GUIDE TO
SUSTAIN
TRANSPORTATION
PERFORMANCE
MEASURES
oEFA
United States
Environmental Protection
Agency
EPA 231-K-10-004
August 2011
www.epa.gov/smartgrowth
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Acknowledgements
This document was prepared for the U.S. Environmental Protection Agency by ICF International. As
part of the development of this document, one-day workshops were conducted at the
Southwestern Pennsylvania Commission (in Pittsburgh, Pennsylvania) and the Mid-America
Regional Council (in Kansas City, Missouri). The assistance from these agencies in organizing the
workshops and providing comments on the draft guidebook is appreciated.
Development of this guidebook also benefited from interviews and other information exchange
with staff at the following agencies: Puget Sound Regional Council, Metropolitan Transportation
Commission (which covers California's San Francisco Bay Area), Southern California Association of
Governments, Denver Regional Council of Governments, Chicago Metropolitan Agency for
Planning, San Diego Association of Governments, and the City of Portland, Oregon. Comments on
the draft guidebook were also provided by the Federal Highway Administration and the Federal
Transit Administration.
All graphics in the report are courtesy of the agency mentioned in the figure title unless otherwise
noted.
All cover photos are courtesy of EPA. From top: Salt Lake City, Utah; Starkville, Mississippi; Boise,
Idaho.
ACKNOWLEDGEMENTS
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Table of Contents
Executive Summary
1. Sustainability in Transportation Decision Making
2. Performance Measurement in Transportation Decision Making
Measure: Transit Accessibility 10
Measure: Bicycle and Pedestrian Mode Share 13
Measure: VMT per Capita 15
Measure: Carbon Intensity 17
Measure: Mixed Land Uses 19
Measure: Transportation Affordability 21
Measure: Benefits by Income Group 23
Measure: Land Consumption 26
Measure: Bicycle and Pedestrian Activity and Safety 29
Measure: Bicycle and Pedestrian Level of Service 32
Measure: Average Vehicle Occupancy 35
Measure: Transit Productivity 37
4. Applications of Sustainable Transportation Performance Measures 40
Long Range Plan Vision, Goals, and Targets 40
Long Range Plan Project Performance Assessment 42
Long Range Plan Evaluation 44
Corridor Level Evaluation 45
Programming 46
Performance Monitoring 50
Endnotes 52
TABLE OF CONTENTS
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GUIDE TO SUSTAINABLE TRANSPORTATION PERFORMANCE MEASURES
Executive Summary
This document describes opportunities to incorporate environmental, economic, and social
sustainability into transportation decision-making through the use of performance measures.
Performance measures allow decision-makers to quickly observe the effects of a proposed
transportation plan or project or to monitor trends in transportation system performance over
time.
While many transportation agencies use performance measures as part of planning and project
development, their use to promote sustainability has historically been limited. However, more and
more agencies have begun to measure the ability of their systems to help protect natural
resources, improve public health, strengthen energy security, expand the economy, and provide
mobility to disadvantaged people. This document provides examples of best practices in
sustainable transportation performance measurement that are being applied across the country.
The measurement of environmental, economic, and social outcomes is already yielding positive
results. Many agencies have found that, once they begin to report sustainable transportation
performance measures, stakeholders quickly see their value and come to expect regular reporting
of measures and more explicit linkages between the measures and public agency decisions. Agency
staff and stakeholders are then able to engage in a much richer conversation about the trade-offs
among policy and investment decisions and the best opportunities for their region or state to reach
its sustainability goals.
Sustainable performance measures can be applied in one or more of these major decision-making
phases:
Land use visioning.
Long-range transportation plans.
Corridor studies.
Programming.
Environmental review.
Performance monitoring.
This guidebook describes 12 performance measures that can readily be applied in transportation
decision-making. The document focuses on transportation decision-making at the regional or
metropolitan level, although many of the performance measures described could be used at the
state or local level. For each measure, the guidebook presents possible metrics, summarizes the
relevant analytical methods and data sources, and illustrates the use of each measure by one or
more transportation agencies. The 12 profiled measures are:
Transit accessibility.
Bicycle and pedestrian mode share.
Vehicle miles traveled per capita.
Carbon intensity.
> Mixed land uses.
EXECUTIVE SUMMARY
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GUIDE TO SUSTAINABLE TRANSPORTATION PERFORMANCE MEASURES
Transportation affordability.
Distribution of benefits by income group.
Land consumption.
Bicycle and pedestrian activity and safety.
Bicycle and pedestrian level of service.
Average vehicle occupancy.
Transit productivity.
The guidebook then describes opportunities to apply sustainable performance measures in the
transportation decision-making process. It provides examples of how metropolitan planning
organizations have used sustainable performance measures as part of the following activities:
Long-range plan: identifying vision, goals, and targets.
Long-range plan: project performance assessment.
Long-range plan evaluation.
Corridor level evaluation.
Programming.
Performance monitoring.
The examples described are indicative of the growing interest in performance-based planning and
in making transportation environmentally and economically sustainable over the long term.
Drawing on the transportation agency experiences described here, this guidebook can spur further
interest and innovation in these fields.
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GUIDE TO SUSTAINABLE TRANSPORTATION PERFORMANCE MEASURES
l.Sustainability in Transportation Decision-Making
Many transportation agencies are now being called upon by their stakeholders to plan, build, and
operate transportation systems that - in addition to achieving the important goals of mobility and
safety - support a variety of environmental, economic, and social objectives. These include
protecting natural resources, improving public health, strengthening energy security, expanding
the economy, and providing mobility to disadvantaged people.
This shift has been decades in the making and is driven by a variety of factors. One factor is the
desire for a more integrated and holistic approach to transportation decision-making. Researchers
have been shedding light on the complex interrelationships between our built and natural
environments and drawing attention to the need to better consider the multifaceted implications
of transportation system changes. At the same time, advanced computer tools are making it easier
to quantify and visualize these relationships.
Other important societal priorities are also driving the need to consider these goals in
transportation decisions:
Environmental Quality. While pollutant emissions from motor vehicles have dropped
dramatically over the last three decades, air quality problems persist in many metropolitan
areas, driven in part by growth in vehicle miles traveled (VMT). Recent scientific research has
more clearly linked air pollution with public health problems and led the U.S. Environmental
Protection Agency (EPA) to establish lower thresholds for acceptable levels of air pollution.
On a global scale, the looming threat of climate change has focused attention on the
environmental impacts of the transportation sector, which contributes more than 25 percent
of our nation's greenhouse gas (GHG) emissions.
Economic Development. Transportation has long been recognized as essential to economic
development. Efficient and reliable movement of people and goods improves productivity
and can spur economic growth. Moreover, with rising regional competition, quality of life has
become increasingly important for drawing and retaining a talented and productive
workforce. Transportation investments are key to boosting a region's attractiveness to
businesses and residents.
> Social Equity People who are economically, socially, or physically disadvantaged need
transportation options to give them opportunities to work, learn, and participate in society.
Transportation is a large and growing expense for many families. Households in locations with
poor accessibility to employment opportunities and other destinations and no alternatives to
driving tend to spend more on transportation. Investments that improve accessibility and
provide more transportation choices allow households to save money.
There no single definition of what constitutes a "sustainable" transportation system. According to
the definition endorsed by the Transportation Research Board Sustainable Transportation
Indicators Subcommittee, a sustainable transport system:1
"Allows the basic access and development needs of individuals, companies, and society to be
met safely and in a manner consistent with human and ecosystem health, and promotes
equity within and between successive generations.
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GUIDE TO SUSTAINABLE TRANSPORTATION PERFORMANCE MEASURES
Is affordable, operates fairly and efficiently, offers a choice of transport mode, and supports a
competitive economy, as well as balanced regional development.
Limits air, water, and noise emissions, waste, and resource use. Limits emissions and waste
within the planet's ability to absorb them, uses renewable resources at or below their rates
of generation, and uses non-renewable resources at or below the rates of development of
renewable substitutes, while minimizing the impact on the use of land and the generation
of noise."
The interagency Partnership for Sustainable Communities reinforces the importance of
environmental, economic, and social sustainability. On June 16, 2009, the U.S. Department of
Housing and Urban Development (HUD), the U.S. Department of Transportation (DOT), and EPA
agreed to coordinate housing, transportation, and environmental policies and investments. The
Partnership breaks down long-standing silos to increase transportation options, improve
accessibility to jobs and other destinations, and lower the combined cost of housing and
transportation while protecting the environment in communities nationwide. The Partnership is
guided by six livability principles:2
Provide more transportation choices. Develop safe, reliable, and economical transportation
choices to decrease household transportation costs, reduce our nation's dependence on
foreign oil, improve air quality, reduce greenhouse gas emissions, and promote public health.
Promote equitable, affordable housing. Expand location- and energy-efficient housing choices
for people of all ages, incomes, races, and ethnicities to increase mobility and lower the
combined cost of housing and transportation.
Enhance economic competitiveness. Improve economic competitiveness through reliable and
timely access to employment centers, educational opportunities, services and other basic
needs by workers, as well as expanded business access to markets.
> Support existing communities. Target federal funding toward existing communities—through
strategies like transit oriented, mixed-use development, and land recycling—to increase
community revitalization and the efficiency of public works investments and safeguard rural
landscapes.
Coordinate and leverage federal policies and investment. Align federal policies and funding to
remove barriers to collaboration, leverage funding, and increase the accountability and
effectiveness of all levels of government to plan for future growth, including making smart
energy choices such as locally generated renewable energy.
Value communities and neighborhoods. Enhance the unique characteristics of all communities
by investing in healthy, safe, and walkable neighborhoods—rural, urban, or suburban.
HUD, DOT, and EPA will use performance measures to target their resources towards planning and
capital programs that support the livability principles, to create baselines for measuring progress
toward sustainable communities objectives, and to evaluate federal initiatives. These livability-
focused performance measures will complement traditional transportation metrics and will have
varied applications for rural and metropolitan regions. The measures described in this document
can help transportation agencies work toward the livability goals of their regions.
SUSTAINABILITY IN TRANSPORTATION DECISION MAKING
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2. Performance Measurement in Transportation Decision-Making
Transportation agencies can better integrate the concepts of sustainability into their planning,
programming, and project development activities through performance measures. Performance
measures provide quantified evidence of the consequences of a decision or action. By translating
data and statistics into a succinct and consistent format, performance measures offer an efficient
way to provide information to decision-makers.
Transportation performance measures predict, evaluate, and monitor the degree to which the
transportation system accomplishes adopted public objectives. They can be applied at all stages of
transportation decision-making, as illustrated in Figure 1.
Figure 1: Opportunities to Use Performance Measures to Improve Transportation Sustainability
Image source: ICF International
Decision Making Steps
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Land Use Visioning
Some metropolitan areas have conducted land use visioning exercises, sometimes called scenario
planning, in an effort to reach consensus on a desired regional growth pattern. In these exercises,
regional stakeholders work to develop a shared vision for the future by analyzing various forces
(e.g., health, transportation, economic, environmental, land use) that affect growth. A land use
visioning process usually includes hands-on stakeholder involvement in developing and selecting a
range of options for future growth.
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While not directly part of the long-range transportation planning process, land use visioning can
result in an adopted growth forecast that informs subsequent transportation investment decisions.
It can also produce preliminary guidance on transportation improvement programs. Performance
measures are frequently used to evaluate and compare alternative land use scenarios and then to
communicate to the public the benefits of an adopted growth vision.
Long-Range Transportation Planning
Long-range transportation planning provides the foundation for all other aspects of transportation
decision-making by establishing the vision and goals for transportation and identifying strategies
and project concepts for implementation. The outcome of long-range transportation planning
should be broad-based consensus and support for the transportation strategies and project
concepts that are recommended. Collaboration with partners and stakeholders is essential if these
decisions are to be recognized and built upon during subsequent corridor planning and project
development.
Performance measures can be used in several ways during transportation planning. Once a
community has established goals and objectives for the transportation system, performance
measures can be used to explore how different policy and investment packages can help achieve
the objectives. At this visioning stage of the long-range transportation planning process, individual
projects are not well defined, and planners create deliberately distinct policy and investment
packages to illustrate the effects of various bundles of policies. Figure 2 illustrates five alternatives
considered in the development of the Puget
Sound Regional Council's (PSRC's)
Transportation 2040 Plan.3
Performance measures can also be used to
evaluate individual projects and programs
being considered for inclusion in the plan.
Project-level assessment is time consuming,
and rarely are agencies able to quantitatively
evaluate all projects submitted for
consideration individually. As a result, it is
most important to apply performance
measurement to the most expensive
projects.
