Managing the Increasing Demand for Freight Infrastructure: Needs versus Limited Resources

An Effort to Prioritize California’s Freight Projects Using the Strategic Highway Research Program’s Wider Economic Benefits Tool

Economic Analysis Branch

California Department of Transportation, Division of Transportation Planning, Office of State Planning

Summer 2016

DISCLAIMER

This report was prepared by the California Department of Transportation’s (Caltrans) Office of State Planning, Economic Analysis Branch as part of its professional and consultative function. The opinions expressed in this report are the branch's own and do not necessarily reflect the opinions, views, or position of Caltrans, or the State of California.

TABLE OF CONTENTSI. Executive Summary................................................................................................................................... i

II. Introduction.............................................................................................................................................1

Responding to Growing Financial Needs.................................................................................................1

Utilization of ECONWORKS-W.E.B. TOOLS..........................................................................................2

III. Expectations and Data Requirements for ECONWORKS W.E.B. TOOLS.............................................4

Shift in Scope...........................................................................................................................................4

Data Requirements for W.E.B. MODELS...............................................................................................4

IV. User Experience with ECONWORKS W.E.B. TOOLS..........................................................................10

Reliability...............................................................................................................................................10

Connectivity...........................................................................................................................................15

Market Access.......................................................................................................................................19

Accounting.............................................................................................................................................19

V. Results and Recommendations.............................................................................................................22

Cal-B/C and Reliability Prioritization Results..........................................................................................22

OTHER W.E.B. Tools results...................................................................................................................22

Outcomes and recommendations.........................................................................................................23

LIST OF TABLES

Table 1: Feedback on the EconWorks W.E.B. Tools......................................................................................i

Table 2: Cal-B/C Data Inputs........................................................................................................................4

Table 3: Reliability Tool Data Inputs............................................................................................................5

Table 4: Connectivity Tool Data Inputs........................................................................................................6

Table 5: Buyer-supplier Accessibility Tool Data Inputs................................................................................7

Table 6: Labor Markets Accessibility Tool Data Inputs................................................................................7

Table 7: Accounting Tool “Forms” Data Inputs............................................................................................8

Table 8: Accounting Tool “Output” Data Inputs..........................................................................................9

Table 9: CAL-B/C and Reliability Prioritization Results...............................................................................22

I. EXECUTIVE SUMMARYFreight movement is vital to commerce, serving as an integral part of the nation’s economic global

competitiveness. California exported over $165 billion worth of goods in 2015 through roads, railroads, waterways, seaports, and airports. The dynamics of freight transportation are changing with the emergence of e-commerce, technology, and logistic business practices. The demand for freight movement is expected to grow from natural population increases and global industrialization. Thus, the need to improve the freight transportation network is imminent in the coming years to maintain the nation’s economic global competitiveness. However, resources to improve the network are scarce. This report outlines the need to prioritize freight investments that utilize public money, while attempting to create a methodology that utilizes the second Strategic Highway Research Program’s Wider Economic Benefits (W.E.B.) of Transportation assessment tools (EconWorks W.E.B.).

Caltrans’ Economic Analysis Branch (EAB) was tasked with developing an objective prioritization method to rank and prioritize freight projects. EAB was awarded a federal grant to test the W.E.B. tools for this effort. Originally, EAB attempted to prioritize a few selected projects from the 2014 California Freight Mobility Plan’s list of over 700 projects. While collecting data, it was determined that these projects were either too conceptual or lacked enough data to run the models. Thus, EAB decided it would be best to run previously analyzed 2006 Transportation Corridor Improvement Fund (TCIF) projects, which Caltrans originally analyzed using the California Benefit-cost Model (Cal-B/C). Cal-B/C primarily assesses user benefits to passenger and commercial vehicles on the highway system by project type. However, Cal-B/C is limited in its ability to assess indirect travel benefits, especially to the freight transportation network. After completing W.E.B. TCIF project runs, EAB found:

Table 1: Feedback on the EconWorks W.E.B. ToolsTool Feedback

Inputs Outputs Practicality of Tools/ResultsReliability - Data requirements are

minimal and mirror what is required in Cal-B/C- Unique frequency duration and incident duration inputs- Frequency can be estimated using accident rate collision table- Trip duration difficult to estimate, zero used

- Accounts for recurring and incident delays to passenger and commercial vehicles- Acceptable, as results were a fraction of Cal-B/C benefit estimates as expected

- Tool is easy to use and requires minimal data- Can complement Cal-B/C

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Connectivity - Data requirements are minimal and impacted facility assumptions can be easily made- Travel time change can be made based on speed improvement estimates from Cal-B/C

- Cannot compare existing baseline performance and the project’s magnitude of improvement to a facility- The “relative connectivity index” such as freight volume and value and distinct locations are static and cannot be adjusted when calculating the “Connectivity Index”

- The “weighted connectivity” score lacks transparency- Difficult to defend if a decision maker asks what values were assumed in a facility’s “relative connectivity index”- The functions used to calculate “relative connectivity” are static and may be outdated.- Limited to current (or outdated) facility conditions and does not account for forecast assumptions

Market Access- Buyer- Supplier- Market AccessLabor Market Access

- Travel demand and forecast data inputs were not available at the prioritization stage for tested projects- Trouble finding employment center data

- Could not test either Market Access tools because data was not available

- Data inputs are rigorous and are not typically available at the prioritization stage of a project

Accounting- Reliability outputs could be fed into the tool as inputs- Connectivity outputs did not provide a no- build and build “weighted connectivity” score to insert into the tool- Market Access inputs were not tested- Uncertain how to determine elasticity calculations within tool- Gross regional product data is accessible and applied in the tool

