Legitimacy refers to the procedural fairness and lack of bias in the indicator’s development.¹

To review current practice in the context of what makes a useful indicator, this chapter covers safe and reliable access to housing, employment, health care, education, and essential services, as well as data and metrics for assessing equity with regard to health impacts and other environmental justice interests. The chapter begins with a review of commonly used equity indicators followed by an assessment of their use in transportation decision-making processes.² Because the committee identified equity outcomes for the federally recognized American Indian Tribes (AI) and Alaska Native (AN) villages as requiring special attention, the chapter reviews how tribal lands and AI/AN peoples are incorporated into prominent equity analysis tools and other data and analysis limitations.

The chapter then moves to a discussion of equity indicators, metrics, analysis, and data according to key challenges in achieving the strongest association with the desired outcomes. Topics covered include the unit of observation, spatial aggregation, observed versus modeled data, comparative and threshold analysis methods, geographic scope, and data ownership and availability. The chapter concludes with a discussion of qualitative information as an equity indicator or metric.

As used in this chapter, an equity indicator or equity metric is simply an indicator or metric used in equity analysis or used to provide an equity component to another type of analysis, such as an analysis of projects according to selection criteria. Indicator and metric are defined according to the definitions in Chapter 2 and Box 2-1.

COMMONLY USED INDICATORS AND METRICS

The committee was charged with identifying data, metrics, and analytical methods to measure and evaluate the effectiveness of surface transportation projects at addressing the transportation challenges and barriers faced by historically disadvantaged and underserved communities, areas of persistent

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¹ Cash, D., W. C. Clark, F. Alcock, N. M. Dickson, N. Eckley, and J. Jäger. 2002. “Salience, Credibility, Legitimacy and Boundaries: Linking Research, Assessment and Decision Making.” SSRN Scholarly Paper (Rochester, NY: Social Science Research Network, November 1). https://doi.org/10.2139/ssrn.372280.

² The review of equity metrics used by state DOTs and MPOs was based on presentations to the committee, commissioned research on a sample of 21 state DOTs, and a review of the literature, including two key studies: Cabello, M., M. Hyland, and N. Marantz. 2023. “From State of the Practice to State of the Art: Improving Equity Analysis in Regional Transportation Plans.” Transportation. https://doi.org/10.1007/s11116-023-10439-4; and Twaddell, H., and B. Zgoda. 2014. “Equity Analysis in Regional Transportation Planning Processes, Volume 2: Research.” TCRP Research Report 214.

poverty, and public transportation–dependent populations. Key points here are a focus on effectiveness and outcomes.

Equity and other transportation system outcomes are generally evaluated using a set of indicators. Metrics are the specific data and measurements used to operationalize indicators.³ For example, travel time to employment opportunities is a common indicator of employment accessibility. One specific metric that operationalizes this indicator is the measurement of average travel times to employment destinations over the regional roadway network using data from a travel demand model. Indicators and related metrics that MPOs and state DOTs typically use to evaluate equity with respect to surface transportation investments are discussed below. Indicators and metrics used solely for the purpose of identifying communities of concern as part of any agency’s equity analysis are excluded.

Indicator: Proximity to Infrastructure or Investments

Indicators for the proximity to transportation infrastructure or other investments are very common and relatively simple to create. The size, share, and characteristics of populations or the number and share of employment opportunities within a certain distance or travel time to mass transit facilities are commonly used infrastructure proximity metrics in transportation planning, but they are less commonly used for equity analysis. A more common practice in equity analysis is to create a map identifying areas of equity concern based on a wide range of possible criteria, tabulating the value or number of investments made in these areas, and finally, comparing these values to other areas to determine if communities of concern receive a proportional share of projects or investments. This type of mapping analysis requires very little technical expertise, readily available project data, and simple Geographic Information System (GIS) analysis. The less commonly used metrics that identify distances or travel times to infrastructure such as transit stops or high-frequency transit corridors require the use of network data (if considering network distances or travel times) and somewhat more sophisticated GIS methods or the use of a travel demand model. This

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³ Parish, R. G. 2016. Environmental Scan of Existing Domains and Indicators to Inform Development of a New Measurement Framework for Assessing the Health and Vitality of Communities. Conducted for the National Committee on Vital and Health Statistics, U.S. Department of Health and Human Services. https://www.ncvhs.hhs.gov/wp-content/uploads/2016/06/NCVHS-Indicators-Envirn-Scan_2016-06-01-FINAL.pdf.

additional computational burden may explain the popularity of the simpler approach.⁴

Indicator: Proximity to Destinations

Destination proximity indicators are relatively common in transportation planning but less used in transportation equity analysis.⁵ These indicators may also be referred to as access-to-opportunity indicators. There are many metrics used to measure proximity by distance or travel time to a wide range of destination types. Most focus on quantifying

• The number of destinations, such as jobs, that can be reached in a given travel time or distance threshold;
• The share of regional destinations that can be reached in a given travel time or distance threshold;
• The number or share of people that can reach destinations within a given travel time or distance threshold; and
• The average travel time to destinations (e.g., average commute time).

Proximity to employment is the most frequently considered destination, and travel time thresholds of 30 to 60 minutes are commonly used in estimating many employment proximity metrics. These metrics often consider travel times by automobile and transit, and sometimes walking and bicycling. It is also common to estimate average travel time to employment or other destinations using the output of regional travel demand models. Destination proximity metrics are also sometimes expressed as the ratio of travel time, number, or share of destinations reachable by mode of travel

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⁴ Cabello, M., M. Hyland, and N. Marantz. 2023. “From State of the Practice to State of the Art: Improving Equity Analysis in Regional Transportation Plans.” Transportation. https://doi.org/10.1007/s11116-023-10439-4; Twaddell, H., and B. Zgoda. 2020. “Equity Analysis in Regional Transportation Planning Processes, Volume 2: Research.” TCRP Research Report 214; Karner, A., K. Levine, L. Alcorn, M. Situ, D. Rowangould, K. Kim, and A. Kocatepe. 2022. “Accessibility Measures in Practice: A Guide for Transportation Agencies.” NCHRP Research Report 1000; ICF. 2019. “Environmental Justice Analysis in Transportation Planning and Programming: State of Practice.” Publication FHWA-HEP-19-022. Prepared by ICF for the Federal Highway Administration (FHWA).

⁵ Karner, A., K. Levine, L. Alcorn, M. Situ, D. Rowangould, K. Kim, and A. Kocatepe. 2022. “Accessibility Measures in Practice: A Guide for Transportation Agencies.” NCHRP Research Report 1000; Twaddell, H., and B. Zgoda. 2020. “Equity Analysis in Regional Transportation Planning Processes, Volume 2: Research.” TCRP Research Report 214; National Academies of Sciences, Engineering, and Medicine. 2023. Elevating Equity in Transportation Decision Making: Recommendations for Federal Competitive Grant Programs. Washington, DC: The National Academies Press. https://doi.org/10.17226/27439.

(e.g., transit versus car). These metrics are typically estimated for geographic units such as census tracts or the travel analysis zones (TAZs) used in travel demand models. Equity is evaluated by comparing areas defined as being an equity concern with other areas or with the region as a whole.⁶

Destination proximity metrics may be calculated using a variety of data and tools. The simplest methods consider the Euclidean (straight-line) distance to destinations, which is relatively straightforward to calculate with simple GIS methods, as no information about travel networks, congestion, or routing is required. More robust methods consider distances or travel time along the transportation network. These methods require more advanced GIS methods and often make use of travel demand models or other tools specifically designed for network or travel analysis.⁷ The consideration of travel time may also include delays caused by network congestion. Information about congestion and travel times can be obtained from travel demand models or traffic probe data (e.g., traffic speed data collected from sample of mobile devices).

Indicator: Proximity to Burdens

Equity indicators for proximity to transportation-related environmental burdens are less common but are sometimes used in analyses of regional transportation plans or the environmental reviews of proposed transportation projects.⁸ These equity analyses often include metrics that measure proximity to air and noise pollution sources such as major roadways or proximity to areas that experience high crash or fatality rates. A range of approaches can be used to measure proximity to transportation burdens.

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⁶ Cabello, M., M. Hyland, and N. Marantz. 2023. “From State of the Practice to State of the Art: Improving Equity Analysis in Regional Transportation Plans.” Transportation. https://doi.org/10.1007/s11116-023-10439-4; Twaddell, H., and B. Zgoda. 2020. “Equity Analysis in Regional Transportation Planning Processes, Volume 2: Research.” TCRP Research Report 214; Karner, A., K. Levine, L. Alcorn, M. Situ, D. Rowangould, K. Kim, and A. Kocatepe. 2022. “Accessibility Measures in Practice: A Guide for Transportation Agencies.” NCHRP Research Report 1000.

⁷ Cabello, M., M. Hyland, and N. Marantz. 2023. “From State of the Practice to State of the Art: Improving Equity Analysis in Regional Transportation Plans,” Transportation. https://doi.org/10.1007/s11116-023-10439-4; Twaddell, H., and B. Zgoda. 2020. “Equity Analysis in Regional Transportation Planning Processes, Volume 2: Research.” TCRP Research Report 214.

⁸ Cabello, M., M. Hyland, and N. Marantz. 2023. “From State of the Practice to State of the Art: Improving Equity Analysis in Regional Transportation Plans.” Transportation. https://doi.org/10.1007/s11116-023-10439-4; Twaddell, H., and B. Zgoda. 2020. “Equity Analysis in Regional Transportation Planning Processes, Volume 2: Research.” TCRP Research Report 214. See, for example, FHWA. 2018. “Community Impact Assessment: A Quick Reference for Transportation.” FHWA-HEP-18-055. https://www.fhwa.dot.gov/livability/cia/quick_reference/index.cfm. Accessed October 3, 2024; FHWA. n.d. “Environmental Review Toolkit.” https://www.environment.fhwa.dot.gov/env_topics/environmental_justice.aspx. Accessed October 3, 2024.

The two most common are to measure the level of burden within a geographic unit or to measure the distance between a person, household, or geographic area and the source of the burden. An example of the first approach is reporting the average ambient air pollution concentration for each census tract. An example of the second approach is the distance to the nearest high-volume roadway, which may be used as a surrogate for exposure to air pollution from roadways.

