Matthew Schroeder

FINAL CONTRACT REPORT





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Scenario-Based Planning for the Regional Impacts of Statewide

Multimodal Transportation Polices



JAMES H. LAMBERT

Center Associate Director

Research Associate Professor of Systems and Information Engineering



MATTHEW J. SCHROEDER

Graduate Research Assistant









Center for Risk Management of Engineering Systems

University of Virginia









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PROJECT TEAM





University of Virginia



James Lambert, Associate Director, Center for Risk Management of Engineering Systems

Matthew Schroeder

Megan Kersh

Ward Williams

Asad Saqib



Project Steering Committee

Wayne Ferguson, VTRC

Katherine Graham, VDOT

Mark McCaskill, Roanoke MPO

John Miller, VTRC

Kimberly Pryor Spence, Multimodal Office

Mary Lynn Tischer, Multimodal Office



Acknowledgements



Ralph Davis, VDOT

Joost Santos, UVa

Chad Tucker, VDOT

Ben Mannell, VDOT

Michael Garrett, VDOT









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Abstract



The Office of the Virginia Secretary of Transportation identified twenty-one

transportation policies and a set of forty-two policy performance evaluation criteria in

Virginia‟s long-range multimodal transportation plan, VTrans2025. The latest long-range

planning effort VTrans2035, which is ongoing, has provided direction for the research

described herein.



While there has been considerable discussion of the potential impacts of the

VTrans policies to the Commonwealth as a whole, there have been few attempts to assess

and characterize the individual local and regional impacts of the policies. Moreover the

sensitivity of the policies to various scenario assumptions about the future has been in

need of further exploration on the statewide, regional, and local levels. An upcoming

summit of transportation thought leaders will convene in November 2008 will have use

for knowledge of how VTrans policies have differential impacts to various regions and

with various scenarios of the future.



This research effort develops and tests methodology for scenario-based

assessments of the impacts of the VTrans polices for multiple regions of the

Commonwealth of Virginia. The methodology is implemented in an MSExcel workbook

available for download at www.virginia.edu/crmes/multimodal2. This report describes

the application of the methodology for a locality or regional planning organization, e.g., a

Metropolitan Planning Organization (MPO) or Planning District Commission (PDC), to

assess the impact of statewide multimodal policies across several of its long-range

planning scenarios. This report includes an application of the methodology to the

Roanoke and Hampton Roads regions of Virginia, a review of scenario-based planning,

documentation of future scenarios, a survey of Metropolitan Planning Organizations in

Virginia for their best practices in scenario-based transportation planning, and

recommendations for next steps.



The effort also describes several other implementations to Northern Virginia and

Richmond regions in Appendix A. A survey and study of scenario-based planning best

practices is featured in Appendix B. Appendix C describes an input/output analysis of

economic growth based on transportation investments that was requested by the

Multimodal Office.









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INTRODUCTION





There are several questions motivating the current research, as follows:

 Can scenario-based planning help regions better coordinate transportation and

other planning with the state?

 How do regional differences such as geography, demographics, and economy

affect multimodal transportation planning?

 Is there a way to standardize planning to consider a wide array of future events

when planning and forecasting?

 Do the varying needs of regions make it difficult to prioritize statewide policy?

Can scenario-based planning be used to help policy makers interpret the varying

needs of regions and better coordinate and prioritize multimodal transportation

policies on a regional level?



Past transportation planning efforts have focused on cost-benefit and impact

models. However, data collection methods proved to be heavily assumption-based and

unrepeatable (Cervero & Aschauer, 2007). Even when the cost-benefit models produce

reliable results for specific transportation investments, policymakers need a better

understanding of the impacts of the investment on a region enhances the decision-making

process. Scenario-based planning is an alternative method for obtaining this knowledge.

Scenario-based planning “highlights the major forces that may shape the future and

identifies how the various forces might interact” (Federal Highway Administration,

2007). In the transportation sector, scenario-based planning emphasizes the relationship

between transportation and the environment, the economy, and society. Scenario-based

planning illustrates how the transportation infrastructure can accommodate variations in

characteristics of a region. For instance, if the United States Census Bureau estimates a

twenty percent increase in the population of a region over the next five years, the

transportation infrastructure will need to expand to grow to match the increased demand.



Scenario-based planning is an add-on or complementary to the following analysis

methods:



 Return on investment

 Cost-benefit analysis

 Risk analysis

 Impact analysis

 Sensitivity analysis

 Systems analysis and integration



The establishment of goals and performance measures for long-range

transportation planning is useful on statewide and regional and local levels for

understanding a variety of activities, including:

 Funding and investments



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 Land use

 Connectivity

 Priority setting



VTrans2035 and the Office of Multimodal Transportation Planning and

Investment (Multimodal Office) are using twenty-one policies and forty-two performance

criteria for evaluating statewide transportation policies. Example policies include

investing in public transit, planning multimodally, and improving travel mode

connections. The criteria encompass safety and security; preservation and management;

efficient movement of people and goods; economic vitality; quality of life; and program

delivery.



The Multimodal Office has two challenges for applying scenario-based planning.

The first challenge is that a set of high-level goals and associated criteria have been

developed for prioritizing multimodal transportation policies, but they have not yet been

integrated into existing prioritization methods. The second challenge is the existence of

several obstacles to multimodal transportation prioritization that have occurred in

Virginia in the past the few years. Three major obstacles are; the inability to achieve

consistency in planning factors and assumptions across modes, different regulatory

processes for modes of transportation, and a lack of methodology for computing a

transportation project‟s return on investment (ROI). Scenario-based planning addresses

the first obstacle, inconsistent planning factors, and also provides a method that adapts to

uncertainty in transportation-related futures.





PURPOSE AND SCOPE



The intended customers of this effort are the Commonwealth of Virginia and the

Metropolitan Planning Organizations (MPOs) and Planning District Commissions

(PDCs) of the Commonwealth, as depicted in Figure 1.









Figure 1. PDCs and MPOs in the Commonwealth of Virginia [Rappahannock Rapidan Regional

Commission, 2008]





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The effort develops a methodology motivated by guidelines of the Federal

Highway Administration (2007) to study the impacts of statewide multimodal

transportation policies on localities and regions under various future scenarios. An MS

Excel workbook is developed to process the inputs from various regions and generate a

local assessment of the impacts of the transportation policies. The report describes four

demonstrations of the workbook to several regions of Virginia, Northern Virginia,

Hampton Roads, Roanoke, and Richmond. The report surveys regional planning

methodologies. For example, in Northern Virginia, TransAction2030 (2007) provide

multimodal analysis to create vision, goals, and strategies for future transportation. In the

Hampton Roads region, the report analyzes the affects of future scenarios for a port-

centered economy as well as the return on investment and economic impacts of the ports.



The effort explored the scenarios used by different transportation departments and

planning groups across the nation. The effort adopts scenarios developed by the

Metropolitan Washington Council of Governments (2004), Delaware Valley Region

Planning Committee (2007), Roanoke Valley Area Metropolitan Planning Organization

(2005) and Thomas Jefferson Planning District Commission (n.d.). The effort sorted the

selected scenarios into four main categories – spatial, demographic, economic, and other,

which include environmental issues and natural disasters. The four categories encompass

major scenarios that transportation planners have to account for in the future.



The effort analyzed the regional impacts of transportation policies across

performance criteria, and under various future scenarios. The effort developed an

automated workbook that enables a regional planner to characterize the impacts of the

policies for a region of Virginia under a base scenario and five other scenarios. The

scenarios are S.2 - acceleration of sprawl, S.17 - mass retirement of an aging population,

S.18 - region-wide natural disaster, S.3 - accelerated growth of information technology

amenities, and S.19 - significant reduction in air quality, all of which were identified via

a review of twelve regional plans and interviews with regional planners. The results

describe which policies are most sensitive to the scenarios. The policy of investing in

technology scores high for all six scenarios.



A survey and analysis of best practices in scenario-based planning of Virginia

Metropolitan Planning Organizations is provided in Appendix B.



Economic growth resulting from transportation investments was also studied via

input-output models with the results provided in Appendix C.





BACKGROUND/LITERATURE REVIEW



This section reviews some fundamentals of scenario-based planning for

transportation systems. The section also examines the methodology recommended by the

Federal Highway Administration and other regional planning organizations.







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Scenario-Based Planning



Scenario-based planning lends itself to many misconceptions about its processes

and aims. Zergas , Sussman, and Conklin (2004) allay misconceptions by researching the

origins and applications of scenario planning. The terms scenario-based planning and

scenario planning are often used interchangeably in literature. „Scenario planning‟ means

the focus on the scenario part of scenario-based planning.



Zergas et al. (2004) follows the evolution of scenario planning from corporate

strategies to transportation planning. Royal Dutch Shell is generally first credited with

using a scenario-based approach to aid strategic business planning. Rapid changes in the

business environment motivated Shell to search for a planning approach that could better

deal with uncertainty. Shell adopted scenario-based planning in order to address a wide

range of situations and aid planners in preparing for a variety of business scenarios.

Zergas et al. (2004) emphasize the use of scenario planning for Shell by mentioning that

the application of scenario planning contributed to Shell‟s ability to anticipate and

prepare for the oil crisis of 1973 and its economic aftermath.



Scenario Planning as a Supplemental Technique



Currently, there appears to be no major statewide transportation departments that

significantly incorporate scenario-based planning to multimodal transportation planning.

A possible reason for slow adaptation of scenario-based planning by transportation

planners is that scenario-based planning involves long term planning and future

scenarios, and as results, years may elapse until the efficacy of scenario-based planning

can be properly evaluated. Criticisms by transportation planners may be another reason

for the slow adaptation of scenario based planning. Cole (2001, p. 373) states another

reason for the lack of popularity for scenario-based transportation planning approaches,

many policy makers prefer specific answers, as opposed to several different possibilities.

Zergas et al. addresses criticisms of scenario planning and clears up misconceptions of its

use and results. Critics attempt to discredit scenario planning by claiming that it is

ineffective in predicting the future. Zergas et al. states that, “Scenario planning is not a

replacement for traditional planning techniques such as forecasting; instead it aims to

help organizations better prepare for the unexpected. In short, scenario planning helps to

make robust strategic choices” (2004, p. 8).