- Reliability and Connectivity tools output differ from Accounting tool benefit estimates- The “Accounting” tool may need to be renamed because it is more than aggregating the benefits of the other three models- Accounting outputs were magnified compared to the other tool outputs

- Some cells are hard coded and uncertain if tool makes calculations as expected- Need technical document for this tool to clarify inputs such as calculating elasticities- Tool does more than aggregating benefits, thus, may need to be renamed to signify that the tool captures gross regional production benefits

Overall, the reliability tool can complement Cal-B/C when prioritizing freight projects. The connectivity, market access, and accounting tools may need refinement to better illustrate economic impacts and assist with a prioritization effort. Some of the data requirements to run W.E.B. tools may go beyond what is available for a project prioritization effort. For example, Caltrans may not conduct a travel demand analysis until the later stages of a project proposal. This type of analysis depends on the resources and expertise available for each district. If such robust data requirements are needed to run the W.E.B. tools, such as a travel demand model, users may wish to use more comprehensive and dynamic economic impact models to conduct their analysis. W.E.B. tools have the potential to be valuable to transportation practitioners if the tool developers curtailed the amount of robust data requirements. As a result of utilizing W.E.B., Caltrans will begin exploring the idea of using the reliability tool to complement Cal-B/C, while seeking to use a dynamic economic impact model to account for connectivity and market access.

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II. INTRODUCTIONThe Federal-Aid Highway Act of 1956 laid the foundation for developing the interstate highway

system. A combination of growth in population, passenger and commute travel, international trade, and freight delivery over the last 60 years have strained this now aging and largely outdated infrastructure network. The Federal Highway Administration (FHWA) and the American Transportation Research Institute reported in 2011 that 15 of the 250 major national freight chokepoints and bottlenecks are in California. This is a pressing concern considering that U.S. freight volume is expected to grow by 45%, from 2015 to 2040, to 29 billion tons.

In 2013, the rail transportation industry responded to this anticipated demand by allocating $14 billion to facility or infrastructure improvements such as rail yards, refueling stations, and additional tracks. The industry hopes this investment leads to improved speed, efficiency, cargo handling, and the flexibility to meet the future demand for freight movement. Decision makers for highways, unlike those in the mostly privatized rail industry, are financially constrained (limited resources) and must ensure that limited taxpayer dollars are spent judiciously on facility and infrastructure projects. An increase in both passenger and freight highway travel demand, coupled with financial constraints, magnifies the need to responsibly allocate resources to meet tomorrow’s freight transport demands.

RESPONDING TO GROWING FINANCIAL NEEDSCalifornia legislators have acknowledged that a significant financial shortfall exists to maintain and

enhance the state’s highway system—an estimated $59 billion in maintenance alone over the next 10 years.1 The legislature is attempting to address this shortfall through bill proposals such as increasing the vehicle fuel tax and license and registration fees (Senate Bill 16, 2014),2 or possibly replacing the vehicle fuel tax structure (SB 1077, 2014).3 Even if transportation revenues were to increase, there is an emphasis by legislators and the public to spend these resources in a cost-effective manner. Thus, the need to develop a pragmatic methodology when prioritizing and ranking projects.

PUSH TO IDENTIFY AND PRIORITIZE NEEDSThe California Department of Transportation (Caltrans) developed the 2014 California Freight

Mobility Plan (CFMP) to align with the Moving Ahead for Progress in the 21st Century Act’s Section 1118 and California Assembly Bill 14 (2014) initiative to develop a statewide freight plan. Within the CFMP, Caltrans compiled a list of 707 projects—valued at $138 billion—to identify future freight needs.4 This effort reinforced the need to objectively assess and prioritize transportation projects. California Governor Edmund

1 Cadelago, C. (2015). Gov. Jerry Brown wants Investment in California Roads. Sacramento Bee. Retrieved from http://www.sacbee.com/news/local/transportation/article5474097.html.2 Office of Senate Floor Analyses. (2015). Third Reading - Transportation Funding. California Senate Rules Committee. Retrieved Jan. 19, 2016 from file:///C:/Users/s134370/Downloads/201520160SB16_Senate%20Floor%20Analyses-%20(1).pdf.3 Office of Senate Floor Analyses. (2015). Unfinished Business. California Senate Rules Committee. Retrieved Jan. 19, 2016 from file:///C:/Users/s134370/Downloads/201320140SB1077_Senate%20Floor%20Analyses-.pdf.4 Office of Freight Planning. (2014). California Freight Mobility Plan. Retrieved on Jan. 18, 2016 from http://dot.ca.gov/hq/tpp/offices/ogm/cfmp.html.

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G. Brown Jr. signed two Executive Orders (EO), B-30-15 and B-32-15 in 2015. EO B-30-15 requires state agencies to “take climate change into account in their planning and investment decisions, and employ full life-cycle cost accounting to evaluate and compare infrastructure investments and alternatives.” The second, EO B-32-15, calls for the development of clear targets to improve freight efficiency, transition to zero-emission vehicle technologies, and to increase the competitiveness of California’s freight system. The number of proposed projects in the CFMP, lack of available funds to complete them, and the goals set forth in the EO’s signifies that Caltrans, and its partner agencies, must develop methods to prioritize projects that support an efficient and competitive freight transportation system. Moreover, the creation of a project prioritization methodology aligns with Caltrans’ mission to “provide a safe, sustainable, integrated and efficient transportation system to enhance California’s economy and livability and vision to create a performance-driven, transparent and accountable organization that values its people, resources and partners, and meets new challenges through leadership, innovation and teamwork.”

