before, the improvement file always assumes that an overlay is conducted with the flexible pavement. Thus, this method can only analyze HMA overlay after YR0 but not PCC overlay. As shown, except for the 2020 value of HMA overlay during the FP1, total costs of this strategy are always equal to or lower than the baseline. Still, the more improvement is delayed, the less total cost savings. Based on the figure, HMA overlay's total cost savings during FP1, FP2, and FP3 are $85 million, $72 million, and $52 million, respectively. Similar to the I-5 project, we calculate each cost type's cumulative present value for each scenario and the percentage change of these values between baseline and each improvement strategy (Table 2). The difference in total user costs and maintenance costs between HMA overlay in YR0 and PCC overlay in YR0 are small. Due to the improvement file's limitation in HERS-ST, the costs of PCC overlay after YR0 cannot be estimated and are missing from the table. For the HMA Overlay, the best time is the current year. It reduces total costs by 1.094% for HMA overlay. The third funding period is the worst time. It reduces total costs by 0.394% for HMA overlay. The PCC overlay during YR0 decreases total costs by 0.964%. Therefore, this analysis confirms the selection of the HMA overlay.
between the baseline and each improvement strategy can be calculated (Table 1). It shows that either HMA overlay or PCC reconstruction can lower the total user costs whenever they are implemented. Both strategies also largely reduce maintenance costs. However, the later implementation occurs, the less savings in total user costs and maintenance costs. The total user cost and maintenance cost savings from PCC reconstruction are higher than those from HMA overlay, no matter the timing. For both HMA overlay and PCC reconstruction, the best time is the current year. It reduces total costs by 0.414% for HMA overlay and 0.247% for PCC reconstruction. The third funding period is the worst time. It reduces total costs by 0.047% for HMA overlay and increases costs by 0.153% for PCC reconstruction. Given that the total cost reduction of HMA overlay strategy is consistently lower than PCC reconstruction, this analysis confirms the HMA overlay as the better choice.
4.2. Case study 2: I-90 westbound project For the second project, the WSDOT pavement group conducted the original LCCA in 2013 to analyze the alternative rehabilitation strategies between PCC pavement overlay and HMA pavement overlay. The original analysis covered the full length of the proposed improvement project for 50 years. It was estimated that the present values of total costs for PCC overlay and HMA overlay would be $30,400,000 and $28,122,000, respectively. All costs here are constant dollar values based on 2013. The committee selected HMA pavement overlay as the chosen rehabilitation strategy. Given the starting year of 2015 in the original LCCA, we supplemented the analysis with the 2015 Kittitas County HPMS file, which includes information for 183 miles of national and state highways. Following the similar procedure in the I-5 project, we obtain various estimated costs in the current or last year of each baseline funding period for each pavement strategy. We present the total costs changing over time for the baseline, HMA overlay implemented during YR0 (i.e., the initial year 2015), and PCC overlay implemented during YR0 (Fig. 5 (a)). Since Kittitas County has substantially more rural areas than King County, all kinds of costs in Kittitas County are much less than King County's. In general, it still shows that total costs increase over time. Unlike the I-5 project, the 2015 total costs of both strategies were higher than the baseline and later became lower. The cost difference between these two strategies was tiny after 2015. This is mainly due to the calculation method of post-improvement IRI WSDOT provided. Based on this method, the
5. Conclusions and discussions Within WSDOT, the pavement management and economic analysis groups evaluate pavement projects differently. In general, the economic analysis of highway projects concentrates on larger construction and improvement projects over longer time horizons for planning purposes. 8
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Fig. 5. Scenario analysis results of implementing pavement improvements across different timings for I-90 westbound project in Kittitas County.
simulation time in HERS-ST. This would allow a better comparison of projects that recoup benefits over longer time horizons. The case studies in this paper are selected from the pavement projects provided by the WSDOT pavement group. The options are limited, and the research team has used the most relevant two. If the project availability increases in the future, a similar framework can be employed to test the applicability of the proposed method. The case studies also reveal the main limitation of this method when applying the improvement file for timing analysis. If a scenario that improvement is implemented during the first, second, or third funding period is studied, it is impossible to apply this method to the strategies of PCC overlay and reconstruction with a new pavement type that differs from the one used by the existing roads. In addition, HERS-ST is not a network model. Although some large infrastructure projects might have a spillover effect, it cannot be captured by the framework described in this paper. The main purpose of this paper focuses on developing an improved
The evaluation of pavement projects within the pavement management framework utilizes the life-cycle cost analysis approach and typically does not consider some measurable user costs, such as travel time costs and vehicle operating costs. In order to mitigate some existing challenges and limitations of using the HERS-ST software, the HERS-ST-BAT was developed to advance HERS-ST and to improve the benefit and cost estimation process. The added flexibility in terms of input variables is the major improvement made within the HERS-ST supplement, as it allows for different scenarios of project timing or treatment types to be evaluated. Two case studies are presented, and the results indicate that the combination of HERS-ST and HERS-ST-BAT has the potential to be more broadly utilized at other state DOTs and offers a more robust evaluation of pavement improvement projects. It should be noted that four funding periods, or 20 years in total, are the default setting in HERS-ST and have therefore been used in these case studies. It would be beneficial in the future to extend this time horizon, regardless of the increased 9
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Table 2 Cumulative present values of costs and its change from baseline to improvement strategies on I-90 W. Improvement Strategy
TTC
Baseline HMA_OL_YR0 HMA_OL_FP1 HMA_OL_FP2 HMA_OL_FP3 PCC_OL_YR0
1749.89 1727.33 1728.12 1728.21 1730.14 1727.33
VOC
(−1.289%) (−1.244%) (−1.239%) (−1.129%) (−1.289%)
2381.29 2339.38 2346.23 2357.78 2368.49 2340.13
Crash
(−1.760%) (−1.472%) (−.987%) (−.537%) (−1.729%)
370.41 370.61 370.76 370.66 370.59 370.61
(.056%) (.095%) (.068%) (.051%) (.056%)
Total User
Maintenance
Emission
Total Costs
4501.65 4437.26 4445.20 4456.64 4469.23 4438.01
2.83 2.37 2.42 2.49 2.60 2.38
93.39 93.27 93.28 93.27 93.28 93.27
4597.87 4547.55 4555.55 4567.05 4579.76 4553.57
(−1.430%) (−1.254%) (−1.000%) (−.720%) (−1.414%)
(−16.207%) (−14.530%) (−11.852%) (−8.187%) (−15.725%)
(−.128%) (−.116%) (−.127%) (−.114%) (−.128%)
(−1.094%) (−0.921%) (−0.670%) (−0.394%) (−0.964%)
Note. 1. Baseline is the no improvement scenario; “HMA_OL_YR0” or “PCC_RCTR_YR0” indicates the strategy that the HMA Overlay or PCC Reconstruction is implemented during the current year; “HMA_OL_FPx” or “PCC_RCTR_FPx” indicates the strategy that the HMA Overlay or PCC Reconstruction is implemented during the x funding period. 2. “TTC” and “VOC” denote travel time costs and vehicle operating costs, respectively; total user costs are the sum of TTC, VOC, and Crash costs; total costs are the sum of total user costs, maintenance costs from HERS-ST, emission costs, initial construction costs ($14.47 million for HMA and $19.26 million for PCC), and user delay costs ($0.17 million for HMA and $0.65 million for PCC) during the construction. 3. The cumulative present value, in the unit of million dollars, is the sum of 5 single-year present values. Each of these five values represents the costs in the last year of each funding period. 4. Each percentage value in parentheses is the percentage change of cumulative present value of corresponding cost type for corresponding improvement strategies.
