Development of a Multimodal Tradeoffs Methodology for Use in Statewide Transportation Planning

Transcription

1 Final Report Development of a Multimodal Tradeoffs Methodology for Use in Statewide Transportation Planning Requested by American Association of State Highway and Transportation Officials (AASHTO) Standing Committee on Planning Prepared by Cambridge Systematics, Inc th Street, Suite 1600 Oakland, California October 2004 The information contained in this report was prepared as part of NCHRP Project 08-36, Task 7(2), National Cooperative Highway Research Program, Transportation Research Board.

2 ACKNOWLEDGE OF SPONSORSHIP This study was requested by the American Association of State Highway and Transportation Officials (AASHTO), and conducted as part of the National Cooperative Highway Research Program (NCHRP) Project The NCHRP is supported by annual voluntary contributions from the state Departments of Transportation (DOT). Project is intended to fund quick response studies on behalf of the AASHTO Standing Committee on Planning. The report was prepared by Cambridge Systematics, Inc. The work was guided by a task group chaired by Neil Pedersen (Maryland State Highway Administration), which included Randall Halvorson (Minnesota DOT), Charles Howard (Washington DOT), Kenneth Leonard (Wisconsin DOT), Ysela Llort (Florida DOT), and Mary Lynn Tischer (Commonwealth of Virginia). The project was managed by Ronald D. McCready, NCHRP Senior Program Officer. DISCLAIMER The opinions and conclusions expressed or implied are those of the research agency that performed the research and are not necessarily those of the Transportation Research Board or its sponsors. This report has not been reviewed or accepted by the Transportation Research Board s Executive Committee or the Governing Board of the National Research Council.

3 Table of Contents Executive Summary... ES Introduction A Generalized Approach for Multimodal Tradeoff Analysis Defining a Tradeoff The Key Elements of a Tradeoff Framework A Framework for Tradeoff Analysis A Generalized Approach for Performing Multimodal Tradeoff Analysis Two Case Applications Findings Possible Next Steps for Further Development Appendix A Templates for Multimodal Tradeoff Analysis Cambridge Systematics, Inc i

4 List of Tables 4.1 Evaluation Summary for I-405 Corridor Case Application List of Figures 2.1 Generalized Framework for a Tradeoff Analysis Existing Washington State Ferry Routes I-405 Corridor Study Area Cambridge Systematics, Inc. ii

5 Executive Summary The National Cooperative Highway Research (NCHRP) Project 8-36, Task 7, Phase I developed an approach for states to use in analyzing investment tradeoffs. Methodologies such as this approach provide an important means for developing the information decision-makers need to understand the consequences of different investment scenarios. The objective of the NCHRP Phase II project is to apply the approach in a real-world situation, using data from a state department of transportation (DOT). The Phase I methodology was applied to two Washington State DOT (WSDOT) case applications. Applying the generalized approach for multimodal tradeoff analysis to these two applications allowed the research team to discover the strengths and weaknesses of the methodology when applied to real-world situations. The primary finding of this research study is that it is possible to apply the Phase I methodology to real-world situations using data from a state DOT. The methodology provided a systematic way to gather and organize data and present the information in a clear, concise way to staff and decision-makers. The research team had difficulty applying the methodology to a program-level analysis (i.e., shifting funds from one program to another, such as transit to highways). This was due to the lack of analytical tools able to provide some key pieces of necessary information rather than a problem with the methodology itself. The missing tool is one that can take project-level performance measure information and roll it up to generate program-level information. For more on this, see Finding 2 in Section 4.0. In the course of applying the methodology, the research team found several improvements that could be made to the Phase I methodology. For a discussion of these, see Findings 4 to 10 in Section 4.0. Finally, the research team developed four possible further research steps. These can be found in Section 5.0. Cambridge Systematics, Inc. ES-1