In their own use of scenario planning, Zergas et al. (2004) applies systematic

scenario planning to transportation planning in the Houston metro area. The study used

scenario planning methodology to examine key issues for the area, the scope of the

problem, and finally generating relevant scenarios. The scenarios generated are

subsequently used to evaluate transportation policies in the area. The results from the

study showed that although the scenario planning could not be directly evaluated, the

concept provided insight into transportation futures for transportation planners.



Bartholomew (2005) describes the usage of using scenarios in planning for land

use issues in transportation. The FHWA (2007) also is using scenario-based planning in



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transportation land use issues. Bartholomew (2005) conducted a survey in 2003-2004 of

MPOs and found that out of one-hundred fifty-two recipeients of the survey, 45%

indicated that they had at least one scenario planning project. Scenario-based planning

allows for increased community involvement in planning and is recommended in

scenario-based planning literature (FHWA 2007; Bartholomew, 2005; Zergas, 2004).



An Existing Methodology with Scenario Planning



The Federal Highway Administration (FHWA) recommends using scenario

planning (About Scenario Planning, 2007) as part of transportation planning. The FHWA

developed a recommended scenario-based planning methodology in an attempt to

familiarize other transportation groups with scenario-based planning. The FHWA

scenario-based planning approach echoes the methodology presented above by Zergas et

al. (2004) through its emphasis on “scenario planning as an enhancement of, not a

replacement for, the traditional transportation planning process” (Zergas et al., 2004, p.

8). In its approach, the FHWA regards the main purpose of scenario planning as aiding in

preparation of potential transportation issues instead of predicting futures.



The FHWA scenario planning methodology involves six steps. The first three

steps of the FHWA methodology involve creating and planning scenarios. The first step

recommended by the FHWA is to research „driving forces‟. Driving forces are, “the

major sources of change that impacts the future” (About Scenario Planning, ¶12). Trends

in local land use, levels of congestion, and local demographics are commonly used

driving forces. The second step is to determine patterns of interactions. Determining

patterns of interactions between driving sources can be done in a variety of ways. The

FHWA recommends that transportation planners use a matrix and develop a metric

related to positive or negative outcome. The third step involves creating scenarios from

planners by fitting realistic situations to patterns between the driving forces. An example

of a scenario is an event where jobs and city population increase. The FHWA describes

the goal of creating scenarios is to “bring life to the scenarios in a way that community

stakeholders can easily recognize and connect the various components” (About Scenario

Planning, ¶16). The fourth through sixth step of the FHWA methodology involve

stakeholders analyzing and evaluating the scenarios. The fourth step is to analyze the

implications of the scenario. Transportation planners can use scenario-planning software

tools to present scenarios visually. Scenario-planning software also gives stakeholders

and planners a better view of the consequences of a scenario. During this step,

transportation planners and stakeholders can develop potential transportation policies that

mesh with the scenarios. Evaluating scenarios is the fifth step in the FHWA‟s

methodology. FHWA details a variety of methods to accomplish scenario evaluation,

such as using various criteria and presenting the scenarios to the community stakeholders.

The sixth and last step is monitoring relevant indicators to the scenario. Scenario

planning is a dynamic methodology, and transportation planners can generate new

scenarios as events occur (About Scenario Planning).



Virginia Applications of Scenario-Based Planning



Several applications of scenario-based planning in Virginia are described below.



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Thomas Jefferson Planning District



Thomas Jefferson Planning District (TJPD) and the Roanoke Valley Area

Planning Commission (RVARC) both apply scenario-based transportation planning, but

take different approaches in application. The RVARC generally uses the approach of

developing detailed objective scenarios that guide planners to relevant policies. These

detailed scenarios are then converted into numbers that apply to transportation area

zones. The numbers are then put into models that such as IMPLAN, an economic impact

modeling system. After planners use forecasting tools, other analysis and decision

making is done by transportation planners and relevant policies are generated. In some

cases, the models are not used and scenarios more used as a post-process tool for relevant

policies (M. McCaskill, personal communication, February 25, 2008).



The Thomas Jefferson Planning District (TJPD) uses scenario-based planning in

the Eastern Planning Initiative project. The Eastern Planning Initiative focuses on the

future of regional growth. Thus, TJPD uses scenarios that focus on growth possibilities

specifically (Jefferson Area EPI, n.d.). TJPD uses the growth scenarios to gauge

stakeholder‟s opinions on the possible futures. Planners develop potential policies based

on the evaluation of scenarios and other constraints.



Though the use of scenario-based planning for TJPD and RVARC are different,

the use and scope of scenarios both are constrained by deadlines and set budgets. Also,

for major transportation forecasting, both organizations rely on the Virginia Department

of Transportation. The project‟s work with Roanoke will also consider the approach of

TJPD as well as other approaches transportation planners use outside of Virginia.



Metro Washington Council of Governments



An application of scenario planning was recently used to predict relevant

transportation futures in Northern Virginia. “What if…The Washington Region Grew

Differently?” (2006) is a regional mobility and accessibility scenario study by the Metro

Washington Council of Governments (MWCOG). The study identifies four key issues

facing the Washington D.C. area, and matches scenarios to each issue. The issues come

from the topics of population growth, economics, and demographics. MWCOG chooses

job growth outpacing household growth as the first key. The second issue is workers

living farther away from their jobs. The third issue is the divide between the eastern and

western part of the region in terms of demographics and economics. The fourth issue is

that most growth areas are located outside transit station areas.



MWCOG‟s approach (2006) of matching a scenario to a key issue uses a

combination of the methods similar to that recommended by the Federal Highway

Administration (FHWA) (2007) and Zergas et al (2004). However, instead of using

objectives and policies, MWCOG treats scenarios as potential policies that transportation

planners can evaluate. MWCOG also develops each key issue is on a large enough scale

to match a scenario whereas FHWA and Zergas et al. both consider key issue

interactions to generate scenarios. The MWCOG approach yields more direct scenario



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addressing the key issues, however, the approach may miss important scenarios that

planners can discover by looking at the interaction between key issues. The proposed

thesis project generates scenarios by using a combination of the Zergas et al. (2004), the

FHWA (2007), and the Metro Washington Council of Government (2006) approach in

consultation with transportation planners.



Scenario-Based Planning Multimodal Planning of Other States



Transportation Planning groups outside of Virginia have also integrated scenario-

based approaches into planning. Envision Utah and the Sacramento Region Blueprint are

two out of seven noteworthy scenario-based planning application the Federal Highway

Commission (FHWA) features on its website. Most of the noteworthy scenario-based

planning applications focus on growth-based or environmental approaches to scenario-

based planning. Both Envision Utah and the Sacramento Region Blueprint are examples

of focuses on growth and land-use in scenario-based planning.



Envision Utah (http://www.envisionutah.org/process-scenario.phtml) guides the

development of Utah growth patterns similar to the Thomas Jefferson Planning District

approach. The scenario focus of Envision Utah includes the environment, economic

strength, and quality of life. Thus, part of the process of Envision Utah is to develop

scenarios that consider multiple modes of transportation in order to accomplish objective

relating to environment, housing, and mobility.



The Sacramento Region Blueprint is a transportation land-use study developed to

(http://www.sacregionblueprint.org/sacregionblueprint) aid growth in Sacramento,

California. The project uses scenarios to evaluate transportation projects and land-use

strategies. Although the Sacramento Region Blueprint uses scenarios as forecasting tools,

which is contrary to scenario-planning expert advice, the project has received planning

awards for its progress from the Environmental Protection Agency and the Federal

Highway Commission.





METHODOLOGY



This effort develops a methodology to analyze the impacts of statewide

multimodal transportation policies on regions under various scenarios, as described in

Figure 2. A Microsoft Excel workbook is automated to process the inputs from various

regions and give a local prioritization of transportation policies as data are entered by a

regional transportation planner.









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Figure 2. Scenario-based planning methodology for evaluating regional impacts of statewide

multimodal transportation policies.



The first step in the methodology is to Select Regions to use scenario-based

planning in assessing the impacts of statewide multimodal transportation policies.

The second step is to Select Scenarios that are relevant to the regions selected.

The process of selecting scenarios is done through a three step process that involves

Identification of Key Issues that effect the region, Identification of Key Factors, and the

Discussion and Combination of Issues and Key Factors. For example, two key issues for

many regions in Virginia are retirement and gas prices. Two key factors that respectively

drive these issues are the baby-boomer population reaching retirement age and the

economy. Thus, transportation planners and policy makers may choose to create two

future scenarios based on the combination of the issues and factors: increased retirement

and transit-oriented development.

The third step involves Scoring Transportation Policies Based On Evaluation

Criteria. In the methodology, the scoring is based on if the policy has a significant,

moderate, or minimal/no impact on the evaluation criteria.

The fourth step is to Weigh Evaluation Criteria with Scenarios. This step uses the

scenarios developed in the second step and the evaluation criteria in the third step.

Transportation planners and policy makers decide whether given the future scenarios if

the evaluation criteria will have anywhere from a major increase in importance to a major

decrease in importance. The importance of the evaluation criteria affects the policy

scoring in step three.

The fifth step is to Assess Policy Performance Sensitivity to the Region. Each

future scenario generates a score for a transportation policy that was evaluated in the third

step. The scenario generates the policy score by modifying the policy score for each

evaluation criterion based on the importance of the criterion in the scenario as determined

in step four. For example, a policy scores a „10‟ for evaluation criterion one.



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Transportation planners determine that for Scenario A the evaluation criterion one will

have a „major increase of importance‟. Since the criterion is more important, it receives a

weight that increases the policy score under the criterion to „15‟. If Scenario A had

evaluated the criterion as having a „major decrease of importance‟ then the policy score

under the criterion could be decreased to „5‟.

The methodology produces a set of scores for a statewide multimodal

transportation policy over relevant regional future scenarios.





RESULTS AND DISCUSSION



This effort applies the methodology to the Roanoke region in Virginia using the

Microsoft Excel Workbook tool. Appendix A features demonstrations the methodology

in the Hampton Roads, Northern Virginia, and Richmond Region.



Finding Relevant Scenarios



The second step to apply the methodology to Roanoke is to Select Scenarios. For

Roanoke, the effort involves research that includes talking to transportation planners in

the Metro Planning Organization and researching the relevant topics that affect

transportation in the region. For the statewide scope of the tool, the research is based on

the work of other states and localities such as the Sacramento Region Blueprint

(http://www.sacregionblueprint.org/sacregionblueprint) and Envision Utah

(http://www.envisionutah.org/process-scenario.phtml). The methodology for scenario-

planning adapts techniques and recommendations from methodologies used by Zergas et

al. (2004), Pearman (1986), the Metro Washington Council of Governments, and the

Federal Highway Administration.