methodology, so the measurement of pavement condition has been simplified by using IRI alone. The post-improvement IRI is also determined by the limited options of pavement and treatment types. Future research can utilize other available data in HPMS datasets and include other available pavement and treatment types for measuring pavement condition more accurately. In conclusion, the improved method in this project provides a solution by showing a comprehensive benefit-cost picture for a variety of pavement improvement scenarios. This improved method can better inform decision makers and avoid unnecessary investments or loss from poor preservation project timing. Consequently, the method is recommended to those state DOTs where a sophisticated evaluation method for pavement improvement project is missing.
Department of Transportation, Materials Laboratory. Banister, D., & Berechman, Y. (2001). Transport investment and the promotion of economic growth. Journal of Transport Geography, 9(3), 209–218. FHWA. HERS-ST (2005). Highway economic Requirements system-state version: Technical reportWashington, D.C.: Federal Highway Administration. Gao, L., & Zhang, Z. (2008). Robust optimization for managing pavement maintenance and rehabilitation. Transportation research record: Journal of the transportation research board, No. 2084. Washington, D.C.: Transportation Research Board of the National Academies55–61. Gillespie, T. D., Karimihas, S. M., Cebon, D., Sayers, M. W., Nasim, M. A., Hansen, W., et al. (1993). NCHRP report 353: Effects of heavy-vehicle characteristics on pavement response and performanceWashington, D.C.: TRB, National Research Council. Kahn, M. E., & Levinson, D. M. (2011). Fix it first, expand it second, reward it third: A new strategy for America's highways. Discussion paper 2011-03. Washington, D.C.: Hamilton Project. Khurshid, M. B., Irfan, M., & Labi, S. (2009). Comparison of methods for evaluating pavement interventions: Evaluation and case study. Transportation research record: Journal of the transportation research board, No. 2108 (pp. 25–36). Washington, D.C.: Transportation Research Board of the National Academies. Lawrence, M., Nguyen, P., Skolnick, J., Symoun, J., Hunt, J., & Alfelor, R. (2015). Transportation systems Management and operations benefit-cost analysis compendium. FHWA-HOP-14-032. FHWA, U.S. Department of Transportation. Lee, D. B. (2000). Methods for evaluation of transportation projects in the USA. Transport Policy, 7(1), 41–50. Li, J., Luhr, D. R., Russell, M., Rydholm, T., & Uhlmeyer, J. S. (2017). Cost-effective performance management for Washington state pavement assets. Transportation research record: Journal of the transportation research board, No. 2639 (pp. 102–109). Washington, D.C.: Transportation Research Board of the National Academies. Li, J., Luhr, D. R., Uhlmeyer, J. S., & Mahoney, J. P. (2015). Evaluation of maintenance effectiveness for WSDOT pavement network. Presented at 94th annual meeting of the transportation research board Washington, D.C. Stevens, A. (2004). The application and limitations of cost-benefit assessment (CBA) for intelligent transport systems. Research in Transportation Economics, 8, 91–111. TIGER grants Overview (pp. –). (2015). Washington, D.C.: U.S. Department of Transportation. Wilde, J. S. Life cycle cost analysis of Portland cement concrete pavements. Austin, TX: The University of Texas at Austin. WSDOT highway construction costs (pp. –). (2016). Construction Office, Olympia, WA: Washington State Department of Transportation. WSDOT pavement policy (pp. –). (2015). Construction Office, Olympia, WA: Washington State Department of Transportation. WSDOT pavement roughness (IRI) report: 2014 (pp. –). (2016). Construction Office, Olympia, WA: Washington State Department of Transportation.
Contribution The authors confirm contribution to the paper as follows: study conception and design: Eric Jessup; data collection: You Zhou, Xiaodong Lang; analysis and interpretation of results: Eric Jessup, You Zhou, Xiaodong Lang; draft manuscript preparation: Eric Jessup, You Zhou. All authors reviewed the results and approved the final version of the manuscript. Acknowledgement This research was funded by the Washington State Department of Transportation under contract T1462-10. The authors would like to specifically thank Wenjuan Zhao, Lizbeth Martin-Mahar, David Luhr, Kim Willoughby, and Doug Brodin for their guidance and assistance throughout the project. References Average pavement life in Washington state (pp. –). (2016). Olympia, WA: Washington State
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Research in Transportation Economics journal homepage: www.elsevier.com/locate/retrec
Research paper
Improved methodology for benefit estimation of highway pavement projects You Zhoua, Eric Jessupb,∗, Xiaodong Langa a b
School of Economic Sciences, Washington State University, PO Box 646210, Pullman, WA, 99164, USA Freight Policy Transportation Institute, Washington State University, PO Box 646210, Pullman, WA, 99164, USA
A R T I C LE I N FO
A B S T R A C T
Keywords: Pavement improvement Economic analysis User benefits
This paper offers an improved process for evaluating the benefits and economic tradeoffs associated with a variety of highway pavement projects at the Washington State Department of Transportation (WSDOT). It first analyzes the WSDOT current evaluation process and their utilization of the Highway Economic Requirement System (HERS-ST) developed by the Federal Highway Administration (FHWA). The assessment identifies some limitations. As a supplement, this study develops the HERS-ST Benefit Application Tool (HERS-ST-BAT) within Excel to improve the HERS-ST software and enhance the capabilities of evaluating highway project analyses. By combining HERS-ST-BAT and HERS-ST, the analyst is able to provide estimates for a variety of regional-level agency and user costs associated with pavement programs and more effectively consider different investment alternatives. Two separate pavement project case studies are selected to apply the HERS-ST-BAT. The results indicate that the improved process is generally applicable to various highway pavement projects. Other transportation agencies, especially for those without a statewide travel demand model, can incorporate this method for evaluating pavement improvement decisions.