UTILIZATION OF ECONWORKS-W.E.B. TOOLSIn an effort to meet the goals stated above, Caltrans’ Economic Analysis Branch (EAB) applied for and

was awarded a Second Strategic Highway Research Program (SHRP2), Implementation Assistance Program, Wider Economic Benefits (W.E.B.) analysis tools grant (Round 4) in the summer of 2015. The Statement of Work proposed applying the EconWorks-W.E.B. tools to sample projects identified in the CFMP, in combination with Caltrans’ Benefit-Cost Analysis Tool (Cal-B/C), to develop a freight project prioritization method. The hope was to capture both user benefits and wider economic impacts, providing a more robust understanding of the impacts associated with individuals, groups, or projects. EAB also sought to develop simple reportable results that would be accepted by policy and decision makers.

MAKING THE CALIFORNIA BENEFIT-COST MODEL ROBUSTCal-B/C is publicly accessible and has been used by a multitude of stakeholders to analyze user

benefits and costs of transportation projects for nearly two decades. The tool measures traditional transportation benefits such as travel time savings, vehicle operation cost savings, safety benefits, and emissions reduction benefits over a 20-year period. Monetary results are reported in net present value terms using an applied discount rate. Since the 1990s, Cal-B/C has been updated numerous times, with the current version being 5.0. Prior to the latest update, the EAB researched methodologies on travel time reliability, particularly freight reliability to incorporate into Cal-B/C. At that time, widely accepted approaches to forecast travel time reliability did not exist. Even to this day, this concept is not measured in the latest version of the tool. Over time, however, there have been other significant research advancements toward assessing reliability, connectivity, and market access in the evaluation process of a transportation project.

Consequently, EconWorks-W.E.B. suite of tools is a pillar of new emerging transportation literature, combining the ability to assess travel time reliability, connectivity to intermodal facilities for freight and passengers, and accessibility to labor and supply chain markets through accessible Excel worksheets. Some inputs and outputs identified in the W.E.B. tools and Cal-B/C are identical, making it plausible to develop a prioritization method that utilizes both tools.

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Whether it is keeping California competitive or facing scarce financial resources, effectively prioritizing projects is critical to meet tomorrow’s freight movement demand, while supporting the local, state, and national economy. The revenue shortfall for maintenance of the transportation system alone underscores the need for decision makers to wisely allocate resources. It is the goal of this grant project to demonstrate if the W.E.B. tools can be utilized to help decision makers prioritize freight projects. Moreover, these tools have the ability to expand upon the analysis of Cal-B/C by analyzing broader economic impacts. In the following sections, this report outlines the W.E.B. expectations, experiences, limitations, and results and recommendations.

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III. EXPECTATIONS AND DATA REQUIREMENTS FOR ECONWORKS W.E.B. TOOLS

Caltrans’ goal for this project was to establish EconWorks W.E.B. tools as an additional means to evaluate and objectively prioritize freight infrastructure projects. EAB initially proposed collaborating with Caltrans’ freight branch to gather and collect necessary data from a selected list of freight projects to run the W.E.B. tools. However, as discussed in the next section, minimal data was available for projects identified in the CFMP; therefore, Caltrans used a list of previously analyzed freight projects for this evaluation process.

SHIFT IN SCOPEAs work proceeded, it became apparent that many of the projects listed in the CFMP were in the

early conceptual stage, resulting in minimal available data to run the W.E.B. tools. EAB exhausted all means available to analyze projects from this list. EAB attempted to collect baseline data from Caltrans’ Performance Measurement System (PeMS). PeMS is a real-time data collection system that continuously reads data from censors located on the state’s highway system. Current and historic traffic counts are stored in a database that shows existing traffic conditions throughout the course of a day, or year, by time intervals. This database provided EAB with a baseline for current conditions, but a project’s improvement expectations could not be determined. In addition, resources were not available to collect travel demand data and other inputs necessary to complete the analysis for the W.E.B. tools, or Cal-B/C.

As a result, EAB decided to run the W.E.B. tools using Transportation Corridor Improvement Fund (TCIF) projects that were previously analyzed between 2006 and 2007 using Cal-B/C. The TCIF projects had the necessary data required to run some of the W.E.B. tools. Even though the analyses are outdated, similar projects are being proposed today. This change in scope was beneficial, allowing EAB to compare W.E.B. and Cal-B/C results. By using TCIF projects, EAB could still attempt to develop a freight project prioritization methodology.

DATA REQUIREMENTS FOR W.E.B. MODELSCaltrans engineers or project managers have provided EAB with Cal-B/C data requirements for more

than 20 years. Some of the Cal-B/C data requirements are applicable to run the W.E.B. tools, but in some cases, additional data is required, which is problematic. The following sections provide an overview of the requirements to run each tool, and describe the level of difficulty in gathering data.

CAL-B/C DATA REQUIREMENTSCaltrans staff can readily provide the following data when conducting benefit-cost analysis using

Cal-B/C:Table 2: Cal-B/C Data Inputs

Type of project, e.g., lane addition, passing lane, pavement rehab, etc.

Roadway type

Traffic lane type, e.g., general purpose lane, high occupancy lane, toll lane, etc.