6 1.0 Introduction NCHRP Project 8-36, Task 7, Phase I developed an approach for states to use in analyzing investment tradeoffs. The Phase I approach was developed to be applicable at several levels where tradeoffs between investment choices could benefit from improved structure and format. These include the programmatic, corridor, and project levels. Methodologies such as this approach provide an important means for developing the information decision-makers need to understand the consequences of different investment scenarios. In Phase I, three hypothetical tradeoff situations were used to illustrate how the approach could be applied. Complete documentation of the approach can be found in the National Cooperative Highway Research Program, Development of a Multimodal Tradeoffs Methodology for Use in Statewide Transportation Planning, Final Report, November 5, The objective of the NCHRP Phase II project is to apply the approach in a real-world situation using data from a state DOT, and documenting the key findings regarding the strengths and weaknesses of the methodology. The approach developed in Phase I was applied to two WSDOT case applications. The first case originally had a programmatic orientation and demonstrates the tradeoffs associated with changes in investment levels for the Washington State Ferry system. The second case has a more focused geographic orientation and demonstrates the tradeoffs associated with different improvement alternatives for the I-405 corridor in the eastern suburbs of the Seattle region. The two case applications largely relied on data, analytical models, and results developed by WSDOT and its planning partners, with additional information inferred by the research team, as appropriate, based on the available information. The remainder of this report is organized into four sections: Section 2.0 A Generalized Approach for Multimodal Tradeoff Analysis. Reviews the approach developed in Phase I. Section 3.0 Two Case Applications. Provides a general description of the two case applications. Section 4.0 Findings. Presents general conclusions about the tradeoff approach from the research effort. Section 5.0 Possible Next Steps for Further Development. Presents suggestions for further research. An Appendix follows the main body of the report: Appendix Templates for Multimodal Tradeoff Analysis. Presents the five Phase I templates discussed in Section 2.4. Cambridge Systematics, Inc. 1-1

7 2.0 A Generalized Approach for Multimodal Tradeoff Analysis This section reviews the multimodal tradeoffs approach developed during Phase I. For complete documentation of the approach, see National Cooperative Highway Research Program, Development of a Multimodal Tradeoffs Methodology, Final Report, November 5, Defining a Tradeoff States confront a wide range of tradeoffs within and between modes, within and between policy objectives or performance goals, and within and between various geographic regions and market segments. All of these tradeoff issues face the same basic question and involve the same basic elements. At the core, a generalized tradeoff in transportation planning asks, How much resource do I allocate to A versus B? The actual tradeoff issue itself is What are the consequences of a particular allocation of resources to A and B? and the choice becomes the allocation and set of consequences that the decision-maker prefers. 2.2 The Key Elements of a Tradeoff Framework The essential elements of a tradeoff analysis include: Clearly defined program areas (i.e., defining what the tradeoff is between); For each area, clearly defined performance objectives, evaluation criteria, or impact categories that define the consequences of different levels of investment in the area; For each area, some method to relate the level of investment in that area to the resulting consequences in that area; and Some method for comparing or equating the consequences generated by each program area as a result of a specific allocation of resources between the areas. 2.3 A Framework for Tradeoff Analysis Figure 2.1 depicts a conceptual framework for undertaking multimodal tradeoff analysis. The figure suggests that any number of program areas or resource areas might be defined to structure an agency s investment program. Objectives and criteria need to be defined for each program area to measure the consequences of investments in that area. These objectives and Cambridge Systematics, Inc. 2-1

8 Figure 2.1 Generalized Framework for a Tradeoff Analysis Agencywide Goals and Objectives Characteristics of Objectives: Measurable Specific Well-defined Relevant Vertical Alignment for Selecting Relevant Criteria Horizontal Alignment for Program Area Tradeoffs Key Cross Program Performance Measures Program Area A Objective A-1 Criteria for A-1 Criteria for A-1 Objective A-1 Criteria for A-2 Criteria for A-2... Program Area B Objective B-1 Criteria for B-1 Criteria for B-1 Objective B Criteria for B-2 Criteria for B-2... What are Program Areas? Program Area C Objective C-1 Criteria for C-1 Criteria for C-1 Objective C-2 Criteria for C-2 Criteria for C-2... Program Area.. Objective 1 Criteria Criteria Objective 2 Criteria Criteria... Modes Agency Functions User Groups Geographic Areas Key Travel Corridors Broad Program Goals Highway, transit, ferry, aviation, etc. Construction, maintenance, admin., etc. Commuters, tourists, shippers, etc. Districts, urban, rural, etc. Intercity, intermodal, etc. Preservation, mobility, safety, etc. Cambridge Systematics, Inc. 2-2