JEL classification: R41 R42
1. Introduction Over the last several decades, the benefits of highway infrastructure have been justified in several aspects. From the micro-level perspective, the principal benefits of a highway project can include savings on travel time and vehicle operating costs, traffic accident rate reductions, and lower on-road emissions (Lawrence et al., 2015). From the macro-level view, it has the potential to create jobs and promote trade (Banister & Berechman, 2001). The U.S. government also commonly uses highway projects to fight against economic downturns (grants Overview. U., 2015). Given the limited infrastructure funding, there is a need for policymakers to be fully informed of the costs and benefits of highway projects. The Washington State Department of Transportation (WSDOT) currently utilizes the Federal Highway Administration (FHWA)-developed Highway Economic Requirements System, State Version (HERSST) model to quantify the benefits associated with new construction projects, as well as existing road improvement projects (FHWA. HERSST, 2005). The estimated benefits from these projects, such as reduced travel times and lower vehicle operating costs, can then be incorporated into the Computable General Equilibrium modeling system developed by REMI-TranSight to quantify broader regional economic impacts in state and local economies.
∗
The above method is not explicitly focused on estimating the benefits of pavement improvement projects; yet such projects do extend the use and longevity of existing infrastructure (Li, Luhr, Uhlmeyer, & Mahoney, 2015). Since many small-scale pavement projects fail to yield measurable reductions in travel time or other benefits, they could be prioritized below new infrastructure construction, thus placing pavement-related improvements at a disadvantage and ultimately resulting in dilapidated highway and bridge infrastructure (Kahn & Levinson, 2011). This further illustrates the need to have tools available to state DOTs for communicating why investment in maintenance and rehabilitation should be a priority in today's fiscally-constrained environment. This paper analyzes the current WSDOT's process for benefit estimation of highway projects and presents an improved method for pavement project evaluation. In particular, we developed the Excel-based HERS-ST Benefit Application Tool (HERS-ST-BAT) to supplement HERSST. It improves the existing process in three primary aspects: 1. Greater control of data inputs used by HERS-ST for simulations of pavement projects; 2. Ability to compare unimproved and improved scenarios at different time periods; 3. Modification of regional input parameters instead of utilizing
Corresponding author. E-mail addresses: [email protected] (Y. Zhou), [email protected] (E. Jessup), [email protected] (X. Lang).
https://doi.org/10.1016/j.retrec.2019.100739 Received 2 January 2019; Received in revised form 28 May 2019; Accepted 22 August 2019 0739-8859/ © 2019 Published by Elsevier Ltd.
Please cite this article as: You Zhou, Eric Jessup and Xiaodong Lang, Research in Transportation Economics, https://doi.org/10.1016/j.retrec.2019.100739
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the total economic value of the initial treatment cost in addition to the discounted future costs of maintenance and rehabilitation associated with the assets (Khurshid, Irfan, & Labi, 2009). The three life-cycle cost components are defined as agency costs, user costs, and external costs (Wilde). Benefit-cost analysis (BCA) is another widely used method for evaluation. Many agency and user benefits accrue from pavement improvement: early maintenance extends the life of the pavement and reduces the life-cycle cost; road condition improvements also result in user benefits such as higher customer satisfaction, user cost reduction, and increased safety (Khurshid et al., 2009). BCA captures these benefits and compares them with relavent costs. There are some variations from LCCA and BCA that have been developed to better facilitate pavement improvement decisions. For instance, user benefits could be alternatively viewed as consumer surplus, an economic concept defined by the difference between what road users in the aggregate would have been willing to pay and what they are actually asked to pay (Stevens, 2004). Some studies also incorporate uncertainty to account for the stochastic process of pavement deterioration (Gao & Zhang, 2008). Although there are several approaches most states would benefit by utilizing a consistent tool to calculate costs and benefits (Lee, 2000). In order to better understand how states are currently evaluating pavement projects, we conducted a comprehensive survey to all 50 state transportation agencies. The survey was divided into two parts. The first part included general questions about the pavement preservation program in each state such as the existence of the program and the age of the program. The second part of the survey mainly focused on their evaluation methods and specifically whether and how they are using HERS-ST software. According to the survey results, the majority of state DOTs do not track or quantify the benefits of pavement improvement. Two most common factors in improvement decision are the budget availability and existing pavement condition. In addition, we only foun four active users of the HERS-ST software (Washington, Oregon, Kentucky, and Iowa). The majority of these states are either unaware of this software or do not have the necessary resources to manage it. Some did report previously using HERS-ST, but they no longer utilize it for vavious reasons such as necessary data inaccessibility and time-consuming simulation processes. The survey results imply that there is a need to develop a more systematic and consistent method to quantify the benefits of pavement projects. Though not widely used in pavement projects, HERS-ST has the potential for such application. The next section analyzes how WSDOT is evaluating pavement projects with HERS-ST in detail and several limitations.
national averages. Once highway pavement is constructed, it starts to deteriorate over time, mainly due to traffic and environmental factors (Gillespie et al., 1993). If appropriate strategies are implemented at the right time, however, they can slow down the deterioration and extend the pavement service life (Li, Luhr, Russell, Rydholm, & Uhlmeyer, 2017). This research focuses on the strategies related to pavement type selection and treatment type selections. 1.1. Pavement type selection The pavement in Washington can be primarily categorized into two types: flexible and rigid. Flexible pavement is either surfaced with Bituminous Surface Treatment (also called chip seal) or Hot Mix Asphalt (HMA). Chip seal lasts 6–8 years and usually applies to low traffic volume roadways with less than 5000 vehicles per day (Average Pavement Life in, 2016). HMA is a high-quality pavement type and more durable than chip seal. On average, HMA pavement in Washington has a 15-year life. The rigid pavement type only refers to Portland Cement Concrete (PCC) at WSDOT, which is typically designed to last 30–50 years (Average Pavement Life in, 2016). The average unit price of PCC is two times higher than HMA (highway Constructio, 2016). HERS-ST-BAT selects pavement type between HMA and PCC. The performance of Washington's highways is monitored by the Washington State Pavement Management System (WSPMS). Typically, the data required by the WSPMS is gathered by performing a pavement condition survey which would evaluate roughness, rutting, faulting, and other distress (Li et al., 2015). The International Roughness Index (IRI) was developed to measure the roadway smoothness. It ranges from 0 to 999, in the unit of inches per mile (FHWA. HERS-ST, 2005). A lower number indicates smoother pavement. In WSDOT's IRI categories, a value below 170 suggests a roadway in good condition and a value above 220 represents a roadway in poor condition (pavement Roughness, 2016). Overall, 91% of Washington's highways are in good condition. WSDOT has used IRI to either ensure the quality of construction or determine a need for rehabilitation. Our analysis measures pavement condition with IRI. 1.2. Treatment type selection Various treatments can generally be classified into three groups: preservation, rehabilitation, and reconstruction (pavement Policy. Wa, 2015). If a preservation program applies the right treatment to the right place at the right time, it can delay the need for rehabilitation and reconstruction, for which the unit costs are substantially higher (Li et al., 2017). When pavement performance has been poor, preservation is less cost-effective, and the other two strategies are required to restore roads. Pavement rehabilitation keeps an existing pavement structure unchanged. It extends pavement service life and/or increases roadway capacity by adding or replacing pavement materials. The overlay is a common rehabilitation method, which lays either HMA or PCC over the remaining structure of the existing pavement (pavement Policy. Wa, 2015). In contrast, the reconstruction method completely removes and replaces the existing pavement structure with the new one. Given that it is a complete replacement, the unit construction cost of reconstruction is high and typically four times more than that of rehabilitation for asphalt pavement in Washington (8). This study focuses on overlay and reconstruction treatments.