Data to measure these burdens come from observational data, modeling, and surrogates. Emissions exposure is usually derived from a combination of travel demand and air quality modeling. Surrogates such as traffic density or proximity to high-volume roads are also used for emission and noise exposure evaluations. The traffic safety data used in equity analysis are typically observed. Information about traffic crashes and related injuries and fatalities is collected by state DOTs and reported to the National Highway Traffic Safety Administration and is widely available.⁹ Crash records include details about individuals involved in crashes and factors associated with each crash along with the location and time of crashes. These data are widely used in highway safety studies and planning, but much less so in equity analysis. For more on remedying the weaknesses of traffic safety data, see Chapter 4.

Indicator: Mobility

Mobility indicators are very common in transportation planning applications but less so in equity analysis.¹⁰ Mobility metrics used in equity analysis include average travel times (e.g., in general, not to destinations), trip lengths, congestion levels (e.g., hours of delay), and average traffic speeds. The data for these metrics are typically obtained from travel demand models and are often aggregated across a time or space dimension.

Indicator: Transportation and Housing Costs

Some agencies also consider indicators that account for cost burdens in their equity analysis.¹¹ The few available examples of this include metrics

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⁹ National Highway Traffic Safety Administration (NHTSA). n.d. “Data.” https://www.nhtsa.gov/data. Accessed October 3, 2024.

¹⁰ Cabello, M., M. Hyland, and N. Marantz. 2023. “From State of the Practice to State of the Art: Improving Equity Analysis in Regional Transportation Plans.” Transportation. https://doi.org/10.1007/s11116-023-10439-4; Twaddell, H., and B. Zgoda. 2020. “Equity Analysis in Regional Transportation Planning Processes, Volume 2: Research.” TCRP Research Report 214.

¹¹ Cabello, M., M. Hyland, and N. Marantz. 2023. “From State of the Practice to State of the Art: Improving Equity Analysis in Regional Transportation Plans.” Transportation. https://doi.org/10.1007/s11116-023-10439-4.

that measure the share of household income spent on travel and housing. Housing and transportation costs are typically considered together, since these costs can amount to more than half of a household’s expenses and because there is typically an inverse relationship between housing and transportation costs, where more expensive housing is often located in areas with greater accessibility and lower travel costs.¹² The Center for Neighborhood Technology’s housing and transportation affordability index is a common source of these data, as are regional travel demand and land use models.¹³ Chapter 4 contains additional discussion of transportation and housing cost burdens.

HOW METRICS ARE USED

In addition to choosing indicators and metrics, agencies must also develop a framework for how these metrics are used to support planning decisions. Agencies must decide how to weigh different metrics when making decisions, how equity metrics are weighed against other planning and decision-making factors, and how the metrics are used to evaluate the effectiveness of past decisions. Although the review of current practice was able to identify numerous accounts of MPOs and state DOTs developing equity indicators and metrics, far less information was available that systematically documents how MPOs and state DOTs use equity metrics in planning decisions. Therefore, the following is intended to describe practices that are currently used based on a review of sources in the public domain and provided to the committee in public sessions.

Equity Metrics Used in Mapping

A common use of transportation equity metrics is to create online mapping applications that identify communities of concern. Federal agencies, including the U.S. Department of Transportation (USDOT) and the U.S. Environmental Protection Agency (EPA) have created map applications that cover the entire United States; state DOTs and MPOs have also created their own custom map applications that consider a wide range of metrics. The mapping applications used by MPOs and state DOTs typically include metrics related to being part of a historically disadvantaged and overburdened

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¹² Makarewicz, C., P. Dantzler, and A. Adkins. 2020. “Another Look at Location Affordability: Understanding the Detailed Effects of Income and Urban Form on Housing and Transportation Expenditures.” Housing Policy Debate 30(6):1033–1055. https://doi.org/10.1080/10511482.2020.1792528.

¹³ Center for Neighborhood Technology. “H+T Index.” https://htaindex.cnt.org. Accessed October 3, 2024.

population and sometimes also include metrics related to exposure to environmental burdens, mobility, accessibility, and other factors.

While access to the large array of geospatial data often included in these applications can be useful, it also presents a practical challenge in making decisions. Constructing a composite index, which represents one method to make meaning out of the variety of data sources, is a common way to enhance or simplify decision making. Composite indices are created by normalizing, weighting, and aggregating individual metrics; many then include a threshold that defines communities of concern. However, in many cases the choice of metrics appears to be guided by data availability and convenience, rather than a particular outcome. In addition, the choice of threshold values may be arbitrary. Both USDOT’s Equitable Transportation Community (ETC) Explorer and the Council on Environmental Quality’s (CEQ’s) Climate and Economic Justice Screening Tool (CEJST) for the Justice40 Initiative use composite indices to define communities of concern. The ETC defines disadvantaged communities as those above the 65th percentile when the composite index is ranked, while the CEJST uses a combination of burdens above the 90th percentile and a socioeconomic indicator (either low-income population above the 65th percentile or the level of high school–educated adults above 10%) in its definition.¹⁴ Other map applications use different thresholds, including communities that are simply above or below the regional average for a given indicator. While simplifying the identification of communities for equity analysis, composite indices combined with binary thresholds that define a community of concern raise the potential of overlooking equity concerns for individuals in communities at the margins of these definitions or who live in otherwise seemingly (from an aggregate view) well-off communities. Adding or removing individual metrics can change rankings, and some communities may lie right below or above threshold values.

An alternative approach is to create composite indices but refrain from defining threshold values. This is the approach used in EPA’s EJScreen, where multiple indices for different categories of environmental burdens, health outcomes, and vulnerabilities are provided and percentile ranked, but no threshold values are provided.¹⁵ The user must determine what constitutes a significant equity concern. A documented drawback of this approach

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¹⁴ USDOT. “ETC Explorer.” Updated December 4, 2023. https://www.transportation.gov/priorities/equity/justice40/etc-explorer; CEQ. “Climate and Economic Justice Screening Tool: About.” https://screeningtool.geoplatform.gov/en/about#3/33.47/-97.5. Accessed October 3, 2024.

¹⁵ U.S. Environmental Protection Agency (EPA). “EJScreen: Environmental Justice Screening and Mapping Tool.” Updated September 9, 2024. https://www.epa.gov/ejscreen.

is that MPOs attempting to be overly inclusive sometimes prepare watered down analyses of plan equity.¹⁶

Qualitative feedback can help identify indicators and geographic areas that reflect community concerns and intuitive understanding of inequities. Discussions with community members, advisory boards, and agency employees familiar with community needs may yield new quantitative variables and thresholds that better match how communities experience transportation inequities. In some cases, community-produced maps result in markedly different geographic definitions of disadvantaged communities than those produced by DOTs or MPOs.¹⁷ In rural areas, where geographic units of aggregation are large and where data may be sparse, community members can help identify smaller areas of disadvantage that would be otherwise be missed when relying solely on quantitative sources of information.

The use of mapping applications beyond identifying communities of concern and defining eligibility for government grants related to the Justice40 Initiative is far less clear.¹⁸ For example, the Vermont Agency of Transportation uses a mapping application for its Social Vulnerability Index (SVI).¹⁹ The map application provides census tract–level SVI scores based on 16 attributes. The SVI increases by one point for each attribute for which the tract is at or above the 90th percentile for that attribute. No thresholds are defined for the SVI and the SVI is not mentioned in any of the agency’s decision-making or planning processes. Some map applications such as ETC Explorer, CEJST, and EJScreen include data and metrics related to accessibility, environmental burdens, and public health outcomes and therefore could be used to identify transportation needs and possibly monitor outcomes. However, there are few examples of mapping applications being used in these ways. The most common use of mapping applications was in project prioritization processes that considered equity.

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¹⁶ ICF. 2019. “Environmental Justice Analysis in Transportation Planning and Programming: State of Practice.” Publication FHWA-HEP-19-022. Prepared by ICF for FHWA, Washington, DC.

¹⁷ Rowangould, D., A. Karner, and J. London. 2016. “Identifying Environmental Justice Communities for Transportation Analysis.” Transportation Research Part A: Policy and Practice 88:151–162. https://doi.org/10.1016/j.tra.2016.04.002.

¹⁸ The White House. “Justice 40: A Whole of Government Initiative” https://www.whitehouse.gov/environmentaljustice/justice40. Accessed October 3, 2024.

¹⁹ The Vermont SVI is a modification of the CDC’s SVI. Vermont Department of Health. “Social Vulnerability Index: A User’s Guide.” https://ahs-vt.maps.arcgis.com/apps/MapSeries/index.html?appid=ffea40ec90e94093b009d0ddb4a8b5c8#map. Accessed October 3, 2024.

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²⁰ Mid-Region Council of Governments (MRCOG). 2022. “Project Selection Process (PSP) Guidebook.” August. https://www.mrcog-nm.gov/DocumentCenter/View/5504/PSP-Guidebook.

²¹ “MRMPO Vulnerability Index 2020.” https://www.arcgis.com/home/item.html?id=5f52351a47564727b3554b96b13664e7. Accessed October 3, 2024.

²² MRCOG. 2022. “Project Selection Process (PSP) Guidebook.” August. https://www.mrcog-nm.gov/DocumentCenter/View/5504/PSP-Guidebook, 5. The MVI is described as a modified version of the CDC’s Social Vulnerability Index that is used to evaluate transportation impacts on social and economically vulnerable communities.

²³ “MRMPO PSP Score Sheet.” https://www.mrcog-nm.gov/DocumentCenter/View/5460/PSP-Scoresheet-PDF?bidId=. Accessed October 3, 2024.

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²⁴ MnDOT. “Project Selection.” https://www.dot.state.mn.us/projectselection/background.html. Accessed October 3, 2024.

development process, which occurs after project selection. However, when information is known about a candidate project’s impact and benefits, MnDOT incorporates these impacts and benefits as well as the geographic distribution of high-scoring candidate projects as qualitative factors in the decision to select or not select a project. For projects where MnDOT is more confident that adjacent environmental justice populations would benefit, MnDOT includes proximity to EJ population in the scoring criteria for the selection of projects, where proximity is measured as adjacent census tracts that have more than 30% EJ population in the Twin Cities metropolitan area or more than 20% in Greater Minnesota. Projects eligible for this qualitative EJ proximity analysis include the selection of urban nonfreeway/nonexpressway pavement projects; the rehabilitation and replacement of existing nonmotorized infrastructure and pedestrian bridges and underpasses; targeted safety improvements; and standalone improvements for nonmotorized transportation users. Equity metrics are also included in the scoring criteria for two specialty and competitive programs. The Clean Transportation Pilot Program awards points to projects sited in areas of environmental justice concern, and the Transportation Economic Development Program includes consideration of whether environmental justice populations will benefit from the jobs created because of a candidate project.