9 criteria create the basis for the vertical alignment required within each area to perform tradeoff analysis of the consequences of different funding levels within that area. Overall, agency goals and objectives provide the horizontal alignment that is required to perform tradeoff analysis between program areas. This connection of issues, goals, objectives, and measures in both horizontal and vertical dimensions is a necessary feature of a framework for multimodal tradeoff analysis, because it will generally not be possible to apply identical performance objectives to each program area. The integration or alignment of concerns within and across resource areas helps the analyst and the decision-maker compare results of investment in dissimilar programs in terms of common desired outcomes. 2.4 A Generalized Approach for Performing Multimodal Tradeoff Analysis The general approach involves a five-step evaluation process in which an analyst establishes appropriate analysis mechanisms, identifies relevant considerations for the evaluation, applies analysis methods and data in a structured sequence, and summarizes key results to highlight tradeoff considerations. In this generalized approach, the summarization of key distinguishing features between alternative investment strategies is the specific tradeoff analysis. A set of templates that may be used in conducting the tradeoff evaluation was developed in Phase I. These can be found in the National Cooperative Highway Research Program, Development of a Multimodal Tradeoffs Methodology, Final Report, November 5, 2001 and are repeated here in Appendix A. These templates are provided to help an agency organize its key policy considerations, performance measures, databases, analytical models, and other elements into a format that will readily support a tradeoff analysis. The five templates correspond (generally) to the five main evaluation steps in the approach, which are summarized below. Evaluation Step A Establish Structure for Inter-Program Analysis This first evaluation step involves identifying and organizing factors that are explicitly or implicitly used by the agency s decision-makers to evaluate key agencywide issues. In many agencies, these factors are the broad goals, objectives, and performance measures that are used in the ongoing statewide transportation planning process, and may also be reflected in toplevel programming and prioritization processes. In general, these factors may reflect common concerns across programs and a broad, systemwide perspective; this perspective differs from the program-specific focus that is inferred in the second step. Furthermore, these top-level goals, objectives, and performance measures generally reflect issues that are of most interest to agency decision-makers and the general public. Evaluation Step B Establish Structure for Intra-Program Analysis The second step involves identifying and organizing factors that are typically used by the agency s front-line managers and staff to evaluate issues within specific program areas. These program areas could reflect modal, geographic, functional, or other orientations depending Cambridge Systematics, Inc. 2-3

10 upon a specific agency s decision-making needs. The related program objectives and performance measures tend to be of greater concern to the operators, managers, users, and advocates of specific programs. For example, in the area of system preservation, a top-level decision-maker might be interested in a systemwide average pavement rating, but the pavement program manager might want a breakout of lane-miles by condition (e.g., good, fair, poor, etc.) and functional classification. In some agencies, identification of these program-specific factors may have been performed as part of the ongoing statewide transportation planning process or, more specifically, as part of the STIP project selection/prioritization process. Evaluation Step C Identify Program Areas of Interest The third evaluation step involves identifying the programs that should be explicitly analyzed in the tradeoff process. An agency may have many program areas that represent the top level for prioritization, decision-making, and current informal tradeoff processes. An agency s top decision-makers need information that reflects tradeoffs among the programs over which it is typically concerned; on the other hand, front-line managers and staff need more detailed information regarding the specific program(s) for which they are responsible. Evaluation Step D Apply Analysis Procedures The fourth tradeoff evaluation step involves applying various tools and procedures to develop tradeoff information from available data for both intra-program and inter-program categories. Subsequent analysis procedures have the potential to produce a wealth of information regarding the different program funding levels that may comprise a specific tradeoff. The result we are trying to achieve is to develop a small set of information that focuses on key distinguishing features between the possible tradeoffs. The organizing templates provide the basis for developing an appropriate structure comprising four discrete analysis steps: 1. D1 Establish current levels of performance, 2. D2 Identify alternative future funding levels, 3. D3 Analyze individual programs for each alternative future funding level, and 4. D4 Analyze inter-program effects for each alternative future funding level. Evaluation Step E Present Tradeoff Information This final tradeoff evaluation step identifies information to help inform decision-makers tradeoff considerations. Essentially, a tradeoff analysis is a way to summarize key distinguishing features between the proposed funding levels. The report presents a general template for pulling together program-specific and inter-program information in a comparative assessment that includes qualitative and quantitative factors. Cambridge Systematics, Inc. 2-4