2. Evaluation of Wsdot benefit estimation process There are two separate groups within the WSDOT that evaluate pavement project benefits: the pavement management group and the economic analysis group. Both have their own methods which allow them to develop results which meet their particular needs. The pavement management analysis group's benefit evaluation method concentrates on Life-Cycle Cost Analysis (LCCA). It primarily calculates the present value of agency cost which includes the initial construction cost and discounted future costs of maintenance and rehabilitation. However, it excludes some unneglectable user cost types such as travel time costs, vehicle operating costs, accident costs, and emissions costs. The only user cost included is the user delay cost during the construction period. In addition, such analysis focuses only on the improved highway segment and does not show regional estimates of agency and user costs and economic indicators, such as employment and income, for state and local planners. The WSDOT economic analysis team currently incorporates the estimated change in user costs from highway improvements run in HERS-
1.3. Current methods for pavement project evaluation There are several approaches commonly utilized for pavement project evaluation. The most common approach is Life-Cycle Cost Analysis (LCCA). LCCA for highway assets is a process that evaluates 2
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HERS-ST: original Highway Performance Monitoring System (HPMS) file, revised HPMS file, and improvement file. The original HPMS file is the HPMS data file directly obtained from WSDOT. Both revised HPMS file and improvement file are derived from the original HPMS file by HERS-ST-BAT (Fig. 2).
ST into the REMI-TranSight model. This is the process to quantify the regional economic benefits associated with a variety of transportation projects. There are several ways that the utilization of HERS-ST could be improved upon to aid in future estimation techniques. First, pavement and treatment type selections, which are integral components in the analysis of pavement management, are absent in the economic analysis process. These two selections largely determine the pavement condition and life after implementing a pavement project. Omitting either can result in less accurate estimates. Since there is no such functionality within HERS-ST to address pavement and treatment types for estimations in the first year of analysis, necessary inputs incorporating pavement and treatment type selections have to be prepared before running HERS-ST. Second, user cost changes might not be measurable immediately after a pavement improvement project is completed. In this case, it is meaningful to compare the improved and unimproved scenarios over a more extended period. If roadway deteriorations are not remedied, the difference of user costs between improved and unimproved scenarios could be much larger as time goes on, which is not taken into account in the current HERS-ST analysis. In addition, due to budget constraints, the necessary funding for a pavement project might not be available during the initial or current period. Therefore, it would be desirable to broaden the analysis to account for timing variations of improvements. While HERS-ST does offer this flexibility for its users, additional data files are required, which presents a usage barrier for those who are not familiar with the software. Third, the HERS-ST system utilizes nationally-averaged parameters for estimation. Given that many pavement improvement projects are only for less than ten-mile roadway sections, having the ability to modify parameters to the state or local level can greatly benefit the accuracy of cost estimates from HERS-ST. Two examples of relevant parameters are state-specific fuel tax and value of travel time for estimating vehicle operating costs and travel time costs, respectively. Fourth, economic impact analysis requires inputs, such as changes in transportation costs from transportation improvement, to produce accurate results on regional economic impacts such as changes in employment and income. The HERS-ST software could provide some simple summaries on cost changes to feed into the economic impact analysis. An in-depth cost analysis and comparison with data summaries would be more insightful and aid in the interpretation of estimation results.
3.2.1. Original HPMS file The HPMS file reflects the current-year highway conditions calibrated for the HERS model run. Throughout this paper, the current year (YR0) refers to the year that the analysis starts. The original HPMS file is used for the unimproved scenario in which no improvement is implemented, and roads will deteriorate over time during the entire analysis period (Fig. 2). 3.2.2. Revised HPMS file The HERS-ST software provides the current-year cost estimates solely based on the information in the loaded HPMS file. If estimates are needed for any improvement implemented and completed during the YR0, however, a user must modify the original HPMS file with some project-specific information before the file is loaded into HERS-ST. One of the main functions of HERS-ST-BAT is to help facilitate this process. The HERS-ST-BAT only requires a user to enter the necessary project-specific information once: the project location, treatment type, pavement type, post-improvement pavement condition (optional), and project timing (Fig. 1 (b) and (c)). It then processes all this information and automatically modifies the original HPMS file for running HERSST. The pavement condition, measured by IRI, is the main variable that affects user costs in HERS-ST. Treatment type choices determine the IRI immediately after improvement. Therefore, it is an essential variable to specify in comparing improvement scenarios. The HERS-ST-BAT provides two main choices for treatment types: Overlay and Reconstruction. By selecting either, the values of pavement conditions within the improved highway segment will be modified in the HPMS file correspondingly. If the “Overlay” option is selected, the post-improvement IRI value will be set as 60; if the “Reconstruction” option is selected, the value will be set as 45. Both numbers are provided by WSDOT's pavement group. It is possible that a user would have a more accurate post-improvement IRI value than the one provided above. The HERS-ST-BAT allows the user the flexibility to specify a different value to override the default one. The pavement type selection is another critical pavement design procedure. Within the HERS-ST-BAT, users choose between HMA and PCC, which determines the material applied to a pavement project. For example, if a user selects the “HMA” for pavement type and “Overlay” for treatment type, the project will lay HMA over an existing pavement structure.
3. Hers-St Benefit Application Tool To address these identified issues in the last section, this analysis offers an improved capability utilizing an Excel module, called as the HERS-ST Benefit Application Tool (HERS-ST-BAT), to supplement HERS-ST for benefit estimation process of pavement projects (Fig. 1). This project-level tool mainly has three functions (Lawrence et al., 2015): economic parameter adjustment (Banister & Berechman, 2001), HERS-ST input preparation, and (grants Overview. U., 2015) HERS-ST output summary.
3.2.3. Improvement file An agency could be interested in the appropriate timing of the improvement and weighing alternative investment choices now or at different times in the future. In HERS-ST-BAT, a user can choose for the improvement to be undertaken during the first, second, or third funding period, while YR0 is always chosen to compare with the unimproved baseline scenario (Fig. 1 (c)). In accordance with the HERS-ST default setting, there are four funding periods after YR0 and each funding period lasts five years. That is, if YR0 represents 2015, then the first funding period (FP1) spans from 2016 to 2020; the second funding period (FP2) from 2021 to 2025; the third funding period (FP3) from 2026 to 2030; the fourth funding period (FP4) from 2031 to 2035. In total, this represents a 20-year analysis period. The simulation is always conducted for the current year and all four funding periods in order to evaluate the impact of improvements over the 20-year period for all the scenarios. The difference in the scenarios is the timing for making such improvements. The scenario of improvement during the fourth funding period is intentionally left out of
3.1. Economic parameter adjustment In this analysis, we have adjusted parameters related to vehicle operating and travel time costs, by vehicle types, whose data is immediately available. They are modified to reflect the situation in Washington State in 2015 as accurately as possible. A complete list of editable parameters can be found in the HERS-ST Technical Report. If the resources of time, labor, and data are available, all editable parameters could be updated for the most accurate estimation results. 3.2. HERS-ST input preparation The analysis for various scenarios requires three types of files for 3
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Fig. 1. HERS-ST-BAT interface.