An example of the second approach, where expected outcomes are evaluated, is the Virginia Secretary of Transportation’s Smart Scale prioritization process.²⁵ The Smart Scale process includes one specific metric focused on equity: access to jobs for disadvantaged persons, which accounts for 20% of the overall accessibility score. “Disadvantaged population” is defined as low-income, minority, or limited English proficiency. The measure is population weighted: within each census block or block group, the change that the project provides in access to jobs within 45 minutes by driving or 60 minutes by other modes is calculated specifically for the disadvantaged population. The metric “access to jobs” uses a travel time decay function. The overall accessibility score, which is one of several criteria, is then weighted differently depending on where the project is located: in higher-density population centers, accessibility accounts for 25% of the total score, but in rural areas, accessibility accounts for only 10%. Overall, this results in the sole equity metric accounting for a maximum of 5% of the score in urban areas or 2% of the score in rural areas.

The Virginia Smart Scale prioritization process has two notable features. First, it focuses on outcomes (access to jobs) rather than inputs

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²⁵ Virginia Commonwealth Transportation Board. 2024. “Smart Scale Technical Guide.” February. https://smartscale.virginia.gov/media/smartscale/documents/508_R6_Technical-Guide_FINAL_FINAL_acc043024_PM.pdf.

(where a project is located). Second, geospatial data are used to define populations of concern rather than communities of concern. Accessibility metrics are weighed by population percentages rather than using population data to categorize geographic areas as either a community of concern or not. This is an example of a population-based metric as opposed to a place-based metric.

As demonstrated by the project prioritization processes used by MRCOG and Virginia’s Smart Scale program, the selection of transportation equity metrics and how they are used by agencies can vary widely and has a large effect on how equity is considered in project selection. The MRCOG process provides a much larger weight to equity than the Virginia Smart Scale process; however, the two processes rely on very different metrics. The MRCOG process considers equity more broadly but it largely focuses on inputs—where a project occurs—rather than outcomes and relies on place-based indicators. The Virginia Smart Scale process depends on a single access-to-employment metric which receives relatively little weight in the overall selection process; however, a strength is that it focuses on expected outcomes and uses a population-based approach.

In a few cases, community engagement is weighted alongside other equity-focused metrics in project prioritization. A community engagement–based metric measures the project sponsor’s involvement of communities of concern before and during a project’s development and typically awards points for projects providing evidence of stronger engagement methods. For example, the Mid-America Regional Council (MARC), the MPO for the bistate Kansas City region, used this type of metric in a recent call for projects under the Surface Transportation Block Grant Program. Projects that included specific techniques to engage disadvantaged population groups in a documented strategy received the most points, while less meaningful forms of involvement received fewer points. The public participation score accounted for about 4% of the overall weight for a project in the ranking process.²⁶ While metrics of the kind employed by MRCOG and Virginia Smart Scale help assess the distributional equity of projects, the metric used by MARC assesses procedural equity to ensure that priority populations have meaningful involvement in the selection and development of projects that will meet their needs.

The Transportation Equity Index (EQI) created by the California Department of Transportation (Caltrans) for use in its system investment strategy (CSIS) is another example of integrating equity into project

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²⁶ Krapp, A., J. M. Barajas, and A. Wennink. 2021. “Equity-Oriented Criteria for Project Prioritization in Regional Transportation Planning.” Transportation Research Record. March 22:03611981211001072. https://doi.org/10.1177/03611981211001072.

prioritization processes.²⁷ In early stages of implementation, the CSIS is a data-driven approach to select transportation projects consistent with California’s climate action plan. The strategy uses 11 metrics consistent with the climate action goals, two of which are focused on transportation impacts to disadvantaged groups (or priority populations), including access and traffic impacts in disadvantaged communities. The EQI uses a limited set of metrics to identify transportation priority populations. Priority populations are defined by a combination of low-income status (in accordance with definitions in state law), whether they are within tribal lands, exposure to traffic volume, exposure to traffic crashes, and multimodal access to destinations. Like the MARC example above, the CSIS selection criteria include qualitative metrics to assess each project’s level of planning, engagement, and responsiveness to feedback, as well as how well the project plan has considered climate risks and impacts to vulnerable communities.

Equity Metrics Used in Plan Evaluation

Transportation equity metrics are also used to evaluate regional transportation plans. In this application, MPOs use metrics to evaluate long-range transportation plans that consist of projects that may not have been proposed or selected based on any equity criteria. A travel demand model may be used to forecast expected outcomes. Although MPOs, and to a lesser extent state DOTs, routinely use travel demand models to evaluate the expected outcomes of their plans, evaluating the equity of accessibility outcomes (i.e., changes in proximity to destinations) does not appear to be very common.

A more common application is evaluating the distribution of investments or environmental burdens. The Federal Transit Administration recommends that grantees such as MPOs conduct a quantitative evaluation of the distributional impacts of the collection of projects in the long-range plan, for example by overlaying the geographic location of proposed investments with the areas where low-income and minority populations live, work, and play, as identified using Census and land use data.²⁸ USDOT guidance on applying the 1994 Executive Order “Federal Actions to Address Environmental Justice in Minority Populations and Low-Income Populations” to

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²⁷ Caltrans. “Caltrans Transportation Equity Index (EQI).” https://dot.ca.gov/programs/esta/race-equity/eqi; Caltrans. “Caltrans System Investment Strategy (CSIS): Public Workshop.” January 2024. https://dot.ca.gov/-/media/dot-media/programs/transportation-planning/documents/division-transportation-planning/csis/csis-deck-public-workshop-jan-2024-a11y.pdf. Accessed October 3, 2024.

²⁸ Federal Transit Administration (FTA). 2015. “Environmental Justice FAQs.” Updated December 10. https://www.transit.dot.gov/regulations-and-guidance/environmental-programs/environmental-justice/environmental-justice-faqs#ref29.

long-range plans clarifies that these plans should not create disproportionately high and adverse effects on minority or low-income populations and, further, that failure to provide a fair share of benefits may be considered an adverse effect. A similar analysis of the prioritized list of projects in the MPO TIP or state TIP is not required because it is presumed that the projects arise from a compliant plan.²⁹ In metropolitan areas, these guidelines result in equity analyses that may be cursory, relying on simple GIS-based proximity to investments indicators.³⁰ Outside of metropolitan areas, there may have been no equity analyses of programs or projects at all, because state long-range transportation plans, unlike metropolitan transportation plans, are not required to be project specific. The review found no examples of long-range plans that identified any disproportionately high and adverse impacts or strategies to minimize or mitigate such impacts.

The Metropolitan Transportation Commission (MTC), the MPO for the San Francisco Bay Area, provides one of the more comprehensive regional transportation plan equity analyses including environmental burdens along with accessibility, mobility, public health, and housing and transportation cost metrics.³¹ The metrics are disaggregated by different units depending on the metric, including income group, geography, area type, and wage level. To accomplish this, MTC uses three integrated modeling platforms: its regional activity-based travel demand model, a land use simulation model, and a regional economic impact model. These models are used to forecast outcomes from plan alternatives and the final regional transportation plan. Rather than weighting the wide range of metrics and combining them into a single score, MTC reports each score separately. To examine equity, each metric is calculated for a particular group of interest, which can be compared to the regional average.

Another example of the use of equity metrics in plan analysis is the “equity checks” used by Washington State DOT for its active transportation plan (ATP).³² Equity checks represent a parallel set of questions to ask about performance measures that ensure they apply to vulnerable communities, defined as census blocks with higher proportions than the

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²⁹ FTA. 2015. “Environmental Justice FAQs.” Updated December 10. https://www.transit.dot.gov/regulations-and-guidance/environmental-programs/environmental-justice/environmental-justice-faqs#ref30.

³⁰ ICF. 2019. “Environmental Justice Analysis in Transportation Planning and Programming: State of Practice.” Publication FHWA-HEP-19-022. Prepared by ICF for FHWA.

³¹ Association of Bay Area Governments and MTC. 2021. “Plan Bay Area 2050: Performance Report.” October. https://planbayarea.org/sites/default/files/documents/Plan_Bay_Area_2050_Performance_Report_October_2021.pdf.

³² Washington State Department of Transportation. 2021. “Washington State Active Transportation Plan: 2020 and Beyond.” https://wsdot.wa.gov/sites/default/files/2021-12/ATP-2020-and-Beyond.pdf.

state average for people in poverty, people with disabilities, and Black and Indigenous people and people of color. Within the ATP, equity checks are conducted by calculating the measures for the overall population and for specific vulnerable communities. For example, the connectivity equity check examines the percentage of bicycle and pedestrian facilities and gaps in the low traffic stress network on or near state highways in vulnerable communities. Similar checks are conducted for performance measures related to safety, opportunity, participation in active transportation, and partnerships in regional and local active transportation plans. The goal of the equity checks is to ensure that planned bicycle and pedestrian infrastructure is benefiting historically disadvantaged population groups.