11 3.0 Two Case Applications Together with WSDOT staff and the NCHRP panel for this project, the research team identified two case applications to demonstrate the multimodal tradeoff analysis approach. The first case was originally constructed to demonstrate the application of the tradeoff approach at a programmatic level by investigating the benefits and costs associated with continuing to invest in ferry service across the Puget Sound versus investing more to improve roadways in the Puget Sound area. Washington State Ferries (WSF) currently operates several ferry routes between the eastern and western shores of Puget Sound (see Figure 3.1). In this case application, service is reduced on these routes, resulting in capital and operating cost savings, but also increased auto and truck travel on roadways around Puget Sound. This case application was to evaluate the benefits from transferring these cost savings to improving roadways. In this case application, there are two factors affecting roadway performance: 1) increased auto and truck traffic caused by reduced ferry service, and 2) roadway improvements from reinvesting ferry cost savings. The analysis found that the impact of the first factor was relatively minor and likely much smaller than the impact of the second. Because of the particular interest during this project on understanding the benefits and costs of reducing ferry service, the analysis of increased roadway funding was dropped so that the impacts directly attributable to reducing ferry services would be clear. Thus, this case application in essence changed from an analysis of shifting funds between programs to a corridor-level analysis of reducing ferry services. The second case application demonstrates the application of the tradeoff approach at a corridor level by investigating the relative merits of several alternatives for improving transportation in the I-405 corridor. The I-405 corridor runs about 30 miles along the eastern shore of Lake Washington, through the eastern suburbs of the Seattle area (see Figure 3.2). An analysis of the I-405 corridor was recently completed in 2002, culminating in the identification of a Preferred Alternative and the completion of a Final Environmental Impact Report (FEIS). The case application re-packages the information developed for this FEIS into the multimodal tradeoff analysis format described in Section 2.0. The two case applications were developed in order to demonstrate and evaluate a proposed approach to conducting multimodal tradeoff analysis at the program level. While the two case study applications demonstrate that the multimodal tradeoff framework can be applied to corridor-level analysis, the research team was unable to identify adequate data to fully test the framework on a program-level tradeoff analysis as was intended. Because of this, the NCHRP panel for this project decided not to include the analytical results from the two case applications in this report. Instead, the researchers have summarized lessons learned from the analysis and have made observations on what will be needed to test the framework at the program level. Cambridge Systematics, Inc. 3-1

12 Figure 3.1 Existing Washington State Ferry Routes Cambridge Systematics, Inc. 3-2

13 Figure 3.2 I-405 Corridor Study Area I Corridor Study Area 5 mi Cambridge Systematics, Inc. 3-3

14 4.0 Findings Applying the generalized approach for multimodal tradeoff analysis to two case applications allowed the research team to discover the strengths and weaknesses of the methodology when applied to real-world situations. Finding 1 The primary finding of this research study is that it is possible to apply the NCHRP methodology to real-world situations using data from a state DOT. The methodology provided a systematic way to gather and organize data and present the information in a way comprehensible to staff and decision-makers. Because of the systematic, clear way the approach organizes and presents information, several interesting and unexpected results were discovered for the ferry investment case application. People involved with the I-405 Corridor FEIS appreciated the clear, concise way the approach presented the tradeoffs associated with this case application. Some said they planned to use some of the concepts arising from the NCHRP methodology in ongoing I-405 analysis. The research team found applying the methodology to a program-level analysis problematic; but this is due to the lack of adequate tools able to provide some key pieces of necessary information, rather than a flaw with the methodology itself. For more on this topic, see Finding 2. Finding 2 The research team found it difficult to apply the multimodal tradeoff approach to programmatic analysis. The key shortcoming is the ability to determine the performance associated with different levels of program-level funding (e.g., how do performance measures change when highway funding is increased by $100 million?). To perform program-level tradeoff analysis, the research team believes tools are needed that start with performance measure information at the project-level, and then rolls-up this information to generate program-level performance measures. There are several challenges to developing such a tool: 1. Consistent and complete performance measure information is needed at the project level. Adding up performance measures across projects within a program is only feasible if the same performance measures are used for each and every project and they are calculated in the same way. 2. A method for ranking projects within a program is needed. For example, suppose the combined capital cost for all the projects in a program is $1 billion. The tool would need to determine which projects to keep and which to drop at lower funding levels. This is only possible if some method is developed to determine which projects are better than others, and are thus better candidates for keeping or dropping. Cambridge Systematics, Inc. 4-1