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maintenance cost whose unit is dollars per mile. All values in HERS-ST are constant dollars based on 2004. The HERS-ST-BAT converts per-unit costs to dollars for comparison purpose. Based on each funding period's total costs, HERS-ST-BAT shows the percentage change in each cost category between no-improvement and improvement scenarios for the entire county, in order to more clearly see the potential benefits of undertaking the improvement project. 3.4. Advantages of HERS-ST-BAT over HERS-ST The selection of pavement and treatment types is one of the most common challenges to pavement management practitioners, confronting state and local highway planners One of the primary challenges with utilizing the HERS-ST system is the inability to incorporate and modify data to reflect local or state conditions. HERS-ST-BAT enables such functionality through comparing HMA and PCC as pavement alternatives and overlay and reconstruction as treatment alternatives and incorporating local data. This is achieved by revising IRI values in the original HPMS file. The HERS-ST software also doesn't have the ability to analyze any pavement improvement if it is implemented during the current year. HERS-ST-BAT allows for these types of comparisons through the functional relationship between pavement and treatment types. For example, an analysis of capacity improvement can be added into HERSST-BAT through revising the number of lanes, width of existing lanes, or peak capacity in the original HPMS. Similarly, a new construction of a high-occupancy vehicle lane (HOV) can be handled by adding the type of HOV and maximum number of HOV lanes. Given state budget constraints, some improvements may not be feasible during the current year but rather considered for other funding periods. Such functionality is difficulty to simulate within HERS-ST. In HERS-ST-BAT, as described in the earlier section, this file can be easily produced in the user-friendly interface. A transportation agency may also have a difficulty to find the best location among several candidates for a specific pavement improvement project. HERS-ST either has no function to do this analysis if the project occurs during the current year or is inconvenient if during other funding periods. HERS-ST-BAT offers increased flexibility in order to address these types of problems. In both cases, one simply enters the beginning and ending milepost points for each location candidate. Corresponding HPMS data can be automatically produced and then input into HERS-ST for comparing purpose.
Fig. 2. Roles of three files in the simulation process.
the option. We investigate the impact of an improvement on various costs over time. Since the fourth funding period is the last funding period, there are no future costs for this scenario. Thus, we only focus on improvements during YR0, FP1, FP2, and FP3, though costs over a 20-year period are always estimated. By applying this option, the HERS-ST-BAT can produce a so-called “improvement file,” which is compatible with HERS-ST. HERS-ST uses this “improvement file” and the original HPMS file together for scenarios where any improvement is postponed. One drawback to applying this particular functionality is that the “improvement file” only contains information about treatment type, not pavement type. HERS-ST assumes that an overlay treatment is always performed with flexible pavements and a reconstruction treatment always applies the pavement type that the existing roads have. As a consequence, the results would be the same if a pavement improvement uses different pavement types but the same treatment type and is implemented after YR0. In contrast, the analysis for the YR0 improvement scenario has no such limitation because pavement type can be directly modified in the revised HPMS file before it is loaded into HERS-ST.
3.3. HERS-ST output analysis 4. Case studies Another primary function of the HERS-ST-BAT is to analyze outputs from HERS-ST (Fig. 1 (d)). The analysis only concentrates on those outputs related to agency and user costs. HERS-ST only provides the cost estimates in the last year of each funding period. For example, the current year is set as 2015 and each of four funding periods lasts five years based on the default setting. A user can obtain cost estimates in 2015, 2020, 2025, 2030, and 2035 for YR0, FP1, FP2, FP3, and FP4, respectively. HERS-ST-BAT calculates a cumulative present value by first converting these five single-year values into present values with an appropriate discount rate and then summing them up. This cumulative present value is used to compare different scenarios. Several highway improvement scenarios can be compared with the baseline case, which allows the roads to deteriorate over time in accordance with no improvement. For each scenario, there are six types of costs shown in the summary statistics: travel time cost (TTC), vehicle operating cost (VOC), crash cost, total user cost, maintenance cost, and emission cost. The total user costs are the sum of TTC, VOC, and crash costs. The estimated pavement maintenance costs are based on the difference between a constant pavement condition, which is defined by HERS-ST, and an actual pavement condition, which is estimated by the HERS-ST built-in pavement deterioration model. All these costs are in terms of dollars per 1000 VMT, except
In order to test the validity of HERS-ST-BAT and the improved method, two past WSDOT projects were selected as case studies (Lawrence et al., 2015): a concrete pavement rehabilitation project on I-5 northbound and (Banister & Berechman, 2001) a replace/rehabilitation concrete project on I-90 westbound (Fig. 3). The selection criteria were primarily based on recent highway projects that WSDOT had evaluated and for which necessary data inputs were available. The WSDOT's pavement group conducted the original life-cycle cost analysis for pavement strategy selection. It focused on agency costs and only estimated user delay costs during construction periods. All costs have been constant dollar values, based on 2015 and 2013 for the project (Lawrence et al., 2015) and (Banister & Berechman, 2001), respectively. The analysis starting year is 2015 for both projects. Therefore, 2015 HPMS files are used for consistency. The improvement costs in the original analysis were constrained to the improved highway segments. It might have been more insightful to investigate the regional user costs for government agencies. In WSDOT's economic analysis group, the percentage change of county-level costs is always calculated and fed into the REMI-TranSight Model for economic forecasting. This section revisits these two projects and provides estimates for user and maintenance costs at the county level. 5
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agency and user costs that these projects have estimated by the original LCCA. Rather, it aims to offer a more comprehensive view of those projects by supplementing the original cost estimations with the county-level user and maintenance costs. The general analysis procedure in this case study section follows the steps below: 1. Obtain the original 2015 county-level HPMS file; 2. Import the original file into HERS-ST-BAT and input the project information into the tool to create the revised HPMS file and improvement files; 3. Import these three types of files into HERS-ST to run simulations for unimproved scenario and improvements during YR0, FP1, FP2, and FP3; 4. Retrieve the HERS-ST results and convert original units to milliondollar increments; 5. Incorporate initial construction costs and user delay costs during construction into various HERS-ST costs from step 4 to see how total costs evolve over time under unimproved scenario and each pavement improvement strategy; 6. Calculate the cumulative present value of each cost type for each scenario of each pavement improvement strategy for comparison. Step 5 creates figures to visualize the cost trends. Step 6 produces tables to compare different scenarios and strategies. 