Location and segment distance

Construction period in years Peak travel period in hours

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Free-flow speed Accident dataNo build (status quo) and build (project implementation) traffic growth estimates

Current and forecasted average daily travel by personal and commercial vehicles

Project cost

W.E.B. – RELIABILITY T O O L DATA REQUIREMENTSThe reliability tool (Reliability) mirrored Cal-B/C’s data requirements and TCIF projects. Most of

Reliability’s data inputs were readily available with a few exceptions:

Table 3: Reliability Tool Data InputsInput Comments

Time horizon - Set to 20 years to match Cal-B/CAnalysis period - 6AM to 7PM timeframe was chosen to best match Cal-

B/C’s daily and annual analysisHighway type - Generalized input when compared to Cal-B/C’s detailed

“Project Type”Post miles - Based on reports, project managers, Google MapsNumber of Lanes (one-way) - Based on reports, or project managers, or Google MapsFree flow speed - Based on project reports, project managers, PeMS, or

speed limitCurrent average annual daily traffic - Obtained from reports, project manager, traffic counts,

or PeMSEstimated annual traffic growth rate - Provided by project manager, or reportsPercent trucks in traffic - Based on traffic count data, reports, project manager, or

PeMSCapacity calculations - Cal-B/C passenger cars per hour per lane differed slightly

•For example, freeway and general purpose lane capacity in Cal-B/C is 2,000 while capacity for speeds less than 70 miles per hour is 2,300 in Reliability

- Suggested Reliability Highway Capacity Manual assumptions were used

Terrain - Not an option in Cal-B/C, but it was tested for this effortPersonal and commercial travel time - Can be adjusted to Cal-B/C rates

- Used default values in this trialEffect of incident management strategy - Change in incident frequency was estimated as

percentage change between Cal-B/C’s no-build and build accident rates

- Incident duration was not estimated since it was not cited in project reports nor do project managers know how to estimate this

Reliability ratio - Unique data input that cannot be estimated since it is not currently measured nor is there an established method for measurement

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- Default Reliability values were used

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W.E.B. – CONNECTIVITY T O O L DATA REQUIREMENTSThe data requirements to run the Connectivity tool (Connectivity) were straight forward. However,

the determination of which freight facilities would be impacted in a given project was estimated and not definitively known. This type of data is difficult to obtain and may not be available for a majority of projects. The Top three facilities were selected based on their size and proximity to the impacted project and region. Thus, maps, traffic volumes, and travel assumptions were used to estimate data input requirements. Most of Connectivity inputs were readily available with a few exceptions:

Table 4: Connectivity Tool Data InputsInput Comments

Intermodal facility - Impacted facilities determined based on their size and proximity to the project’s location

- Rail facilities were excluded because unit lift capacity for the rail yards were not available

Distance of improvement from facility - Determined using Google MapsNumber of trucks within study area - Based on Cal-B/C’s “Percent Trucks” in traffic

- Reviewed truck traffic volume around the closest analyzed facility to ensure the entered total did not exceed the project segment’s truck volume

- The project’s segment volume was used if the facility truck volume was a higher amount

Hours saved per truck - Cal-B/C speed improvement calculation estimate for trucks was used

Value per truck hour saved - Used default value for this trial effort- May use California-specific value later by using Bureau of

Labor Statistics data, which includes Californian crew (driver labor) cost but not freight logistics cost

Fraction of trucks related to facility location

- Used default values, which are based on a distance-decay-factor formula

W.E.B. – MARKET ACCESSIBILITY T O O L DATA REQUIREMENTSMarket access is the concept that an improvement in the transportation network leads to overall

growth in economic productivity. Conceptually, the economic impact and benefit-cost analytical techniques should be given individual consideration and incorporated into a total economic finding when prioritizing projects. Trip destination data gathering for the market access tool (buyer-seller and labor market models) was not possible due to the lack of travel demand data for TCIF projects. The project’s impact area(s), or influential boundary, could not be determined because this type of data was not reviewed during the original analysis, nor does a benefit-cost analysis require this type of data. Thus, the market access tool (Market Access) could not be run. Below describes each required variable and the level of difficulty in obtaining data:

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Table 5: Buyer-supplier Accessibility Tool Data InputsInput Comments

Impedance decay factor - Technical document states typical range is from 0-5- It is a function of distance, travel time, skims, or costs- Could not determine a value for this since we had no

commuting profiles nor suggested valuesBase and reference years of analysis - Easily determinedProductivity elasticity - Suggested values are provided for population,

employment, and manufacturingActivity data - Current and forecasted population or labor pool data

can be determined through databases or reports such as, the U.S. Census, U.S. Bureau of Labor Statistics, U.S. Bureau of Economic Analysis (BEA), California Department of Finance, California Employment Development Department

Impedance data - Required skim matrices to develop a “no-build” and “build” origin-destination trip estimate by zone

- Could not come up with impedance data since origin0destination data was not required for TCIF projects and TCIF project-by-project travel volumes were inconsistent with the recently developed statewide travel demand model (data collection year and model development year)

Gross regional product data - Requires metropolitan statistical area data (available from BEA) or average annual wages for small regions (available in Caltrans’ county-level socioeconomic forecast reports

Table 6: Labor Markets Accessibility Tool Data InputsInput Comments

Year of analysis - Determined using project reports or managersClassify site/location by industry - Not available for TCIF projects

- Ideally used to analyze industry dependent on commercial transportation

Type of labor force - Population data is more easily obtainable than employed labor force by place of work or residence

Sub-category of data - County-level U.S. Census or California sub-category population breakdown can be used as an estimate

Threshold impedance - Distance or time spent traveling can be estimated at the county-level using Caltrans’ socioeconomic forecast or the American Community Survey

Commuter trip and corresponding percentage

- Difficult to determine at the county-level for TCIF projects

Wage per hour/ value of time - California specific values, based on Cal-B/C technical documents, can be determined

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Average speed - Determined through project reports and managers, or PeMS

Employment centers and labor market - Number of employment centers/sites in a region could not be determined

- Number of employment for all industries within an identified employment center could not be determined

- Recommendations on how to obtain these data requirements may need to be included in the technical document

Impedance and the trip table - TCIF projects did not require origin destination impedance or trip estimates and could not be determined