With regard to simpler, proximity-based evaluations of long-range plans, an emerging practice is to divide the collection of projects into project types that have greater potential for negative impact on the adjacent community (such as road-widening projects) and less impactful project types that are more likely to be considered beneficial by the neighboring community (such as resurfacing projects). Hillsborough (Florida) Transportation Planning Organization’s (TPO’s) Environmental Justice evaluation of the TIP classifies all TIP investments into five categories (state of good repair, safety, congestion, modal choice, and major capacity projects) before evaluating whether a fair share of each type of investment falls into EJ areas.³³ While crude, this method of plan evaluation adds some nuance to the common practice of mapping a collection of projects and assuming that they are all equally desirable to the adjacent communities.³⁴

Equity Metrics Used in Project Identification, Scoping, and Development

Except for agencies applying for the limited number of Justice40 discretionary grants, the review identified very few examples of agencies following a defined process for considering equity concerns related to access to opportunities, environmental justice, or public health concerns in their initial project identification and scoping processes. In developing state transportation improvement plans, states are required to consider performance measures for the National Highway Performance Program, including pavement and bridge condition, travel time reliability, and areawide crash rates. These measures also affect local project identification as locals seek federal aid. The National Highway Performance Program and Surface Transportation Block Grant (STBG) Program, which constitute a majority of the

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³³ Hillsborough TPO. 2022. “Transportation Improvement Program: Fiscal Years 2022/23-2026/27.” https://planhillsborough.org/wp-content/uploads/2023/03/TIP-FY23-27-9-19-22.pdf.

³⁴ ICF. 2019. “Environmental Justice Analysis in Transportation Planning and Programming: State of Practice.” Publication FHWA-HEP-19-022. FHWA, Washington, DC.

FHWA funding made available to and through states, are not included in the Justice40 Initiative, with the exception of a small STBG set aside for Transportation Alternative projects. The identification of projects for funding from these programs does not require an analysis of population groups experiencing infrastructure deficiencies.

The review of practice identified a lack of information about typical practices for identifying and scoping projects. For example, in theory, projects in metropolitan areas derive from or must be coordinated with a long-range transportation plan/metropolitan transportation plan for which an environmental justice impact assessment or a more comprehensive equity analysis has been conducted. However, a national review of such MPO analyses indicates that few MPOs document how these analyses affect even the selection of projects that make up their plans. In practice, this equity analysis is likely to be conducted as a final check toward the end of drafting the long-range plan and therefore may have little effect on how the projects were initially identified or developed.³⁵

The evaluation of project alternatives during a project development process compliant with the National Environmental Policy Act (NEPA) has a more thoroughly developed practice for evaluating equity considerations. Typical measures begin with demographic analysis. For example, MnDOT uses EJScreen for greater Minnesota Districts that provide census analysis for race and poverty at the block-group level, whereas the Twin Cities metro area provides racial analysis at the block-group level using census data and poverty analysis at the block-group level using American Community Survey data for more fine-grained analysis.³⁶ The measures then quantify the differing project impacts on multimodal access and safety, emergency response, crime, community cohesion, social values, cultural changes, isolation, long-term and short-term business and employment impacts, barrier effects, aesthetics, and other considerations.³⁷ If there is a disproportionately high and adverse impact on an environmental justice population, FHWA can approve the project only if project alternatives and mitigation measures that reduce or avoid the impact are not practicable.³⁸

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³⁵ ICF. 2019. “Environmental Justice Analysis in Transportation Planning and Programming: State of Practice.” Publication FHWA-HEP-19-022. FHWA, Washington, DC.

³⁶ MnDOT. “Environmental Justice Process, Project Development.” https://dot.mn.gov/project-development/subject-guidance/environmental-justice/process.html and https://edocs-public.dot.state.mn.us/edocs_public/DMResultSet/download?docId=38616489. Accessed October 21, 2024.

³⁷ FHWA. 2018. “Community Impact Assessment: A Quick Reference for Transportation.” FHWA-HEP-18-055. https://www.fhwa.dot.gov/livability/cia/quick_reference/index.cfm.

³⁸ FHWA. “Environmental Review Toolkit.” https://www.environment.fhwa.dot.gov/env_topics/environmental_justice.aspx. Accessed October 3, 2024.

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³⁹ Sonja Piper, Active Transportation Safety Engineer, MnDOT, email communication with committee, August 23, 2024.

⁴⁰ AASHTO. 2024. “State DOTs Outline Ongoing ‘Moonshot Project’ Efforts.” https://aashtojournal.transportation.org/state-dots-outline-ongoing-moonshot-project-efforts.

⁴¹ Kaliski, J. 2024. “Collective and Individual Actions to Envision and Realize the Next Era of America’s Transportation Infrastructure.” NASTO Annual Conference, NCHRP 20-24 (138A), July 23.

⁴² Hillsborough TPO. 2023. “Hillsborough 2050 LRTP: Equity Needs Assessment.” https://planhillsborough.org/wp-content/uploads/2023/11/ENA_Neighborhood-Profile-Memo_project-development_FINAL.pdf.

disease, gaps in multimodal networks, deficiencies in state of good repair and tree canopy, exposure to severe injury crash areas, and vehicular PM_2.5 (particulate matter that is 2.5 micrometers or less in diameter) emissions. The needs assessment then used a typical community planning process to propose improvements to rectify the identified disparities. Members of the public were invited to contribute ideas, and the TPO prepared cost estimates for the proposed improvements so that these projects could be considered for inclusion in the cost-feasible long-range plan alongside projects proposed based on a more traditional vehicular level of service deficiencies.

Evaluating Outcomes and Monitoring Performance

The review of practice did not identify any examples where state DOTs or MPOs evaluate the equity of accessibility, environmental justice, and public health outcomes after a project is completed. Evaluations of existing conditions do not explicitly connect current circumstances to specific past investments. However, because mapping applications such as the ETC Explorer, CEJST, and EJScreen include data and metrics related to accessibility, environmental burdens, and public health outcomes, tracking these data and metrics over time could provide one means of evaluating outcomes and monitoring performance at a national scale.

EQUITY ANALYSIS AND AMERICAN INDIAN/ALASKA NATIVE PEOPLES AND TRIBAL GOVERNMENTS

The committee identified equity indicators and metrics for surface transportation projects and programs affecting tribal lands and/or AI/AN peoples as requiring special attention. The 574 federally recognized AI Tribes or AN entities have a complex relationship with the federal government that is defined by both dependency and sovereignty. Tribal governments have the right to define their own needs with respect to equity outcomes related to surface transportation investments. In addition, 87% of AI/AN individuals live outside of tribal lands or territory.⁴³

This section reviews the three most prominent federal equity analysis tools and their treatment of tribal lands and AI/AN peoples and concludes with a brief discussion of other data limitations.

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⁴³ Office of Minority Health, U.S. Department of Health and Human Services. “American Indian/Alaska Native Health.” https://minorityhealth.hhs.gov/american-indianalaska-native-health. Accessed September 11, 2024.

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⁴⁴ U.S. Census Bureau. 2022. “Glossary.” Last revised April 11. https://www.census.gov/programs-surveys/geography/about/glossary.html.

⁴⁵ U.S. Census Bureau. 2021. “Understanding and Using American Community Survey Data: What Users of Data for American Indians and Alaska Natives Need to Know.” https://www.census.gov/content/dam/Census/library/publications/2021/acs/acs_aian_handbook_2021.pdf.

is designated as disadvantaged. The mapping tool uses two shades of gray to designate disadvantaged status, and the darker shade of gray designates tribal lands. Second, for a specified standard census tract, the data displayed include the percentage of the tract that is tribal land as well as the tract’s status under the analysis of burdens. Therefore, it is possible to determine whether a standard census tract is designated disadvantaged because of tribal lands and/or because of burdens.

To illustrate, Figure 3-1 shows standard census tract 04019941000 as represented in the CEJST mapping tool. The tool explains that 61% of the land area of this census tract are lands of a federally recognized tribe (the dark gray), in this case the Pascua Yaqui Tribe of Arizona. The tool also shows that the entire census tract is also considered disadvantaged because of the climate, energy, health, and workforce development burdens and their intersection with their associated socioeconomic burdens.

The CEJST tool can be used to ascertain the racial makeup of a selected census tract; in this case 83% of the census tract in Figure 3-1 identifies as AI or AN. However, the tool alone cannot be used to screen multiple

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⁴⁶ “EJScreen Community Report for Block Group 040199410002.” Generated June 21, 2024. https://ejscreen.epa.gov/mapper. EJScreen does not generate a unique URL for a report.

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⁴⁷ Although the census tract numbers are the same, the land area is not identical because the CEJST is based on the 2010 census tracts and the ETC Explorer is based on the 2020 Census tracts.

⁴⁸ U.S. Commission on Civil Rights. 2018. “Broken Promises: Continuing Federal Funding Shortfall for Native Americans.” https://www.usccr.gov/files/pubs/2018/12-20-Broken-Promises.pdf.

⁴⁹ Brewer, J. P., et al. 2023. “Life and Times of Data Access: Regarding Native Lands.” Environment and Planning F 2(1–2):305–315. https://doi.org/10.1177/26349825231164616.

⁵⁰ U.S. Government Accountability Office (GAO). 2017. “Tribal Transportation: Better Data Could Improve Road Management and Inform Indian Student Attendance Strategies.” GAO-17-423. https://www.gao.gov/assets/d17423.pdf. Accessed September 25, 2024; GAO. 2024. “Tribal Transportation: Better Data Could Improve Road Management and Inform Indian Student Attendance Strategies: Recommendations Status.” GAO-17-423. https://www.gao.gov/products/gao-17-423. Accessed September 25, 2024.

⁵¹ GAO. 2022. “Tribal Funding: Actions Needed to Improve Information on Federal Funds That Benefit Native Americans.” GAO-22-104602. https://www.gao.gov/assets/d22104602.pdf.

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⁵² GAO. 2017. “Tribal Transportation: Better Data Could Improve Road Management and Inform Indian Student Attendance Strategies: Recommendations Status.” GAO-17-423. https://www.gao.gov/products/gao-17-423. Accessed September 25, 2024.

⁵³ NHTSA. 2023. “Traffic Safety Facts 2020 Data: Race and Ethnicity.” DOT HS 813 493. https://crashstats.nhtsa.dot.gov/Api/Public/ViewPublication/813493.

⁵⁴ FHWA. 2017. “Tribal Governments and Transportation Safety Data.” Submitted to Congress on May 22. https://highways.dot.gov/sites/fhwa.dot.gov/files/docs/federal-lands/tribal-transportation-program/ttp-safety/8641/2016-tribal-governments-safety-data.pdf.

⁵⁵ Section 14008, Infrastructure Investment and Jobs Act, Public Law 117-58, November 15, 2021. https://www.congress.gov/117/plaws/publ58/PLAW-117publ58.pdf.