4.1. Case study 1: I-5 northbound project For this project, the WSDOT pavement group conducted the original LCCA in 2015 to compare PCC pavement reconstruction with HMA pavement overlay. The original analysis only evaluated 4.3 out of the 8.87-mile construction for 50 years. The present value of total costs for PCC reconstruction and HMA overlay were estimated at $130,600,000 and $28,058,000, respectively. It included the agency costs with initial construction costs, subsequent maintenance, and rehabilitation costs and user delay costs during initial construction, maintenance, and rehabilitation periods. Given the estimates, WSDOT pavement selection committee chose HMA pavement overlay as the rehabilitation strategy. To supplement the above analysis, we used the 2015 King County HPMS file, which contains information for the 407 miles of national and state highways within the county. Importing it into the HERS-ST-BAT and HERS-ST allowed supplemental evaluation and analysis and illustrated the application of the tool. Two points need to be clarified before proceeding. First, HERS-ST outputs are constant dollar values based on 2004, while original LCCA costs are based on 2015. We converted the LCCA costs to be based on 2004 with FHWA National Highway Construction Cost Index (NHCCI) and Consumer Price Index (CPI). Second, any subsequent maintenance and rehabilitation costs provided in the original LCCA were not included in the calculation of total costs in this analysis. The future NHCCI and CPI do not exist, so it is difficult to convert these costs. Moreover, the HERS-ST annual maintenance costs, which are estimated costs to maintain roads in good condition, has been added to the total costs. The exclusion of similar costs from the original analysis avoids potential double-counting. By combining HERS-ST outputs and original LCCA estimates, we calculate the total costs in the current or last year of each baseline funding period for each pavement strategy by summing up total travel time costs, total vehicle operating costs, crash costs, HERS-ST-defined maintenance costs, emission costs, initial construction costs, and user delay costs in the original LCCA. We present how total costs will change over time for the baseline, HMA overlay implemented during YR0 (i.e., the initial year 2015), and PCC reconstruction implemented during YR0 (Fig. 4 (a)). In general, the total costs of all scenarios will keep increasing. Due to high initial construction costs and associated user delay costs, the total costs of the
Fig. 3. Locations for I-5 northbound project in King County, WA and I-90 westbound project in Kittitas County, WA.
Although results are shown at the county level, other projects in this county during the same period are not considered in the analysis. If those projects were incorporated, it would be impossible to focus on the effects of the project being studied. In other words, we assumed that the project being studied was the only project within the county during the analysis period. Since HERS-ST assumes no construction time, we were unable to estimate any user costs during the construction period with the methods proposed in this paper, except those from WSDOT pavement group's original LCCA. Also, the effects of pavement improvement can be observed immediately. For the present value calculation, a 4% discount rate was selected in accordance with the WSDOT pavement policy (12). It should be noted that this section is not challenging the accuracy of 6
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Fig. 4. Scenario analysis results of implementing pavement improvements across different timings for I-5 northbound project in King County.
projects in the county during the analysis period. In the last year of the funding period that PCC reconstruction was implemented, the total costs of PCC reconstruction strategies were higher than baseline and HMA overlay but then became lowest after that. The total costs of HMA overlay strategies are always lower than the baseline. Also, the longer the project is delayed, the fewer benefits there are within a certain number of funding periods. For example, comparing the strategies of implementing HMA overlay during FP2 and FP3: the total cost savings of FP2 HMA overlay are $51 million, while the total cost savings of FP3 HMA overlay are $44 million. Based on the HERS-ST results, the present cost values in the current year and the last year of each funding period for different scenarios can be calculated with the 4% discount rate. Except for initial construction costs and associated user delay costs, there are five single-year values (2015, 2020, 2025, 2030, and 2035) for each cost type in each scenario. The cumulative present value is obtained by adding these five values (Table 1). With this value, the percentage change in each type of costs
YR0 PCC reconstruction scenario in 2015 were even higher than the baseline costs. In contrast, the 2015 total costs of the YR0 HMA overlay scenario were still lower than the baseline costs. After 2015, the total costs of both strategies will be lower than the baseline. Moreover, PCC reconstruction values are always the lowest, even though the differences are small. The benefit of an improvement strategy can be defined by cost savings, which are the differences of summed total costs over all periods between the baseline and improvement strategies. Therefore, the benefit of HMA overlay improvement made in YR0 is $143 million in cost savings while PCC reconstruction has saved $113 million. If the improvement for some reason cannot be implemented during YR0, HERS-ST-BAT allows for the scenario that the improvement is postponed until FP1, FP2, or FP3. We compare these three scenarios (Fig. 4 (b), (c), (d)). Again, it consistently shows an increase in total costs. Before an improvement implementation, costs are the same as the baseline. This is because we assumed that there were no other ongoing 7
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Table 1 Cumulative present values of costs and its change from baseline to improvement strategies on I-5 NB. Improvement Strategy
TTC
Baseline HMA_OL_YR0 HMA_OL_FP1 HMA_OL_FP2 HMA_OL_FP3 PCC_RCTR_YR0 PCC_RCTR_FP1 PCC_RCTR_FP2 PCC_RCTR_FP3
9730.75 9729.27 9765.71 9756.83 9747.03 9728.31 9771.51 9761.58 9750.38
VOC
(−.015%) (.359%) (.268%) (.167%) (−.025%) (.419%) (.317%) (.202%)
8620.15 8516.68 8533.86 8552.88 8575.96 8506.74 8521.95 8543.66 8568.38
Crash
(−1.200%) (−1.001%) (−.780%) (−.513%) (−1.316%) (−1.139%) (−.887%) (−.601%)
2693.07 2693.06 2695.47 2694.45 2693.65 2693.00 2695.33 2694.92 2693.94
(−.000%) (.089%) (.051%) (.022%) (−.003%) (.084%) (.069%) (.032%)
Total User
Maintenance
Emission
Total Costs
21044.31 20938.85 20995.04 21004.16 21016.64 20928.32 20988.75 21000.17 21013.04
4.83 4.61 4.63 4.66 4.71 4.60 4.60 4.65 4.70
197.09 197.08 197.32 197.22 197.16 197.08 197.36 197.24 197.17
21246.23 21158.30 21214.75 21223.80 21236.27 21193.79 21254.51 21265.84 21278.70
(−.501%) (−.234%) (−.191%) (−.132%) (−.551%) (−.264%) (−.210%) (−.149%)
(−4.478%) (−4.216%) (−3.420%) (−2.427%) (−4.832%) (−4.691%) (−3.803%) (−2.742%)
(−.003%) (.120%) (.066%) (.035%) (−.004%) (.138%) (.077%) (.042%)
(−.414%) (−.148%) (−.106%) (−.047%) (−.247%) (.039%) (.092%) (.153%)
Note. 1. Baseline is the unimproved scenario; “HMA_OL_YR0” or “PCC_RCTR_YR0” indicates the strategy that the HMA Overlay or PCC Reconstruction is implemented during the current year; “HMA_OL_FPx” or “PCC_RCTR_FPx” indicates the strategy that the HMA Overlay or PCC Reconstruction is implemented during the x funding period. 2. “TTC” and “VOC” denote travel time costs and vehicle operating costs, respectively; total user costs are the sum of TTC, VOC, and Crash costs; total costs are the sum of total user costs, maintenance costs from HERS-ST, emission costs, initial construction costs ($9.93 million for HMA and $11.33 million for PCC), and user delay costs ($7.83 million for HMA and $52.46 million for PCC) during the construction. 3. The cumulative present value, in the unit of million dollars, is the sum of 5 single-year present values. Each of these five values represents the costs in the last year of each funding period. 4. Each percentage value in parentheses is the percentage change of cumulative present value of corresponding cost type for corresponding improvement strategies.