W.E.B. – ACCOUNTING FRAMEWORK DATA REQUIREMENTSThe EconWorks W.E.B. Accounting Framework tool (Accounting) serves as a way to aggregate direct

benefit-cost and wider economic impact results. By using the Accounting tool to aggregate the two types of analytical techniques, this could complement traditional Cal-B/C direct user benefit results. Thus, the analysis of a project would be more robust when prioritizing freight projects. Accounting focuses on aggregating the benefits of four different types of general project classifications: capacity expansion, new residential areas to employment centers enhancement, truck delivery market area enhancement, and truck movement to/from air, marine or rail terminals. The type of project being analyzed determines which W.E.B. tool should be run. Below is a description of the level of difficulty in gathering data inputs that are needed to run the tool:

Table 7: Accounting Tool “Forms” Data Inputs Input Comments

Standard travel benefits - Persons per trip, vehicle operation costs, value of time per person, and average cost per crash; available in Cal-B/C

Wider benefit Assumptions - General range provided for elasticity factors- Technical document should explain how to determine a

value within the suggested ranges, e.g., by industry elasticity

Traffic impact - Vehicle-miles of travel (VMT), which is determined by traffic volume and segment length

- Vehicle-hours of travel, which is determined by traffic volume, distance, and speed

- Crashes per 100,000 VMT, which is estimated using collision data tables

Reliability - Incident equivalent delay and cost of unreliability; both easily transferred

Effective density access - Tool could not be tested; left value as zeroIntermodal connectivity - Connectivity tool computed only a single “net

connectivity weighted value”, with no mention of “build” and “no-build” values

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•Calculations were made to estimate these two values—see “Build and No Build Relativity Calculation” (p. 21) for details

Table 8: Accounting Tool “Output” Data InputsOutput Comments

Traditional travel benefits - Multiplier values are hard-coded- According to reference notes, values are pulled from the

“Forms” tab and “GDP Conversion” tabWider economic benefits - Multiplier value and elasticity values are hard-coded and

the formula may not be functioning properly- According to reference notes, values are pulled from the

“Forms” tab and “GDP Conversion” tabGross regional product conversion - The number of regions allowed appeared to be limited

to two, which could pose a problem in analysis involving multiple regions

The following sections discuss how Reliability, Connectivity, Market Access, and Accounting were utilized for this trial effort.

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IV. USER EXPERIENCE WITH ECONWORKS W.E.B. TOOLSThe success of using Reliability, Connectivity, Market Access, and Accounting to assess projects was

mixed. This section will describe the effort needed to utilize each tool’s feasibility and results. Note: the values used in the example runs for each of the W.E.B. Tools come from the highlighted “Truck Passing Lanes” project in the B/C ranking chart (table 9) near the bottom of pg. 22.

RELIABILITYReliability is the most straightforward of the three EconWorks W.E.B. tool components. The data

requirements, functionality, and results were easy to use and interpret and capable of complementing Cal-B/C. The reliability component—incident frequency and duration—utilizes the same data inputs required to conduct analyses using Cal-B/C. The TCIF projects’ Cal-B/C inputs were easily transferred to run Reliability, and outputs for the current and future years were converted, in a separate Excel spreadsheet, to annual figures. The annualized figures were then inserted into the original Cal-B/C analysis to account for incident frequency and duration benefits. However, there are ambiguities in Reliability, which created uncertainty as to the robustness of the tool. For instance, Reliability categorizes lane-additions, such as on-ramps, truck climbing lanes, passing lanes, etc., as simply an additional lane, regardless of the difference in the types of traffic and speeds on different types of lanes.

In running various projects in the reliability tool, it became evident that there is a hardcoded lower-limit in traffic per lane, beyond which no reliability benefit/delays are detected. While it is logical that streets with little traffic volume are not likely to be affected by related delays, reliability benefits—defined as extra time “cushions” that users observe to be on time—would be present even on more remote stretches of road. This is especially plausible if the segment is plagued with frequent accidents or frequent traffic stops. In addition, Reliability’s analysis focuses on weekday travel ranging between 6am to 7pm, which is the majority timeframe susceptible to delay costs. However, it would be beneficial to include a daily analysis timeframe that includes weekends, as California’s traffic counts are typically reported in daily terms.

Based on the TCIF project analyses conducted, benefit figures from Reliability tended to be within 20-30% of traditional travel-time-savings benefits. Most TCIF projects, unless they were specifically aimed at accident prevention/clearing, only provide figures on existing traffic flow and growth and other measures associated with traditional travel-time benefits. Reliability requires incident frequency and duration inputs, which is unique and differs from traditional transportation benefit-cost models. However, the Reliability benefit figures for this trial of TCIF analyses only captures incident frequency improvement. This is reflected in the tool by taking the difference between build and no build roadway design accident collision rates. Incident duration improvement is not typical data that are analyzed at a project prioritization level; therefore, an input value of zero was assumed within the tool. Thus, the reported benefit figures may be conservative because incident duration improvement was not accounted.

INCORPORATING RELIABILITY RESULTS INTO CAL-B/C TO PRIORITIZE PROJECTSThe results reflected in Reliability can be incorporated into Cal-B/C to complement the overall

benefit-cost results, as an improvement in incident frequency or duration yields travel time savings. Reliability benefit figures were combined with Cal-B/C results to come up with a more robust analysis. The current and future Reliability benefit figures were linearly annualized over 20 years and inserted into Cal-B/C. In addition, a 5% discount rate was applied to the Reliability results to be consistent with Cal-B/C (see

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below). The adjusted reliability results were then inserted into Cal-B/C’s calculation page to account for Reliability, and a new benefit-cost analysis was generated. As a result, the overall benefit-cost ratio increased by fractions of a point. By accounting for reliability, projects may be considered that were once on the cusp of being funded.