15 3. Information is needed for existing and potential projects. A tradeoff analysis might consider funding levels higher than current. To analyze this possibility, the tool would have to include information not only for existing projects, but also for potential projects. Program-level tools with these capabilities currently exist in the asset management area (e.g., bridge management and pavement management), but are rare outside this area. For example, there is no readily-available tool that can define the benefits and impacts of an additional $100 million investment in generic highway capacity expansion without requiring the analyst to identify specific projects. WSDOT is currently developing the Multimodal Investment Choice Analysis (MICA) model. This model could potentially serve as the needed program-level performance measures tool. MICA is a multimodal model able to handle a wide variety of projects (e.g., capacity enhancement, preservation, etc.). To use MICA, the analyst first identifies the set of relevant projects. The analyst then develops information for a pre-determined set of performance measures used by MICA and enters them into the model for each project. MICA then ranks all the projects using a user-specified prioritization scheme based on setting weights for the various performance measures and determines the optimal set of projects for a given funding level. For further documentation on MICA, see Washington State Transportation Center, Final Research Report, Research Project T1803, Task 36, Multimodal Investment Choice Analysis, Volume I: Phase I, June A prototype of the MICA model has been developed, but has not been tested with real data. Two steps would need to be completed for MICA to be usable for multimodal tradeoff analysis: 1. Complete MICA development and testing, and 2. Develop and enter consistent project-level performance measure data. The MICA model contains a pre-determined set of performance measures. The analyst can choose to only include a subset of these measures in an analysis. However, MICA cannot include any performances measures outside its pre-programmed set. This could be a shortcoming for generalized multimodal tradeoff analyses, because decision-makers may prefer to include measures not included in MICA. Finding 3 Before embarking on a multimodal tradeoff analysis, the analysis team should first determine whether a marginal analysis will suffice or if a base-level analysis will be needed. Most of the time, only a marginal analysis that considers incremental changes from existing conditions is needed (e.g., what are the costs and benefits of increasing level of funding for a program of reducing transit service, etc.). On rare occasion, a base-level analysis that considers completely eliminating a program or system is needed (e.g., what are the costs and benefits of eliminating an entire transit system). In a marginal analysis, the analyst only needs to determine the change in costs and benefits between various alternatives. Base-level analyses are generally much harder, because they require determining the overall costs and benefits of a system or program. Once a choice of marginal versus base-level analysis is made, the analyst will need to make Cambridge Systematics, Inc. 4-2

16 sure the analytical tools used in the evaluation can support that type of analysis. Most analytical tools such as MICA are built to conduct marginal analyses only. Finding 4 The NCHRP methodology includes the identification of the decision-making factors and structure at the inter-program and intra-program-levels (i.e., Evaluation Steps A and B). Upon completing the two case applications, the research team now believes Evaluation Steps A and B should be replaced with a single step that identifies the decision-making factors and structures at the appropriate level for the decision being considered. Some decisions are at a high enough level that considering program-specific objectives and performance measures is unnecessarily detailed. Other decisions are at a low enough level that they have little impact on interprogram objectives and measures. For both the ferry investment and I-405 case applications, fairly high-level goals, objectives, and measures were identified that presented the key information needed to make a fairly high-level decision between corridor-level alternatives. Adding goals, objectives or measures at a lower level would have only complicated the analysis and presentation of results without adding information relevant to the decisions being made. Finding 5 In the description of the NCHRP methodology in Section 2.0, alternative funding levels are identified first, and then the resulting impacts to specific programs and projects are analyzed to identify the consequences. For some decisions, this is the natural sequence. However, for other decisions, it may be more natural to identify the program and/or project alternatives first, and have the funding consequences follow. This was the case for both the ferry investment and I-405 case applications. In both of these cases, the selection of transportation alternatives determined what the required funding would be, rather than the other way around. The NCHRP methodology was developed with flexibility as a key feature and can accommodate either order. It can be applied in situations where a planner needs to identify the best way to allocate a given level of funding. This may occur, for example, in a pavement management program context, where alternative funding levels are identified first and the results are expressed in terms of alternative future pavement condition scenarios and/or life cycle costs. Finding 6 The NCHRP methodology assumes the appropriate analysis structure is that used by the decision-making agency. This makes sense as long as a single agency is the decision-maker. However, many transportation decisions involve multiple agencies. For example, the I-405 case application involved the state DOT, the Federal Highway Administration (FHWA), the Federal Transit Administration (FTA), the regional transit provider, the county, and several cities. In these cases, an appropriate evaluation structure will need to be developed that is suitable for the situation under consideration. The resulting structure of goals, objectives, and performance measure will likely be a synthesis of those used by the individual agencies. Cambridge Systematics, Inc. 4-3