post-improvement IRI would be assumed to be the same if the treatment types are the same for two strategies. That is, pavement type will not affect post-improvement IRI. Given that total user costs and maintenance costs are mainly influenced by pavement condition, the difference in pavement type plays only a minor role in determining total cost difference. The savings for the strategy of HMA overlay implemented during YR0 are $94 million, while they are $87 million for PCC overlay during YR0. Due to the high initial construction costs and associated user delay costs, the 2015 total costs of HMA overlay and PCC overlay are $1.063 and $1.068 billion, respectively. Both are higher than 2015 baseline total costs ($1.058 billion). Therefore, the 2015 cost savings of both HMA overlay and PCC overlay from the baseline are negative. For this I-90 project, we only compare the timing of HMA overlay strategies (Fig. 5 (b), (c), and (d)). The results for any improvement after YR0 was obtained from HERS-ST with the improvement file. As mentioned before, the improvement file always assumes that an overlay is conducted with the flexible pavement. Thus, this method can only analyze HMA overlay after YR0 but not PCC overlay. As shown, except for the 2020 value of HMA overlay during the FP1, total costs of this strategy are always equal to or lower than the baseline. Still, the more improvement is delayed, the less total cost savings. Based on the figure, HMA overlay's total cost savings during FP1, FP2, and FP3 are $85 million, $72 million, and $52 million, respectively. Similar to the I-5 project, we calculate each cost type's cumulative present value for each scenario and the percentage change of these values between baseline and each improvement strategy (Table 2). The difference in total user costs and maintenance costs between HMA overlay in YR0 and PCC overlay in YR0 are small. Due to the improvement file's limitation in HERS-ST, the costs of PCC overlay after YR0 cannot be estimated and are missing from the table. For the HMA Overlay, the best time is the current year. It reduces total costs by 1.094% for HMA overlay. The third funding period is the worst time. It reduces total costs by 0.394% for HMA overlay. The PCC overlay during YR0 decreases total costs by 0.964%. Therefore, this analysis confirms the selection of the HMA overlay.
between the baseline and each improvement strategy can be calculated (Table 1). It shows that either HMA overlay or PCC reconstruction can lower the total user costs whenever they are implemented. Both strategies also largely reduce maintenance costs. However, the later implementation occurs, the less savings in total user costs and maintenance costs. The total user cost and maintenance cost savings from PCC reconstruction are higher than those from HMA overlay, no matter the timing. For both HMA overlay and PCC reconstruction, the best time is the current year. It reduces total costs by 0.414% for HMA overlay and 0.247% for PCC reconstruction. The third funding period is the worst time. It reduces total costs by 0.047% for HMA overlay and increases costs by 0.153% for PCC reconstruction. Given that the total cost reduction of HMA overlay strategy is consistently lower than PCC reconstruction, this analysis confirms the HMA overlay as the better choice.
4.2. Case study 2: I-90 westbound project For the second project, the WSDOT pavement group conducted the original LCCA in 2013 to analyze the alternative rehabilitation strategies between PCC pavement overlay and HMA pavement overlay. The original analysis covered the full length of the proposed improvement project for 50 years. It was estimated that the present values of total costs for PCC overlay and HMA overlay would be $30,400,000 and $28,122,000, respectively. All costs here are constant dollar values based on 2013. The committee selected HMA pavement overlay as the chosen rehabilitation strategy. Given the starting year of 2015 in the original LCCA, we supplemented the analysis with the 2015 Kittitas County HPMS file, which includes information for 183 miles of national and state highways. Following the similar procedure in the I-5 project, we obtain various estimated costs in the current or last year of each baseline funding period for each pavement strategy. We present the total costs changing over time for the baseline, HMA overlay implemented during YR0 (i.e., the initial year 2015), and PCC overlay implemented during YR0 (Fig. 5 (a)). Since Kittitas County has substantially more rural areas than King County, all kinds of costs in Kittitas County are much less than King County's. In general, it still shows that total costs increase over time. Unlike the I-5 project, the 2015 total costs of both strategies were higher than the baseline and later became lower. The cost difference between these two strategies was tiny after 2015. This is mainly due to the calculation method of post-improvement IRI WSDOT provided. Based on this method, the
5. Conclusions and discussions Within WSDOT, the pavement management and economic analysis groups evaluate pavement projects differently. In general, the economic analysis of highway projects concentrates on larger construction and improvement projects over longer time horizons for planning purposes. 8
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Fig. 5. Scenario analysis results of implementing pavement improvements across different timings for I-90 westbound project in Kittitas County.