Once a region has reached consensus on
project priorities and adopted a long-range
plan, performance measures can be used to
compare the plan against current conditions
or a future business-as-usual scenario. The
results can help communicate the benefits of the plan to the public.
Figure 2: Puget Sound Regional Council -
Alternatives Considered in Development of
Transportation 2040 Plan
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Corridor Studies
Corridor planning builds on the foundation of long-range planning by studying concepts and
solutions for individual corridors or small areas within a region, leading to the selection of a
preferred concept. Corridor planning is not a legally required process, so the purpose and process
of corridor planning efforts can vary considerably. In some metropolitan areas, corridor plans are
done concurrently with the development of the long-range plan. In rural areas, corridor plans are
sometimes used as a substitute for long-range plans.
Performance measures can help transportation agencies identify alternatives to be considered
during corridor planning and facilitate comparison across alternatives and selection of a
preferred option. The performance measures used in corridor studies have traditionally focused
on congestion reduction and vehicle mobility. But planners are finding that use of measures to
evaluate environmental, economic, and social equity outcomes can help identify a more widely
accepted alternative and avoid unnecessary delay during the subsequent environmental review
process.
Programming
Programming is the process by which agencies select and invest limited transportation funds in a
list of projects that will be built within a set time frame, usually three to five years. The
transportation improvement program (TIP) is a list of prioritized projects, drawn from the long-
range transportation plan, that are approved for funding. The use of performance measures at this
stage often involves a benefit-cost metric that encompasses multiple categories of benefits.
In addition to the formal TIP process, performance measures are ideal for selecting among smaller
transportation projects to receive state or regional grant support. For example, several
metropolitan planning organizations (MPOs) have established programs to fund local government
bicycle and pedestrian improvements and other transportation investments that support compact
and transit-oriented development. Requests for funding from these programs often exceed total
available funds. Performance measures can be used to screen grant applications and select
projects for funding that are most supportive of regional sustainability objectives.
Environmental Review
Environmental review is a regulatory process that encompasses the actions required under the
National Environmental Policy Act, the Clean Water Act, the Endangered Species Act, and various
other state and federal regulations. Environmental review is generally the last step in the planning
process for a transportation improvement and is followed by final design and construction. By the
time of environmental review, the location and general parameters of a project have been
decided. Performance measures can be instrumental in selecting a project alternative and
associated mitigation measures that minimize adverse impacts.
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Performance Monitoring
Many metropolitan areas create annual "state of the region" reports that track progress using a set
of key performance measures. Performance monitoring allows a region to view trends in a variety
of quality of life indicators in areas such as employment, poverty, housing, congestion, air quality,
energy, waste, education, and public safety. Performance reports can also allow a region to
compare itself against peer regions.
MPOs often report indicators that relate to regional planning goals. The Delaware Valley Regional
Planning Commission, for example, reports 27 indicators organized under five categories:
Growth management.
Urban revitalization.
The environment.
Economic development.
Transportation.
Figure 3 shows an example of how the Delaware Valley Regional Planning Commission has
presented results of its performance monitoring program.4
Typically, regional performance monitoring involves reporting indicators that are already compiled
and analyzed for other purposes. In some cases, MPOs have launched new initiatives to develop a
much larger set of performance measures. The Chicago Metropolitan Agency for Planning, for
example, has a Regional Indicators project that involves creating more than 500 tables to measure
more than 200 indicators across different times and regional geographies.
Performance monitoring can inform transportation investment decisions by highlighting trends
that may be inconsistent with regional objectives. The use of performance measures for
monitoring can also help to illustrate the impacts of specific transportation investments and
programs.
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Figure 3: Delaware Valley Regional Planning Commission - Performance Monitoring Results
What We Tra
TR 1: Have vehicle crashes an
lilies declined'
TR 2: Is congestion getting
worse?
IK transit ride
creasing?
s the number of
•ieed
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re roads better
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TR 6: Are fewer people driving
3 work alone?
j-e people driving less1?
re DVRPCs TIP
vestments in keeping
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How is the D'
Between 2001 and 2005. the DVRPC region experienced
an 18% decrease in fatalities per million VMT and less
than 1% decrease in all crashes per million VMT.
However, the overall number of crashes rose by 4,6%
during this same time period
Congestion appears to be stable - neither improving nor
worsening, though VMT has increased.
While transit ridership has experienced some fluctuation,
it has increased in the last 5 years.
The number of bridges identified as structurally deficient
in the DVRPC region has remained steady, but remains
twice as high as the acceptable level set by FHWA in its
current strategic plan
The region saw a slight increase in road miles
considered to be deficient, mostly due to NJDOT's
stricter standards
The number of people driving to work by themselves
continues to increase and is now 73% of all commuters
There are more cars and more drivers driving more miles
every year in the region. The region appears to be more
auto-dependent.
Trend
Approximately 97% of the mapped 2007-2010 TIP
project funding supports the Long Range Plan and its
stated goals.
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3. Performance Measure Examples
This section describes 12 performance measures that can help to incorporate sustainable
communities objectives into transportation decision-making. These examples are not intended to
be a comprehensive set of measures, nor are they necessarily the 12 most appropriate measures
for a given community. They were selected as representative examples that span the various
phases of transportation decision-making and the different elements of sustainability. All the
measures profiled have been used by one or more transportation agencies. The performance
measures are:
Transit Accessibility.
Bicycle and Pedestrian Mode Share.
VMT per Capita.
Carbon Intensity.
Mixed Land Uses.
Transportation Affordability.
Benefits by Income Group.
Land Consumption.
Bicycle and Pedestrian Activity and Safety.
Bicycle and Pedestrian Level of Service.
Average Vehicle Occupancy.
Transit Productivity.
For each measure, this section includes a description, a list of the decision-making phases in which
it can be applied, a list of possible metrics, a brief discussion of analytical methods and data
sources, and one or more examples of the measure in use.
Measure: Transit Accessibility
Measures the ability of people to reach destinations using public transportation
Description
Transit accessibility reflects the relative convenience of transit as a mode choice. It can be
measured in terms of distance to transit stops or travel time on transit. Metrics typically
emphasize the availability of transit where people live, where people work, and on routes that
connect the two.
Both capital investments in transit and enhancements to transit operations can improve transit
accessibility. The location of jobs and housing relative to transit services also has a major impact on
transit accessibility. Higher transit accessibility can use energy more efficiently, reduce GHG
emissions, improve air quality, and make transportation more affordable.
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A transit accessibility measure can be easily adapted to account for social equity considerations.
Transit tends to be an important mode of transportation for low-income populations, who are less
likely to have access to a car. Transit accessibility metrics can be calculated specifically for low-
income populations, as compared to the total population.
Application
Land use visioning.
Long-range transportation planning.
Corridor studies.
Programming.
Metrics
Individual metrics measure the share of jobs or population that fall within a given threshold of
accessibility. Most accessibility metrics fall into one of the following two groups:
Distance to transit stops. These metrics capture the amount of jobs, population, trip origins, or trip
destinations within a certain radius of a transit stop. The radius often represents a reasonable
distance that people are willing to walk to and from transit stops, typically between % mile and VT.
mile. Examples include:
Percent of daily/peak period trips (origins and destinations) starting or ending within % mile of
a transit stop.
Percent of population and employment within 0.4 miles of transit.
Households within five miles of park-and-ride lots or major transit centers.
Destinations accessible by transit. These metrics capture not just the accessibility of transit stops,
but the connection that transit provides to various destinations. For example, a metric could
capture the number of jobs accessible within a certain travel time. This type of metric incorporates
the relationships of various land uses and the performance of the transit system. For example, a
suburban housing development served by a bus route could largely fall into a threshold defined by
distance to transit stops, but may not meet a threshold for destinations accessible by transit if it is
located far from job centers. Examples include:
Share of population with good transit-job accessibility (100,000+jobs within 45 minutes).
Number of households within a 30-minute transit ride of major employment centers.
Percentage of work and education trips accessible in less than 30 minutes transit travel time.
Percentage of workforce that can reach their workplace by transit within one hour with no
more than one transfer.
Analytical Methods and Data Sources
To calculate transit accessibility metrics based on distance to transit stops, the following
information is required:
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Data on regional trip origins and destinations (locations of population and employment).
Data on the locations of transit stops.
Defining a transit stop requires establishing a threshold for service frequency (e.g., 15-minute
headways during peak periods). Thus, an agency needs information on transit service frequency in
addition to stop locations. Identifying transit stops can be challenging when forecasting new bus
service in areas of growth. Metrics based on distance to transit stops can be calculated through a
spatial analysis of the above two data points, supported by Geographic Information Systems (CIS)
software.
Calculating metrics based on destinations accessible by transit requires additional steps. A travel
demand model incorporating a robust transit network must be used to estimate the travel time or
distance between origins and destinations on the transit network.
Example
In its 2030 Regional Transportation Plan, the Atlanta Regional Council evaluated the share of
population and employment within walking distance (0.4 miles) of a transit stop. Figure 4 provides
the results of the analysis for the current year, which was 2005; 2030 without the strategies
suggested by the plan; and 2030 with the implementation of the plan.5 Because most growth is
occurring on the periphery of the region, transit accessibility is projected to decline in the future
under both alternatives. However, this decrease in transit access is smaller under the plan scenario
(EnvisionG) than it is under the no-plan scenario.
Figure 4: Atlanta Regional Council - Share of Population and Employment
within Walking Distance of Transit
40.0V;
2030 without Envisions 2030 with Envisions
| | Households within .4mile
(Employment within .4mile
The San Diego Association of Governments evaluated accessibility of work, college, and non-work
destinations by mode in its most recent long-range transportation plan. Accessible work and
college destinations were defined as those within 30 minutes of travel from home. Accessible non-
work destinations were defined as those within 15 minutes of travel from home. Figure 5 shows
the results of the analysis for the current year, which was 2006, and four future-year scenarios.6
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The various "build" alternatives all improve future accessibility as compared to the business-as-
usual, or "no build," scenario.
Figure 5: San Diego Association of Governments - Accessibility Measures
Goals and Performance
Measures
Percent of work and higher
education trips accessible in
30 minutes in peak periods
Long Range Transportation Plan Scenarios
Current
(2006)
61%
Revenue
Constrained
(2030)
54%
Reasonably
Expected
(2030)
56%
Smart
Growth
RE
(2030)
57%
No
Build
(2030)
53%
Percent of work and higher education trips accessible in 30 minutes in peak periods by mode
Auto
Transit
Carpool
Percent of non-work-related
trips accessible in 15 minutes
65%
10%
67%
66%
57%
13%
64%
63%
58%
15%
68%
63%
60%
16%
70%
64%
55%
10%
59%
62%
Percent of non-work-related trips accessible in 15 minutes by mode
Auto
Transit
Carpool
67%
4%
68%
63%
6%
66%
63%
7%
66%
64%
7%
67%
63%
4%
64%
Measure: Bicycle and Pedestrian Mode Share
Measures the proportion of trips taken by bicycle and walking mode
Description
Bicycling and walking are core elements of a sustainable transportation system. Trips by bicycling
and walking produce no emissions and let people work physical activity into their daily routines to
improve their health and save money. Drivers who switch to walking and bicycling can reduce their
expenditures on fuel and vehicle maintenance while helping to reduce traffic congestion. A safe
and attractive environment for pedestrians can also help promote economic development by
increasing foot traffic near local businesses and attracting tourists and other consumers.
Bicycle and pedestrian travel can be encouraged through investments in infrastructure (i.e., bicycle
paths and lanes, sidewalks, crosswalks), supporting amenities (i.e., bicycle parking, benches), and
educational and promotional programs. Opportunities for travelers to choose walking and biking
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increase when growth patterns provide more housing in close proximity to jobs, stores, schools,
and recreational destinations.
Most pedestrian and bicycle trips are short—typically no more than two miles for walking trips and
five miles for bicycling trips. As a result, improvements to bicycling and walking facilities can have a
large impact on non-work trips (e.g., shopping, school, and recreational trips), which tend to be
short. In addition, improved pedestrian connections to transit systems have the potential to divert
long automobile trips to walking-plus-transit trips.
Application
Land use visioning.
Long-range transportation planning.
Corridor studies.
Programming.
Performance monitoring.
Metrics
Bicycle and pedestrian mode share represents bicycle and pedestrian trips as a percent of trips by
all travel modes. Typical metrics include:
Bicycle mode share (bicycle trips divided by total trips).
Pedestrian mode share (pedestrian trips divided by total trips).
Bicycle and pedestrian mode share can be calculated for all trip purposes, for work trips only, or for
other trip purposes. It can cover peak-period travel or average daily travel.
