Accessibility Measures in Practice: A Guide for Transportation Agencies (2022)

Below is the uncorrected machine-read text of this chapter, intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text of each book. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

6 Accessibility measures, concepts, data sources, analysis methods, and application areas vary widely across regions. This variation is partly due to the different resources and capacities of agencies and the unique needs of different locations and planning contexts. However, in many cases, this variation also reflects the gap between the state of the art and standard practice. This gap arises, at least in part, because accessibility measurement is dynamic and often difficult to translate into easily digestible measures. Data and methodological advances offer oppor- tunities to improve and expand accessibility measurement so that measures better reflect the experiences of residents and the transportation and land use conditions they face. At the same time, analysts should proceed thoughtfully, as measures that are misinterpreted or fail to capture what was intended can be misleading. This chapter outlines types of accessibility measures, provides examples of accessibility measure- ment in practice, discusses the challenges and gaps that agencies face when applying accessibility concepts, and describes where accessibility measurement is heading in the future. 2.1 Types of Accessibility Measures Integrating accessibility into transportation planning is not as simple as identifying a single measure that can be used by all agencies in all application areas. Academic research has identi- fied a wide range of accessibility measures that vary dramatically in terms of their interpret- ability, data requirements, multimodalism, and relevance to different areas of transportation planning and decision-making. The research team identified nine types of accessibility measures with different mathematical formulations, data requirements, and outputs. Each reflects a different approach to operational- izing accessibility, but conceptually they all measure how easily opportunities can be reached. Each measure can be formulated in many different ways depending on a user’s needs. Most of the measures identified are appropriate for calculating both baseline accessibility conditions and the impacts of planned changes in transportation and land use. The types of accessibility mea- sures are presented in Table 1 with short descriptions and examples and subsequently described in more detail. Additional real-world examples of commonly used measure types are included in Appendix A. 2.1.1 Proximity (to the transportation network) The simplest accessibility measures are based on proximity to transportation infrastructure such as highways, transit stops, or bicycle paths. Proximity measures represent transportation C H A P T E R 2 Accessibility Measurement Principles and Practices

Accessibility Measurement Principles and Practices 7   infrastructure as the primary “opportunity,” or destination, of interest. They can use any appli- cable travel cost, or impedance, such as distance or travel time, and can be estimated in any geographic unit (e.g., census tract, block, etc.). Proximity can be estimated as the number of opportunities within a given proximity (e.g., the number of highway access points within 1  mile of census tract centroids) or the proximity of the nearest n opportunities (e.g., walk time to the nearest high-frequency transit stop). Proximity can also be evaluated as the share or total number of people experiencing a given level of proximity (e.g., the share of the region’s low-income popu- lation living within ¼ mile of a transit station). The map shown in Figure 4 illustrates the ¼-mile buffer areas around transit stations in Columbus, Ohio. The buffer zone can be used to identify areas that are within ¼ mile of transit stations or can be combined with population data to estimate the share of residents living within the buffer area. Accessibility measure types Description Example measures Proximity (to the transportation network) How close is transportation infrastructure? • Number of highway access points within 1 mile of census block centroids • Walk time to the nearest high-frequency transit stop • Share of the low-income population that lives within ¼ mile of a transit station Access to Opportunities (cumulative opportunities and gravity measures) How many destinations can be reached, or how quickly can destinations be reached? • Number of jobs reachable within 30 minutes by car • Number of parks reachable within 15 minutes by bicycle • Time-weighted grocery stores reachable (gravity measure) • Transit travel time to the nearest three grocery stores • Transit fare (dollar cost) to reach the nearest hospital Competitive How does competition from others affect access? • Time-weighted number of jobs reachable divided by the time-weighted number of job seekers that can reach those same jobs, estimated using automobile and transit travel times • Number of primary care physicians per person (potential patient) in a floating catchment area defined using automobile travel times Trip Characteristics How easily can people travel to destinations? • Average automobile commute travel time (based on observed travel data, e.g., American Community Survey) • Wait time and in-vehicle time on public transit (modeled) • Number of transfers required to get to work for travelers without access to a personal vehicle • Weekly travel cost (dollars) of commute Potential Path Areas Where can I go given my destination, time, mode, and socioeconomic constraints? • Total number of grocery facilities accessible to someone with a car, a 9:00 am to 5:00 pm job, responsibilities for picking up and dropping off children, and a 90-minute travel-time budget Logsums What value do people derive from available choices? • The value of all possible mode-destination combinations for a transit- dependent, low-income household traveling to work Conceptual Conceptual representation of accessibility • Including accessibility concept in discussions; may include a score or rank determined based on practitioner assessment and/or discussions with stakeholders Qualitative Qualitatively determined accessibility score or rank • Accessibility score or rank based on qualitative data collection (e.g., survey of traveler perceptions, focus groups, participatory mapping, or other evaluation of public or expert perspectives assessed with qualitative data) Other Other types of measures or novel combinations • Combinations of listed measure types into a single index • Other original measures Table 1. Nine types of accessibility measures with examples.