17 Finding 7 The Evaluation Step A template (see Tables A.1 and A.2 in Appendix A) includes the identification of long-term targets for each of the performance measures. However, in many cases, agencies have either not yet developed targets, or have chosen not to develop them. For example, in both the ferry investment and I-405 case applications, no long-term targets were established for their respective performance measures. In these cases, long-term targets should be left out of the evaluation. Finding 8 In several places, the NCHRP methodology includes an assessment of current performance. For some performance measures, this is not applicable. For example, current performance is not meaningful for a measure such as construction impacts. For these measures, it is not necessary to establish a current level of performance. Finding 9 The Evaluation Step E template (see Tables A.9 and A.10 in Appendix A) includes identifying which alternative performs best for each performance measure. This works well if there are only two alternatives. However, it may give an incomplete and misleading impression if there are more than two alternatives. For example, an alternative that performs second best on every performance measure may in fact be the best alternative; however, this would not come across in the Evaluation Step E template. Finding 10 For both the ferry investment and I-405 corridor case applications, the final evaluation table proved very complex. Both contained a large number of performance measures, making them quite long and difficult to follow. The research team recommends keeping the full evaluation table, but also creating a good evaluation summary table that is more easily comprehended by decision-makers. Care and creativity may be needed to generate a table that makes the key points clearly. The summary table created for the I-405 case is an example (see Table 4.1). This alternative Consumer Reports style format rates the relative performance of various alternatives, and summarizes the complex information in the full evaluation table in a way that is more easily comprehended by the decision-makers. Some features of this table that make it particularly useful include: 1. Limited to one page; 2. Results for several performance measures are grouped and summarized at a higher level (i.e., at the outcome objective level for the ferry investment case and at the objective level for the I-405 corridor case); and 3. Use of easy-to-understand symbols to summarize information. Cambridge Systematics, Inc. 4-4

18 Table 4.1 Evaluation Summary for I-405 Corridor Case Application = Much Better than No Action = Much Worse than No Action Alternative Goal/Objective HCT/TDM Emphasis Mixed Mode with HCT/ Transit Emphasis Mixed Mode Emphasis General Capacity Emphasis Improve Mobility Serve 2020 corridor travel demand Reduce SOV mode share Reduce travel time for all modes Improve reliability for all modes Provide connections to other systems Accommodate post-2020 demands Reduce Congestion Reduce study area congestion Improve Livability Accommodate study area growth Minimize neighborhood impacts Improve Safety Improve safety of all modes Environmentally Responsive Minimize regional emissions Accommodate study area land use, development patterns, infill Consistency with adopted land use and transportation plans Avoid disproportionate impacts on minority and low-income populations Encourage study area economic activity Solutions Can Be Implemented Capital and operating costs Public support is evident Cambridge Systematics, Inc. 4-5

19 5.0 Possible Next Steps for Further Development This section describes four possible further research steps to address some of the findings in Section Some NCHRP panel members feel this project did not test the Phase I methodology s ability to conduct a program-level tradeoff. While the ferry investment case started as a programlevel analysis, it changed into a corridor-level evaluation. A possible next research step is to try again to identify a real-world, program-level tradeoff analysis that the NCHRP methodology could be applied to. 2. Conduct a review of models and analytical procedures available or under development that might fulfill the need for a tool that develops program-level performance measure information. As described under Finding 2 in Section 4.0, the research team believes developing such a tool is needed to apply the NCHRP methodology to program-level analyses. Surveying available and under-development models will assess whether a model exists that could fulfill this need. 3. Apply the MICA model to a real-world, program-level tradeoff analysis. As discussed in Finding 2 in Section 4.0, the MICA model might overcome the primary hurdle to applying the multimodal tradeoff approach to program-level analysis. Testing MICA will determine if this model is able to support program-level tradeoff evaluation. 4. Refine the Phase I generalized approach for multimodal tradeoff analysis described in Section 2.0 and the Phase I templates presented in Appendix A to incorporate Findings 4 to 10 in Section 4.0. Cambridge Systematics, Inc. 5-1