Because bicycle and pedestrian mode shares are typically small, differences across plan or project
alternatives may not be apparent. Rather than reporting mode share by alternative, it may be
more illustrative to report the percentage change in non-motorized trips by plan alternative, as
compared to a plan baseline.
Analytical Methods and Data Source
Reliable data on biking and walking trips are often difficult to obtain. For many transportation
agencies, the only consistent data source is Census data, which reports only work trips and is likely
to undercount non-motorized activity. Household travel surveys provide the most accurate
measure of non-motorized travel, but they are typically expensive and conducted infrequently. In
some regions (e.g., Portland, Oregon), an annual survey collects information about travel mode.
Some sophisticated regional travel demand models can produce relatively accurate forecasts of
bicycle and pedestrian travel. However, most conventional travel models have only limited
capabilities to forecast non-motorized mode shares. Activity-based travel models, which derive
travel forecasts from information about activities that people perform, can significantly improve
representation of bicycle and pedestrian trips.
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Example
As part of the Puget Sound Regional Council's Transportation 2040 long-range planning process,
the agency forecasted daily trips in 2040 by three non-motorized modes: walk, bike, and walk to
transit. For each of the five plan alternatives, PSRC calculated the percentage change in trips by
these modes as compared to a baseline scenario. (The baseline reflects existing transportation
facilities plus future transportation investments that can be implemented with funds available
through currently authorized transportation revenue instruments.) Figure 6 shows the results of
the application of this performance measure. Alternative 5 (Reduce Emissions with Limited
Highway Investments and Regional Tolling) results in the largest increase in walk and bike trips.7
Figure 6: Puget Sound Regional Council - Change in Walk and Bike Trips as Percent of
Total Non-Motorized Trips from 2040 Baseline
8.0%
6.0%
4.0%
2.0%
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AttB
Measure: VMT per Capita
Measures the amount of vehicle activity normalized by population
Description
Increases in VMT contribute to traffic congestion and air pollution, causing carbon dioxide and
particulate matter emissions. Because of population growth and economic development, most
regions cannot feasibly reduce absolute VMT. Reducing per capita VMT can help a region achieve
air quality, climate change, and congestion reduction goals without penalizing it for population
growth.
For regions interested in reducing transportation GHG emissions, an advantage of using a VMT
metric is that VMT is more straightforward to analyze, since it does not account for vehicle fleet
characteristics and fuel carbon content. Additionally, transportation planning agencies do not
directly influence vehicle technologies and fuels, but their decisions can influence VMT. Measuring
VMT also avoids the possibility that unexpected changes in vehicle and fuel characteristics would
significantly affect a region's ability to meet its goals.
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GUIDE TO SUSTAINABLE TRANSPORTATION PERFORMANCE MEASURES
However, transportation GHG emissions are affected by factors other than VMT-vehicle fuel
economy, fuel carbon content, and the efficiency of system operations-and the usefulness of VMT
as a proxy for GHGs diminishes as vehicles and fuels become more efficient. In addition, a VMT
metric will not capture the potential GHG benefits of transportation system management and
operations strategies, such as lower speed limits, traffic signal improvements, and incident
management programs that reduce traffic delay.
Application
Land use visioning.
Long-range transportation planning.
Programming.
Performance monitoring.
Metrics
VMT per capita metrics can be set up to analyze the activity of all vehicles. Alternatively, since
demand management strategies have little influence on heavy-duty vehicles, metrics can focus on
light-duty vehicles only. Some agencies have measured VMT per capita separately for work and
non-work trips, or VMT per employee.
VMT per capita.
Light-duty VMT per capita.
VMT per employee.
Analytical Methods and Data Sources
Nearly all MPOs develop or obtain forecasts of VMT and population as part of the long-range
planning process, so calculating a VMT per capita metric is simple. Most MPOs used travel demand
models to forecast VMT. Because the model networks do not include most local roads, VMT on
these facilities must be estimated outside the model framework; local roadway VMT typically
ranges from 5 to 20 percent of total metropolitan VMT.
Because of the limitations of travel demand models, they generally will not fully capture the effects
of some strategies to reduce VMT, such as small-scale land use changes or improvements to
bicycle and pedestrian facilities.
Some small and mid-size metropolitan areas are not covered by a travel demand forecasting
model. Regions without travel demand forecasting models generally rely on calculations that
involve spreadsheets to forecast future VMT. The methodologies range from very simple linear
trend lines to more complex non-linear regression analyses.
Smaller MPOs may only estimate future traffic volumes for peak periods. Thus, estimating average
daily VMT may require extrapolation of peak-period volumes.
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GUIDE TO SUSTAINABLE TRANSPORTATION PERFORMANCE MEASURES
Examples
In its most recent Regional Transportation Plan, the Metropolitan Transportation Commission
(MTC - the San Francisco Bay Area MPO) established a goal of reducing daily per capita VMT by 10
percent by 2035. Baseline VMT per capita is forecast to grow 12 percent by 2035. Figure 7 shows
that infrastructure investment packages had minimal effect on VMT, achieving a maximum of 1.4
percent reduction from the baseline.8 The addition of aggressive land use and pricing strategies
was found to be much more effective at reducing VMT per capita, although they still did not
achieve the 2035 goal.
Figure 7: Metropolitan Transportation Commission (San Francisco Bay Area) - VMT per Capita
under Investment and Policy Scenarios
22.0-,
21.5
S
1 21.0-j
u
g. 20.5 -I
*
g 20.0 -
8 19.5-
I
« 19.0 -
1
> 18.5-1
18.0
Trend
Best Infrastructure
Add Pricing and
Land Use
2035 Objective
2000 2005 2010 2015 2020 2025 2030 2035
Measure: Carbon Intensity
Measures the amount of carbon dioxide (CO 2) emitted from transportation per person
Description
CO2 is the primary greenhouse gas emitted by transportation, accounting for 95 percent of
transportation's impact on climate change. In gasoline-powered vehicles, CO2 emissions are nearly
directly proportional to the amount of fuel burned.
Transportation investments and compact development patterns can reduce carbon intensity by
bringing activity centers closer together; by providing more robust transit, walking, and biking
connections; and by encouraging carpooling. Shorter travel distance and fewer vehicle trips mean
lower CO2 emissions per capita. Some investments in freight systems can also reduce CO2
emissions per capita.
Carbon intensity metrics are best applied at a regional scale. Individual transportation projects
tend to affect carbon intensity beyond their geographical scopes. It is difficult to capture these
broader changes at smaller scales of analysis.
PERFORMANCE MEASURE EXAMPLES
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GUIDE TO SUSTAINABLE TRANSPORTATION PERFORMANCE MEASURES
Application
Land use visioning.
Long-range transportation planning.
Programming.
Performance monitoring.
Metrics
Carbon intensity is represented as CO2 emissions per capita for all modes or individual modes of
transportation. Examples include:
Total transportation CO2 emissions per capita
Passenger transportation CO2 emissions per capita
Heavy-duty vehicle CO2 emissions per capita
Analytical Methods and Data Sources
For on-road travel, there are two approaches to estimate emissions from VMT:
CO2 emissions can be estimated using a simple formula: CO2 equals VMT divided by average
fuel economy (miles per gallon) times carbon content of fuel (grams per gallon). This formula
can be adapted to individual modes and vehicle classes, depending on the detail of the data
available.
Emissions models, including EPA's MOBILE and MOVES, can estimate CO2 emissions from
travel demand inputs.9'10 In California, the Air Resources Board's EMFAC, or EMissions FACtors
model, provides similar functionality.11
If fleet mix, average fuel economy, and the mix of fuels are relatively constant, there is a near
linear relationship between VMT and on-road CO2 emissions. Thus VMT per capita can serve as a
proxy for CO2 emissions per capita under some circumstances. VMT is a poorer proxy for CO2
emissions in the following situations:
Traffic-smoothing measures, changes in vehicle technology, or changes in fleet mix are
expected to improve average fuel economy.
Changes in the type of fuel used are expected to change the carbon emissions of fuel per
gallon.
Some passenger travel is expected to shift from private vehicles to buses or trains, or freight
is expected to shift from truck to train.
There is some uncertainty about how to account for lifecycle GHG emissions of alternative fuels.
Typically only the CO2 emitted from the tailpipes of conventional gasoline and diesel vehicles is
counted in carbon intensity metrics; however, the "upstream" production and distribution of
gasoline and diesel also emit CO2. Alternative fuels change both upstream emissions and tailpipe
emissions. For example, electric vehicles emit no tailpipe CO2, but the production of the electricity
used to power them typically creates CO2 emissions.12 The decisions to include or exclude
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emissions from certain categories of fuel lifecycles can substantially affect the calculation of CO2
emissions.
Examples
MTC established an ambitious target for CO2 emissions from transportation in its most recent
Regional Transportation Plan. Notably, the agency aimed to reduce not just CO2 emissions per
capita, but total CO2 emissions, even with projected population growth. MTC tested several
packages of infrastructure investments, along with transportation pricing policies and land use
policies, for their impacts on CO2 emissions.
Figure 8 shows the results of the final analysis.13 Ultimately, improvements in vehicle fuel
economy are expected to reverse the trend of rising CO2 emissions, reducing total emissions
from 90,000 tons per day in 2006 to 77,000 tons per day in 2035. The infrastructure investments
in the plan will reduce CO2 emissions an additional 1,000 tons per day, to 76,000. Additional land
use and pricing measures were found to further reduce CO2 emissions, although they did not
achieve the 2035 target.
Figure 8: Metropolitan Transportation Commission (San Francisco Bay Area) - CO2 Emissions per
Day under Investment and Policy Scenarios
100,
95
_ 90
" 35.
o
(J
•6
fr
•o
a
Trend
Best
Infrastructure
Add Pricing and
Land Use
2035 Objective
1990 1995 2000 2005 2010 2015 2020 2025 2030 2035
Note: The trend line from 2006 to 2035 is simplified. Passenger and light-duty vehicle fuel economy improvements required by state
legislation are phased in between 2009 and 2030. CO2 will continue to increase until about 2010, with a gradual decrease to 2035 as
state standards phase in and the existing vehicle fleet turns over with cleaner vehicles.
Measure: Mixed Land Uses
Measures the proportion of residents living in locations with mixed land uses
Description
Conventional zoning often results in segregation of residential and commercial land uses. In
contrast, mixed-use development locates land uses with complementary functions close together.
Complementary uses may include housing, retail, offices, restaurants, and services—destinations
that people travel to on a regular basis.
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Locating activities closer together can reduce trip lengths, allowing trips to be made by walking and
bicycling rather than by driving and increasing opportunities to combine trips. Individuals can drive
to one destination, for example, and then walk to others once they have parked their car. Reducing
vehicle trips can bring environmental and quality of life benefits. Furthermore, facilitating access to
employment and shopping by walking and bicycling reduces the need to own a motor vehicle for
personal mobility.
Application
Land use visioning.
Performance monitoring.
Metrics
Land use mix can be measured in numerous ways. The appropriate options for measuring land use
mix depend in part on the scale of analysis (e.g., metropolitan, city/county, transportation analysis
zone [TAZ], parcel).
One of the simplest metrics is the ratio of jobs to housing. At the metropolitan scale, the ratio of
jobs to housing is usually close to 1, but cities and neighborhoods often have a large imbalance
between jobs and housing, meaning that people have to commute farther to work. Land use
visioning at the neighborhood scale can involve calculating an employment-to-dwelling unit ratio.
Alternatives that shift this ratio closer to 1 are considered preferable, as this means jobs are
available near where people live, reducing commute times and increasing accessibility by foot,
bicycle, and public transit.
An index of population and employment mix in a study area can be calculated using the following
equation, where ABS stands for absolute value:
Regional population
~—: ; ; . * Study area pop. - Study area emp.
Regional employment J
1 - ABS
Regional population
Regional employment * Study area pop. | + Study area emp.
The closer this index is to 1, the more the study area mirrors the region in terms of population and
employment balance.
More complex measures of land use mix account for various land use types. For example, studies
have developed an entropy index that measures the degree of balance across multiple land uses.14 A
dissimilarity index can measure how closely different land uses come into contact with one another.
Analytical Methods and Data Sources
For analysis at a regional scale, most agencies use population and employment as proxies for land
use type. Simple metrics of land use mixing use population and total employment, which are
readily available to most MPOs for historic and forecast years at a variety of scales. Most complex
land use mixing metrics might require data on different land use types, such as residential, retail,
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office, public, and industrial. Many MPOs will have data on retail versus non-retail employment,
and some have employment data by major industry sector.
Analysis of land use mixing at a city, neighborhood, or parcel scale can often make use of data
on acreage of land by use type. Such land use types may be consistent with local government
zoning categories.