⁵⁶ Maxim, R., G. R. Sanchez, and K. R. Huyser. 2023. “Why the Federal Government Needs to Change How It Collects Data on Native Americans.” Brookings. https://www.brookings.edu/articles/why-the-federal-government-needs-to-change-how-it-collects-data-on-native-americans.

affecting tribal government capacity.⁵⁷ There is a need for equity-related data, metrics, and tools that tribal governments can use to inform their own transportation decisions. There is also a need to improve data and analysis methods related to the equity outcomes for tribal governments and AI/AN peoples that follow transportation decisions made by federal agencies and state and local governments.

KEY CHARACTERISTICS AND CONSIDERATIONS FOR EQUITY INDICATORS AND METRICS

The ability of an indicator to evaluate the effectiveness of transportation projects in achieving more equitable outcomes relates to both the strength of its association with an outcome of interest and the characteristics of the metrics that operationalize it (e.g., level of spatial resolution and amount of uncertainty). This section discusses the key characteristics of commonly used transportation equity indicators and metrics along with their strengths and weaknesses.

Strength of Association with Outcomes

The best indicators have a direct connection to outcomes of interest. Most indicators in current use are indirectly associated with outcomes because of limitations in available data or the complexity of calculating metrics. This weakness extends to the indicators in current use for accessibility and environmental burdens.

The main purpose of transportation is to provide access to destinations. Access can be improved by making it easier and faster to research desirable destinations. Generally speaking, the ease of access can be improved through land use and economic development strategies that result in desirable destinations being closer to where people (and firms) are located. Reducing the distance to destinations can reduce travel time and cost and

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⁵⁷ The federal government directly provided all transportation infrastructure and services on tribal lands until 1991, when federal law allowed tribal governments to exercise self-determination for transportation planning and programming for what is now called the Tribal Transportation Program (TTP). However, the federal government did not allow tribal governments to elect to exercise full self-determination over surface transportation on tribal lands until 2004. To date, 135 of the 574 federally recognized tribes have taken over responsibility for their share of the TTP. These tribal governments form Tribal Departments of Transportation whose activities are subject to “stewardship and oversight” by FHWA through its Office of Tribal Transportation. Federal law for tribal self-determination for transportation is at 23 USC § 202 and the implementing regulations are at 25 CFR Part 170; Kitchel, K. 2015. “A New Era Is Dawning.” Public Roads November/December. https://highways.dot.gov/public-roads/novemberdecember-2015/new-era-dawning; FHWA. “Office of Tribal Transportation.” https://highways.dot.gov/federal-lands/tribal. Accessed September 23, 2024.

increase the feasibility, exposure risk, and cost effectiveness of alternative travel modes, including walking, bicycling, and public transit. Removing barriers to travel, including barriers to people with disabilities, is another strategy for increasing access by making it easier to reach destinations. Increasing mobility, or how fast you can travel across the transportation network, can also increase access to destinations by reducing travel times. Mobility strategies often focus on congestion relief or increasing the speed of vehicle traffic, for example, by building a limited-access highway or bus-only lanes where higher-speed travel can be achieved.

Destination proximity indicators and metrics have a relatively strong association with accessibility outcomes. There are many destination proximity metrics in use, but they all provide a measure of how close, in travel time or distance, a person, household, or area is to destinations. However, destination proximity indicators have several limitations and challenges. An important limitation is that destination proximity metrics that are commonly used do not measure the actual travel experience of individuals or their ability to reach desired destinations.⁵⁸ Information about actual travel experiences could reveal that some individuals need to travel farther than a particular threshold to access what they need or that some modes of access are not available to them due to disability, cost, safety concerns, or other factors. Many destination proximity metrics are also limited to specific types of destinations. Proximity to employment is by far the most common, with proximity to other destinations such as school, health care, natural amenities, and food being far less common.⁵⁹ The focus on employment or a small subset of destinations provides an incomplete picture of access to what people may need or want, which likely varies from person to person and among households. For example, closer proximity to employment says little about transportation equity for people who do not work because they are retired or who work remotely. Furthermore, not all destinations of a particular type are equally desirable to all people. For example, the nearest grocery store may not sell the type of food desired. Even data on actual trips taken can provide an incomplete picture of access because there may be latent demand for trips that are

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⁵⁸ National Academies of Sciences, Engineering, and Medicine. 2023. Elevating Equity in Transportation Decision Making: Recommendations for Federal Competitive Grant Programs. Washington, DC: The National Academies Press. https://doi.org/10.17226/27439.

⁵⁹ Cabello, M., M. Hyland, and N. Marantz. 2023. “From State of the Practice to State of the Art: Improving Equity Analysis in Regional Transportation Plans.” Transportation. https://doi.org/10.1007/s11116-023-10439-4; Twaddell, H., and B. Zgoda 2020. “Equity Analysis in Regional Transportation Planning Processes, Volume 2: Research.” TCRP Research Report 214.

currently suppressed, for example, because of a lack of safe and reliable transportation.⁶⁰

When used to evaluate how accessibility changes with the addition of a new project, destination proximity metrics provide a method for estimating project outcomes and evaluating the associated equity implications. As place-based metrics, they still face limitations in understanding how a project is likely to impact access for different population groups and individuals within a defined area. The complexity of measuring accessibility, which generally requires the use of a travel demand model, also presents a barrier to their wider use.⁶¹ As discussed in Chapter 4, new web-based services offer some simplified approaches for agencies lacking the required technical expertise or resources.

Mobility indicators generally have a weaker association with accessibility outcomes than destination proximity indicators.⁶² How much and how quickly a person travels by itself does not provide information on the ability to reach specific destinations. A mobility metric that is associated with travel to a destination (e.g., travel time to employment) is an accessibility metric. However, when a mobility metric is not associated with a destination (e.g., hours of delay or average traffic speed) the association of the metric with accessibility outcomes is much weaker. Relying on mobility indicators to guide transportation planning or project decisions may also reduce accessibility overall to the extent that increasing mobility (i.e., speed) enables housing and destinations to spread over a larger area, thus increasing the distance (and eventually the travel time) to destinations.

Indicators focused on proximity to infrastructure and transportation investments are among the most common in transportation equity analysis but have relatively weak associations with accessibility or burdens. A typical example is number of residents within a fixed distance of a rail station or a bus stop. These indicators focus on project inputs and outputs, rather than outcomes, and therefore have limited value in evaluating the effectiveness of projects causing changes in accessibility or addressing environmental burdens. The use of these indicators often leads to incorrectly associating access

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⁶⁰ Ferenchak, N. N., and W. E. Marshall. 2019. “Suppressed Child Pedestrian and Bicycle Trips as an Indicator of Safety: Adopting a Proactive Safety Approach.” Transportation Research Part A: Policy and Practice 124:128–144. https://doi.org/10.1016/j.tra.2019.03.010.

⁶¹ Sun, Y., D. Olaru, C. Bright. G. McCarney, T. W. Reed, S. Sabri, Y. Chen, S. Amirebrahimi, S. Biermann, and A. Rajabifard. 2023. “Making Accessibility Accessible: A Flexible Planning Tool for Enhanced Urban Analytics.” Research in Transportation Business & Management 51:101042. https://doi.org/10.1016/j.rtbm.2023.101042.

⁶² Boisjoly, G., and A. M. El-Geneidy. 2017. “How to Get There? A Critical Assessment of Accessibility Objectives and Indicators in Metropolitan Transportation Plans.” Transport Policy 55:38–50. https://doi.org/10.1016/j.tranpol.2016.12.011; Handy, S. 2020. “Is Accessibility an Idea Whose Time Has Finally Come?” Transportation Research Part D: Transport and Environment 83:102319. https://doi.org/10.1016/j.trd.2020.102319.

to transportation infrastructure with access to destinations.⁶³ For example, living near a bus route that does not connect to where you work does not provide access to employment. Similarly, evaluations that use infrastructure and investment proximity metrics may ignore the potential for projects to burden adjacent neighborhoods. For example, living near a new limited-access highway that cuts through your neighborhood may not benefit you, and it may increase your exposure to higher concentrations of air pollution from vehicle emissions. Infrastructure and investment proximity indicators often also lack information about infrastructure or service quality that is important when considering access, such as the cost and reliability of transit service or how the infrastructure affects safety.⁶⁴

While metrics for evaluating exposure to environmental burdens attributable to transportation are relatively well developed and widely used in project-level environmental analysis such as that required by NEPA and similar state environmental regulations, existing literature suggests they are not commonly used by MPOs and DOTs in transportation equity analysis. Metrics that are commonly used often consider proximity to vehicle traffic as a surrogate for exposure to vehicle emissions and noise. Modeled concentrations of traffic emissions and traffic crash rates summarized by geographic area are sometimes also used. Surrogate methods based on proximity to traffic are supported by a large body of research linking living in close proximity to major traffic sources with both higher exposure to air pollution and a wide range of negative health outcomes.⁶⁵ Even so, it is also important to recognize that people are exposed to environmental burdens

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⁶³ Cabello, M., M. Hyland, and N. Marantz. 2023. “From State of the Practice to State of the Art: Improving Equity Analysis in Regional Transportation Plans.” Transportation. https://doi.org/10.1007/s11116-023-10439-4; Karner, A., K. Levine, L. Alcorn, M. Situ, D. Rowangould, K. Kim, and A. Kocatepe. 2022. “Accessibility Measures in Practice: A Guide for Transportation Agencies.” NCHRP Research Report 1000; National Academies of Sciences, Engineering, and Medicine. 2023. Elevating Equity in Transportation Decision Making: Recommendations for Federal Competitive Grant Programs. Washington, DC: The National Academies Press. https://doi.org/10.17226/27439.

⁶⁴ National Academies of Sciences, Engineering, and Medicine. 2023. Elevating Equity in Transportation Decision Making: Recommendations for Federal Competitive Grant Programs. Washington, DC: The National Academies Press. https://doi.org/10.17226/27439.