8 Accessibility Measures in Practice: A Guide for Transportation Agencies As one of the simplest types of accessibility measures, proximity measures have some limitations. Access to opportunities can be very low even with good proximity to transportation infrastructure if the infrastructure is connected to a limited number of destinations or destinations of limited use. Fundamentally, proximity measures are designed to capture the ease of reaching transportation infrastructure rather than the ability of that infrastructure to connect to destinations. One way to overcome this limitation is by limiting the proximity analysis to high-quality infrastructure, such as high-frequency transit stops or transit stops that are directly connected to job centers. In some cases, proximity measures do not reflect some travelers’ mode options. For example, measures of proximity to automobile infrastructure are not a good indication of accessibility for people who do not have access to a vehicle. Additionally, there may be characteristics of the trans- portation system that affect travelers’ experiences that are not captured by these measures. These include feelings of safety that are affected by lighting or police presence or physical ability to use the system that may be affected by sidewalk widths and the presence of curb cuts. 2.1.2 Access to Opportunities Measures of access to opportunities are commonly found in both academic research and trans- portation planning practice. Typically, these measures quantify the number of opportunities that can be reached from origin locations within a travel cost threshold. A typical example of a region- wide measure assesses the average number of jobs reachable from all census tracts in a region within a 30-minute public transit trip weighted by the population living within each census tract. This measure can also be estimated for each origin location rather than population-weighted to understand how accessibility varies across a region (see Figure 5). It can be designed to capture different types of destinations and travel modes. The number of destinations can also be weighted so that closer opportunities have a greater impact on the calculated measure. In contrast to measures of the total number of opportunities available, access-to-opportunities measures sometimes assess the minimum time required to reach one or more destinations. An Source: Franklin County Auditor, Esri, HERE, Garmin, INCREMENT P, USGS, EPA Map image is the intellectual property of Esri and is used herein under license. Copyright 2020 Esri and its licensors. All rights reserved. Figure 4. Map of Columbus, Ohio, highlighting ¼-mile network distances around transit stops.

Accessibility Measurement Principles and Practices 9   example of the latter type of measure is travel time to the nearest hospital by car. When access to more options indicates greater opportunity, as with access to jobs, summing total destinations would likely be more desirable. However, when only one or a few destinations are desirable, such as a grocery store, assessing minimum travel times is preferred. Access to more opportunities and shorter travel times to destinations are generally posi- tive outcomes that capture the concept of accessibility. These outcomes will be consistent with greater trip-chaining ease. However, like proximity measures, measures of access to opportuni- ties can be misleading if they do not reflect a traveler’s available mode options, fail to capture the effects of transportation network quality on the ability to reach destinations, or do not use destinations that are well suited to a traveler’s needs. Historically, the data used to estimate measures of access to opportunities were obtained from outputs of regional travel demand models and MPO-maintained land use information. However, other data on multimodal travel times and costs and land use are now publicly avail- able, making measuring access to opportunities feasible for more types of organizations and a support in more decision-making contexts. 2.1.3 Competitive Competitive accessibility measures are similar to measures of access to opportunities, except that in addition to capturing the opportunities that can be reached from a given location they also account for other travelers who are trying to reach the same opportunities (2). Figure 5. Number of jobs reachable within a 30-minute drive in the Austin-Round Rock-San Marcos, Texas, region (green and yellow shading indicate the fewest jobs reachable, orange shading indicates more jobs reachable, and red shading indicates the most jobs reachable) (1).

10 Accessibility Measures in Practice: A Guide for Transportation Agencies These measures are most useful for calculating accessibility to opportunities whose consump- tion or use would make them unavailable to others, such as employment or healthcare. With an appropriately specified competitive measure, the access presented by locations with apparently high accessibility is diminished if other travelers desire and can easily access the same locations. Examples of competitive accessibility measures include the time-weighted number of jobs accessible by car divided by the time-weighted number of job seekers who can reach the same jobs or the number of primary care physicians per person in a floating catchment area defined by automobile travel time. When formulating competitive accessibility measures, travel using different modes can be considered individually or combined into a single indicator. Most commonly, public transit and automobile accessibility are assessed in combination. For example, Figure 6 shows a competitive measure of access to jobs that accounts for both automobile and transit travel times. In principle, nonmotorized competition from cyclists and pedestrians could also be included, but would likely represent a small fraction of the overall competition in all but the densest metropolitan regions in the United States. The limitations of competitive accessibility measures are similar to those of measures of access to opportunities in that they may not reflect travelers’ mode options, the quality of transporta- tion infrastructure, or other factors that affect travelers’ experiences and desire to reach specific destinations. Figure 6. Map of competitive access to jobs in Toronto, Canada, estimated using automobile and transit travel times. Greater access to jobs when accounting for the number of job seekers is indicated by darker blue shading (3).