Examples
As part of its Blueprint land use visioning exercise, the Sacramento Area Council of Governments
developed a mixed-use development measure based on the ratio of employees to dwelling units at
the TAZ level. An optimum mix of jobs and housing is defined as a ratio of employees to dwelling
units that is greater than 0.5 and less than 2.0. Figure 9 shows the comparison of the preferred
Blueprint scenario versus the base land use scenario.15
Figure 9: Sacramento Area Council of Governments - Land Use Mix Measure from Blueprint Visioning
Mixed Use
Well planned and designed mixed use developments encompass all ol the ele-
ments of the other growth principles. Buildings homes and shops, entertainment,
office and even light industrial uses near each other create active, vital neighbor-
hoods, or villages. This mixture of uses can be either in a vertical arrangement
{mixed in one building) or horizontal (with a combination of uses in close proximi-
ty) These types of projects function as local activity centers, contributing to a
sense ol community, where people tend to walk or bike to destinations and inter-
act more with each other. Separated land uses, on the other hand, lead to more,
and longer, automobile trips because of the distance between uses. Mixed land
uses can occur at many scales Examples include a hous-
ing project located near an employment center, a
small shopping center located within a res-
idential neighborhood, and a building
with ground floor retail and apartments
or condominiums on the
upper floorjs).
^x
Baso Caso
Scenario
Preferred
Blueprint Scenario
0 10 20 30 40 50 60 70 80 90 100
Under the Base Case scenario, 26 percent of people would live in communi-
ties with a good, or balanced, mix of land uses by 2050. In the Blueprint
Scenario, 53 percent would live in balanced commumiiH;
Measure: Transportation Affordability
Measures the cost of transportation relative to income
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Description
Affordability captures the ability of transportation system users to pay for transportation. Whereas
measures of transportation cost capture only the dollar amount that transportation system users
pay, affordability puts cost in the context of income and other expenditures. A more affordable
system is one that consumes a smaller share of users' incomes.
Transportation investments and compact development patterns can make transportation more
affordable by reducing travel distances and providing less expensive options such as walking,
bicycling, and transit. Changes in fares or tolls may have other cost implications for transit riders
and motorists. An affordability measure tracks the financial impact of such actions on
transportation system users.
Because affordability is particularly important for low-income and disadvantaged groups, this measure
is often included in equity analyses. It can be calculated and compared across income groups.
Application
Long-range regional transportation planning.
Corridor studies.
Programming.
Metrics
Transportation affordability is calculated as the annual cost of transportation relative to annual
income. Alternatively, transportation costs can be calculated for different income groups to assess
the direction and magnitude of forecasted changes in transportation costs.
Analytical Methods and Data Sources
Components of transportation cost can include:
Public transportation fares
Private vehicle ownership and operating costs
• Fixed costs
Vehicle depreciation
Insurance
Finance charge
License fee
• Variable costs (per mile or per trip)
Fuel and oil
Tires
Maintenance
User fees
Some components of cost may be difficult to forecast using existing models.
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Transportation affordability measures could also include a component representing housing costs.
Including housing costs accounts for the trade-off that many households make between cheaper
housing and longer travel distances. In practice, however, it is not possible to forecast zone-level
changes in housing costs 20 or more years in the future with reasonable accuracy.
Examples
MTC included a transportation and housing affordability measure in its most recent long-range
transportation plan. Without any reliable means to forecast housing cost, MTC merely held
housing costs constant from 2006 to 2035. Figure 10 provides the results of the final analysis.16
Affordability is expected to improve in the future, but the planned investments do not change
affordability from the trend scenario. In a previous round of policy analyses, MTC found that
pricing policies would increase the share of income spent on transportation and housing, while
land use policies would decrease the share of income spent on transportation and housing.
Figure 10: Metropolitan Transportation Commission (San Francisco Bay Area) - Share of Income Spent
on Transportation and Housing
70% n
65% -
60% -
55%-
Trend and
Draft
Transportation
2035 Plan
2035 Objective
2000 2005 2010 2015 2020 2025 2030 2035
Measure: Benefits by Income Group
Measures transportation plan benefits by income group
Description
The principles of environmental justice require that transportation plans do not disproportionately
burden low-income and minority communities and that disadvantaged communities receive a fair
share of the benefits of transportation system improvements.17'18 Many transportation
performance measures can be analyzed for different population groups to illustrate how
transportation decisions will affect disadvantaged communities compared to other groups. A
common approach is to calculate transportation benefits by income group.
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Application
Long-range regional transportation planning.
Corridor studies.
Programming.
> Environmental Review.
Metrics
/Access to employment by income group. Employment accessibility measures generally count the
number of jobs that are accessible within a given travel time from each TAZ. The travel time should
be in the range of typical commute times. Calculations must be conducted separately for vehicle
and transit trips if the results will be useful to assess conditions for people without vehicle access.
In some cases, agencies have distinguished between access to professional and service-sector
employment. Distinguishing between types of employment becomes particularly important in
regions where there are concentrations of professional jobs without service jobs that provide
opportunities for low-skilled workers.
/Access to other destinations by income group. Agencies have evaluated the accessibility to other
destinations that are particularly important to disadvantaged groups, such as health care,
education, and recreational facilities.
Travel time by income group. Travel time performance measures indicate the average time needed
for trips that people actually take or, in the case of future travel time, for trips that people are
predicted to take. This measure may be more useful than accessibility when there are fewer central
destinations. Average travel time may also be more meaningful than accessibility in assessing actual
travel needs. If the jobs that exist near a low-income community require a high degree of
professional training, the community could show a high degree of jobs accessibility. But the average
travel time would better reflect the reality that those low-income individuals must travel long
distances to reach jobs for which they are qualified. Travel time metrics for equity analysis include
the following, each of which can be measured by mode and income group:
Work trip travel time.
Non-work trip travel time.
Travel time to key destinations.
Travel time for some specific trip types (shopping, recreation).
Travel time to specific major activity centers.
Transportation service provision by income group. The provision of transportation service is
another valuable measure for equity analysis. This measure is useful because it addresses
conditions under the direct control of transportation agencies. Measures of service provision are
also among the most tangible and easy-to-understand performance measures. They should,
however, be combined with other measures such as the accessibility measure described above,
since accessibility is the goal of service provision. Options for metrics include:
Average distance to the nearest transit stop.
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Availability of nighttime service.
> Availability of low-cost transit options.
Frequency of service.
Degree of crowding.
Number and quality of bus shelters.
Analytical Methods and Data Sources
Analysis of transportation plan benefits by income group typically requires classifying TAZs using
average household income data. All trip productions from a given TAZ are then assumed to be
representative of the average household income of that TAZ.
Employment accessibility metrics are calculated using zone-to-zone peak-period travel time by
mode. Accessibility to other destinations may be calculating using peak or off-peak travel times,
depending on the destination type. The location of destinations other than jobs may not be readily
available to the transportation agency, but other agencies, institutions, or commercial associations
may maintain such information. For example, county community service agencies may keep
records on the size and location of all hospitals and clinics.
Calculating transit accessibility requires a travel demand model that includes a robust transit
network to estimate the travel time or distance between origins and destinations on the
transit network.
Metrics involving transportation service provision may require detailed information on transit
service by route and zone, information that is available from service providers.
Examples
PSRC estimated the change in transportation costs (per work trip) in terms of the monetary value
of reduced travel time, unreliability, vehicle operating costs, and other user costs. Work trips were
divided into four income groups to show the distribution of benefits. Figure 11 shows these
benefits (reduction in transportation costs) across the five plan alternatives, as compared to the
2040 Baseline scenario.19 Compared to the baseline, improvements in system efficiency and
expansion of travel alternatives reduce transportation costs for all users under Alternatives 1, 2,
and 3. Because Alternatives 4 and 5 involve extensive new roadway pricing, they increase
transportation costs for low-income residents compared to the 2040 baseline.
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Figure 11: Puget Sound Regional Council - Transportation Benefits per Work Trip by Income Group
(Change from 2040 Baseline)
I Low I ncome
I Low-Mid Income
HiRh-Mid Income
I High Income
Altl
Alt 2
Alt 3
Alt4
AltS
The Southern California Association of Governments (the MPO for the Los Angeles region) analyzed
access to local, state, and national parks by travel model and income quintile. For this analysis,
they defined park accessibility as the percentage of park acreage reachable within a 30-minute off-
peak travel time period via: 1) automobile; 2) local bus/rail reached by automobile; and 3) local
bus/rail reached by walking. For transit travel time, both the waiting time and the on-board time
are included. Figure 12 shows the finding that low-income residents would receive larger
improvements in transit access to parks as compared to higher-income residents.20
Figure 12: Southern California Association of Governments - Improvements in Park Accessibility by
Travel Mode and Income Group
(Plan vs. 2035 Baseline)
I Auto Accessibility I Local Bus/Rail-Access by Auto I Local Bus/Rail-Access by Walking
100
80
60
40
20
Quintile I
Quintile II
Quintile III Quintile IV Quintile V
Measure: Land Consumption
Measures the amount of land consumed by new transportation infrastructure and/or new
development served by new transportation infrastructure
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Description
Compact development patterns and transportation investments that support these patterns use
land more efficiently. Using land efficiently for development preserves farmland, open space,
natural habitat, and watershed protection areas, which are important to communities for many
reasons, including their scenic qualities, the economic activities they support, and their
recreational value. These landscapes also conduct essential natural ecological functions, such as
filtering pollutants from the air and water and reducing contaminated stormwater runoff.
Application
Land use visioning.
Long-range transportation planning.
Corridor studies.
Programming.
Metrics
Land consumption metrics can measure the amount of land affected by various types of
development and can focus on impacts on particular types of natural lands. Examples include:
Acreage of sensitive lands (e.g., parkland, habitat) on which new transportation infrastructure
is built.
Number of residential units and square feet of non-residential space near agricultural and
natural resource lands.
Number of lane miles of roadways, amount of square footage of buildings, and number of
parking spaces in park-and-ride lots.
> Amount of new housing and jobs in greenfields.
> Acres of land consumed per residential unit.
Acres of farmland converted to development.
Analytical Methods and Data Sources
Land consumption measures are often forecast as part of regional land use and transportation
visioning exercises. Such exercises often use sketch planning tools to model development patterns
and facilitate stakeholder input. Development alternatives can be matched with existing land uses
in a GIS analysis to estimate what types of natural lands would be affected.
Land consumption can also be modeled in long-range transportation planning exercises. Ideally, in
order to demonstrate meaningful differences between alternatives, planners should use a model
that incorporates feedback between the transportation network and land development patterns.
An integrated transportation and land use model can predict how greenfield sites might be
developed if new roads are built that improve access to them.
To the extent that land use patterns are established prior to long-range transportation planning,
alternative scenarios will show less variation in impacts on land consumption. In these cases, it
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may be more appropriate to assess the land consumption impacts only for transportation
infrastructure.
Examples
PSRC evaluated the impact of its most recent plan on natural lands. The agency modeled the
amount of development that would occur on parcels adjacent to agricultural and natural resource
lands under five different plan alternatives. Figure 13 shows the impact of alternatives relative to a
2040 trend baseline.21 All alternatives increase the amount of non-residential development and
decrease the amount of residential development near natural resource and agricultural lands.
Alternative 1 (Emphasize the Efficiency of the Existing System) and Alternative 5 (Reduce Emissions
with Limited Highway Investments and Regional Tolling) create the least pressure on natural lands.
Figure 13: Puget Sound Regional Council - Development on Parcels in Proximity to Resource and
Agricultural Lands
(Change from 2040 Baseline)
j_
QJ
3
-Q
l/l
u?
QJ
—i
5.0% -
4.0% -
3.0% -
2.0% -
1.0% -
0.0% -
-1.0% -
-2.0% -
-3.0% -
-4.0% -
-5.0% -
Residential Units
I Non-Residential sq.ft.
Altl
Alt 2
Alt3
Alt4
AltS
In 2004, the Mid-Ohio Regional Planning Commission (the MPO for Columbus, Ohio) conducted a
visioning exercise to explore the impacts of alternative land use and transportation scenarios for
a 2030 horizon year. The amount of new development in greenfield areas was one criterion used
to assess alternatives. Figure 14 shows the results of the analysis.22 Two scenarios reduced the
amount of new jobs and housing in greenfields compared to the trend scenario, although they
did not affect total jobs and housing in the region.
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Figure 14: Mid-Ohio Regional Planning Commission—Comparison of Transportation and Land Use
Alternatives
Scenarios
Trend
Shifting Inward
Shifting Inward with Increased Transit
Aggressively Inward
VMT vs.
Current
46%
40%
31%
21%
Total Sq.