⁶⁵ Karner, A. A., D. S. Eisinger, and D. A. Niemeier. 2010. “Near-Roadway Air Quality: Synthesizing the Findings from Real-World Data,” Environmental Science & Technology 44(14):5334–5344. https://doi.org/10.1021/es100008x; Health Effects Institute. 2010. “Traffic-Related Air Pollution: A Critical Review of the Literature on Emissions, Exposure, and Health Effects.” Special Report 17. https://www.healtheffects.org/system/files/SR17TrafficReview.pdf; Health Effects Institute. 2023. “Systematic Review and Meta-Analysis of Selected Health Effects of Long-Term Exposure to Traffic-Related Air Pollution.” Special Report 23. Updated April 5. https://www.healtheffects.org/system/files/hei-special-report-23_6.pdf; Askariyeah, M. H., J. Zietsman, and R. Autenrieth. 2020. “Traffic Contribution to PM2.5 Increment in the Near-Road Environment.” Atmospheric Environment 224:117113. https://doi.org/10.1016/j.atmosenv.2019.117113.

in multiple places as they travel and spend time in different locations.⁶⁶ Few studies in practice or research settings consider how exposure to environmental burdens from transportation are accumulated over time and space as a person participates in various activities. Household proximity to high-crash-rate locations is a common method for evaluating equity with regard to traffic safety thanks to widely available and spatially detailed crash data; however, as is the case with exposure to vehicle emissions, a limitation is that these metrics do not capture risks encountered in the various places that people engage in different activities.

Transportation and housing cost burden indicators provide a holistic assessment of the combined effects of housing affordability and the value of proximity of residential locations to other important destinations. Because housing and transportation reflect the two largest categories of household spending and because they are generally related, cost burden indicators can help identify economic vulnerability for low-income households. These indicators are increasingly being used for identification of vulnerable neighborhoods. However, if transportation and housing cost burdens are calculated for only an average or typical household in a geographic area, they may mask variation due to individual household characteristics like income, vehicle access, and participation in subsidized housing programs.

Unit of Observation

An important aim of transportation equity is ensuring that benefits and burdens do not disproportionately accrue to persons or population groups. However, the units of observation for most metrics are geographic areas or population groups that pose certain limitations in evaluating the distribution of benefits and burdens.

Place-based metrics are the most common. They describe accessibility, burdens, or other outcomes associated with a particular geographic area or a specific location. Examples are the travel time by walking to the nearest school from a particular neighborhood or the air pollution concentration at a specific location. Although place-based metrics can be highly granular, they do not describe the outcomes of individuals (or individual households) or of populations defined by characteristics other than geography, which presents several limitations when considering equity.

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⁶⁶ Tayarani, M., and G. Rowangould 2020. “Estimating Exposure to Fine Particulate Matter Emissions from Vehicle Traffic: Exposure Misclassification and Daily Activity Patterns in a Large, Sprawling Region.” Environmental Research 182:108999. https://doi.org/10.1016/j.envres.2019.108999.

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⁶⁷ Cabello, M., M. Hyland, and N. Marantz. 2023. “From State of the Practice to State of the Art: Improving Equity Analysis in Regional Transportation Plans.” Transportation. https://doi.org/10.1007/s11116-023-10439-4.

⁶⁸ National Academies of Sciences, Engineering, and Medicine. 2024. Constructing Valid Geospatial Tools for Environmental Justice. Washington, DC: The National Academies Press. https://doi.org/10.17226/27317.

⁶⁹ National Academies of Sciences, Engineering, and Medicine. 2023. Elevating Equity in Transportation Decision Making: Recommendations for Federal Competitive Grant Programs. Washington, DC: The National Academies Press. https://doi.org/10.17226/27439; Rowangould, D., A. Karner, and J. London. 2016. “Identifying Environmental Justice Communities for Transportation Analysis.” Transportation Research Part A: Policy and Practice 88:151–162. https://doi.org/10.1016/j.tra.2016.04.002.

in an affordable housing development located in an otherwise affluent census tract).

Individual or household-level metrics are the smallest possible units of observation. These metrics describe outcomes at the person or household level such as the travel time to work for a specific individual. They avoid the limitations of place- and population-based metrics because outcome data are tied directly to individual characteristics and circumstances. It is therefore possible to understand intersectional issues and the heterogeneity of outcomes faced by different people and populations. Individual and household-level data are generally obtained from survey data and therefore represent a sample of the population. They may not be collected on a consistent basis and may be limited to specific geographic areas where surveys are fielded. Individual-level travel metrics may also be collected from passively generated source data (e.g., mobile phone or GPS data), though in many cases the individual socioeconomic and demographic characteristics are modeled rather than observed. The additional effort required to collect individual-level data also adds to their costs, which may present additional barriers to their use.

Spatial Aggregation

Whether placed based or individual, most metrics are aggregated over a geographic area. Indicators reported at a smaller geographic scale, such as the neighborhood, are generally more useful than those reported at a larger scale.⁷⁰ Many metrics are reported for census tracts or a travel demand model’s TAZ, which is often similar in size to census tracts or block groups. Although individual-level data records are maintained, detailed location information is often replaced with a more aggregate geographic description. For example, surveys such as the National Household Travel Survey provide individual-level travel and socioeconomic data, but do not provide detailed information on the location of the individual’s home or travel destinations without special permission. In many cases, place-based data are available with greater spatial granularity while individual data are often provided over a larger geographic area. This is typically because of policies protecting the privacy of these relatively small samples of the population.

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⁷⁰ Pineo, H., K. Glonti, H. Rutter, N. Zimmermann, P. Wilkinson, and M. Davies. 2020. “Use of Urban Health Indicator Tools by Built Environment Policy- and Decision-Makers: A Systematic Review and Narrative Synthesis.” Journal of Urban Health 97(3):418–435. https://doi.org/10.1007/s11524-019-00378-w; Rodgers, K. 2023. “The Use and Influence of Health Indicators in Municipal Transportation Plans.” Doctoral dissertation, Portland State University.

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⁷¹ Cabello, M., M. Hyland, and N. Marantz. 2023. “From State of the Practice to State of the Art: Improving Equity Analysis in Regional Transportation Plans.” Transportation. https://doi.org/10.1007/s11116-023-10439-4.

⁷² Cabello, M., M. Hyland, and N. Marantz. 2023. “From State of the Practice to State of the Art: Improving Equity Analysis in Regional Transportation Plans.” Transportation. https://doi.org/10.1007/s11116-023-10439-4; Karner, A., K. Levine, L. Alcorn, M. Situ, D. Rowangould, K. Kim, and A. Kocatepe. 2022. “Accessibility Measures in Practice: A Guide for Transportation Agencies.” NCHRP Research Report 1000.

⁷³ Cabello, M., M. Hyland, and N. Marantz. 2023. “From State of the Practice to State of the Art: Improving Equity Analysis in Regional Transportation Plans.” Transportation. https://doi.org/10.1007/s11116-023-10439-4; Twaddell, H., and B. Zgoda. 2020. “Equity Analysis in Regional Transportation Planning Processes, Volume 2: Research.” TCRP Research Report 214.

The output of activity-based models includes information about trips made by each individual along with their socioeconomic characteristics, which enables the possibility of detailed, intersectional output metrics for different places and populations.

Travel demand models can be used to evaluate changes in placed-based or individual-level accessibility. Demand models can go further to also forecast how the trips people make are likely to change with respect to travel time, distance, cost, route, and mode. Demand models can also evaluate how a collection of projects and policies interacts within a region to affect accessibility and other outcomes. Although most MPOs use travel demand models to evaluate their regional transportation plans, the review of practice suggests that few use standard model outputs for the accessibility outcomes of disadvantaged groups and, perhaps as a result, TDMs are not commonly used to evaluate equity outcomes with respect to accessibility. Furthermore, because only some state DOTs have TDMs, many smaller communities and rural areas outside of metropolitan areas are left with little or no means to forecast the accessibility outcomes of proposed projects.

Comparative and Threshold Methods

There are two common definitions of what may constitute an equitable outcome. One definition is concerned with the relative distribution of an outcome. For example, an equitable outcome is achieved when everyone can access health care of the same quality when they need it or when everyone experiences the same air quality. This is generally referred to as an egalitarian definition. A second definition is concerned with achieving an acceptable or defined level of an outcome. For example, an equitable outcome is achieved when everyone can access quality health care within 45 minutes of their home or when no one is exposed to air quality that exceeds regulatory limits. This is generally referred to as a sufficientarian definition.⁷⁴

Many of the metrics evaluated for this study align with one of these two equity concepts. For example, some agencies use metrics to compare outcomes in communities of concern to the broader region. More equitable outcomes are indicated when disparities between communities are minimized. This comparative approach is aligned with an egalitarian concept of equity. In other cases, thresholds or targets may be set. For example, agencies set a target that the concentration of air pollution meets regulatory standards or that communities have access to employment within a certain travel time threshold. More equitable outcomes are indicated by progress toward these thresholds or targets, rather than closing gaps in outcomes

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⁷⁴ Karner, A., R. H. M. Pereira, and S. Farber. 2024. “Advances and Pitfalls in Measuring Transportation Equity.” Transportation. https://doi.org/10.1007/s11116-023-10460-7.

between communities. This approach is aligned with a sufficientarian concept of equity.

Egalitarian concepts of equity that use comparative metrics have the advantage that they do not require setting thresholds and therefore defining what is a desirable or acceptable level of access or burden. On the other hand, a sufficientarian approach to equity can ensure that at least minimally desirable or safe outcomes are achieved, which is not guaranteed under an egalitarian definition. For example, everyone can have equally bad air quality. In practice, agencies should consider both concepts when addressing equity; however, the metrics they use may not be suitable to both approaches to equity.

There is no consensus on which measures are most appropriate for equity analysis under an egalitarian or sufficientarian approach. Scholarship on the distributional effects of transportation has used inequality measures familiar in economic analyses such as the Gini, Palma, Theil, Atkinson, and concentration indices, as well as comparative ratios, absolute differences, and composite indices.⁷⁵ Each serves a certain purpose but may not be appropriate in all circumstances. For example, the Gini index measures the overall inequality across the population, an important point to know from a systems-level perspective, but it is unable to account for key egalitarian considerations such as between-group inequalities or weighting by socioeconomic status.⁷⁶ The sufficientarian approach requires a baseline threshold that is considered “sufficient” or “adequate” for the being measured. Sufficiency is a normative value that cannot be defined without reference to community priorities and needs and political considerations determined through a deliberative process.⁷⁷ Using universal guidelines to establish thresholds risks appearing arbitrary and can exclude groups or people from inclusion if they fall just below the threshold value.