CAL-B/C AND RELIABILITY INTEGRATION EXAMPLEThis section provides an illustrative overview of how Cal-B/C and Reliability were integrated to

provide a more robust benefit-cost analysis.

CAL-B/C INPUT PAGE:

Base (Year 1) and Forecast (Year 20) ADT are used to calculate a geometric growth rate for Reliability

Percent Trucks is applied directly into Reliability Highway Free-Flow Speed is used as the speed in Reliability, (speeds with values of 55, 65, or

70 are assumed to be stated speed limits) Differences in Accident Rate (per million vehicle-miles) are used as incident reduction in Reliability

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(in this case (1.80−0.60)

1.80=23=66.67 %)

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RELIABILITY NO-BUILD INPUTS:

RELIABILITY BUILT INPUTS:

No. of Lanes (One-way) increased from 4 to 6 with the addition of the truck passing lanes Commercial Travel Time Unit Cost (per vehicle hr.) has been changed from default to CA values

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RELIABILITY CURRENT-YEAR RESULTS:

Only the difference between build and no-build Commercial Delay under Total Annual Weekday Congestion Costs is used since it is a freight-benefits focused study

RELIABILITY FUTURE-YEAR RESULTS:

For the sake of simplicity, as mentioned in the report, the 20-year aggregate reliability benefit is estimated by calculating a geometric growth between Future year – 2035 (the Future year – 2022 displayed in red is a bug with the Reliability) and Current year – 2035 values

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RELIABILITY DISCOUNTED AGGREGATE (SPREADSHEET MADE BY EAB):$ Cost Values

Future $ Equivalent Commercial Delay No Build Build

Discount Rate

Present Recurring Equivalent Delay $1,269,672 $123,828 5%Present Incident Equivalent Delay $297,940 $7,239Future Total Equivalent Delay $18,141,900 $4,800,714Future Incident Equivalent Delay $7,617,968 $1,632,238

Year 1 Results $1,567,612 $131,067 Reliability Tool Outputs

Year 20 Results $25,759,868 $6,432,952

Percentage ChangeNo Build Build

15% 21%

Current Dollars 5% Discount DollarsNo Build Build Difference No Build Build Difference

1 1,803,117

159,235 1,643,882

1,717,254

151,652 1,565,6022 2,074,00 193,457 1,880,54 1,881,18 175,471 1,705,71

3 2,385,58 235,034 2,150,54 2,060,75 203,031 1,857,72

4 2,743,97 285,546 2,458,42 2,257,47 234,919 2,022,55

5 3,156,203

346,914 2,809,289

2,472,967

271,816 2,201,1516 3,630,364 421,471 3,208,893 2,709,03 314,508 2,394,52

7 4,175,759 512,051 3,663,708 2,967,634 363,905 2,603,72

8 4,803,089 622,099 4,180,990 3,250,920 421,061 2,829,859

9 5,524,664 755,797 4,768,867 3,561,248 487,194 3,074,054

10 6,354,643 918,229 5,436,414 3,901,199 563,713 3,337,486

11 7,309,310 1,115,5 6,193,740 4,273,602 652,251 3,621,351

12 8,407,399 1,355,32 7,052,075 4,681,554 754,695 3,926,859

13 9,670,455 1,646,603

8,023,852 5,128,449 873,229 4,255,220

14 11,123,261 2,000,48 9,122,779 5,618,003 1,010,3 4,607,623

15 12,794,325 2,430,41 10,363,909 6,154,289 1,169,07 4,985,217

16 14,716,436 2,952,75 11,763,686 6,741,769 1,352,68 5,389,080

17 16,927,308 3,587,340

13,339,968 7,385,328 1,565,145

5,820,184

18 19,470,322 4,358,31 15,112,009 8,090,321 1,810,96 6,279,352

19 22,395,377 5,294,98 17,100,397 8,862,611 2,095,40 6,767,208

20 25,759,868 6,432,95 19,326,916 9,708,623 2,424,51 7,284,112

Aggregate 185,225,457 35,624,564 149,600,893 93,424,215 16,895,614 76,528,601

5% discounted is used in Cal-B/C for the TCIF projects tested for this EconWorks W.E.B. trial

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CONNECTIVITYConnectivity was more demanding to run than Reliability and interpreting the model’s inputs,

freight facility assumptions, and outputs were difficult to comprehend with the simplistic user guide. The lack of descriptive guidelines limited the ability to obtain necessary data and reduced the number of projects that were analyzed. Overall, the tool’s values appear static and locked, which may be problematic if there is a shift in the usage of a facility. When a value can be adjusted, there is a lack of detailed guidance. For example, the Connectivity technical document cites a default $86 value per truck hour saved was ascertained from a 2012 urban mobility report (Schrank et al. 2012). However, within the tool, a default value of $57 is assumed. Moreover, guidance on how to calculate state specific crew and freight logistic costs would be helpful, as it is assumed that California would have a higher freight cost than the national average.

At the prioritization level for projects, trip origin-destination is not assessed, making it difficult to determine which hub(s) should be analyzed in the tool. As a result, the three closest and largest airport or marine facilities to a given project were analyzed. However, in some cases, it is possible that a project’s segment exclusively serves as an access point to a smaller facility. The hub impact analysis determination was arbitrarily kept to the closest and largest facilities as a result of no origin-destination data. This issue could be alleviated having planners begin thinking about the origin-destination of travelers using a proposed project’s segment.