The scenario-based planning methodology first identifies key issues in the area

that may affect the future. Several broad categories exist for these factors that include

demographics, land usage, and population shifts. This suggests individual categories for

each factor. Second, the design identifies factors that create the issues. Third,

transportation planners discuss potential scenarios that may occur because of these

factors and key issues, which are then combined to create scenarios. Scenarios that

transportation planners generate from the methodology should cover a wide scope of

issues to provide insight for transportation planners and allow anticipation of future

events that affect transportation. Figure 3 shows an example of general statewide

scenarios chosen for the effort.









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Figure 3 - Scenarios for Assessment of Transportation Policies



Case Study Scenarios



In order to demonstrate the methdology, the effort conducted a case study of the

region based on five scenarios. Bartholomew (2007, p. 14) recommends choosing an

amount of scenarios that is “not too many to confuse participants, but enough to allow for

divergent thinking and coherent story telling (Godet, 2001; Ringland, 1998, 2002).” First,

the effort interpreted the scenario, S.2 - Urban sprawl. Urban sprawl is an issue that

affects many places of growth in the region and the nation. As developers continue to

plan future residential and commercial buildings around the region and as the number of

sites to build in the city decreases, urban sprawl will increase. If the current growth rates

continue in the region, urban sprawl is inevitable despite public opposition. Thus,

regional transportation planners will need to consider the impacts of urban sprawl when

prioritizing multimodal transportation policies.

Second, the effort analyzed the impacts of scenario, S.17 - Retirement. As the

demographics of an area changes, the transportation system must adapt to meet new

demands. This is an important issue as the baby-boomer generation, a major cross-section

of the population in the United States, is reaching the retirement age. An aging population

“implies additional transit needs, changing housing needs, the need for heightened safety

standards, and residents with inflexible financial situations” (Federal Highway

Administration [FHWA], 2007). Businesses must even change how they operate, by

developing new products to target the current demographics and compensating for the

expected labor shortages (MIT Center for Transportation & Logistics, 2007). The

retirement scenario is particularly important for the region in the case study, since the

area is considered one of top places in the country to retire, as 40% of the population of

the region is 45 or older (The Roanoker Magazine, 2007). This age demographic is

concerned with maintaining their mobility, within the limits of their physical and

financial capabilities. The older population requires different forms of public transit,



DRAFT

especially ones that link them with residential, retail, and health centers (The Roanoke

Valley Area Metropolitan Planning Organization [RVAMPO], 2005).

Third, the effort studied scenario S.18 - Natural disasters relevant to the region.

Areas across the country are subject to natural disasters that cost millions of dollars in

damages.

Through the study of past disasters and local environmental factors, the hazard analysis

workgroup of the region identified flooding and wildfires as the two most likely natural

disasters for the area. The streams running through the steep terrain of the region subject

the area to periodic flash flooding. To highlight the importance of this scenario, flood

related research and documentation from the past shows that there are an estimated 5,400

structures that could possibly be impacted by flooding in the region (RVAMPO, 2000).

Fourth, the effort consider the potential of scenario S.3 - IT amenities growing in

the region. This high priority scenario is due to the large information technology and

engineering base that has developed in several surrounding areas. Many companies have

chosen to locate their work facilities and headquarters throughout the surrounding areas

due to its highly skilled technology workforce, policies that encourage business growth,

and advanced IT infrastructure (Commonwealth of Virginia, Office of the Governor,

2007).

Fifth, scenario S.19 - Decrease in air quality, is more specific to the region.

Intermodal and multimodal sources of transit stations are needed throughout the country

to support a wider range of transportation solutions for public, commercial, and several

other uses. Recently, ten areas that are in close proximity to the region were selected as

possible locations for a new rail and truck intermodal transit station. However, there has

been opposition to building transit stations in the region from environmental groups

(Christopolus, 2007). Health hazards from higher levels of soot include a 30% increased

risk of death for individuals with heart disease, lung disease, and diabetes. The current

soot level of the region already approaches the EPA soot limit of PM 2.5. Thus, a new

transit station could cause dangerous levels of soot for the local communities.



Identification of Policies



In preparation for the next step of the methodology, Score Policies Based on

Evaluation Criteria, the effort identifies multimodal transportation policies. The effort

used the 21 policies established in the statewide long-range transportation

plan, VTRANS 2025 (Virginia Department of Transportation [VDOT], 2004). The

policies fall into four main categories: funding/investment, land use, connectivity, and

priority setting. Examples of the policies include improving connections between modes,

considering state versus local rules, increasing rail funding, and starting a trust fund for

transportation.



The effort identified policies that are special to the region to allow for more direct

options for the regional transportation planners. The policies are meant to correlate with

the regional- specific scenarios that the effort developed. The additional policies relevant

to the region include P.22 - Smart growth, P.23 - Bicycle and pedestrian facilities feeder

system, P. 24 - Environmental focus, and P. 25 - Diesel and filter regulation.







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Policy P.22 - Smart growth is a growth strategy that impacts multimodal

transportation use. Smart growth focuses on building desirable communities for residents.

In a public workshop, it was shown that the public rejected urban sprawl scenarios in

favor of more “Smart-growth” patterns. Smart growth patterns mainly refer to having

denser town and urban centers. Proponents of Smart growth claim that increasing

density of population centers will decrease driving time, traffic congestion, and preserve

farmland (Thomas Jefferson Planning District Commission, 2007). Implementation of

Smart Growth would place more influence on multimodal transportation because with

more dense population centers, there is potential to use different modes of transportation.

Therefore, policy P.22 - Smart growth, will be added to the list of policies considered for

the region.

Next, the effort consider Policy P.23 - Bicycle and pedestrian facilities feeder

system (RVAMPO, 2007). Effective mobility of the baby boomers can be maintained by

providing better walking and biking facilities, as many areas lack safe or formal paths

(RVAMPO, 2006). The implementation of 12 ft. lanes to the current infrastructure

provides room for bicyclists, walkers, and users of any other personal ride-along type

devices to travel. The lanes could connect shopping and residential districts, bus stops,

and park and ride lots. Many bikes are publicly available and buses have been equipped

with bike racks. Policy P.23 - Bicycle and pedestrian facilities feeder system, will give

the aging population more transportation options, while allowing them to maintain a

healthy lifestyle and help the environment.

Policy P.24 - Environmental focus, is another potential policy for the region.

Some of the more recent natural disasters have been linked to global warming

(Environmental Protection Agency, 2007). Scientists have suggested that the recent

drought is linked to climate changes associated with global warming. The land being

extremely dry increases the likelihood of wildfires. If the region and the nation set forth

efforts to reduce carbon emissions, the more recent climate extremes and possibility of

natural disasters would be reduced (RVAMPO, 2007).

Last, the effort study Policy P.25 - Mandate of ultra low sulfur diesel and filters

for all new trucks (Christopulos, 2007). To allow the intermodal truck and train transit

station to be built in the region, all new trucks must use ultra low sulfur diesel with air

filters. The filter rule would only apply to trucks of model year 2007 and beyond, and

eventually to all trucks by the year 2030. The policy would reduce the sulfur emissions

by 90% or more, particulate emissions up to 80%, and nitrogen oxide up to 20% . The

reduction of emissions would help to maintain levels of soot under the EPA monitored

levels of PM 2.5. Ultra low sulfur diesel mandates would also apply to all other diesel

vehicles using the facility, such as off-road vehicles.





Selection of Performance Criteria



Next, the effort identified performance criteria from the statewide long-range

transportation plan to measure the impact of a policy and to weight different scenarios.

The performance criteria consist of safety, efficiency, economic vitality, quality of life,

and feasibility. Sub-criteria are used to more specifically define the different aspects of

the performance criteria. For example, sub-criteria, C.1.1.a under safety asks if the policy



DRAFT

will, "Improve safety for system users and operators within the system and at mode

origins/destinations (e.g., improve safety at at-grade crossings, improve bicycle and

pedestrian safety, correct sub-standard (safety) designs and other geometric/pathway

(e.g., runway obstructions, channel depth, bridge clearance, etc) deficiencies)."

Within the subcriteria are the performance measures, which directly evaluate the

policies. The performance measure under sub-criteria C.1.1.a is, "Does the policy

significantly reduce crashes and/or incidents?" There are 13 criteria and 34 sub-criteria

and performance measures currently included in the tool. To determine the overall scores

for policies, the effort evaluated the impact of each policy across each of the performance

measures. The methodology uses a rating of 0 for a minimal or an unknown impact, 0.5

for a moderate impact, and 1 for a significant impact.



Scoring Policies Based on Evaluation Criteria



Figure 5 shows how in step three of the methodology transportation planners score

policies using a high, medium and low/not sure scale. In the application the

methodology, the effort uses a 0, 0.5, 1, scale for scoring the impacts.









Figure 5 - Multimodal Transportation Policy Assessment Before Scenario Evaluation









Using Scenarios for Scoring Policies



The fourth step of the applied methodology is to Weigh Evaluation Criteria with

Scenarios. Since the scenarios weigh the policies, they must cover a wide range of topics

and concerns. Moreover, scenarios do not serve to predict the future, they do not have to



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be proven inevitable or probable; they must represent transportation planning concerns.

Thus, the survey tool allows transportation planners to add new scenarios as time

changes. Therefore, transportation planners can easily update the survey tool. Because the

survey tool is built with Microsoft Excel, most planners will be able to edit the survey

tool with little difficulty.



Modifying Scenario Impacts for Users



The weighting of the scenarios by transportation planners is one of the most

important aspects of the methodology. The Virginia Department of Transportation

provides high level criteria for regional transportation planners to evaluate against the

scenarios. The criteria include safety, land preservation, efficient movement of people

and goods, economic vitality, quality of life, and program delivery. Transportation

planners rank the criteria importance from major increase to minor decrease in the case of

a scenario as shown in Figure 4.