simulation time in HERS-ST. This would allow a better comparison of projects that recoup benefits over longer time horizons. The case studies in this paper are selected from the pavement projects provided by the WSDOT pavement group. The options are limited, and the research team has used the most relevant two. If the project availability increases in the future, a similar framework can be employed to test the applicability of the proposed method. The case studies also reveal the main limitation of this method when applying the improvement file for timing analysis. If a scenario that improvement is implemented during the first, second, or third funding period is studied, it is impossible to apply this method to the strategies of PCC overlay and reconstruction with a new pavement type that differs from the one used by the existing roads. In addition, HERS-ST is not a network model. Although some large infrastructure projects might have a spillover effect, it cannot be captured by the framework described in this paper. The main purpose of this paper focuses on developing an improved
The evaluation of pavement projects within the pavement management framework utilizes the life-cycle cost analysis approach and typically does not consider some measurable user costs, such as travel time costs and vehicle operating costs. In order to mitigate some existing challenges and limitations of using the HERS-ST software, the HERS-ST-BAT was developed to advance HERS-ST and to improve the benefit and cost estimation process. The added flexibility in terms of input variables is the major improvement made within the HERS-ST supplement, as it allows for different scenarios of project timing or treatment types to be evaluated. Two case studies are presented, and the results indicate that the combination of HERS-ST and HERS-ST-BAT has the potential to be more broadly utilized at other state DOTs and offers a more robust evaluation of pavement improvement projects. It should be noted that four funding periods, or 20 years in total, are the default setting in HERS-ST and have therefore been used in these case studies. It would be beneficial in the future to extend this time horizon, regardless of the increased 9
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Table 2 Cumulative present values of costs and its change from baseline to improvement strategies on I-90 W. Improvement Strategy
TTC
Baseline HMA_OL_YR0 HMA_OL_FP1 HMA_OL_FP2 HMA_OL_FP3 PCC_OL_YR0
1749.89 1727.33 1728.12 1728.21 1730.14 1727.33
VOC
(−1.289%) (−1.244%) (−1.239%) (−1.129%) (−1.289%)
2381.29 2339.38 2346.23 2357.78 2368.49 2340.13
Crash
(−1.760%) (−1.472%) (−.987%) (−.537%) (−1.729%)
370.41 370.61 370.76 370.66 370.59 370.61
(.056%) (.095%) (.068%) (.051%) (.056%)
Total User
Maintenance
Emission
Total Costs
4501.65 4437.26 4445.20 4456.64 4469.23 4438.01
2.83 2.37 2.42 2.49 2.60 2.38
93.39 93.27 93.28 93.27 93.28 93.27
4597.87 4547.55 4555.55 4567.05 4579.76 4553.57
(−1.430%) (−1.254%) (−1.000%) (−.720%) (−1.414%)
(−16.207%) (−14.530%) (−11.852%) (−8.187%) (−15.725%)
(−.128%) (−.116%) (−.127%) (−.114%) (−.128%)
(−1.094%) (−0.921%) (−0.670%) (−0.394%) (−0.964%)
Note. 1. Baseline is the no improvement scenario; “HMA_OL_YR0” or “PCC_RCTR_YR0” indicates the strategy that the HMA Overlay or PCC Reconstruction is implemented during the current year; “HMA_OL_FPx” or “PCC_RCTR_FPx” indicates the strategy that the HMA Overlay or PCC Reconstruction is implemented during the x funding period. 2. “TTC” and “VOC” denote travel time costs and vehicle operating costs, respectively; total user costs are the sum of TTC, VOC, and Crash costs; total costs are the sum of total user costs, maintenance costs from HERS-ST, emission costs, initial construction costs ($14.47 million for HMA and $19.26 million for PCC), and user delay costs ($0.17 million for HMA and $0.65 million for PCC) during the construction. 3. The cumulative present value, in the unit of million dollars, is the sum of 5 single-year present values. Each of these five values represents the costs in the last year of each funding period. 4. Each percentage value in parentheses is the percentage change of cumulative present value of corresponding cost type for corresponding improvement strategies.
methodology, so the measurement of pavement condition has been simplified by using IRI alone. The post-improvement IRI is also determined by the limited options of pavement and treatment types. Future research can utilize other available data in HPMS datasets and include other available pavement and treatment types for measuring pavement condition more accurately. In conclusion, the improved method in this project provides a solution by showing a comprehensive benefit-cost picture for a variety of pavement improvement scenarios. This improved method can better inform decision makers and avoid unnecessary investments or loss from poor preservation project timing. Consequently, the method is recommended to those state DOTs where a sophisticated evaluation method for pavement improvement project is missing.
Department of Transportation, Materials Laboratory. Banister, D., & Berechman, Y. (2001). Transport investment and the promotion of economic growth. Journal of Transport Geography, 9(3), 209–218. FHWA. HERS-ST (2005). Highway economic Requirements system-state version: Technical reportWashington, D.C.: Federal Highway Administration. Gao, L., & Zhang, Z. (2008). Robust optimization for managing pavement maintenance and rehabilitation. Transportation research record: Journal of the transportation research board, No. 2084. Washington, D.C.: Transportation Research Board of the National Academies55–61. Gillespie, T. D., Karimihas, S. M., Cebon, D., Sayers, M. W., Nasim, M. A., Hansen, W., et al. (1993). NCHRP report 353: Effects of heavy-vehicle characteristics on pavement response and performanceWashington, D.C.: TRB, National Research Council. Kahn, M. E., & Levinson, D. M. (2011). Fix it first, expand it second, reward it third: A new strategy for America's highways. Discussion paper 2011-03. Washington, D.C.: Hamilton Project. Khurshid, M. B., Irfan, M., & Labi, S. (2009). Comparison of methods for evaluating pavement interventions: Evaluation and case study. Transportation research record: Journal of the transportation research board, No. 2108 (pp. 25–36). Washington, D.C.: Transportation Research Board of the National Academies. Lawrence, M., Nguyen, P., Skolnick, J., Symoun, J., Hunt, J., & Alfelor, R. (2015). Transportation systems Management and operations benefit-cost analysis compendium. FHWA-HOP-14-032. FHWA, U.S. Department of Transportation. Lee, D. B. (2000). Methods for evaluation of transportation projects in the USA. Transport Policy, 7(1), 41–50. Li, J., Luhr, D. R., Russell, M., Rydholm, T., & Uhlmeyer, J. S. (2017). Cost-effective performance management for Washington state pavement assets. Transportation research record: Journal of the transportation research board, No. 2639 (pp. 102–109). Washington, D.C.: Transportation Research Board of the National Academies. Li, J., Luhr, D. R., Uhlmeyer, J. S., & Mahoney, J. P. (2015). Evaluation of maintenance effectiveness for WSDOT pavement network. Presented at 94th annual meeting of the transportation research board Washington, D.C. Stevens, A. (2004). The application and limitations of cost-benefit assessment (CBA) for intelligent transport systems. Research in Transportation Economics, 8, 91–111. TIGER grants Overview (pp. –). (2015). Washington, D.C.: U.S. Department of Transportation. Wilde, J. S. Life cycle cost analysis of Portland cement concrete pavements. Austin, TX: The University of Texas at Austin. WSDOT highway construction costs (pp. –). (2016). Construction Office, Olympia, WA: Washington State Department of Transportation. WSDOT pavement policy (pp. –). (2015). Construction Office, Olympia, WA: Washington State Department of Transportation. WSDOT pavement roughness (IRI) report: 2014 (pp. –). (2016). Construction Office, Olympia, WA: Washington State Department of Transportation.
Contribution The authors confirm contribution to the paper as follows: study conception and design: Eric Jessup; data collection: You Zhou, Xiaodong Lang; analysis and interpretation of results: Eric Jessup, You Zhou, Xiaodong Lang; draft manuscript preparation: Eric Jessup, You Zhou. All authors reviewed the results and approved the final version of the manuscript. Acknowledgement This research was funded by the Washington State Department of Transportation under contract T1462-10. The authors would like to specifically thank Wenjuan Zhao, Lizbeth Martin-Mahar, David Luhr, Kim Willoughby, and Doug Brodin for their guidance and assistance throughout the project. References Average pavement life in Washington state (pp. –). (2016). Olympia, WA: Washington State
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