The decay factor that models truck traffic from hubs is of equal concern because there is a lack of directional travel consideration when distance and volume are part of the calculation. It is unclear if the tool assumes that there would be equal amounts of freight movement to facilities on a given segment in the direction of a major metropolis or another hub. For example, if a highway has 10,000 trucks and the Port of Stockton is closer than the Port of Oakland from a proposed segment improvement, it is unknown how the tool assigns trucks to facilities, i.e., decay factor assigns 8,000 trucks to the Port of Stockton and 2,000 trucks to the Port of Oakland. Further guidance is needed to explain how truck volumes are assigned or associated to a facility rather than a general decay factor function. Moreover, a lack of considering the factors of directional freight movement could lead to skewed results if trucks are utilizing facilities that are farther away than ones that may be closer.

UNABLE TO USE CONNECTIVITY RESULTS TO PRIORITIZE PROJECTSThe greatest challenge with Connectivity was interpreting the results. Connectivity presents its

results as a unitless “weighted connectivity” score, with no directions as to how this could be monetized. In fact, the accompanying W.E.B. Accounting spreadsheet makes no mention of this “weighted connectivity.” In its place, the user is required to input the connectivity scores for the “Build Scenario” and “No Build Scenario”—values that are not provided in Connectivity. In consultation with the W.E.B. developer, “build” and “no build” connectivity scenarios were estimated, albeit through a separate calculation, by equating the ratio of “weighted connectivity” to differences in speed improvements and total travel time between the segment and the hub. See Build and No Build Relativitity Calculation, p. 21.

Overall, a transparent and monetized weighted connectivity result is necessary when evaluating a project. The technical document only states that a high score means there are more levels of connectivity. It is unclear as to what monetized values are associated with “weighted connectivity,” and may lead to questioning how the score was generated. The weighted connectivity score should be translated into

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monetary terms, so that the tool’s results compare to other benefit-cost or wider economic impact analysis models and tools.

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CONNECTIVITY USAGE EXAMPLEAs mentioned above, running Connectivity was easy, but interpreting the data requirements and

outputs proved to be challenging when trying to find a common connection between other tools and models.

CONNECTIVITY FACILITY SELECTION:

The EAB decided to use the three closest major intermodal facilities instead of simply the three nearest ones

The EAB avoided using rail facilities since Unit Lift Capacity data could not be obtained

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CONNECTIVITY INPUTS:

The inputs required are the same across all three facilities Distance of Improvement from Facility (miles) is calculated by Google Maps Number of trucks within study area is calculated by multiplying Base (Year 1) ADT from Cal-B/C

by Percent Trucks Hours saved per truck is obtained by calculating the difference in travel time on the improved

segment between build and no-build (length of the improved segment is divided by build and no-build speeds on the improved segment in Cal-B/C in five years)

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CONNECTIVITY RESULTS:

Note that there is only a single Weighted connectivity score, no base vs. improved21

MARKET ACCESSMarket access may not be suitable for the prioritization phase because of the required detailed data

inputs. This type of data was not requested when originally analyzing TCIF projects. When attempting to gather the missing data, it was difficult or not possible to collect regional zone activity values, origin-destination trips, gross regional product, and employment/labor force data. A potential solution to this issue would be to collect this type of data at the sketch level phase. If accessibility were to be included when prioritizing projects, there may need to be an “accessible” alternative to circumvent the required origin-destination trip table. This may be done, if plausible, by establishing rule of thumbs that users can apply for this requirement.

The trip modeling requirements for this tool are onerous for most local district offices at the planning-prioritization phase. As it stands, the accessibility component can only be used on major infrastructure projects where data is likely to be available. The tool’s data requirements are also similar to what is required to run more comprehensive economic impact models/software. The comprehensive economic impact model/software requires less effort to gather data inputs when measuring an areas market, trade, and labor pool accessibility. Thus, this tool may be more beneficial to users if the tool required less data, serving as a bridge between EconWorks Case Studies (C03) and other comprehensive economic impact models/software. As a result of the difficulty in gathering data, this tool could not be utilized.

ACCOUNTINGThe accounting tool accompanying the three EconWorks W.E.B. tools appears to be unfinished. Some

values in the spreadsheet are hard-coded instead of being derived from formulas as identified within the tool, e.g., the “4a-Output” tab’s multiplier values (Cells G4-G8, etc.) and elasticity values (I7-I8, etc.). It is worth noting that the monetized values for reliability are different in the accounting tool than values calculated natively in Reliability due to differences in value of time multipliers. Furthermore, only “incident delay hours” is required for Accounting; there is no explanation as to why “recurring equivalent delay”—which is much higher than incident delay for most projects—is not considered. In addition, Connectivity benefits for projects in wealthier counties like San Francisco and Los Angeles are suspiciously high, sometimes into the hundreds of millions. This may be due to Connectivity results being monetized by applying the percentage improvement in connectivity to the economic activity levels of the surrounding counties.

UNABLE TO USE THE ACCOUNTING TOOL TO PRIORITIZE PROJECTSThe accounting tool is a critical piece, as it is a way normalize benefit-cost results and wider

economic impact results into a monetary format. However, there is a lack of confidence in reporting the results due to the uncertainty of the tool such as the hard-coding of formulas.

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ACCOUNTING USAGE EXAMPLEThis section illustrates the data requirements and outputs within the Accounting tool.