Miles
Developed
1.543
1,440
1,370
1.186
% New on Greenfields
Housing
84%
84%
73%
51%
Jobs
91%
91%
61%
22%
Measure: Bicycle and Pedestrian Activity and Safety
Measures the level of bicycle and pedestrian activity and safety in specific locations
Description
Unlike driving, bicycle and pedestrian activity is generally not measured in an accurate and
consistent manner over time. As a result, it can be more difficult to identify locations for bicycle
and pedestrian system improvements, to observe the effects of those improvements, and to justify
additional investments.
This measure is used primarily for regional performance monitoring and can inform programming,
corridor studies, and project-level environmental review. It can be used to monitor trends in
bicycle and pedestrian activity in key corridors or across an entire region. When combined with
crash data, it can provide a better measure of the locations of safety problems. Traditionally,
bicycle and pedestrian crash data are reported as the number of incidents per location, without
information on the level of bicycle and pedestrian activity in that location. This can lead to
erroneous conclusions that low-activity locations are relatively safe and high-activity locations are
relatively unsafe. By calculating a crash rate (crashes divided by bicycle or pedestrian counts),
regions can better target locations for safety improvements.
Application
Corridor studies.
Programming (grant awards).
Environmental review.
Performance monitoring.
Metrics
The basic metrics for bicycle and pedestrian activity are simply volumes per unit of time, such as:
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Bicycles per day.
Pedestrians per day.
As discussed above, accurate bicycle and pedestrian counts can be paired with crash data to assess
safety. Measures of safety can consider exposure by calculating the rate of crashes per unit of
volume, such as:
Bicycle crashes per 1,000 cyclists.
Pedestrian crashes per 1,000 pedestrians.
Analytical Methods and Data Sources
MPOs may not need to collect this activity data themselves. Cities, counties, and park districts
often perform their own bicycle or pedestrian counts-sometimes systemwide to develop a bicycle
or pedestrian plan, or sometimes at a single location as part of an impact analysis. By setting
regional standards for counts and serving as a repository for them, the MPO can develop a large
database of bicycle and pedestrian activity.
The National Bicycle and Pedestrian Documentation Project, an effort to promote consistency in
data collection methods, has produced guidance on collecting bicycle and pedestrian data,
including:23
> Selection of count methods. Manual and automatic counters can each be used and have
different advantages and disadvantages.
> Selection of count locations. Screenline counts, which measure the number of bicyclists and
pedestrians crossing a line "drawn" at a key location, are generally used to identify trends in
bicycle and pedestrian volume. Intersection counts are done to develop crash exposure
information and identify safety problems.
> Selection of count dates. Official national count/survey days (in September) are selected, with
additional optional days in January, May, and July.
> Selection of time of day. At least 2 hours of count data is needed.
Example
Since 1991, Portland, Oregon, has conducted screenline bicycle counts on four main Willamette
River bridges that connect downtown with many of the city's residential areas. Through this
consistent count program, the city has shown a remarkable increase in bicycling to and from
downtown Portland. This growth in bicycle use has coincided with a more than three-fold increase
in bikeway miles in the city. The city has also maintained data on bicycle crashes over this period,
which have remained relatively constant. Using bridge bicycle activity as a proxy for citywide
activity, Portland shows a declining bicycle crash rate (see Figure 15).24
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Figure 15: City of Portland, OR - Bicycle Counts and Crashes on Four Main Bicycle Bridges
Cyclists per Day
Crashes and Indexed Crash Rate
15,000
12,500
10,000
7,500
5,000
2,500
0
Bridge Bicycle Traffic
Reported Bicycle Crashes
Indexed Bicycle Crash Rate (Trend Line)
900
800
700
600
500
400
300
200
100
1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
Bridge Bicycle Traffic 2,850 3,555 3,885 3,830 3,207 4,520 5,225 5,690 5,910 6,015 7,686 8,250 8,562 8,875 10,192 12,046 14,563 16,711
Reported Bicycle Crashes 155 163 171 189 195 160 167 166 161 179 175 173 164 174 188 203 186 *
Indexed Bicycle Crash Rate (Trend Line) 544 459 440 493 514 354 320 292 272 298 230 210 192 196 184 168 128 *
Bicycle Fatalities 20432153005041 4060
In recent years, Portland has significantly expanded its program of consistent collection of bicycle
counts at non-bridge locations citywide. These counts have mostly been manual counts, taken by
volunteer counters and city staff; the city also conducts several 24-hour automated pneumatic
hose counts on some bridges and pathways. In 2009, bicycle counts were conducted at more than
100 locations (Figure 16).25
Figure 16: City of Portland, OR - 2009 Non-Bridge Bicycle Counts Compared with Prior Years
DISTRICT/
LOCATION
%CHANGE
SINCE 2000/01
BASED ON #
LOCATIONS
% CHANGE
SINCE 2008
BASED ON #
LOCATIONS
Citywide Total
190%
30
-4.6%
101
Central City
(west side)
North
Northeast
Southeast
East
Northwest
Southwest
212%
183%
138%
243%
no
81%
161%
1.5%
na
3.5%
-11.5%
8
12
14
21
16
9
21
The city of Chicago, in partnership with the Chicago Metropolitan Agency for Planning, collects
block-level pedestrian counts for much of the city's downtown area. The counts are available on
the city's interactive web map, together with traffic counts and signal information. A sample map is
shown in Figure 17.26
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Figure 17: Chicago Department of Transportation - Block-Level Pedestrian Counts Over One Day, in
Thousands (Sample)
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GUIDE TO SUSTAINABLE TRANSPORTATION PERFORMANCE MEASURES
Application
Metrics
Corridor studies.
Programming (grant awards).
Environmental review.
Performance monitoring.
Bicycle LOS (grade A - F).
Pedestrian LOS (grade A - F).
Analytical Methods and Data Sources
Methods for calculating bicycle and pedestrian LOS are documented in reports such as the National
Cooperative Highway Research Program's Report 616: Multimodal Level of Service Analysis for
Urban Streets and the Florida Department of Transportation Quality/Level of Service Handbook.2*'25
The 2010 Highway Capacity Manual also includes these methods.30
In general, bicycle LOS focuses on rating the comfort and perceived safety of an adult cyclist. It
requires information such as roadway width, bike lane widths and striping combinations, traffic
volume, pavement surface conditions, motor vehicles speed and type, and on-street parking.
Similarly, pedestrian LOS evaluates walking conditions from the point of view of perceived comfort
and safety. It requires information such as roadway/street width and striping combinations,
presence of a sidewalk, traffic volumes, motor vehicles speed, and on-street parking.
Figure 18 shows typical input parameters for calculating bicycle and pedestrian LOS.
Figure 18: Bicycle and Pedestrian LOS Input Parameters
Image source: ICF International
Bicycle LOS Input Parameters
ADT - Traffic volume
Pedestrian LOS Input Parameters
ADT - Traffic volume
Directional, Peak-to-daily, and Peak Hour Factors
Directional, Peak-to-daily, and Peak Hour Factors
Number of through lanes
Number of through lanes
Speed limit
Traffic speed
Percentage of traffic that is heavy vehicles
Buffer width
Surface condition rating
Sidewalk width
Width of outside lane
Width of outside lane
On-street parking permitted, percentage occupied parking
On-street parking permitted, percentage occupied
parking
Pavement width to the right of outside lane stripe
(including paved shoulder, parking area, bike lane)
Pavement width to the right of outside lane stripe
(including paved shoulder, parking area, bike lane)
Parking width (to the right of a bike lane)
Existence and spacing of trees
Ideally, LOS for automobiles, transit, bicyclists, and pedestrians are all reported for a street as part
of a multimodal LOS.
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Examples
The Chicago Metropolitan Agency for Planning developed bicycle and pedestrian LOS measures for
selected communities across the region as part of the region's comprehensive bicycle and
pedestrian plan. Figure 19 shows a sample of these results.31
Figure 19: Chicago Metropolitan Agency for Planning - Bicycle LOS for Sample of Communities
BLOS - LS3S3JS.
Harrington
_ • 1 L*nw,
Major trails
CTA/Metra (M)
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Measure: Average Vehicle Occupancy
Measures the ratio of passengers to vehicles on the roadway (the average number of people in
each vehicle)
Description
Average vehicle occupancy (AVO) (also called average vehicle ridership or vehicle occupancy rate)
captures the number of people traveling in each vehicle. AVO is a simple indicator, with broad
implications for the sustainability of the transportation system. A higher AVO indicates that more
people are traveling in fewer vehicles. As a result, the existing roadway capacity can handle more
passenger travel with less congestion. More passengers per vehicle also means that per passenger
emissions are lower. Finally, a higher AVO suggests a more affordable transportation system, since
sharing a ride is typically cheaper than driving alone.
A wide range of policies and programs can increase AVO. Preferential treatment for carpools and
vanpools, such as high-occupancy vehicle (HOV) lanes and preferred parking, encourages
ridesharing. Programs that help people find a shared ride to a common destination, such as ride-
matching websites, also make carpooling easier and more attractive. Transportation pricing
measures, such as tolls and parking fees, encourage carpooling by increasing the price of driving
alone. Improving transit service can also increase AVO if transit vehicles are included in the
calculation.
Application
Land use visioning.
Long-range transportation planning.
Corridor studies.
Programming.
Performance monitoring.
Metrics
AVO is measured as the number of passengers traveling on a roadway segment or network divided
by the number of vehicles traveling on the segment or network. Agencies may define the
numerator and denominator differently depending on their goals. For example, the Mid-America
Regional Council (MARC) in the bistate Kansas City region calculates AVO as the average number of
occupants in private, passenger vehicles (e.g., automobiles, vans, minivans, pick-up trucks, and
motorcycles). Other agencies include buses and bus passengers in the calculation.
AVO can be calculated at almost any temporal or geographical scale. MPOs commonly focus on
AVO during peak travel periods (commute hours) and may estimate AVO on particular corridors in
addition to regionwide AVO.
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Analytical Methods and Data Sources
For monitoring purposes, AVO is typically estimated by sampling data from one of two sources:
Travel surveys. Travel surveys administered at the household level or by employers can
capture modal travel patterns for particular trips or trip purposes.
Vehicle and passenger counts. Vehicle and passenger counts can be gathered from a
combination of manual observation and automatically collected data along key corridors or at
cordon points.
For forecasting purposes, many travel demand models estimate changes in AVO in response to
transportation investments and policies. A mode choice component is required. In addition, several
off-model analysis packages can be used to predict the impact of transportation strategies on AVO.
For example, both EPA's COMMUTER model and the Center for Urban Transportation Research's
TRIMMS model estimate the impact of employer-based financial incentives and other programs on
carpool and vanpool mode share.32'33 AVO can be derived from mode share figures, provided that
the average number of occupants per carpool, vanpool, and bus is also known. A sample
calculation is provided below:
AVO = (% carpool trips * avg. carpool occupancy) + (% SOV trips *1) + (% vanpool trips *
avg. vanpool occupancy) + (% bus trips * avg. bus occupancy)
COMMUTER and TRIMMS do not estimate changes in vehicle occupancy for individual modes.
Example
MARC included Vehicle Occupancy Rate as a performance measure in its long-range transportation
plan, Transportation Outlook 2040. The agency set a goal to increase AVO from its 2002 baseline of
1.22. As described above, MARC calculates AVO as the average number of occupants in private,
passenger vehicles. MARC sampled occupancy rates during weekday peak periods in an effort to
focus on commute trips, but some non-commute trips were inevitably captured. Data for the 2002
study that established the baseline were collected by counting the total number of occupants in a
sample of vehicles passing selected sites throughout the Kansas City region (Figure 20).
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Figure 20: Mid-America Regional Council (Kansas City region)—Average Vehicle Occupancy Trends
Vehicle Occupancy Rate Comparison
1980 1989 1990 1991 1992 1993 1997 2000 2002 2008
•MARC
Census
Measure: Transit Productivity
Measures the average number of riders on transit vehicles
Description
Transit productivity is a measure of return on investment in the transit system. It measures how
much travelers use the transit service provided in a region. Many local buses in the United States
travel with few passengers, suggesting that transit systems are not providing transportation
benefits consistent with their capital and operating costs.35 Having more passengers on each bus
generates more revenue for transit agencies and can result in better air quality and less
congestion.
Transit productivity is increased by more closely matching transit capacity (supply) with transit
demand. Transit demand can be stimulated through a variety of policies and programs, including
marketing and outreach to customers and providing financial incentives to use transit. Investments
in the transit system that improve the overall performance of transit and locate transit nodes in
high-density areas also stimulate demand for transit. Conversely, reducing transit service in areas
with low demand can improve the ratio of passengers to capacity, but reducing service may
conflict with key goals of transit agencies, such as providing a minimum level of service in low-
income communities.