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⁷⁵ van Wee, B., and N. Mouter. 2021. “Evaluating Transport Equity.” Chapter 5 in Advances in Transport Policy and Planning (Vol. 7, pp. 103–126). New Methods, Reflections and Application Domains in Transport Appraisal, edited by N. Mouter. Academic Press. https://doi.org/10.1016/bs.atpp.2020.08.002.

⁷⁶ Karner, A., R. H. M. Pereira, and S. Farber. 2024. “Advances and Pitfalls in Measuring Transportation Equity.” Transportation. https://doi.org/10.1007/s11116-023-10460-7.

⁷⁷ Martens, K., J. Bastiaanssen, and K. Lucas. 2019. “Measuring Transport Equity: Key Components, Framings and Metrics.” In Measuring Transport Equity (pp. 13–36), edited by K. Lucas, K. Martens, F. Di Ciommo, and A. Dupont-Kieffer. Elsevier. https://doi.org/10.1016/B978-0-12-814818-1.00002-0; Sheller, M. 2018. “Theorising Mobility Justice.” Tempo Social 30(2):17–34. https://doi.org/10.11606/0103-2070.ts.2018.142763.

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⁷⁸ Mahajan, V., N. Kuehnel, A. Intzevidou, G. Cantelmo, R. Moeckel, and C. Antoniou. 2022. “Data to the People: A Review of Public and Proprietary Data for Transport Models.” Transport Reviews 42(4):415–440. https://doi.org/10.1080/01441647.2021.1977414.

In research on the municipal use of indicators in transportation plans, the time lag associated with data collection and reporting was cited as a key barrier to indicator usability.⁷⁹

USING QUALITATIVE INFORMATION AS AN INDICATOR OR METRIC

Qualitative data supplement quantitative data by providing context and filling in information gaps. Quantitative metrics, such as accessibility, miles of bicycle lanes, and concentrations of particulate matter, offer measures that can be replicated across different geographies or contexts, provided the methodology for calculating them is known. In transportation decision making, quantitative measures typically provide the “what”; however, they do not provide information about why such quantitative patterns exist. Although quantitative measures can serve as numerical benchmarks upon which to assess equity, they only sparingly offer insights into how diverse individuals experience the transportation system in different ways, the diverse purposes of transportation beyond getting from point A to point B, the multidimensional nature of transportation barriers, or how transportation facilitates community and social connection.⁸⁰

Prominent mobility justice advocates have called for the transportation profession to more highly value community-based data.⁸¹ In addition, a recent National Academies report called for sustained community dialog to improve understanding of lived experiences.⁸² A metropolitan planning organization could, for example, set a policy to increase service to improve access to grocery stores via public transit within 30 minutes. Such a quantitative measure would be conceptually simple to estimate and to benchmark.

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⁷⁹ Rodgers, K. 2023. “The Use and Influence of Health Indicators in Municipal Transportation Plans.” Doctoral dissertation, Portland State University.

⁸⁰ Lowe, K., and K. Mosby. 2016. “The Conceptual Mismatch: A Qualitative Analysis of Transportation Costs and Stressors for Low-Income Adults.” Transport Policy 49:1–8. https://doi.org/10.1016/j.tranpol.2016.03.009; Kent, J. L. 2022. “The Case for Qualitative Methods in Transport Research.” Australasian Transport Research Forum. https://australasiantransportresearchforum.org.au/wp-content/uploads/2022/05/ATRF2022_Resubmission_48.pdf; Purifoye, G. Y., and D. R. Brooms. 2020. “Transit Affinities: The Distinctiveness of Black Social Interactions on Public Transportation,” Du Bois Review: Social Science Research on Race 17(2):389–410. https://doi.org/10.1017/S1742058X2000017X.

⁸¹ Untokening Collective. 2017. “Untokening 1.0—Principles of Mobility Justice.” November 11. http://www.untokening.org/updates/2017/11/11/untokening-10-principles-of-mobility-justice.

⁸² National Academies of Sciences, Engineering, and Medicine. 2024. Constructing Valid Geospatial Tools for Environmental Justice. Washington, DC: The National Academies Press. https://doi.org/10.17226/27317; see also Linovski, O., H. Dorries, and S.-A. Simpson. 2021. “Public Transit and Equity-Deserving Groups: Understanding Lived Experiences.” University of Manitoba. https://mspace.lib.umanitoba.ca/items/c4be3abb-a7eb-4ed4-9ee0-0bebe939b451.

However, without qualitative data, it could be difficult to understand how people would experience such changes in transit service. Certain communities could prioritize access to culturally relevant grocery stores; others could feel unsafe boarding certain transit stops or riding certain vehicles because of neighborhood environments or their previous experiences riding public transit. In these cases, the numeric value of access may not match the lived version of access. Such factors point to the importance of contextualizing quantitative metrics with qualitative data, drawing on the lived experience of individuals and community members to identify ways that the quantitative data may not capture the full transportation experience.⁸³

Qualitative data are also important in understanding unmet travel needs and why those needs are unmet. Travel surveys capture realized travel behavior, but typically do not gather data on trips that are difficult to make or not made. Low-income groups and other socioeconomically disadvantaged groups often make complex adaptations to travel barriers that would be hard to capture efficiently in a survey.⁸⁴ Similarly, barriers, needs, and adaptations vary markedly across social groups in ways that do not easily reduce to a set of metrics.⁸⁵ In this way, unrealized travel is a latent demand that is difficult to quantify, yet represents many of the problems that equity-focused investments in transportation are trying to solve.⁸⁶ Qualitative data help contextualize and describe the multiple purposes of transportation.

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⁸³ Vigar, G. 2017. “The Four Knowledges of Transport Planning: Enacting a More Communicative, Trans-Disciplinary Policy and Decision-Making.” Transport Policy 58:39–45. https://doi.org/10.1016/j.tranpol.2017.04.013; Lowe, K., J. Barajas, and C. Coren. 2023. “‘It’s Annoying, Confusing, and It’s Irritating’: Lived Expertise for Epistemic Justice and Understanding Inequitable Accessibility.” Journal of Transport Geography 106:103504. https://doi.org/10.1016/j.jtrangeo.2022.103504.

⁸⁴ Lovejoy, K., and S. Handy. 2011. “Social Networks as a Source of Private-Vehicle Transportation: The Practice of Getting Rides and Borrowing Vehicles Among Mexican Immigrants in California.” Transportation Research Part A: Policy and Practice 45(4):248–257. https://doi.org/10.1016/j.tra.2011.01.007; Blumenberg, E., and A. Weinstein Agrawal. 2014. “Getting Around When You’re Just Getting By: Transportation Survival Strategies of the Poor.” Journal of Poverty 18(4):355–378. https://doi.org/10.1080/10875549.2014.951905.

⁸⁵ Barajas, J. M. 2020. “Supplemental Infrastructure: How Community Networks and Immigrant Identity Influence Cycling.” Transportation 47(3):1251–1274. https://doi.org/10.1007/s11116-018-9955-7; Fan, Y., G. Greenberg, N. Panchai, M. Wilson, C. Luna, J. Amrhein, S. Benda, Y. Song, and X. Zeng. 2023. “Centering the Margins: The Transportation Experience of Underserved Communities.” MN 2023-32, MnDOT. August. https://cts-d8resmod-prd.oit.umn.edu/pdf/mndot-2023-32.pdf.

⁸⁶ Ward, C., and D. Walsh. 2023. “‘I Just Don’t Go Nowhere’: How Transportation Disadvantage Reinforces Social Exclusion.” Journal of Transport Geography 110:103627. https://doi.org/10.1016/j.jtrangeo.2023.103627.

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⁸⁷ USDOT. 2023. Promising Practices for Meaningful Public Involvement in Transportation Decision-Making. Updated November. https://www.transportation.gov/sites/dot.gov/files/2023-11/Promising%20Practices%20for%20Meaningful%20Public%20Involvement_2023Update_FINAL.pdf.

⁸⁸ Arnstein, S. R. 1969. “A Ladder of Citizen Participation.” Journal of the American Institute of Planners 35(4):216–224. https://doi.org/10.1080/01944366908977225; USDOT. 2023. “Promising Practices for Meaningful Public Involvement in Transportation Decision-Making.” Updated November. https://www.transportation.gov/sites/dot.gov/files/2023-11/Promising%20Practices%20for%20Meaningful%20Public%20Involvement_2023Update_FINAL.pdf.

⁸⁹ National Academies of Sciences, Engineering, and Medicine. 2019. NCHRP Research Report 905: Measuring the Effectiveness of Public Involvement in Transportation Planning and Project Development. Transportation Research Board, Washington, DC. https://doi.org/10.17226/25447.

of the population at large creates a benchmark. However, what constitutes a significant difference in engagement has not been defined. For example, the Hillsborough TPO includes, in its biennial Public Participation Measures of Effectiveness Report, the percentage of meetings that the TPO hosted or participated in that were held in environmental justice areas.⁹⁰

Equity in the effectiveness of input looks at whether and how feedback received from underserved population groups affects the agency’s decision making. This requires documenting how public input shaped and affected the final form of transportation plans and projects and, further, documents how input from specific demographic groups was addressed. In situations with competing interests, the effectiveness of input can be derived from an analysis of whether underserved populations benefit from transportation plans at the same rate as the general population.

Public participation can be used to shape the metrics used to make transportation decisions. One method is in deriving community-based equity metrics and priorities. Surveys led by transportation agencies versus equity-focused community groups have been shown to produce differing community priorities.⁹¹ Another example is using participatory mapping or crowdsourced GIS data to identify important locations for infrastructure provision, safety improvements, or other purposes. For example, participatory mapping methods have been used to identify community-derived locations for bicycle sharing docks and sites for pedestrian and bicycle safety improvement.⁹² The more

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⁹⁰ Environmental Justice areas in Hillsborough County are census tracts one standard deviation above the county’s median in concentration of one or more of the following characteristics: low income, race, and ethnicity. Hillsborough TPO. 2022. “Public Participation Plan Measures of Effectiveness Report: Two-Year Public Engagement Evaluation for 2020 & 2021.” May 11. https://planhillsborough.org/wp-content/uploads/2023/04/Measures-of-effectiveness-Report-FINAL-051122.pdf.