Figure 4 – Policy Evaluation Criteria Weighting By Scenario



The survey tool has the criteria set to equal values for default. If a transportation planner

increases the weight for criteria, the score that each policy receives in the criteria will

increase for the scenario. Transportation planners choose major increase for criteria that

may have a large increase in an importance during a scenario. For example, in the event

of a natural disaster, the efficient movement of people would have a higher importance.

Conversely, transportation planners chose major decrease for criteria that may indicate a

large decrease in importance during a scenario. There were not any major decreases for

the Roanoke case. Most of the impacts for the Roanoke case are minor increases and

decreases. Major increases and decrease affect the criteria by doubling the magnitude of

the score, minor decreases and increase the magnitude of the score by 1.5 times. The

increase in weight for the criteria is relative, meaning that if all criteria importance

increase or decrease in the same manner for a scenario, the criteria will still have the

same weight. In the results section of the survey tool, the tool displays the policies and

their scores in different scenarios.



The Sensitivity of Policy Ranking on Scenario Evaluations



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The fifth and final step, Assess Policy Performance Sensitivity to Region, involves

synthesizing the information developed in the previous steps of the methodology. To

inform the transportation planners of the effects of the scenarios on the policy

prioritization, there are several displays in the survey tool representing the policy scoring.

The survey tool uses a table to display the scores of the policies against the scenarios as

well as the mean score of each policy. The tool includes another table that shows the

ranking of each policy against other policies for each scenario. Scatter plot graphs

accompany both tables in the survey tool. The graphs show the wide range of policy

effects. The displays of policy scores are critical for the survey tool to fulfill the

objective of providing a method for transportation planners to get more acquainted with

the affects of multimodal transportation policies in varied futures.

After planners enter input into the survey, the survey tool outputs scores for the

policies. Transportation planners can choose from different methods to prioritize these.

The mean score is presented as one method; however, different policies score higher

depending on scenarios. Figure 6 shows the results of the policy scoring for Roanoke.









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Figure 6 - Overall Policy Impact Scoring









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The mean score of the policy for all the scenarios is the main scoring method the team

uses in this iteration of the survey tool. Figure 7 shows that most of the range of scores

for each policy, using the highest score and lowest score for a scenario. Many of the

scores overlap, which indicates that transportation planners need to consider more than

just the mean score of the policies.









Figure 7 - Range of Policy Impact Scores with Top Scores Circled









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Figure 8 and 9 shows the relative ranking for each of the policies. The highest

scoring policies are highlighted in green in figure 8.









Figure 8 - Rankings of Policies Based on Scenarios









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Figure 9. – Graph of Rankings of Policies Based on Scenarios





The top five policies based on the mean score are P.2 - support transit, P.15 -

think multimodally, P.13 - invest in technology, and P.22 - smart growth. The specific



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policies chosen in the prioritization are less important than the methodology and ability

for transportation planners to adapt and effectively use the methodology to prioritize

policies.

The top rated policies, P.1 - invest in technology and P.15 - think multimodally,

both have the same amount of first and second place rankings throughout the scenarios.

Policies P.22 - smart growth and P - support transit also have the same score; however,

they rank higher and lower in different scenarios. The next chapter discusses the results

of the applying the methodology with the survey tool as well as scenario-based planning

in tools and transportation planning methodologies.



A recommendation for the survey tool is that transportation planners consider

both mean score and individual scenario rankings. Some of the possible evaluation

methods for transportation planners are weighting scenarios, using one scenario as a tie-

breaker or most important scenario, or using the standard deviation in rankings. The

survey tool provides the information to the transportation planners to allow for several

ways to prioritize the policies.



Uses of the Methdology



The effort designed the methodology and survey tool to be adaptable to several

metropolitan planning organizations (MPO) and regions of Virginia. Therefore, one of

the major benefits of the survey tool is its flexibility. Transportation planners can add and

take away scenario and policies as well as change the weighting of policy evaluation

criteria compared to scenarios. The survey tool contributes a formal methodology for

prioritizing multimodal transportation policies as requested by the sponsors of the effort,

the Multimodal Office. The scenario-based approach of the survey tool provides an

improvement over other methodologies in terms of providing transportation planners with

a more holistic view of the future in addition to forecasting methods.



Demonstrations in Other Virginia Regions



The purpose of these examples is to demonstrate the robustness of regional

scenario-based planning for evaluating statewide multimodal transportation policies. The

examples include regions in the commonwealth of Virginia that have varying long term

transportation planning needs based on geographical location, demographics, and other

characteristics. Each example portrays the utilization of scenario-based planning on a

regional level and its effects on the prioritization of transportation policies. The result of

these examples illustrates the ability for scenario-based planning to coordinate statewide

multimodal transportation policy prioritization among regions.

In order to demonstrate the needs of the region and the efficaciousness of

scenario-based planning, the effort performed a case study of four major regions in the

commonwealth of Virginia. These regions are based on the boundaries for the Virginia

Association of Planning District Commission. In addition to R.1 – Roanoke, the regions

chosen were Region R.4 - Richmond, R.2 - Hampton Roads, and R.3 - Northern Virginia.

For each region, the effort observed and analyzed regional factors such as population,

employment, researched long term predictions and planning methodologies and



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interviewed transportation planners (reference survey?). In the case studies, after

expounding on regional factors, the effort applied the scenario-based planning workbook

tool to the region. The demonstrations are featured in Appendix A. The final result

provides a policy prioritization recommendation that indicates the results of the diverse

needs of the differing areas.



Findings from Demonstration



The case studies in the diverse regions of Virginia displayed the variety of potential

futures based on the unique characteristics of each region. One of the top policies for all

regions was Policy P.2 – Support Transit. The other demonstrations are detailed in

Appendix A. However, there were other policies that scored similarly and robustness

against future scenarios must be taken into consideration during policy prioritization by

transportation planners. The effort utilized scenario-based planning to account for the

different futures of the region and improve coordination potential among the regions by

considering the regional impacts of scenario-based planning on statewide multimodal

transportation policies. The variety in these regions shows an increased need for

coordination of future plans. Scenario-Based planning provides a way to better anticipate

future state and regional transportation needs.



Scenario-Based Planning Integrated with Current Methods



Transportation planners can use the survey tool in conjunction with other current

methods. In Roanoke, transportation planners can use the survey tool as a filter to decide

which policies transportation planners will forecast and evaluate (M. McCaskill, personal

communication, February 25, 2008). Also, transportation planners can use scenario-based

planning to account for different characteristics in multiple regions. Scenario-based

planning can also be applied to transportation planning other than policy planning.

Feedback from the Roanoke MPO and Multimodal Office indicate that the scenario-

based planning methodology has potential to integrate with current planning methods and

provide more insight into the possible impacts of multimodal transportation policies in

the future (M. McCaskill, personal communication, February 25, 2008). Transportation

planners often need to evaluate long-term transportation projects and transportation

planners can use scenario-based planning in similar way as they can with prioritizing

long-term transportation policies. Financial constraints are another large concern for

transportation planners. Transportation planners can integrate financial future scenarios to

use scenario-based planning to better understand financial risks for transportation policies

and projects. For transportation planners in Virginia to use scenario-based planning

effectively, the approach must be understood by planners and reasonably integrated into

current planning methods. The scenario-based approach‟s ability to integrate into other

Virginia regional transportation areas is integral to further proving scenario-based

planning use in Virginia and may serve as the topic of a future project.

Economic, demographic, spatial, and environmental scenarios are more important

than ever before, and it is essential that local, state, and federal government agencies

properly plan for the scenarios. The survey workbook incorporates scenario-based

thinking into long-range transportation planning and is the foundation of a model that



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will be the next generation of transportation planning.

In order to expand the use of the survey workbook and scenario-based planning

approach, the team researched scenario-based planning throughout the state and

conducted a preliminary survey of other Metropolitan Planning Organizations (MPO) in

the state. The survey included high level scenarios such as industrial growth, population

growth, and natural disasters. Regional needs for scenario-based planning differ. The

results of the survey indicated that adjustments are necessary to the survey workbook and

the scenario-planning approach to effectively aid transportation planning.





CONCLUSION



The application of the policy prioritization methodology in Roanoke successfully

introduced scenario-based planning to the Roanoke Valley Metropolitan Planning

Organization. The effort exceeded most applications of scenario-based planning in

literature by working with transportation planners to revise and improve the survey tool

for usage in other regions of Virginia. As discussed in the literature review, one of the

major criticisms of traditional transportation planning is the lack of single resulting

strategy and lack of holistic approach for future predictions. The project‟s scenario-based

planning approach exposed transportation planners in Roanoke to the holistic approach of

considering multiple futures and categories of events when evaluating long-term

transportation policies. The project prepares scenario-based planning for usage in other

regions in Virginia and potentially in other states. The Multimodal Office also approved

of the concept of the survey tool, and its potential to coordinate state transportation policy

prioritizations and evaluation criteria with regions within the state.

The survey tool may have to be thoroughly revised for other regions based on

existing methods, but the focus, scenario-based planning, can integrate more smoothly

with other regions. The survey workbook can be customized and used in different regions

and localities. The Office of Multimodal Transportation Planning will able to use

regional and local policy prioritizations to support its overall statewide plan. With more

testing and evaluation, the survey workbook can be used to help states, regions, and

localities more effectively prioritize multimodal transportation policies for the long-term

and positively impact transportation. Additional scenarios and regions may be added in

the future. The ability of the survey workbook to integrate scenario-based planning

maximizes its effectiveness in ranking additional policies to be added in the future. Long-

range planning decisions can be made by determining the potential impacts on additional

regions and their scenarios.

The survey tool is a simple demonstration of the use of scenario-based planning.

The main reason for the ease of integration for the scenario-based planning approach the

project uses is its flexibility. For example, the survey tool uses Virginia Department of

Transportation criteria to evaluate policies. A Metropolitan Planning Organization (MPO)

can easily change the evaluation criteria to the federal mandated criteria. The scenario-

based planning approach can be made more complex or simpler to account for other

regions transportation processes. Transportation planners and policy makers can also use

scenario-based planning to evaluate transportation projects and their financial constraints,

in addition to the main focus of the project, prioritizing transportation policies. As the



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literature states, there is still hesitation from transportation planners for using scenario-

based planning as part of a formal transportation planning methodology. The approval of

metropolitan planning organizations such as Roanoke will help scenario-based planning

to quickly gain more acceptance as a formal tool for transportation planning.