Application
Land use visioning.
Long-range transportation planning.
Corridor studies.
Programming.
Performance monitoring.
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Metrics
Transit productivity is the ratio of passenger travel to transit service provided. Metrics can take
several forms, including:
> Average weekday transit boardings per vehicle revenue hour.
Average transit boardings per vehicle revenue mile.
> Average annual transit boardings per route mile.
Passenger miles traveled per vehicle revenue mile.
Transit productivity is typically measured at either the corridor level or the system level. At the
corridor level, productivity is often forecast for individual transit investments as part of long-range
planning and funding procedures. At the system level, transit productivity can be used to evaluate
long-range plan alternatives, including modal alternatives.
The return on transit investments has historically been subject to a higher level of scrutiny than
investments in other modes. For example, DOT requires that transit projects applying for federal
funding must be evaluated for cost effectiveness, defined as project cost per hour of projected
user (i.e., travel-time) benefits. No such evaluation is required for general-purpose roadway
investments. Without metrics that can be used to compare investments between different modes,
there is a possibility of over-investment in one mode versus another.
Other return on investment metrics could allow comparison between different modes of travel.
For example, person trips per dollar of public and private expenditure could be used to evaluate
transit, roadway, bicycle, and pedestrian infrastructure investments at the network level. However,
this metric might not be informative when applied to long-range plan alternatives because federal
planning statutes require that MPOs hold total person trips constant across plan alternatives. To
date, few MPOs have used a multimodal return on investment measure.
Analytical Methods and Data Sources
Forecasting transit productivity requires the use of a travel demand model with a mode choice
component. For a systemwide evaluation, a typical model automatically outputs both boardings
(unlinked trips) and passenger miles traveled. To evaluate individual investments, the model
automatically outputs boardings along each corridor. Additional calculation steps are required to
allocate passenger miles traveled to each corridor.
For performance monitoring, systemwide transit productivity can be calculated from data that
transit agencies report annually to the National Transit Database. The database contains statistics
on number of boardings (unlinked trips), vehicle revenue hours, vehicle revenue miles, passenger
miles traveled, and route miles by transit mode for each agency in the United States. Some
information is also available by time of day. Transit agencies may also collect more detailed data
on the performance of individual routes. Typically, transit agencies estimate demand-side variables
using a combination of automatic passenger counts and rider surveys. Supply-side data are
recorded in operating statistics.
Some MPOs use transit ridership as a performance measure in their long-range plans. In order
to reflect transit's return on investment, transit productivity can be easily calculated from
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transit ridership by dividing by transit supply. Transit supply assumptions are inherent in the
ridership forecasting model.
Example
Metro, the MPO for Portland, Oregon, included transit productivity as a performance measure in
its 2035 Regional Transportation Plan. The metric used was average weekday (AWD) transit
boardings per revenue hour. Productivity was forecasted to increase from 2005 to 2035 even
without additional investments in the transit system. Under the fiscally constrained investment
scenario (Federal Priorities System), transit productivity would increase an additional 7 percent
over the no-build scenario (Figure 21).36
In addition to using transit productivity as a measure to evaluate investment alternatives, Metro
has established a system monitoring plan that includes transit productivity as a performance
measure. Transit productivity will be measured periodically for each of 24 designated corridors,
and a system performance report will be prepared every two years. The performance report will
inform the allocation of regional flexible funds.
Figure 21: Portland (OR) Metro -Transit Productivity Evaluation
Transit productivity
AWD transit boardings/
revenue hour"
2005
Base Year
65
2035
No Build
109
2035 RTF
Federal Priorities
System
117
2035 RTP
Investment
Strategy
117
sFor the entire region including Clark. Clackamas, Multnomah and Washington counties
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4. Applications of Sustainable Transportation Performance Measures
Transportation agencies have a variety of opportunities to apply performance measures to protect
the environment, spur economic development, and promote healthy communities. This section
describes six examples of how MPOs have applied sustainable transportation performance
measures.
Long-Range Plan: Identifying Vision, Goals, and Targets
Performance measures help decision-makers assess how transportation policies and investments
contribute to achieving regional goals. The selection of performance measures should follow
directly from a region's vision, goals, and objectives.
Many long-range transportation plans begin with adopting a vision. A vision statement articulates a
region's aspirations for the transportation system in a few sentences or paragraphs. Written in
clear, simple language and using well-defined terms, a vision statement typically includes
ambitious, but not unrealistic, aspirations.
Goals are more specific and directed than vision statements. While the vision describes an end-
state, goals describe paths of action that lead to the vision. Figure 22 shows the transportation
vision adopted by the Mid-America Regional Council and the nine transportation goals that are the
foundation for the region's 2040 long-range transportation plan.37
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Figure 22: Mid-America Regional Council - Vision and Goals in the Transportation Outlook 2040 Plan
Regional Vision
Greater Kansas City is a sustainable region that increases the vitality of our society, economy and environment for
current residents and future generations.
Transportation Vision
A safe, balanced, regional, multimodal transportation system that is coordinated with land use planning, supports
equitable access to opportunities, and protects the environment.
Transportation Goals
Accessibility- Maximize mobility and access to opportunities for all area residents.
Climate Change and Energy Use - Decrease the use of fossil fuels through reduced travel demand, technology
advancements and a transition to renewable energy sources.
Economic Vitality - Support an innovative, competitive 21st century economy.
Environment- Protect and restore the region's natural resources (land, water and air) through proactive
environmental stewardship.
Place Making - Coordinate transportation and land-use planning as a means to create quality places in existing
and developing areas and to strengthen the quality of the region.
Public Health - Facilitate healthy, active living.
Safety and Security - Improve safety and security for all transportation users.
System Condition - Ensure transportation system is maintained in good condition.
System Performance - Manage the system to achieve reliable and efficient performance.
Transportation Objectives
Each goal in the MARC plan was further defined by a set of objectives. For example, MARC
identified the following six objectives under the goal of "Place Making":
"Create places that are walkable and pedestrian friendly.
Create places that support density and integrate multiple land uses (residential, commercial,
office, etc.
Create places that support a range of lifestyle and transportation options (transit, bicycle,
auto, etc.).
Create places that maximize the use of existing infrastructure through infill, redevelopment,
and increased density.
Create places that preserve and leverage the natural environment.
Create places that are attractive, built to last, and integrated with their surroundings."
Once goals have been established, some regions have adopted performance targets related to the
goals. These performance targets are numerical benchmarks to assess how well the long-range
transportation plan achieves the goals and vision. For example, Figure 23 shows 10 performance
targets included in Portland Metro's long-range transportation plan.38 These targets are intended
to provide policy direction for the development of the plan's investment strategy.
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Figure 23: Portland (OR) Metro - 2035 Regional Transportation Plan Performance Targets
Image source: ICF International
Topic Area Target
Safety By 2035, reduce the number of pedestrian, bicyclist, and motor vehicle occupant fatalities
plus serious injuries each by 50% compared to 2005.
Congestion
By 2035, reduce vehicle hours of delay (VHD) per person by 10% compared to 2005.
Freight reliability
By 2035, reduce vehicle hours of delay truck trip by 10% compared to 2005.
Climate change
By 2035, reduce transportation-related carbon dioxide emissions by 40% below 1990 levels.
Active transportation By 2035, triple walking, biking, and transit mode share compared to 2005.
Basic infrastructure
Clean air
By 2035, increase by 50% the number of essential destinations accessible within 30 minutes
by trails, bicycling and public transit or within 15 minutes by sidewalks for all residents
compared to 2005.
By 2035, ensure zero percent population exposure to at-risk levels of air pollution.
Travel
By 2035, reduce vehicle miles traveled per person by 10% compared to 2005.
Affordability By 2035, reduce the average household combined cost of housing and transportation by 25%
compared to 2000.
Access to daily needs
By 2035, increase by 50% the number of essential destinations accessible within 30 minutes
by bicycling and public transit for low-income, minority, senior, and disabled populations
compared to 2005.
The use of performance measures or targets in the visioning stage of long-range planning can help
elected officials and stakeholders to understand the potential benefits of emphasizing different
policy and investment priorities. For example, MPOs have applied performance measures to
illustrate the potential to reduce VMT through "levers" such as land use, pricing, and aggressive
transit expansion. Typically, a visioning exercise does not apply the fiscal constraints that will
ultimately be included in an adopted transportation plan.
Long-Range Plan: Project Performance Assessment
Performance measures can be used to evaluate individual projects being considered for inclusion
in a long-range transportation plan. This is the best opportunity to ensure that the final plan
includes projects that best support the region's vision and goals. However, quantitatively
evaluating individual projects can be time consuming and may require technical capabilities not
available to every transportation agency. As a compromise, agencies can apply quantitative
evaluation to only those projects with the largest cost and greatest regional significance, while
using qualitative assessment for all projects.
The Metropolitan Transportation Commission applied a quantitative and qualitative performance
assessment to projects considered for the region's 2035 long-range transportation plan. The
overall purpose of this assessment was to identify outliers—those projects that most strongly
supported the plan's goals and objectives and those that most notably did not. The results of the
assessment helped to guide the commission in making the trade-offs necessary to develop the
plan, but it was not the only factor used to select projects. The MTC recognized that the
performance assessment could not capture and weigh all relevant policy considerations, so local
priorities could outweigh performance in some cases. The commission allowed exceptions after
receiving formal explanations for such projects.
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Approximately 700 projects were submitted for consideration in MTC's 2035 plan. MTC applied the
quantitative evaluation to approximately 60 projects, most of which had areawide impacts and
costs of more than $50 million. While this sub-set included less than 10 percent of the projects
submitted, it made up roughly three-quarters of the discretionary investments in the plan. The
projects selected for quantitative evaluation included major highway and transit projects as well as
several regional investment programs, such as a regional bicycle network and the Transportation
for Livable Communities program, which supports transportation projects that help revitalize
downtown areas, commercial cores, and other existing neighborhoods. Figure 24 shows the
quantitative project evaluation measures and the plan performance objectives addressed by
each.39 The benefit-cost ratio is a composite measure that includes travel time, user cost,
emissions, and safety components.
Figure 24: Metropolitan Transportation Commission (San Francisco Bay Area) - Quantitative Project
Evaluation Measures
Image source: ICF International
Measures
Benefit-Cost Ratio (monetized), reflecting:
> Recurrent delay (vehicle hours)
> Non-recurrent delay (vehicle hours)
> Transit travel time 1
> Particulate matter emissions (PM2.5 and PM10)
> Carbon dioxide emissions
> Fatal and injury collisions
> Direct user costs (vehicle operating and, in some cases,
auto ownership costs)
> Public and private cost savings from performing on-time maintenance '
Plan Performance Objective
Reduce Congestion, Reduce
Emissions, Reduce Collisions and
Fatalities
Reduction in VMT and cost per VMT reduced
Reduce Vehicle Miles Driven
Reduction in CO2 emissions and cost per ton reduced
Reduce Emissions
Cost per low-income household served by transit (trial measure)
Improve Affordability
Notes: 1) For HOV and HOT projects only; 2) For maintenance programs only; 3) Fortransit projects only.
MTC also performed a qualitative performance assessment for all projects submitted for plan
inclusion. The agency determined that presenting an assessment for each of 700 individual projects
would result in "information overload," so projects were grouped into 21 types. Each project type
was then assessed in terms of how well it supported the plan goals. Figure 25 lists the criteria used
to make this determination.40 Each project type was judged to "strongly support," "support," or be
"neutral toward" the criteria associated with each goal. MTC then tabulated the number of plan
goals supported by each project type. All project types supported at least one goal; no project type
"strongly supported" all five goals. The agency also calculated the total cost of projects supporting
one goal, two goals, three goals, or four goals.
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Figure 25: Metropolitan Transportation Commission (San Francisco Bay Area) - Project-Level Qualitative
Assessment Criteria
Image source: ICF International
Plan Goals
Maintenance
Criteria for Determining Support
Advances maintenance of the existing transportation system
Congestion Relief
(Reliability and Efficient
Freight Travel)1
Improves freight mobility
Improves transit mobility, effectiveness, or efficiency
Improves local mobility or circulation
Completes a critical transportation gap (geographic or temporal)
Institutes or enables a new user-based pricing program
Implements technology-based operations or traveler information
Improves roadway safety
Emissions Reduction
Focused Growth
Access and Safety (non-
motorized) 2
Provides an alternative to driving alone
Improves transit mobility, effectiveness, or efficiency
Marketing, education and incentive programs that encourage mode shift away from
driving alone or during peaks
Located within a proposed or planed priority development area
Connects two priority development areas
Provides a transit alternative to driving on a future priced facility
Provides an alternative to driving alone
Improves access for youth, elderly, and disabled persons
Improves safety for pedestrians and cyclists
Reduces transportation or housing costs for low-income households
Notes: 1) Includes roadway safety; 2) Includes affordability for low-income households and non-motorized safety.