⁹¹ Linovski, O., and D. M. Baker. 2023. “Community-Designed Participation: Lessons for Equitable Engagement in Transportation Planning.” Transportation Research Record 2677(6):172–181. https://doi.org/10.1177/03611981221145131.

⁹² Griffin, G. P., and J. Jiao. 2019. “Crowdsourcing Bike Share Station Locations: Evaluating Participation and Placement.” Journal of the American Planning Association 85(1):35–48. https://doi.org/10.1080/01944363.2018.1476174; Griffin, G. P., and J. Jiao. 2019. “The Geography and Equity of Crowdsourced Public Participation for Active Transportation Planning.” Transportation Research Record 2673(1):460–468. https://doi.org/10.1177/0361198118823498; Barajas, J. M., K. M. Beck, J. F. Cooper, A. Lopez, and A. Reynosa. 2019. “How Effective Are Community Pedestrian Safety Training Workshops? Short-Term Findings from a Program in California.” Journal of Transport & Health 12:183–194. https://doi.org/10.1016/j.jth.2019.01.002; Nelson, T., C. Ferster, K. Laberee, D. Fuller, and M. Winters. 2021. “Crowdsourced Data for Bicycling Research and Practice.” Transport Reviews 41(1):97–114. https://doi.org/10.1080/01441647.2020.1806943.

“community oriented” the public involvement process is, the more likely it is to lead to more equitable and just outcomes.⁹³

Qualitative approaches in the public participation process via focus groups, small group discussions, and interviews may provide rich insight into community needs and policy preferences overlooked or not understood by planners, decision makers, and others who may be outsiders to a community.⁹⁴ Such approaches have been used to validate findings of a study of community needs among the population with disabilities, identify proper alternatives to credit card payments for shared mobility services, and determine the mix of services available in a new mobility hub co-located at affordable housing residences.⁹⁵

Qualitative Metrics

Outside of public engagement, the review found a handful of examples of using qualitative data in transportation decision making. The Illinois Department of Transportation uses a simple qualitative checklist as part of a broader process for project review.⁹⁶ The checklist was designed to help determine whether a project would be required to undergo a complete community impact assessment during the environmental review process. The checklist requires the project sponsors to identify the degree to which major businesses and employers in the area serve or employ marginalized or vulnerable groups, whether there would be significant impacts to community facilities, the degree to which the project would displace businesses or residents or catalyze gentrification, and the degree to which there would be complex community impacts. The checklist is meant to supplement

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⁹³ Karner, A., J. London, D. Rowangould, and K. Manaugh. 2020. “From Transportation Equity to Transportation Justice: Within, Through, and Beyond the State.” Journal of Planning Literature 35(4):440–459. https://doi.org/10.1177/0885412220927691.

⁹⁴ USDOT. 2023. “Promising Practices for Meaningful Public Involvement in Transportation Decision-Making.” Updated November. https://www.transportation.gov/sites/dot.gov/files/2023-11/Promising%20Practices%20for%20Meaningful%20Public%20Involvement_2023Update_FINAL.pdf.

⁹⁵ King County Mobility Coalition. 2021. “King County Community Transportation Needs Assessment.” https://irp-cdn.multiscreensite.com/c86a044e/files/uploaded/KCMC%20Community%20Transportation%20Needs%20Assessment.pdf; Golub, A., V. Satterfield, M. Serritella, J. Singh, and S. Phillips. 2019. “Assessing the Barriers to Equity in Smart Mobility Systems: A Case Study of Portland, Oregon.” Case Studies on Transport Policy 7(4):689–697. https://doi.org/10.1016/j.cstp.2019.10.002; TransForm. 2020. “Car Sharing and Mobility Hubs in Affordable Housing Pilot Project: Community Transportation Needs Assessment Process, Results, and Lessons Learned.” https://www.transformca.org/wp-content/uploads/2024/06/community-transportation_needs_assessment.pdf.

⁹⁶ Barajas, J. M., L. M. Braun, A. Merck, B. Dean, P. Esling, and H. Persaud. 2022. “The State of Practice in Community Impact Assessment.” FHWA-ICT-22-011. Illinois Center for Transportation.

the quantitative description of the community in terms of socioeconomic characteristics, housing vulnerability, and transportation access. As part of its Advancing Transportation Equity Initiative, MnDOT engaged in a Community Conversations project, which is a series of conversations between MnDOT staff and individuals and organizations who work with and represent underserved communities in Minnesota. Started in 2018, the intent of these conversations is to learn directly from underserved communities about their unique experiences and challenges with transportation. MnDOT conducts interviews with nonprofit, government, transit, education, tribal, and other partners to understand the transportation needs for underserved and underrepresented communities, and then documents the findings so they can be used to inform the agency’s transportation funding, planning, and programming efforts. Conversations have been completed in all seven Greater Minnesota Districts; a similar but separate process is expected for the Metro District.⁹⁷

Another important use for qualitative data is to develop metrics that account for unusual needs that are important to consider for equity purposes but are not likely to be accounted for by methods that gather the average or majority perspectives, even among vulnerable populations. For example, engagement with older adults as part of the Better Bus Plan, produced by the Massachusetts Bay Transportation Authority and the Massachusetts Department of Transportation, identified fare vending machines as a barrier in accessing the transit system, because this group preferred a retail option as a more comfortable way to pay fares. Similarly, outreach conducted by other transit agencies has identified safety and comfort as transit needs, though these metrics are difficult to quantify using standard service quality metrics.⁹⁸

Qualitative data can help generate different quantitative metrics or validate metrics used in practice. For example, researchers working in support of MnDOT conducted a workshop and focus groups with interested parties from the public, community organizations, and department staff to identify equity-focused performance measures for the department.⁹⁹ These workshops yielded numerous observations about proposed performance measures that called for additional data collection, more spatial granularity

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⁹⁷ MnDOT. “Advancing Transportation Equity Initiative.” https://www.dot.state.mn.us/planning/program/advancing-transportation-equity/community-conversations.html. Accessed November 23, 2024.

⁹⁸ Transit Center 2021. “Equity in Practice: A Guidebook for Transit Agencies.” https://transitcenter.org/wp-content/uploads/2021/09/Equity-in-Practice_web.pdf.

⁹⁹ Elgart, Z., T. Hansen, I. Sener, J. Cardenas, B. Ettelman, and A. Mahmoudzadeh. 2023. “Qualitative and Quantitative Analysis to Advance Transportation.” MN 2023-14, MnDOT. https://rosap.ntl.bts.gov/view/dot/67847.

in data, and development of additional metrics related to transportation outcomes, among others.

CHAPTER SUMMARY

This review of commonly used indicators and metrics was divided between those addressing accessibility (or access to destinations) and those addressing public health and environmental burdens. The review also performed a critical assessment of what makes a useful metric, aimed at achieving more equitable long-term outcomes.

For access to housing, employment, health care, and education, the review found that the metrics in use that are most aligned with these societal outcomes are proximity-to-destinations metrics (i.e., access-to-opportunity metrics). However, state DOTs and MPOs typically analyze just proximity to employment via automobile or mass transit and use these metrics in general transportation planning rather than for transportation equity analysis. Proximity-to-transportation infrastructure metrics, which are output metrics, are still in widespread use for equity analysis that is part of assessing project or program impact.

Proximity-to-transportation infrastructure metrics are also still in widespread use for equity analysis related to public health and environmental burdens. In some cases, proximity-to-infrastructure metrics may be an adequate surrogate for such burdens. However, it is possible and, in some cases, preferable to measure actual exposure—such as to air pollution or traffic crashes—with observational data or modeling.

For equity metrics to influence societal outcomes, they must be integrated meaningfully into transportation decision-making processes. Among the state DOTs and MPOs taking such steps, the most common use of equity metrics is to identify and map disadvantaged areas or communities of concern. Some state DOTs and MPOs also use equity metrics as part of at least some of their project prioritization and selection processes. Types of equity metrics used in project prioritization and selection processes include transportation output metrics, transportation outcome metrics, and community engagement metrics. Fewer examples were available of state DOTS or MPOs using equity metrics as part of plan-level evaluation, project identification and development outside of NEPA processes, or postproject evaluation of outcomes and performance.

For tribal governments and AI/AN peoples, there are significant limitations to current federal equity analysis tools, which is part of a larger problem of poor or incomplete data. There is a need for equity-related data, metrics, and tools that tribal governments as well as federal agencies, state departments of transportation, and local governments can use to inform their transportation decisions affecting tribal lands and AI/AN peoples.

The process used to develop and refine the needed data, metrics, and tools should recognize tribal sovereignty and self-determination.

As informed by causal chain analysis, the best metrics for equity are those that accurately measure and strongly align the transportation input, output, and outcome, with the long-term outcome resulting in a more equitable society. Using this rubric for best metric, key findings from the review are as follows.

Individual-based metrics, because they allow greater understanding of intersectional issues, are preferred over population-based and place-based metrics. Place-based metrics can be particularly problematic because they may fail to identify disparate outcomes faced by different populations within the geographic unit.

Metrics reported at smaller geographic scales tend to be more useful to equity analysis than those at larger geographic scales. Smaller geographic scales can compensate for some of the disadvantages of place-based metrics.

Metrics using data produced by appropriately frequent collection and timely reporting will be required for some critical uses such as system monitoring.

The cost of data can pose a significant barrier to developing appropriate equity metrics in less well-resourced states and MPOs. To improve the metrics—adopting individual-based or population-based metrics and using data that are more frequently collected and reported at smaller geographic scales—will increase costs. The cost of data is an important consideration for developing analysis capacity that is equitable across governments and agencies of differing capabilities.

The use of composite indices of multiple metrics for identifying and selecting communities of concern can result in arbitrary, inaccurate, and inconsistent designations. Vetting of the metrics and composite indices by the affected communities is one way to address these problems.

To assess project and program effectiveness for communities of concern requires forecasting models capable of assessing the expected transportation outcome of proposed projects for the specified communities. Observational data are not sufficient.

Because quantitative metrics will have gaps and limitations no matter how well they are constructed and measured, qualitative data or information is necessary to gain a more complete picture of a community’s priorities and desired outcomes. This includes their input on the types of quantitative metrics that best represent their relevant contexts.