20 Appendix A. Templates for Multimodal Tradeoff Analysis This Appendix contains the five Phase I templates referred to in Section 2.4, as well as examples of these templates filled in for a hypothetical application. These templates are intended to help an agency organize its key policy considerations, performance measures, databases, analytical models, and other elements into a format that will readily support a tradeoff analysis. The five templates correspond (generally) to the five main evaluation steps in the approach described in Section 2.4. Note that the letter in parentheses for each table refers to the evaluation steps described in Section 2.4. These templates have not been modified to incorporate the research team s Phase II findings. Cambridge Systematics, Inc. A-1

21 Table A.1(A) General Template: Key Issues and Analysis Process Across Program Areas Top-Level Agency Goals and Objectives Agencywide Goal Goal 1 Goal 2 Goal 3 Goal 4 Agency Objective Agency Performance Measure Long-Term Target Assessment Data and Procedures Objective 1-1 ~ ~ ~ Objective 1-2 ~ ~ ~ Objective 2-1 ~ ~ ~ Objective 2-2 ~ ~ ~ Objective 3-1 ~ ~ ~ Objective 3-2 ~ ~ ~ Objective 4-1 ~ ~ ~ Objective 4-2 ~ ~ ~ Cambridge Systematics, Inc. A-2

22 Table A.2(A) Example: Key Issues and Analysis Process Across Program Areas Top-Level Agency Goals and Objectives Agencywide Goal Mobility Agency Objective Provide competitive travel time for non-auto modes Safety Reduce number and severity of crashes Agency Performance Measure Long-Term Target Avg. speed by mode Transit times w/in 30% of peak-period auto time Level of modal integration Fatal, injury, and property damage Crash rates by mode Assessment Data and Procedures HPMS; count programs; travel models; user surveys N/A GIS; network maps; user surveys; expert panel Reduce by 10% from current levels Crash databases; HERS/ST; safety management systems; crash prediction models Cambridge Systematics, Inc. A-3

23 Table A.3(B) General Template: Key Issues and Analysis Process Within Program Areas Program-Specific Considerations Agencywide Goal Goal 1 Goal 2 Goal 3 Goal 4 Program Objective Program Area: XXXX Program Performance Measure Long-Term Target Assessment Data and Procedures Program objective 1-1 ~ ~ ~ Program objective 1-2 ~ ~ ~ Program objective 2-1 ~ ~ ~ Program objective 2-2 ~ ~ ~ Program objective 3-1 ~ ~ ~ Program objective 3-2 ~ ~ ~ Program objective 4-1 ~ ~ ~ Program objective 4-2 ~ ~ ~ Cambridge Systematics, Inc. A-4

24 Table A.4(B) Example: Key Issues and Analysis Process Within Program Areas Program-Specific Considerations Agencywide Goal System Preservation Program Objective Provides smoother roads Program Area: XXXX Program Performance Measure Pavement rating (PSR) by functional class Mobility Maintain travel times Average speed by functional class Long-Term Target Freeway: >3.2 Arterial: >3.0 Collector: >2.8 Other: >2.7 Assessment Data and Procedures Pavement management system; HERS/ST HERS/ST; travel models; user surveys No reduction from current conditions Cambridge Systematics, Inc. A-5

25 Table A.5(C) General Template: Assessment of Intra-Program Effects XXXX Program Area Agencywide Goal Goal 1 Goal 2 Goal 3 Goal 4 Program Performance Measures Program Area: XXXX Long-Term Target Current Condition Future Funding Level 1 Future Funding Level 2 Program objective 1-1 ~ ~ ~ ~ Program objective 1-2 ~ ~ ~ ~ Program objective 2-1 ~ ~ ~ ~ Program objective 2-2 ~ ~ ~ ~ Program objective 3-1 ~ ~ ~ ~ Program objective 3-2 ~ ~ ~ ~ Program objective 4-1 ~ ~ ~ ~ Program objective 4-2 ~ ~ ~ ~ Cambridge Systematics, Inc. A-6