RECOMMENDATIONS



In the future, the scenario-based planning approach will need several more test

cases and reviews by transportation planners. Since there are many different applications

for scenario-based planning, it is not necessary that the scenario-based planning approach

is unique to the survey tool. Surveys and polls of how transportation planners can use

scenario-based planning in the transportation process will provide guidance to the

creation of a more formal scenario-based planning approach. Appendix E details a brief

survey this effort undertook. Appendix D shows an additional draft-survey that could be

issued to transportation planners in Virginia. The focus for testing scenario-based

planning should be mainly among the metropolitan planning organizations (MPO‟s) in

Virginia. The Virginia Department of Transportation should also be strongly involved in

developing scenario-based planning so the process can be better standardized throughout

the state.

Transportation is an industry that affects all residents of Virginia and many more

people that travel in Virginia. Transportation policy makers and planners acknowledge

the importance of being able to properly plan for transportation in the future as

population increases and more people use transportation (M. McCaskill, personal

communication, February 25, 2008). Scenario-based planning provides a new way for

transportation planners and policy makers to holistically plan for a complex future. Thus,

the attempt to implement and use scenario-based planning as part of the transportation

process is a beneficial and worthwhile project.



COSTS AND BENEFITS ASSESSMENT



This report has described initial steps and associated lessons for the use of regional

scenario-based planning. The potential benefits of such a framework include:



 Coordination of regional long term planning with other regions and

commonwealth

 Characterization of the future to improved policy decisions

 Facilitation of communication among regional planners

 Identification of regional needs through future scenarios

 Potential for quantifying policies better with future scenarios







The costs of implementing such a framework whose development is approached in this

report include:





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 Resources needed to survey and hold workshops for regions

 Time needed to update and adjust regional long term planning standards

 Resources to accommodate shift in planning approach

 Time and resources needed to coordinate efforts regionally



ACKNOWLEDGMENTS



We would like to thank members across Virginia‟s transportation agencies that

provided a wealth of information and advice, notably: Mary Lynn Tischer of the

Multimodal Office, Kimberly Spence, Katherine Graham, and Michael Garret of VDOT,

Mark McCaskill of RVAMPO, Wayne Ferguson and John Miller of the Virginia

Transportation Research Council, members of the Multimodal Advisory Committee, and

Ralph Davis, Deputy Secretary of Transportation for Virginia.









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REFERENCES



TransAction2030 (2006). Transaction 2030: Transportation for Today and Tomorrow.

Northern Virginia Transportation Authority. 12 pp.



Bartholomew, K. (2005). Integrating Land Use Issues Into Transportation Planning:

Scenario Planning. Retrieved June 3, 2008, from http://nepa.fhwa.dot.gov/.



Cervero, R., & Aschauer, D. (1998). Economic impact analysis of transit

investments:Guidebook for practitioners. Retrieved October 30, 2007, from

http://trb.org/news/blurb_detail.asp?id=2582



Christopulos, D. (2007). Sierra Club Opposes Intermodal Transfer Station in Roanoke

Region. Retrieved December 3, 2007, from

http://virginia.sierraclub.org/roanoke/intermodal.pdf



Cole, Sam (2001). Dare to Dream: Bringing Futures into Planning. Journal of the

American Planning Association, 67(4), 372 – 383.



Commonwealth of Virginia, Office of the Governor. (2007). Governor Kaine

Announces New Jobs for Arlington County-GridPoint, Inc. to Invest $5 Million

and Move Headquarters to Virginia. Retrieved November 24, 2007, from

http://www.yesvirginia.org/About_Us/NewsArticle.aspx?newsid=900.





Delaware Valley Regional Planning Commission. (2005). Regional Analysis of What-If

Transportation Scenarios. Retrieved October 31, 2007 from

http://www.dvrpc.org/LongRangePlan/2030/WhatIfFinal.pdf.





Environmental Protection Agency. (n.d.). Climate Change – Health and Environmental

Issues. Environmental Protection Agency. Retrieved December 12, 2007, from

http://www.epa.gov/climatechange/effects/extreme.html



Federal Highway Administration. (2007). FHWA Scenario Planning Initiatives.

Retrieved June 4, 2008, from

http://transportation.ky.gov/planning/Scenario/1%20McCullough%20FHWA.pdf



Federal Highway Administration. (2004). Scenario Planning Peer Workshop –

Binghamton, NY. Retrieved October 18, 2007, from

http://www.fhwa.dot.gov/planning/scenplan/nyscenplanrpt.htm



Federal Highway Administration. (n.d.). Scenario planning. Retrieved October 24, 2007,

from http://www.fhwa.dot.gov/planning/scenplan/about.htm







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ICF International. (2007). The Potential Impacts of Global Sea Level Rise on

Transportation Infrastructure. Retrieved June 6, 2008, from

http://climate.dot.gov/publications/potential_impacts_of_global_sea_level_rise



MIT Center for Transportation & Logistics and The Zaragoza Center at the ZLC. (2006).

Proceedings of the Supply Chain 2020 Project’s European Advisory Council Spring 2006

Meeting. Retrieved October 18, 2007, from

http://ctl.mit.edu/public/spring_2006_sc2020_eac.pdf



National Capital Region Transportation Planning Board. (2007). Financially Constrained

Long-Range Transportation Plan. Retrieved June 6, 2008 from http://www.

Mwcog.org/clrp



National Capital Region Transportation Planning Board and the Metropolitan

Washington Council of Governments. (2004). What If The Washington Region Grew

Differently?: The TPB Regional Mobility and Accessibility Scenario study. Retrieved

October 4, 2007, from

http://www.mwcog.org/transportation/activities/regional/documents/Generic%2

0for%20Web%207-07.pdf



Richmond Area Metropolitan Planning Organization. (2007). 2031 Long-Range

Transportation Plan. Retrieved July 5, 2008, from

http://www.richmondregional.org/Urban%20Transp-MPO/MPO_Div_Cats/toc.htm



Roanoke Valley Area Regional Commission. (2006). Pedestrian Access to Commercial

Centers: Connecting residential and commercial Land uses. Retrieved December 1,

2007, from http://www.rvarc.org/work/access06final.pdf



Roanoke Valley Area Regional Commission. (2006). Roanoke Valley-Alleghany

Regional Commission Pre-Disaster Mitigation Planning. Retrieved October 17, 2007

from http://www.rvarc.org/disaster/index.htm



Roanoke Valley Area Metropolitan Planning Organization. (2005). Planning for Elderly

and Disabled Mobility. Retrieved October 18, 2007, from

http://www.rvarc.org/work/mobilityfinal.pdf



Roanoke Valley Area Metropolitan Planning Organization. (n.d.). What happens when

the ‘baby boom’ generation retires? Retrieved November 3, 2007, from

http://www.rvarc.org/temp/retirement.pdf



The Roanoker Magazine. (2007) Where to Retire. Retrieved November 1, 2007, from

http://www.theroanoker.com/visitorguide/wheretoretire/index.cfm.



Rovner, N. (2008). Governor’s Commission on Climate Change. Presentation to the

Hampton Roads Planning District Commission.







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Thomas Jefferson Planning District Commission. (n.d.). Jefferson Area Eastern Planning

Initiative. Retrieved December 3 2007, from http://www.tjpdc.org/community/epi.asp



Transportation Accountability Commission. (2007). Final Report of the Transportation

Accountability Commission to the Governor and General Assembly of Virginia. Retrieved

November 3, 2007, from

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ft%20_%20full_report_9_5_07.pdf



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Range Transportation Plan: Phase 3 and Final Report to the General Assembly.

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Zergas, C., Sussman, J., Conklin, C. (2004). Scenario Planning for Strategic Regional

Transportation Planning. J. Urban Planning and Development, 130(1), 2-13.









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APPENDIX A: SCENARIO-BASED PLANNING DEMONSTRATIONS





Region R.2 - HAMPTON ROADS



Overview



Hampton Roads is located in southeast Virginia and borders the Chesapeake Bay as well

as the Atlantic Ocean. Figure 10 depicts the Hampton Roads Planning District

Commission boundaries.









Figure 10. Hampton Roads Planning District (Hampton Roads Planning District Commission, 2008)



The boundaries of the planning district are the focus for the case studies. The

geographical location of the area, along with the demographics and cities give the area

several unique characteristics. Multimodal transportation policies that consider increaing

population and employment will be considered, as well as the relevant scenario of sea

level rising.



Policies



The Hampton Roads area is a growing region and thus must account for the complexities

associated with population growth and employment shifts. For example, according to the

long term transportation plan (cite), there is an expected increase in population in the

area by over 442,000 between 2000 and 2030, an annual growth rate of 0.8%. Virginia

Beach will experience the largest locality increase in population, with an increase of over

105,000 people (17). In terms of population, The HRMPO area is expected to add an

additional 243,000 employees between 2000 and 2030, an annual growth rate of 0.8%

(18). The following policies were used in conjunction with the workbook tool:



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P.4 – Fund Rail



The Intermodal Management System Regional Study for Hampton Roads was published

in 2007 (cite). The study analyzes and summarizes the important of freight movement for

the Hampton Roads area.

One of the major ways freight movement is performed is through rail. Four major

rail routes that connect the nations east-west rail system begin and end in Hampton roads.

According to the study, for “Hampton Roads to remain competitive in attracting new

business, it must facilitate the rapid and efficient movement of new materials and finished

products using…trains” (2). For example, $322 million project cost is predicted for

improving the Heartland Corridor (103). As shown in figure X, the dollars per ton for

Hampton Roads freight is expected to increase in the future.



Table 1. Dollars Per Ton for Hampton Roads Freight (Intermodal Management System Regional

Freight Study, 2007)









P.24 - Going Green



Environmental concerns are relevant to the Hampton Roads area. Given the high

population of the area and increasing freight activity, there is the potential for a high

amount of pollution. The Hampton Roads 2030 Transportation Planning report (cite)

contains a section for environmental mitigation activities. Potential policies and methods

for going green mentioned in the report include “avoiding impacts altogether,

minimizing a proposed activity/project size or its involvement, rectifying impacts

(restoring temporary impacts), precautionary and/or abatement measures to reduce

construction impacts, employing special features or operational management measures

to reduce impacts, and/or compensating for environmental impacts by providing

suitable, replacement or substitute environmental resources of equivalent or greater

value, on or off-site.” (99).