Long-Range Plan Evaluation
When a draft transportation plan has been developed, performance measures can be used to
assess key system supply-and-demand characteristics. These measures should relate to the plan
goals and objectives established early in the process. While this stage in the plan development may
be too late to meaningfully influence project selection, applying performance measures allows the
agency to evaluate the plan as a whole and sets the stage for future planning activities.
Figure 26 shows a sample of performance measures used to assess the 2031 regional
transportation plan of the Central Lane MPO (Eugene-Springfield, Oregon).41 A total of 24
performance measures were used to evaluate the plan, with comparisons to 2004 existing
conditions. These measures confirmed that the plan was consistent with many of the region's
sustainability objectives, including the expansion of walking and bicycling facilities and an increase
in the number of people who use them.
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Figure 26: Central Lane MPO (Oregon) - Summary of Sample Performance Measures
Image source: ICF International
Category
VMT and Trip
Length
Mode Shares -
All Trips
System
Characteristics
Key
PM5b
PM6
PM7
PM8a
PM8b
PM8c
PM8d
PM8e
PM8f
PM8g
PM15
PM17
PM18
PM21
PM22
Description
Internal VMT/Capita
Average Trip Length (miles)
% Person Trips Under 1 Mile
Walk
Bike
Transit
Shared Ride (2 or more)
Drive Alone
% Non-Auto Trips
Person Trips per Auto Trip
Ratio of Bikeway Miles to Arterial and
Collector Miles
% of Households Within 1/4 Mile of a
Transit Stop
Transit Service Hours per Capita
Bikeway Miles
Priority Bikeway Miles
2004
Conditions
Amount
12.11
3.60
14.8%
9.2%
3.5%
2.1%
41.3%
43.9%
14.8%
1.65
59%
83%
1.30
223.4
27.3
2031 Financially
Constrained Plan
Amount
12.49
3.74
16.1%
9.8%
3.9%
2.5%
42.0%
41.9%
16.1%
1.67
86%
83%
1.17
305.5
62.3
% Change
3.2%
3.9%
8.8%
6.3%
11.8%
16.4%
1.6%
-4.5%
9.0%
1.2%
45.8%
0.0%
-10%
37%
128%
Corridor-Level Evaluation
Corridor or sub-area studies provide opportunities for more focused and detailed consideration of
sustainability measures and strategies. At the corridor level, accessibility performance measures
become more specific, and the consideration of multimodal options can be refined. Agencies can
measure improvements in bus headways, route ridership, signalization, and access management
techniques. Analysis to compare potential solutions is often more time consuming and costly due
to the level of detail required. However, this level of detail allows agencies to identify specific
needs and to calibrate solutions to address them.
Multimodal analysis at the corridor or sub-area level can inform both the broader understanding of
the regional transportation system as well as project-level decision-making. Another benefit to
using corridor-level performance measures along with regional ones is the more efficient allocation
of resources. For example, agencies can supplement volume or capacity information provided for
the corridor by the travel demand model with transit ridership data and pedestrian and bicycle
counts to identify where changes in mode split have occurred. This information informs the
regional selection of individual strategies and provides specific data support for selecting project
alternatives.
One example of this approach comes from the Hillsborough County MPO, covering the Tampa,
Florida, area. The Hillsborough County MPO developed a tiered structure for performance
measures that is intended to monitor the transportation system in an effective and resource-
efficient way. The program measures performance by corridor, first applying Primary Performance
Measures, including basic performance measures for roadway (volume-to-capacity), transit
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(ridership and frequency), bicycle (extent of corridor with bicycle facilities), and pedestrian travel
(extent of corridor with sidewalks). For identified congested corridors, the MPO tracks a more
detailed set of measures, drawing on data such as travel time surveys, pedestrian counts, employer
rideshare programs, and transit on-time performance.
Figure 27 shows an example of how this information is presented for one corridor in the
Congestion Management System Performance Report (Hillsborough Avenue).42 Similar information
is presented for all 39 corridors covered in the report.
Figure 27: Hillsborough County MPO (Tampa area) - Sample Corridor Performance Report
Hillsborough Ave
Bus Routes
•Route 15 Route 6
—Route 32 —Route 39
—Route 31 -Route -11
Segment V/MSV Ratio
I
Hi
55
§
Isborbugh Ave
ffi
.c
$
f £
/ I
2 °
V/MSV Ratio
0 CO u 50 U 7'. ; 00 • J5 1 :•;*
.^^
• " r
C~3
£03
Corridor Length (mi.)
Weighted V/MSV Ratio
2000
2.50
1.25
2004
2.51
1.10
Transit Service
Route
Number
6
15
32
39
41
Passengers/
Revenue Hour
24.32
15.58
14.87
18.04
11.04
Headway (minutes)
AM
30
45
35-60
60
60
Mid
30
45
35-60
60
60
PM
30
45
35-60
60
60
Sidewalk Availability
% North Side
29 3%
% South Side
29.3%
Bicycle Facility Availability
% North Side
70.3%
% South Side
70.3%
Blke/Ped Facilities
Hillsborough Ave
Bicycle Facilities
Sidewalks
U% 1U% 30% «J% /b% 100%
Programming
In the programming phase of decision-making, performance measures can be used to prioritize
among candidate projects submitted for funding. Measures at this stage are often both qualitative
(e.g., does the project support specific program objectives?) and quantitative (e.g., how much does
the project reduce VMT or emissions?).
Many transportation agencies use performance measures to select projects to receive funding
through the federal Congestion Mitigation Air Quality Program (CMAQ). For example, the
Southwestern Pennsylvania Commission evaluates candidate projects using quantitative and
APPLICATIONS OF SUSTAINABLE TRANSPORTATION PERFORMANCE MEASURES
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GUIDE TO SUSTAINABLE TRANSPORTATION PERFORMANCE MEASURES
qualitative measures. Using standardized tools from the Pennsylvania Department of
Transportation, the commission estimates the following metrics for each project:
Change in emissions.
Change in VMT.
Change in vehicle trips.
Dollar per ton of emissions reduced by potential CMAQ activities.
Dollar per unit change in vehicle trips and VMT from potential CMAQ activities.
The Southwestern Pennsylvania Commission also completes a scorecard to rate each candidate
CMAQ project using qualitative measures. Based on federal guidance and regional priorities, the
commission gives funding priority to the following types of eligible projects: diesel retrofits, traffic
signal improvements, transportation demand management, and commuter bicycle/pedestrian
improvements. They then score projects on nine ancillary selection factors, with each factor given
a weight (5, 7, or 10) and assigned a score of low (1), medium (2), or high (3), as shown in Figure 28
(each project's scores are recorded in the blank columns).43 These scorecards, together with the
quantitative impact measures, result in a prioritized list of CMAQ projects.
Figure 28: Southwestern Pennsylvania Commission - CMAQ Project Rating Scorecard
Image source: ICF International
Factors
Weight
Score
l=low
2=med
- ' ' h
Weighted Possible
Score Score
1. Consistency with 2035 Long Range Plan Vision and Policies
that Impact Air Quality
2. CMP Congested Corridor Rating
3. Deliverability / Project Readiness
4. Raise Public Awareness of Transportation Demand
Management Options
5. Grouped Projects
6. Safety Improvements
7. Sustainable Development Benefits
8. Projects that bring Non-Traditional Funding to TIP
9. Non-Federal Funding Share
10
10
10
7
5
7
5
5
5
30
30
30
21
15
21
15
15
15
MPOs can develop detailed measures to evaluate projects considered for inclusion in the TIP. In
addition to traditional roadway projects, these evaluation measures can be extended to transit,
bicycle/pedestrian, and other projects supportive of regional sustainability goals.
The Denver Regional Council of Governments (DRCOG) has developed eligibility requirements and
evaluation criteria for 11 project types, including three types of transit projects, bicycle/pedestrian
projects, and other enhancement projects.44 For example, all bicycle/pedestrian projects must
satisfy the following four eligibility requirements:
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"Pedestrian and bicycle projects must be on facilities contained in an adopted local or
regional plan.
2) Any new or reconstructed pavement must be designed and constructed to withstand
occasional vehicle travel (emergency vehicles).
3) If project consists of multiple, non-contiguous elements, all elements must either be a) on the
same facility (primary corridor) OR b) within % mile of the largest element of the project.
4) Projects that consist of both a new construction element and an upgrade and/or
reconstruction element must be categorized as either one or the other to score the project.
That categorization is determined by the element proposed in the largest contiguous segment
of the project, based on linear feet."
DRCOG then applies a detailed system for scoring candidate bicycle/pedestrian projects. Figure 29
shows the scoring system for new construction projects.45 A separate set of measures is applied for
scoring upgrade or reconstruction projects.
Figure 29: Denver Regional Council of Governments - TIP Evaluation Measures for
Bicycle/Pedestrian Projects (New Construction)
Image source: ICF International
Evaluation
Criteria
Safety
Points Scoring Instructions
0-10 Projects will be evaluated on the anticipated improvement of existing safety problems to be
made by building new facilities for non-motorized travel. Three measures of safety
improvement will be awarded:
1. Relevant crash history
Based on the number of documented injury accidents:
> created by the interaction between motorized and non-motorized traffic;
> in the area to be affected by the proposed new facility; and
> occurring over the last three-year period for which data is available.
1 point will be awarded for each applicable injury accident, up to a maximum of 4.
2. Conflict factor
If the existing facilities are roadways that allow interaction between motorized and non-
motorized traffic, and if the project will build new facilities for the non-motorized traffic, to
eliminate or reduce the conflict factor, the project will earn safety points. Based on the
speed limit on the existing facilities, up to 4 points will be awarded as follows:
> 1 points will be awarded if the existing speed limit is 30 MPH or less;
> 2 points will be awarded if the existing speed limit is 35 MPH;
> 3 points will be awarded if the existing speed limit is 40 MPH; or
> 4 points will be awarded if the existing speed limit is 45 MPH or above.
3. Facility lighting
2 points will be awarded to projects that will provide ADA/AASHTO compliant lighting to
facilitate non-motorized travel on the planned facilities, if no lighting is currently available.
APPLICATIONS OF SUSTAINABLE TRANSPORTATION PERFORMANCE MEASURES
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Evaluation
Criteria
Points Scoring Instructions
Connectivity
0-17 Up to 17 points will be awarded for specific project attributes that address existing local or
regional connectivity of non-motorized travel. Points will be awarded as follows:
Connectivity measures - gap closure (score points for only one of these two)
> 4 points - completely closing a gap between two existing bicycle facility/sidewalk
sections.
> 2 points - completely closing a gap between an existing pedestrian/bicycle facility and an
RTP roadway that serves pedestrian/bicyclists.
Connectivity measures - access (score points for only one of these three)
> 3 points - provide direct access (project directly touching) to a school.
> 2 points - provide direct access (project directly touching) to an employment center with
greater than 2,000 jobs.
> 1 points - provide direct access (project directly serving) to such destinations as
employment, shopping, dining, or government buildings, or recreational destinations
such as parks or recreational facilities.
Connectivity measures - barrier elimination (score points for only one of
these three)
> 5 points - entirely eliminate a barrier (railway, highway, waterway) for pedestrians or
cyclists by grade separating.
> 3 points - entirely eliminate a barrier (railway, highway) for pedestrians or cyclists by
providing a controlled crossing where one does not currently exist (demonstrate
achievement of signal warrant if signal proposed).
> 1 point - construct at least one phase of a multi-phase improvement (as dictated through an
approved plan) towards eliminating a barrier (railway, highway, waterway).
Connectivity measures-transit (score points for only one of these if applicable)
> 3 points - provide new direct access to "transit" within 1.5 miles for bike projects and
within 0.5 miles for pedestrian projects. "Transit" is stations, park-n-Ride lots, or transit
terminals existing, in final design, or under construction; or existing bus stops serving 3
or more routes.
> 1 point - provide new indirect access (serving via an existing linkage) to "transit" within 1.5
miles for bike projects and within 0.5 miles for pedestrian projects. "Transit" is stations,
park-n-Ride lots, or transit terminals existing, in final design, or under construction; or
existing bus stops serving 3 or more routes.
Connectivity measures - location (score 2 points maximum)
> 2 points - project is located in the jurisdiction of more than one local governmental
entity (with written confirmation and agreement by the other affected governmental
entities besides the applicant).