GSP CALCULATION:

Affected counties are selected based on closest geographic proximity to project Gross regional product and wage data were pulled from Bureau of Economic Analysis website

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BUILD AND NO BUILD RELATIVITY CALCULATION (SPREADSHEET MADE BY EAB):

No Build Scenario and Build Scenario Weighted Connectivity Scores are calculated by assuming the following:

WeightedConnectivity output∈ConnectivityNoBuildWeightedConnectivity Score

= minutes saved per truck on the new faciltytotal travel timebetweenthe intermodal facility∧the improved segment

ACCOUNTING BENEFITS CALCULATIONS:

Accounting requires Weighted Connectivity Scores for No Build Scenario and Build Scenario, but Connectivity only produces a single Weighted Connectivity output

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V. RESULTS AND RECOMMENDATIONS

After testing all of the components of EconWorks W.E.B. tools, Reliability is the most feasible tool that can complement Cal-B/C when attempting to prioritize projects. Cal-B/C and Reliability outputs are reported in common monetary terms, which is critical when attempting to rank projects. Connectivity and Market Access concepts are important to consider, but at this moment, the rigorous data requirements to run the tools or determine how to interpret the results present a challenge. Moreover, without interpretable monetary outputs, Caltrans would need to make an internal decision on how much weight each tool should be given if the reportable results are not the same. For example, an internal decision must be made to determine how much value should be placed on travel time savings over a better weighted connectivity score. Without guidance and concerns with some of the tools results, Reliability was the only tool used to complement Cal-B/C’s prioritization analysis.

CAL-B/C AND RELIABILITY PRIORITIZATION RESULTS

Overall, Reliability benefit is a fraction of the benefits that Cal-B/C projects. When comparing the benefits of Cal-B/C and Reliability alone, the prioritization of projects differed. The preferred method of combining the two tools together resulted in no prioritization change when compared to Cal-B/C results alone. Thus, the preferred method of prioritizing projects would be to combine the two tools, where Reliability complements Cal-B/C. In some instances, this method may be beneficial to projects that are on the cusp of being funded without the consideration of reliability. Also, if incident duration could be determined for each project, it is likely the reliability outputs and overall benefit-cost ratio would increase.

Table 9: CAL-B/C and Reliability Prioritization ResultsProject

DescriptionLength(miles)

Project Cost($1,000,000)

ProjectBenefits

($1,000,000)

B/CRatio

B/CRank

ReliabilityBenefits

($1,000,000)

ReliabilityB/C

Reliability B/C Rank

Reliability/Traditional

Benefits

Traditional/ Reliability

B/C

Traditional/Reliability B/C Rank

Operational Improvements 0.8 90.5 18.9 0.21 8 1.5 0.02 8 0.1 0.23 8

Truck Climbing Lane 3.3 62.8 188.6 3.00 3 49.9 0.80 2 0.3 3.80 3

Route Improvement Project

4.4 76.2 91.6 1.20 5 1.1 0.01 9 0.0 1.22 5

Widening/Capacity Improvement

12.7 32.6 161.9 4.97 2 2.6 0.08 4 0.0 5.05 2

Interchange 1.0 87.0 21.8 0.25 7 3.8 0.04 5 0.2 0.29 7Truck Passing Lanes 4.9 107.6 838.8 7.79 1 76.5 0.71 3 0.1 8.51 1

Bridge Replacement 2.1 837.4 44.7 0.05 9 21.9 0.03 7 0.5 0.08 9

Widening & Interchange Reconstruction

3.0 227.7 530.0 2.33 4 189.1 0.83 1 0.4 3.16 4

New Hwy Segment 5.0 390.3 345.7 0.89 6 12.8 0.03 6 0.0 0.92 6

*Note: The above projects are actual, completed TCIF projects, with names hidden. The blue highlighted “Truck Passing Lanes Project” was used for the example runs found in the previous sections

OTHER W.E.B. TOOLS RESULTSAs mentioned, the connectivity and market access tool could not be utilized due to the limited amount

of travel data available for projects. FHWA and two other SHRP2 W.E.B. (C11) grant recipients—Connecticut’s Department of Transportation and the Rhode Island’s Statewide Planning Program—were contacted in an effort to seek EconWorks W.E.B. assistance. After speaking with each agencies on multiple occasions, it was determined that Connectivity, Market Access, and Accounting results were achievable, but there was a lack of

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confidence in utilizing the results for project prioritization purposes.OUTCOMES AND RECOMMENDATIONS

The concepts that the EconWorks W.E.B. tools attempt to account for are critical to developing a more robust and comprehensive project prioritization method. However, the amount of data needed to run most of the tools and the lack of common monetary units needed to aggregate a uniform prioritization value makes it difficult to integrate or compare benefits with other tools and models. Moreover, practitioners may find using a dynamic economic impact model more beneficial to run as opposed to the static W.E.B. tools with similar and comprehensive data inputs required to run either tool/model. It would be beneficial for practitioners if W.E.B. tools could require fewer data inputs, such as travel demand model data, to function. This could be done by possibly generalizing travel conditions and making assumptions for data requirements to run the tools.

As a result of this effort, Caltrans will explore other SHRP2 planning tools such as PlanWorks, and TravelWorks analytical tools. The American Association of State Highway and Transportation Officials’ (AASHTO) Matt Hardy, Program Director for Policy and Planning, provided an overview and hands-on training session of these tools for Caltrans management and staff on June 7, 2016. Data input requirements have become robust, as new tools and models become available. It may be of interest for Caltrans to review available tools and models and identify existing data shortfalls to ensure they can be utilized. While working with staff, it is evident that robust data such as travel skims are not readily available for projects at the planning, programming, or prioritization phase.

Reliability is a tool that already fits these parameters, as there is minimal data needed to run the tool and outputs are presented in monetary terms. This discovery is one of the successes that the EAB experienced in test W.E.B. tools. As a result of having success and confidence in the tool, the EAB utilized Reliability in its benefit-cost analyses for Caltrans’ Fostering Advancements in Shipping and Transportation for the Long-term Achievement of National Efficiencies grant applications. Moreover, the EAB will explore the possibility to better incorporate Reliability into Cal-B/C during the next update.

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