Scenarios



Because of the high population of the Hampton Roads area and the wealth of multimodal

transportation, there are several scenarios that should be considered in order to properly

prioritize transportation policies. The scenarios that this thesis analyzed were sea rise and

IT amenities growth.



S.20 - Sea Rise



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One of the region‟s main concerns is global warming. Deputy Secretary of Transportation

for Virginia Ralph Davis gave a presentation on (some date) about the dangers of global

warming and the potential effects of climate change. (further info, numbers and stuff)

The Hampton Roads area is especially prone to the negative effects of global warming

given its environment. One of these effects is sea level rising.

In 2007, ICF International published a report entitled “The Potential Impacts of

Global Sea Rise on Transportation Infrastructure”. The report covers the District of

Columbia, Maryland, North Carolina, and Virginia. Norfolk Harbor was identified as an

area of concern given the density of its economic activity and location. The figure below

is from a presentation by Nikki Rovner, Deputy Secretary of Natural Resources on the

Governor‟s Commission on Climate Change (2008). The dark blue areas represent areas

at-risk for flood damage.









Figure 11. Risk Areas for Flood Damage around the Hampton Roads Area



The presentation discusses the effects of sea-rise and the areas most at risk in the

Hampton Roads Area, as well as throughout Virginia. Planners in the Hampton Roads

area should be consider this scenario when developing future transportation policies.



S.5 - Transit Oriented Development



In a survey sent out to Planning District Commissions in Virginia, the Hampton Roads

Planning District mentioned transit oriented development as an important scenario for

consideration in the future. One of the goals for the area in the long term transportation

plan is to “Increase the accessibility and mobility options available to people and for

freight. And set aside funding for mass transit projects.” Two current long term projects

in the Hampton Roads district are the Norfolk Light Rail and Peninsula Fixed Guideway.

Both these projects will help the area in increasing transit usage and capability.



Workbook Analysis

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We used the background information and simulated the use of our workbook tool to

recommend a prioritization of multimodal transportation policies for Hampton Roads.



We used the background information and simulated the use of our workbook tool to

recommend a prioritization of multimodal transportation policies for Hampton Roads.

Figure 12 shows the weighting of the critieria against the future scenarios for the

Hampton Roads region.









Figure 12. Survey Workbook Criteria Weighting over Scenarios for the Hampton Roads Region



The weighting of the criteria based on the scenarios relevant to Region R.2 – Hampton

Roads results in the prioritization of the five policies shown in figure X.









The lines extending from the points represent the minimum and maximum scores of the

policies using the scenarios S.5 – Transit Oriented Development and S.20 – Sea Rise.

Policy P.2 – Support Transit ranked the highest overall, however, the policy score



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overlapped with Policy P.4 – Fund Rail. Policy P.23 – Bicycle and Pedestrian Facilities

Feeder System and Policy P.24 – Going Green both scored lower than the other three

policies. The result does not suggest that these policies should not be considered, on the

contrary, these policies are important policies. The results indicate that these policies may

need to be examined for robustness in future scenarios and closely examined when being

combined with other policies and projects that implement the policies.



Conclusion



We found that several multimodal transportation policies score strongly against future

scenarios relevant to the region. Some policies score lower than others and thus may not

be as robust in future scenarios. The diversity of the Hampton Roads area poses many

challenges for transportation planners. As demonstrated in this case study, scenario-based

planning helps planners identify future factors and needs of the area that contribute to

current policy decisions.





Region R.3 - NORTHERN VIRGINIA



Overview



The northern Virginia area is one of the most populous in the commonwealth. The region

generates a significant portion of the wealth for Virginia. Regional planning in Northern

Virginia is managed by the Metro Washington Council of Governments. Figure 20

displays the boundaries of the Metro Washington Council of Governments.









Figure 20. Virginia Member Jurisdictions for Metro Washington Council of Governments

(http://www.mwcog.org/about/jurisdiction/, 2008)









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Fairfax, Loudon, Arlington and Prince William counties are included in the

region. The combined population of the four counties out of ninety five total

commonwealth counties sums to 1,863,407 (2006 census) or roughly 25% of the Virginia

population. As of January, 2008, Fairfax County, Loudon County, Arlington County, and

Prince William County rank first, second, ninth, and eighteenth respectively in a list of

the highest median in the nation. Along with the density and prosperity, the region also

contains a multitude of transportation planning issues.



Policies



P.2 - Support Transit



One of the five main strategies in the MWCOG vision plan is to encourage the use of

transit, especially for tourists. In the long range plan, there are 13 major transit related

project plans including Dulles Corridor Rapid Transit and increasing HOV lanes on the

National Capital Beltway.



P.22 – Increase Investment in Transportation



According to MWCOG, the traffic infrastructure in the region needs heavy maintenance.

Moreover, the highway system will not keep pace with the population growth in the

region as shown in Figure 21.









Figure 21. Forecast Trends for Transportation Volume in Northern Virginia (National Capital

Region Transportation Planning Board and the Metropolitan Washington Council of Governments,

2004)



As predicted population and jobs increase as shown by Figure 22 the area will continue to

need to invest in transportation.









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Figure 22. Predicted Job and Household Growth Rate in MWCOG Jurisdiction (National Capital

Region Transportation Planning Board and the Metropolitan Washington Council of Governments,

2004)







P.23 - Bicycle and Pedestrian Facilities Feeder System



Objective four in the TBP‟s vision plan is to create convenient bicycle and pedestrian

access. This policy also aligns with the Air Quality: Mobile Source Emissions plan

(National Capital Region Transportation Planning Board, 2007) in the long range plan.

There also several environmental iniativies in the area such as

http://www.commuterpage.com/ as presented at the Virginia Associate of Planning

District Commissions Summer Conference 2008.



Scenarios



S.5 – Transit Oriented Development



Smart growth, or higher density planning, is one of the concepts regional planners are

currently considering. In the long range plan (National Capital Region Transportation

Planning Board, 2007) indicates a vision of “healthy regional core and dynamic regional

activity centers with a mix of jobs, housing and services in a walkable environment.” The

scenario planning MWCOG document provides an example of potential “regional activity

centers” represented in red (National Capital Region Transportation Planning Board,

2007).









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Figure 23. Scenario of Regional Centers (National Capital Region Transportation Planning Board

and the Metropolitan Washington Council of Governments, 2004)







S.4 - Job/House Shifts



Job and Households may shift in the region, especially in Fairfax county, where new jobs

and population is continually increasing. The jobs/houses may shift as a result of

commute times, as displayed in Figure 24.









Figure 24. Commute Time During Morning Rush Hour in Northern Virginia Region and the

Metropolitan Washington Council of Governments, 2004)









S.5 - Transit Oriented Development (see survey)



Transit oriented development is a probable scenario that the region will face. It is

mentioned in the MWCOG “What If the Region Grew Differently?” Scenario planning

paper (2004). Figure 25 below represents potential extensions of transit in the region.





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Figure 25. Transit Oriented Development Scenario (National Capital Region Transportation

Planning Board and the Metropolitan Washington Council of Governments, 2004)







The effect of transit oriented development may lead to more people moving closer to jobs

and vice versa. Housing and population shift are two major policy concepts that are

impacted by this scenario.



Workbook analysis



We used the background information and simulated the use of our workbook tool to

recommend a prioritization of multimodal transportation policies for Northern Virginia.

Figure 26 shows the weighting of the criteria against the future scenarios for the Norhtern

region.









Figure 26. Survey Workbook Criteria Weighting over Scenarios for the Northern Virginia Region









The weighting of the criteria based on the scenarios relevant to Region R.3 – Northern

Virginia results in the prioritization of the five policies shown in Figure 27.



DRAFT

The lines extending from the points represent the minimum and maximum scores of the

policies using the scenarios S.4 – Region Divided and S.5 – Transit Oriented

Development. Policy P.2 – Support Transit ranked the highest overall, however, the

policy score overlapped with Policy P.1 – Invest More in Transportation. Policy P.4 –

Fund Rail scored lower overall than policy P.9 – Address Transportation/Land Use

Conflicts, however, it scored much higher in one of the scenarios and may need further

analysis during policy consideration and prioritization.



Conclusion



In conclusion, the northern Virginia area is a highly populated and prosperous area that

faces many transportation-related challenges in the future. The Metro-Washington

Council of Governments has used scenario-based planning in the form of normative

scenarios to help anticipate and improve future transportation conditions. Planning for the

future is an integral activity in this region as the region is crucial to the economy of the

commonwealth.



RICHMOND



Overview



The Richmond region is considered one of “the big three” among the Virginia

Association of Planning District Commissions due to its population. The city of

Richmond is home to the capital of the commonwealth as well as the governors office.

The city of Richmond deals with similar issues as Northern Virginia, though considers

different geographical situations. Figure 28 shows the areas associated with the

Richmond region.









DRAFT

Figure 28. Richmond Planning District Commission Jurisdiction

(http://www.richmondregional.org/default.htm)







Policies



P.1. – Invest More in Transportation



Invest more in transportation is one of the policies transportation planners chose in the

scenario-based planning survey. Table 2 shows the planned spending by the region for

the long-range 2031 transportation plan. (2007)



Table 2. 2031 Long-Range Transportation Plan Estimated Funds ($1,000's)

(http://www.richmondregional.org/Urban%20Transp-MPO/MPO_Div_Cats/toc.htm)









P.6 - Strengthen Planning and Modeling



Strengthen planning and modeling was also selected by the Richmond regional

transportation planners in the survey. Planning and modeling standards are emphasized





DRAFT

by SAFETEA-LU regulations which require Metro Planning Organizations (MPOs)

within PDC‟s to create and adhere to long range plans.



Scenarios



Scenarios:



S.2 - Sprawl accelerates



Sprawl acceleration is a common scenario in regions with large cities, such as Richmond.

Forecasts by the region show an overall predicted population increase of 56.5% and a

percent change in households of 61.9% as shown by Table 3.



Table 3. Population and Households - Richmond Region

(http://www.richmondregional.org/Urban%20Transp-

MPO/MPO_Div_Cats/lrtp_files/Chapter_6_August_2008.pdf)









S.10 – In-Migration Increases



Increased urban population accompanies the previous scenario of sprawl acceleration.

Both scenarios may very well happen in conjunction as well as independently. The

Region predicts a 3.4% increase in population for Richmond in 2031. Figure 29 shows

the increased population density forecast for 2031, with high density increases predicted

in Richmond with the higher density in darker red and Richmond focused in the

rectangle.