> 1 point - project connects 2 or more neighborhoods where an exclusive bicycle and/or
pedestrian access does not currently exist, excluding roadways.
Multiple 0-4 Up to 4 points will be awarded for multiple enhancements (score all that apply):
Enhancements > 2 points if project will provide facilities for bidirectional use by both bicycles and
pedestrians (10 ft. minimum width)
> 1 or 2 points if project will provide bicycle lockers or racks; 1 point for each 10 racks or 3
lockers, up to 2 points
Air Quality 0-8 New bike/ped projects may reduce air pollution by reducing VMT. Based on the daily
Benefits reduction in pounds of total air pollutants expected from this project, as a percentage of the
regional total from mobile sources, 8 points will be awarded to projects which would reduce
0.3% of the regional total or more; 0 points to projects which would reduce no pollution; with
straight-line interpolation between.
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Performance Monitoring
Performance monitoring enables a region to observe trends in key indicators and assess the
progress the region is making toward its goals and objectives. Many MPOs create an annual "state
of the region" report that showcases selected performance measures in areas such as
transportation, land use, environment, economic development, and public health. A long-range
transportation plan can also identify performance-monitoring measures that relate directly to the
plan goals and objectives.
The Mid-America Regional Council identified one or more performance measures to assess
progress toward each of the nine goals adopted as part of the region's 2040 plan, shown in Figure
30.46 The measures and associated data are intended to "inform decisions and strategies that will
be necessary to move these indicators in the desired direction toward stated goals."
Figure 30: Mid-America Regional Council - Performance Measures in the Transportation Outlook 2040
Plan
Image source: ICF International
Goal
Accessibility
Economic Vitality
Climate Change/
Energy Use
Environment
Place Making
Public Health
Safety and Security
System Condition
System Performance
Factor
Level of Transit Service
Environmental Justice
Transportation Costs
Vehicle Miles Traveled /C02
Vehicle Occupancy
MetroGreen Network
Multi-modal Options
Ozone
Physical Health
Crash Fatality and Injury Rate
Bridge & Pavement Condition
Level of Service
Congestion
Travel Time
On-Time Performance
Measure
> Revenue service hours
Ridership
> Percent of transportation investments in environmental
justice tracts
> Combined transportation and housing costs as a
percentage of median income
> Systemwide daily VMT/C02 emissions
Vehicle occupancy rate
> Percent/miles of MetroGreen Network Completed
> Modal balance (mode share)
Ozone levels
Obesity rate
> Annual crash fatalities and disabling injuries
> Pavement condition
Bridge condition
> Observed speed vs. posted speed on Congestion
Management System network
> Percent of Congestion Management System network
congested
> Average commute time
> On-time performance of transit system
Conclusion
The examples described in this guidebook indicate the growing interest in both performance-based
planning and in making transportation environmentally and economically sustainable over the long
term. By providing sample performance measures, identifying where in the transportation
decision-making process they can be applied, and offering examples of recent transportation
agency work in this area, this guidebook can spur further interest and innovation.
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GUIDE TO SUSTAINABLE TRANSPORTATION PERFORMANCE MEASURES
Developing and using performance measures is not necessarily easy. At a minimum, it requires
working with stakeholders to identify the most appropriate measures and new analysis and
reporting by MPO staff. In some cases, it requires collecting new data or assembling and processing
data collected by other agencies, both of which can be time consuming and costly. Perhaps the
biggest challenge is overcoming resistance to changing long-established procedures for prioritizing
projects.
Nonetheless, the rewards of these efforts can be substantial. MPOs have found that, once they
begin to report performance measures, stakeholders quickly see their value and then come to
expect regular reporting of measures and a more explicit linkage between the measures and public
agency decisions. Transportation agency staff and stakeholders can then engage in a much richer
conversation about the trade-offs among policy and investment decisions and the best
opportunities for a region or state to reach its sustainability goals.
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Endnotes
Transportation Research Board Sustainable Transportation Indicators Subcommittee. Sustainable
Transportation Indicators: A Recommended Research Program for Developing Sustainable Transportation
Indicators and Data. 2008. http://www.vtpi.org/sustain/sti.pdf
(Note: The definition endorsed by the Subcommittee originally came from the European Council of Ministers of
Transport.)
U.S. Environmental Protection Agency. HUD-DOT-EPA Partnership for Sustainable Communities.
http://www.epa.gov/smartgrowth/partnership/index.html
3 Puget Sound Regional Council. Transportation 2040: Draft Environmental Impact Statement. 2009.
http://www.psrc.org/transportation/t2040/t2040-pubs/trans2040-deis/
Delaware Valley Regional Planning Commission. Tracking Progress Toward 2030: Regional Indicators for the
DVRPC Long Range Plan. http://www.dvrpc.org/LongRangePlan/Regionallndicators/
Atlanta Regional Council. 2030 Regional Transportation Plan.
http://www.atlantaregional.com/transportation/regional-transportation-plan
6 San Diego Association of Governments. 2030 Regional Transportation Plan.
http://www.sandag.org/index.asp?projectid=292&fuseaction=projects.detail
Puget Sound Regional Council. Transportation 2040: Draft Environmental Impact Statement. 2009.
http://www.psrc.org/transportation/t2040/t2040-pubs/trans2040-deis/
Metropolitan Transportation Commission. Transportation 2035 Plan for the San Francisco Bay Area,
Performance Assessment Report. 2008.
http://www.mtc. ca.gov/planning/2035_plan/Supplementary/T2035Plan-Perf_AssessmentReport.pdf
U.S. Environmental Protection Agency. EPA MOBILE Model, http://www.epa.gov/oms/mobile.htm
U.S. Environmental Protection Agency. MOVES Model, http://www.epa.gov/otaq/models/moves/index.htm
California Environmental Protection Agency, Air Resources Board. EMFAC2007 Release.
http://www.arb. ca.gov/msei/onroad/latest_version. htm
12 U.S. Department of Energy, Energy Efficiency and Renewable Energy. Electric Vehicles.
http://www.fueleconomy.gov/feg/evtech.shtml
13 Metropolitan Transportation Commission. Transportation 2035 Plan for the San Francisco Bay Area,
Performance Assessment Report. 2008.
http://www.mtc. ca.gov/planning/2035_plan/Supplementary/T2035Plan-Perf_AssessmentReport.pdf
14 Kockelman, Kara. 'Travel Behavior as Function of Accessibility, Land Use Mixing, and Land Use Balance:
Evidence from San Francisco Bay Area."Transportation Research Record: Journal of the Transportation
Research Board. 1997. No. 1607.
Sacramento Area Council of Governments. Preferred Blueprint Alternative.
http://www.sacregionblueprint.org/
16 Metropolitan Transportation Commission. Transportation 2035 Plan for the San Francisco Bay Area,
Performance Assessment Report. 2008.
http://www.mtc. ca.gov/planning/2035_plan/Supplementary/T2035Plan-Perf_AssessmentReport.pdf
17 U.S. Environmental Protection Agency. Environmental Justice Basic Information.
http://www.epa.gov/compliance/ej/basics/index.html
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GUIDE TO SUSTAINABLE TRANSPORTATION PERFORMANCE MEASURES
U.S. Department of Transportation, Federal Highway Administration. Title VI - Nondiscrimination in Federally
Assisted Programs, http://www.fhwa.dot.gov/environment/title_vi.htm
19 Puget Sound Regional Council. Transportation 2040: Draft Environmental Impact Statement. 2009.
http://www.psrc.org/transportation/t2040/t2040-pubs/trans2040-deis/
Southern California Association of Governments. 2008 Regional Transportation Plan: Making the Connections,
Environmental Justice Report, http://www.scag.ca.gov/rtp2008/index.htm
21 Puget Sound Regional Council. Transportation 2040: Draft Environmental Impact Statement. 2009.
http://www.psrc.org/transportation/t2040/t2040-pubs/trans2040-deis/
22 Mid-Ohio Regional Planning Commission. Regional Fact Book. 2004.
http://www.morpc.org/pdf/RegionalFactBook.pdf
National Bicycle and Pedestrian Documentation Project, http://bikepeddocumentation.org
City of Portland, Oregon. Portland Bicycle Count Report. 2009. http://bikeportland.org/wp-
content/uploads/2010/01/bikecount2009reportfinal.pdf
25 City of Portland, Oregon. Portland Bicycle Count Report. 2009. http://bikeportland.org/wp-
content/uploads/2010/01/bikecount2009reportfinal.pdf
26 Chicago Department of Transportation. City of Chicago Traffic Information.
http://www.cityofchicago.org/traffic/
Transportation Research Board. Highway Capacity Manual 2010.
http://www.trb.org/Main/Blurbs/Highway_Capacity_Manual_2010_HCM2010_164718.aspx
28 Transportation Research Board, National Cooperative Highway Research Program. Report 616: Multimodal
Level of Service Analysis for Urban Streets. 2008.
http://onlinepubs.trb.org/onlinepubs/nchrp/nchrp_rpt_616.pdf
Florida Department of Transportation. Quality/Level of Service Handbook. 2009.
http://www.dot.state.fi.us/planning/systems/sm/los/pdfs/2009FDOTQLOS_Handbook.pdf
30 Transportation Research Board. Highway Capacity Manual 2010.
http://www.trb.org/Main/Blurbs/Highway_Capacity_Manual_2010_HCM2010_164718.aspx
Chicago Area Transportation Study. Soles and Spokes: The Pedestrian and Bicycle Plan for Chicago Area
Transportation. 2004. http://www.catsmpo.com/prog-bikeped.htm
32 U.S. Environmental Protection Agency. Transportation-Related Documents - Commuter Programs.
http://www.epa.g0v/oms/stateresources/policy/pagj:ransp.htm#cp
33
34
35
University of South Florida Center for Urban Transportation Research, http://www.cutr.usf.edu/index.shtml
Mid-America Regional Council. Transportation Outlook 2040. 2010. http://www.marc.org/2040/
U.S. Department of Transportation, Federal Transit Administration. Public Transportation's Role in Responding
to Climate Change. 2010.
http://www.fta.dot.gov/documents/PublicTransportationsRolelnRespondingToClimateChange2010.pdf
36 Portland Metro. Draft 2035 Regional Transportation Plan. 2010.
http://www.oregonmetro.gov/index.cfm/go/by.web/id=25036
37
38
Mid-America Regional Council. Transportation Outlook 2040. 2010. http://www.marc.org/2040/
Portland Metro. Draft 2035 Regional Transportation Plan. 2010.
http://www.Oregon metro.gov/index.cfm/go/by.web/id=25036
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GUIDE TO SUSTAINABLE TRANSPORTATION PERFORMANCE MEASURES
Metropolitan Transportation Commission. Transportation 2035 Plan for the San Francisco Bay Area,
Performance Assessment Report. 2008.
http://www.mtc. ca.gov/planning/2035_plan/Supplementary/T2035Plan-Perf_AssessmentReport.pdf
Metropolitan Transportation Commission. Transportation 2035 Plan for the San Francisco Bay Area,
Performance Assessment Report. 2008.
http://www.mtc. ca.gov/planning/2035_plan/Supplementary/T2035Plan-Perf_AssessmentReport.pdf
Central Lane Metropolitan Planning Organization. Regional Transportation Plan. 2007.
http://docs.lcog.org/mpo/PDF/rtp/2031/2031RTP_Chaptersl-4_Nov-07Adoption_Corrected.pdf
Hillsborough County Metropolitan Planning Organization. Congestion Management System Performance
Report. 2005. http://www.hillsboroughmpo.org/pubmaps/pubmaps_folders/congestion-management-process-
its-plan/March%202006%20RCMS.pdf/view
Southwestern Pennsylvania Commission. Application Instructions: Congestion Mitigation Air Quality Program
for the 2011-2014 Transportation Improvement Program. 2009.
http://www.spcregion.org/pdf/cmaq09/SPC_CMAQ_lnstruction Package_2009.pdf
Denver Regional Council of Governments. Policy on Transportation Improvement Program Preparation,
Procedures for preparing the 2008-2013 TIP. 2007. http://www.drcog.org/documents/2008-
20130/o20TIP0/o20Policy0/o20FINAL0/o20Amended°/o2012-19-07.pdf
45 Denver Regional Council of Governments. Policy on Transportation Improvement Program Preparation,
Procedures for preparing the 2008-2013 TIP. 2007. http://www.drcog.org/documents/2008-
20130/o20TIP0/o20Policy0/o20FINAL0/o20Amended°/o2012-19-07.pdf
46 Mid-America Regional Council. Transportation Outlook 2040. 2010. http://www.marc.org/2040/
ENDNOTES
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