26 Table A.6(C) Example General Template: Assessment of Intra-Program Effects Highway Program Area Agencywide Goal System Preservation Program Performance Measures Pavement Rating (PSR) by functional class Mobility Average speed (mph) by functional class Program Area: Highway Long-Term Target Freeway: >3.2 Arterial: >3.0 Collector: >2.8 Other: >2.7 No reduction from current conditions Current Condition Future Funding Level Urban Freeway: 46 Rural Freeway: 63 Urban Arterial: 30 Rural Arterial: 39 Other: Future Funding Level Cambridge Systematics, Inc. A-7

27 Table A.7(D) General Template: Assessment of Inter-Program Effects Agencywide Goal Goal 1 Goal 2 Goal 3 Goal 4 Agency Performance Measure Long-Term Target Current Condition Future Funding Level 1 Future Funding Level 2 Objective 1-1 ~ ~ ~ ~ Objective 1-2 ~ ~ ~ ~ Objective 2-1 ~ ~ ~ ~ Objective 2-2 ~ ~ ~ ~ Objective 3-1 ~ ~ ~ ~ Objective 3-2 ~ ~ ~ ~ Objective 4-1 ~ ~ ~ ~ Objective 4-2 ~ ~ ~ ~ Cambridge Systematics, Inc. A-8

28 Table A.8(D) Example General Template: Assessment of Inter-Program Effects Agencywide Goal Mobility Agency Performance Measure Avg. speed by mode Level of modal integration Safety Fatal, injury, and property damage crash rates by mode Long-Term Target Transit time w/in 20% of peak-period auto time Current Condition Auto: 31 mph Transit: 20 mph N/A Urban: Medium Rural: Low Reduce by 10% Auto from current Fatal: 1.5 levels Injury: 6.0 PDO: 21.3 Transit Fatal: 0.1 Injury: 3.1 PDO: 9.4 Future Funding Level 1 33 mph 24 mph Medium-High Medium Future Funding Level 2 28 mph 20 mph Low-Medium Low Cambridge Systematics, Inc. A-9

29 Table A.9(E) General Template: Selected Performance Measures for Tradeoff Considerations Agencywide Goal and Corresponding Objectives* Goal 1 Agency or Program Performance Measure Overall Objective 1-a Quantitative Measure Long-Term Target Performance Under Existing Investment Priorities Performance Under Alternative Investment Priorities Overall Objective 1-m Quantitative Measure Qualitative objectives N/A N/A Qualitative description Qualitative description or considerations Goal 2 Overall Objective 2-b Quantitative Measure Overall Objective 2-n Quantitative Measure Qualitative objectives N/A N/A Qualitative description Qualitative description or considerations Goal 3 Overall Objective 3-c Quantitative Measure Overall Objective 3-o Quantitative Measure Qualitative objectives N/A N/A Qualitative description Qualitative description or considerations Goal 4 Overall Objective 4-d Quantitative Measure Overall Objective 4-p Quantitative Measure Qualitative objectives N/A N/A Qualitative description Qualitative description or considerations Best Program in Achieving Targets *Agency or program objectives for which a meaningful difference is expected to occur between alternative future funding levels. Cambridge Systematics, Inc. A-10

30 Table A.10(E) Example General Template: Selected Performance Measures for Tradeoff Considerations Agencywide Goal and Corresponding Objectives* System Preservation Provide smoother roads Mobility Maintain travel times Provide competitive travel times for non-auto modes Safety Reduce number and severity of crashes Agency or Program Performance Measure Long-Term Target Pavement rating (PSR) by functional class Avg. speed by functional class Level of modal integration Crash rates by mode Freeway: >32 Arterial: >3.0 Collector: >2.8 Other: >2.8 Urban Freeway: No Rural Freeway: Net Urban Arterial: Reduction Rural Arterial: from Other: Current Performance Under Current Conditions N/A Urban: Medium Rural: Low Reduce by 10% from current Auto Fatal: 1.5 Injury: 6.0 PDO: 21.3 Performance Under Funding Increase Medium-High Medium Performance Under Funding Decrease Low Low Best Program in Achieving Targets Funding increase Funding increase Funding increase Funding increase *Agency or program objectives for which a meaningful difference is expected to occur between alternative future funding levels. Cambridge Systematics, Inc. A-11