DRAFT

Figure 29. 2031 Predicted Population Density Forecast for Richmond Region

(http://www.richmondregional.org/Urban%20Transp-

MPO/MPO_Div_Cats/lrtp_files/Chapter_6_August_2008.pdf)



Workbook analysis



We used the background information and simulated the use of our workbook tool to

recommend a prioritization of multimodal transportation policies for Richmond. Figure

30 shows the weighting of the criteria against the future scenarios for the Richmond

region.









Figure 30. Survey Workbook Criteria Weighting over Scenarios for the Richmond Region



The weighting of the criteria based on the scenarios relevant to Region R.4 – Richmond

results in the prioritization of the five policies shown in figure 31.









DRAFT

The lines extending from the points represent the minimum and maximum scores of the

policies using the scenarios S.2 – Sprawl Accelerates and S.10 – In-Migration increases.

Policy P.2 – Support Transit ranked the highest overall, however, the policy score

overlapped with Policy P.1 – Invest More in Transportation. Policy P.4 – Fund Rail

scored lower overall than the two other policies; however, the policy maximum scores

overlapped the scores of the top two policies. Policy P.6 – Strengthen Planning and

Modeling is the second highest scoring policy and is robust against the two scenarios

which may make the policy a higher priority for planners.



Conclusion



Several of the policies evaluated using the workbook tool had similar overall scores but

varied with future scenarios. The variation of the impacts of regional scenarios on

statewide policies indicates the significance of scenario-based planning. The Richmond

region contains many similar challenges to Northern Virginia but differs in terms of

demographics and geography. Planning and investment in transportation stand as

important policies with the consideration of future scenarios that may affect

transportation.









DRAFT

APPENDIX B: SURVEY AND ANALYSIS OF SCENARIO-BASED PLANNING

BEST PRACTICES





Example of Survey Sent to Metropolitan Planning Organizations









DRAFT

DRAFT

























































DRAFT

DRAFT

DRAFT

DRAFT

DRAFT

Thank you for your participation.





Analysis of Survey







The following PDCs and MPOs responded:

 George Washington Regional Commission

 Hampton Roads PDC

 National Capital Region

 Region 2000

 Blacksburg, Christiansburg, Montgomery Area MPO

 Roanoke Valley-Alleghany Regional Commission

 Northern Shenandoah Valley Regional Commission

 Crater Planning District Commission

 Lenowisco Planning District Commission

 Richmond Regional Planning District Commission



We recorded and analyzed the quantifiable results of the survey. To analyze the regional

differences in Virginia, we included analysis of the west and east PDCs and MPOs. The

west PDCs/MPOs include: Region 2000, Northern Shenandoah Valley Regional

Commission, Blacksburg/Christiansburg/Montgomery Area MPO, Roanoke Valley-

Alleghany Regional Commission, and Lenowisco Planning District Commission. The

east PDCs/MPOs include: Hampton Roads PDC, National Capital Region, Crater

Planning District Commission, George Washington Regional Commission, and

Richmond Regional Planning District Commission. Figures 14 and 15 show the overall

percent relevance of scenarios and policies to the PDCs/MPOs.

100.00%

80.00%

Percent Use

60.00%

40.00%



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Figure 14. Overall Relevant Policy Percentage









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70%

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Figure 15. Overall Relevant Scenario Percentage



The policies P.23 - Bicycle and Pedestrian Facilities Feeder System, P.1 - Invest more in

transportation, and P.2 - Support Transit stand out in the survey as being overall

important policies in the commonwealth of Virginia. The scenarios of S.8 - Energy cost

rises and S.2 - Sprawl accelerates were found to be important in Virginia with a 70% and

60% use in the PDCs/MPOs surveyed.

Figures 16 and 17 show the breakdown of relevant policies for the east and the west

region.





100.00%

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60.00%

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Figure 16. Eastern PDCs/MPOs Policy Importance









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60.00%

40.00%

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Figure 17. Western PDCs/MPOs Policy Importance



For the eastern PDCs/MPOs, P.1 - Invest more in transportation and P.23 - Bicycle and

Pedestrian Facilities Feeder System appear to be important, being picked 100% and 80%

Feeder System and P.2 - Support Transit are the most important, with 100% and 80% use.









Figures 18 and 19 show the breakdown of relevant scenarios for the east and west region.









ts ts

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respectively. For the western PDCs/MPOs, P.23 - Bicycle and Pedestrian Facilities









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transit and strengthen planning and modeling is more important in the east.









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Figure 19. Western PDCs/MPOs Scenario Importance

Figure 18. Eastern PDCs/MPOs Scenario Importance

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For the eastern PDCs/MPOs the relevant scenarios are S.9 - Infrastructure investment

expands, S.8 - Energy cost rises, S.2 - Sprawl accelerates, S.5 - Transit oriented

development, and increased overall public transit. In the west, the scenarios of S.8 -

Energy cost rises, S.2 - Sprawl accelerates, and S.17 - Retirement are relevant to the

PDCs/MPOs. The scenario S.9 - Infrastructure investment expands is much more

important in the east than in the west (80% importance vs. 0% importance). The scenario

S.17 - Retirement appears to be more important in the west than the east (60% importance

vs. 0% importance).



We also recorded and analyzed the questions in the survey considering the effect of

scenarios and regional use of scenario-based planning. The results of the scenarios show

the regional differences in policy needs and future scenarios. Many regions are using

scenario-based planning in a variety of ways. Thus, it is crucial that there is coordination

among regions during policy prioritization and long term planning. Standardized

scenario-based planning will aid the region in planning coordination.

APPENDIX C: ECONOMIC IMPACT PORT STUDY



TO: Dr. Mary Lynn Tischer, Multimodal Office



FROM:



Megan Kersh

Asad Saqib

Matthew Schroeder

Ward Williams

Professor James Lambert



University of Virginia

Center for Risk Management of Engineering Systems



DATE: January 28, 2008



SUBJECT: The impacts of increasing output in transportation on final demand/GDP in

Virginia



Executive Summary



We analyzed the impacts of transportation investment in Virginia and to overall output

and final demand in sixty sectors of the economy.



For this study, we purchased data from the Bureau of Economic Analysis

(http://www.bea.gov/regional/rims/index.cfm). The data set was released in 2005 and is

the most recent data available.



Our observations from Bureau of Economic Analysis data are as follows:



 The seven transportation sectors are interconnected with the sixty sectors through

the expression x = Ax + c (expressed per year).

o x - total output per year (million dollars)

o A - input output matrix for output recycled to each sector [60 x 60]

o Ax – recycled output into other sectors per year (dollars)

o c - "final demand" output of the economy per year or GDP(dollars)

 GDP = consumption + investment + (government spending) +

(exports − imports)

 Output in Virginia is broken down into 60 sectors for this problem.

 Of the sixty sectors the total output is $226B

 Of the sixty sectors, the final demand is $128B

 The seven transportation sectors are

o Air transportation

o Rail transportation

o Water transportation

o Truck transportation

o Transit and ground passenger transportation

o Pipeline transportation

o Other transportation and support activities

 Output for the seven transportation sectors is $7.2B

 The seven transportation sectors constitute 2.5% of total output

 Final demand for the seven transportation sectors is $3.2B

 The seven transportation sectors constitute 3.2% of the final demand

 This database does not distinguish between public and private investment or

between services and construction.



We found the following in complementary analysis:



 Stimulating total output: A 1% increase to transportation output, x, results in a

$37M increase to final demand, c, across all sectors

o The 1% increase in transportation output also resulted in over a 1%

increase in final demand for all transportation sectors

 Stimulating final demand: (say something about graph results)

o Mention difference between stimulating demand and increasing output

Results of Increasing Transportation Output



We analyzed the results of increasing transportation output by raising transportation

output in all the transportation sectors by 1%. Table 4 provides the sectors and increased

output in millions of dollars.



Table 4 - Transportation sector increase in output

Increase in

Sector ouput sector output

Sector ($ millions) ($ millions)

Air transportation 1801.7 18.0

Rail transportation 699.3 7.0

Water transportation 292.0 2.9

Truck transportation 2538.1 25.4

Transit and ground passenger

transportation* 344.1 3.4

Pipeline transportation 80.0 0.8

Other transportation and support

activities* 1443.3 14.4



Using the formula x= Ax + c, new c values (output or final demand) values were

calculated. Figure 32 displays the increased output for the respective transportations

sectors.



30

25

20

millions 15



10

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Figure 32 – Increase in output for transportation sectors given 1% increase in output



The total output increase for all transportation sectors is 64 millions dollars. The total

output increase for all sectors in Virginia is 37 million dollars. The difference between

the transportation sector gains and overall gains is due to increased transportation output

absorbing output from other sectors. It is important to note that there is still a strong

overall increase in output overall when increasing output for transportation by 1%.

Results from Stimulating Final Demand



We use the formula x = Ax + c to exchange the desired unknown c value with x. After

manipulating the formula we obtain c(I-A)-1 = x.



When stimulating demand, we found that output for all sectors increases, in contrast to

the first approach, which was increasing output for specific sectors. Figure 33 shows the

ten sectors with greatest percentage increase in output based on a 1% increase in final

demand in the transportation sectors.







3.50%

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Figure 33 – Percent increase in output per 1% increase in final demand for transportation sectors







These following issues should be considered when deciding whether to increase output or

attempt to stimulate demand:

 Ease of stimulating demand in a sector compared to ability to increase output for a

sector

o Stimulating final demand for transportation sectors by 1% results in a 3%

increase in petroleum and coal manufacturing output, however, it must be

considered if this output is feasible

 Need to increase output for many sectors

o Stimulating demand has a greater overall positive effect in increasing

output over a variety of sectors

 Specific sectors that currently may be in higher demand or have a higher ability

for production/output

o For example, rail as a form of public transportation has become more

popular in past years, thus making it easier to stimulate demand for the

sector





(Appendice within appendice)

Results from increasing output across all manufacturing sectors



For comparison, we increased all manufacturing sector output values by 1% as described

in Table 5.



Table 5 – Manufacturing sector increase in output

Sector ouput Increase in sector

Sector ($ millions) output ($ millions)

Wood product manufacturing 1805.2 18.1

Nonmetallic mineral product manufacturing 910.5 9.1

Primary metal manufacturing 753.3 7.5

Fabricated metal product manufacturing 1642.4 16.4

Machinery manufacturing 1774.7 17.7

Computer and electronic product manufacturing 2500.6 25.0

Electrical equipment and appliance

manufacturing 749.1 7.5

Motor vehicle, body, trailer, and parts

manufacturing 1562.2 15.6

Other transportation equipment manufacturing 2916.9 29.2

Furniture and related product manufacturing 1424.0 14.2

Miscellaneous manufacturing 674.6 6.7

Food, beverage, and tobacco product

manufacturing 5960.6 59.6

Textile and textile product mills 1585.6 15.9

Apparel, leather, and allied product

manufacturing 378.4 3.8

Paper manufacturing 2006.4 20.1

Printing and related support activities 1482.3 14.8

Petroleum and coal products manufacturing 127.7 1.3

Chemical manufacturing 2238.5 22.4

Plastics and rubber products manufacturing 2083.7 20.8





Table 6 provides output increases for the manufacturing sector compared to the

transportation output increases.



Table 6 - Comparison of transportation and manufacturing increased output results

Change in final demand for Change in final demand

transportation sectors per for all sectors per one

Agglomerated Sector one unit change in output unit change in output

Transportation 0.89 0.52

Manufacturing 0.66 0.37



The first column represents the increased final demand for the respective agglomerated

sector per one unit change in output for the agglomerated sector. Another interpretation

for the first column is an increase in final demand per $1 increased output in the

agglomerated sector. The second column represents the sum of increased final demand

for all sixty sectors per one unit output increase for the agglomerated sector. We found

that the transportation sector produces more final demand per increased output than

manufacturing, or in other words, requires less output increase to produce a comparable

level of final demand.



To justify the one percent increase in output, we calculated the resulting change in output.

The output change is displayed in Table 7.



Table 7 - Percent Increase of Output for Transportation Sectors

Percent

Sector change

Air transportation 1.6%

Rail transportation 1.7%

Water transportation 1.2%

Truck transportation 2.2%

Transit and ground passenger transportation* 1.5%

Pipeline transportation 1.1%

Other transportation and support activities* 3.1%



Every percent increase is above 1%, the amount of increase in output. In the

manufacturing sector, five industries had less than 1% return.



Based on the data analysis above, it is predicted that increasing output in the

transportation sector will result in a beneficial output. Further analysis may be done to

focus on which transportation sectors provide the best output per increased output and

how other sector‟s increased outputs compare to transportation.

Figure 34 – Input/Output sector output (A matrix)









Table 8 - Sector Output (x)

Sector Codes Sector Description Sector ouput

($ millions)

CROP Crop and animal production 920

FRST Forestry, fishing, and related activities 581

OILG Oil and gas extraction 492

MING Mining, except oil and gas 811

MINS Support activities for mining 82

UTIL Utilities* 1,907

CNST Construction 19,147

WOOD Wood product manufacturing 1,805

NMET Nonmetallic mineral product manufacturing 910

PMET Primary metal manufacturing 753

FMET Fabricated metal product manufacturing 1,642

MACH Machinery manufacturing 1,775

COMP Computer and electronic product manufacturing 2,501

ELEC Electrical equipment and appliance manufacturing 749

MOTR Motor vehicle, body, trailer, and parts manufacturing 1,562

TREQ Other transportation equipment manufacturing 2,917

FURN Furniture and related product manufacturing 1,424

MFGM Miscellaneous manufacturing 675

FOOD Food, beverage, and tobacco product manufacturing 5,961

TEXT Textile and textile product mills 1,586

APPR Apparel, leather, and allied product manufacturing 378

PAPR Paper manufacturing 2,006

PRNT Printing and related support activities 1,482

PETR Petroleum and coal products manufacturing 128

CHEM Chemical manufacturing 2,239

PLAS Plastics and rubber products manufacturing 2,084

WTRD Wholesale trade 9,557

RTRD Retail trade 16,126

AIRT Air transportation 1,802

RAIL Rail transportation 699

WATR Water transportation 292

TRCK Truck transportation 2,538

GRND Transit and ground passenger transportation* 344

PIPE Pipeline transportation 80

TRNM Other transportation and support activities* 1,443

WRHS Warehousing and storage 754

PUBL Publishing including software 3,557

MPIC Motion picture and sound recording industries 250

BRDC Broadcasting and telecommunications 7,846

INFO Information and data processing services 4,382

BANK Federal Reserve banks, credit intermediation and related services 6,102

SECU Securities, commodity contracts, investments 1,947

INSR Insurance carriers and related activities 4,350

FUND Funds, trusts, and other financial vehicles 873

REAL Real estate 5,566

RENT Rental and leasing services and lessors of intangible assets 1,792

PROF Professional, scientific, and technical services 39,096

MNGT Management of companies and enterprises 8,697

ADMI Administrative and support services 8,481

WSTE Waste management and remediation services 492

EDUC Educational services 3,080

HLTH Ambulatory health care services 9,515

HOSP Hospitals and nursing and residential care facilities 8,373

SOCL Social assistance 1,747

PERF Performing arts, museums, and related activities 852

AMST Amusements, gambling, and recreation 958

ACCO Accommodation 1,541

FSRV Food services and drinking places 6,372

OTHR Other services* 9,611

60 Households

APPENDIX D: DRAFT OF POTENTIAL MPO SURVEY



We also created a draft of a survey that transportation planners can fill out to help

identify scenario-based planning in the MPO‟s. The preliminary survey is shown below.



Survey



Survey Tool Draft:

Survey Tool – Scenarios - Example



Given the following criteria –



C.1 Safety and Security

C.2 Preservation and Management

C.3 Efficient Movement of People and Goods

C.4 Economic Vitality

C.5 Quality of Life

C.6 Program Delivery



What kind of impact would these scenarios on your area? (please highlight your choice)



S.2 – Sprawl Accelerates



C.1 Safety and Security

(Significant Impact) (Moderate Impact) (None or Unknown Impact)



C.2 Preservation and Management

(Significant Impact) (Moderate Impact) (None or Unknown Impact)



C.3 Efficient Movement of People and Goods

(Significant Impact) (Moderate Impact) (None or Unknown Impact)



C.4 Economic Vitality

(Significant Impact) (Moderate Impact) (None or Unknown Impact)



C.5 Quality of Life

(Significant Impact) (Moderate Impact) (None or Unknown Impact)



C.6 Program Delivery

(Significant Impact) (Moderate Impact) (None or Unknown Impact)



S.17 – Retirement



C.1 Safety and Security

(Significant Impact) (Moderate Impact) (None or Unknown Impact)

C.2 Preservation and Management

(Significant Impact) (Moderate Impact) (None or Unknown Impact)



C.3 Efficient Movement of People and Goods

(Significant Impact) (Moderate Impact) (None or Unknown Impact)



C.4 Economic Vitality

(Significant Impact) (Moderate Impact) (None or Unknown Impact)



C.5 Quality of Life

(Significant Impact) (Moderate Impact) (None or Unknown Impact)



C.6 Program Delivery

(Significant Impact) (Moderate Impact) (None or Unknown Impact)



S.18 – Natural Disaster



C.1 Safety and Security

(Significant Impact) (Moderate Impact) (None or Unknown Impact)



C.2 Preservation and Management

(Significant Impact) (Moderate Impact) (None or Unknown Impact)



C.3 Efficient Movement of People and Goods

(Significant Impact) (Moderate Impact) (None or Unknown Impact)



C.4 Economic Vitality

(Significant Impact) (Moderate Impact) (None or Unknown Impact)



C.5 Quality of Life

(Significant Impact) (Moderate Impact) (None or Unknown Impact)



C.6 Program Delivery

(Significant Impact) (Moderate Impact) (None or Unknown Impact)





S.3 – IT Amenities Grow



C.1 Safety and Security

(Significant Impact) (Moderate Impact) (None or Unknown Impact)



C.2 Preservation and Management

(Significant Impact) (Moderate Impact) (None or Unknown Impact)



C.3 Efficient Movement of People and Goods

(Significant Impact) (Moderate Impact) (None or Unknown Impact)

C.4 Economic Vitality

(Significant Impact) (Moderate Impact) (None or Unknown Impact)



C.5 Quality of Life

(Significant Impact) (Moderate Impact) (None or Unknown Impact)



C.6 Program Delivery

(Significant Impact) (Moderate Impact) (None or Unknown Impact)



S.19 – Decrease in Air Quality



C.1 Safety and Security

(Significant Impact) (Moderate Impact) (None or Unknown Impact)



C.2 Preservation and Management

(Significant Impact) (Moderate Impact) (None or Unknown Impact)



C.3 Efficient Movement of People and Goods

(Significant Impact) (Moderate Impact) (None or Unknown Impact)



C.4 Economic Vitality

(Significant Impact) (Moderate Impact) (None or Unknown Impact)



C.5 Quality of Life

(Significant Impact) (Moderate Impact) (None or Unknown Impact)



C.6 Program Delivery

(Significant Impact) (Moderate Impact) (None or Unknown Impact)

APPENDIX E: PRELIMINARY MPO SURVEY





We surveyed the regional MPO‟s to analyze how they use scenario based planning in

their transportation planning. Some MPO‟s used scenarios directly, and others used

scenario-based planning indirectly. Table 9 below shows the result of the MPO survey.



Table 9. Results of user MPO survey

MPO Use of Scenarios in

Planning

1. Blacksburg-Christiansburg- Some

Montgomery Area (BCM)

2. Central Virginia Some

3. Danville Little

4 Charlottesville-Albemarle Complete-direct

5. Richmond Area MPO Some

6. Roanoke Valley Area Complete-direct

MPO*

7. Tri-Cities Area MPO Some

8. Fredericksburg Area Some

MPO

9. Hampton Roads PDC Little

10. Harrisonburg-Rockingham Little

MPO

11. West Piedmont PDC Little

(Danville MPO)

12. Winchester-Frederick Little

MPO





We observed that smaller MPOs have less evidence of use of scenario-based planning,

whereas larger MPO‟s tend to use scenarios either directly or indirectly in planning.

Figure 34 displays an excerpt of a workbook that keeps track of the types of scenarios for

MPO‟s.









Figure 34. Excerpt from spreadsheet of MPO scenario usage