Accessibility Measurement Principles and Practices 11   2.1.4 Trip Characteristics Trip characteristics are accessibility measures based on individual trips that people actually make or are expected to make. Travel times, costs, number of transfers, or other impedance measures can be used to evaluate trip characteristics. These impedances can be estimated using revealed (observed) or modeled travel behavior data. Trip characteristics are accessibility measures because they quantify the ease with which des- tinations can be reached; all else being equal, lower impedance means greater accessibility. These measures quantify the characteristics of a single trip, in contrast to other commonly employed accessibility measures, which quantify access to all possible trips within a certain mode/opportunity category. Examples of measures of trip characteristics include average automobile commute travel time, wait time on public transit, number of transfers to reach work for zero-car households, and the weekly travel cost of a commute. Table 2 presents an example of a trip characteristics assess- ment that evaluates morning peak-period trips under different scenarios. Measures of trip characteristics differ from more common accessibility measures in that they provide an indicator of accessibility as actually experienced by people rather than representing accessibility as the opportunities available from a specific place. This approach overcomes many of the limitations of other accessibility measures that do not reflect travelers’ actual experiences and the difficult-to-quantify factors that impede travel. For example, the differences between high- and low-income transportation system users and their respective commute modes and travel times can be illustrated. At the same time, the revealed behavior in measures of trip char- acteristics may not match actual travel demand since demand may be suppressed (or unmet) at the individual level because of constraints such as residential location, income, mandatory activity locations, and travel options. Further, it is sometimes difficult to determine whether the magni- tude of a trip characteristic is “good” or “bad.” Increasing travel distances can be good if it allows people to engage in desired activities, but bad if it is a result of a lack of options. This ambiguity is important but can be thoughtfully addressed by determining appropriate criteria to home in on groups of interest. It has long been understood that some public transit users have no option but to use public transit while others freely choose it. Other work has differ- entiated between car-less (constrained) and car-free (choice) households. It may be misleading to group all zero-vehicle households or all public transit users together when calculating perfor- mance measures, but with care, relevant groups can be identified and their trip characteristics can be assessed. 2.1.5 Potential Path Areas Measures of potential path area capture the set of possible opportunities a person can reach given their available travel modes, travel-time budget, and destination locations. A potential path area tracks an individual’s position in both space and time throughout the day for a given set of space and time constraints. Well-developed approaches for analyzing the related concepts Table 2. Trip characteristics during morning peak period (6:00–9:00 am) for all transportation analysis zones (TAZs) and environmental justice (EJ) TAZs (4).

12 Accessibility Measures in Practice: A Guide for Transportation Agencies of potential path areas and activity spaces, or space-time prisms, have been widely applied to accessibility measurement. Figure 7 shows a theoretical space-time prism in the upper right. The space-time prism encom- passes all intermediate locations in space (shown along the x and y axes) and time (shown along the vertical axis) that an individual can reach given their constraints, including mandatory origin and destination locations, travel-time budget, and activity time (time spent at intermediate desti- nations). The two-dimensional projection of the space-time prism shown below the prism in the x-y plane is the potential path area, which represents the area in space that encompasses all possible intermediate locations that a traveler could reach without violating their constraints. The map on the left side of the figure shows an example of the potential path area for a transit traveler in Toronto, Ontario, with a given origin and destination, a travel-time budget of 90 min- utes, and variable (< and ≥ 30 minutes) mandatory activity time. This potential path area might represent a transit traveler leaving home from the orange point (origin) to go to work at the green point (destination). The traveler has 90 minutes to reach work and needs to run an errand (such as shopping, dropping children off, or stopping by the post office) on the way. If the errand will take less than 30 minutes, the traveler can reach the locations shown in blue. If the errand will take more than 30 minutes, they can reach a smaller range of locations (shown in purple). In this example, the area of possible locations is the potential path area. Figure 7. Potential path area illustrating the intermediate locations that a transit traveler moving from the origin to the destination can reach given a travel-time budget of 90 minutes and variable activity times spent at the intermediate location (5).

Accessibility Measurement Principles and Practices 13   Because they are derived from the reality of individual travel needs, potential path areas capture how trip chaining affects accessibility. However, as with most of the more common accessibility measures, measures of potential path area may not reflect the quality of transportation infrastruc- ture or other factors that affect travelers’ experiences and their ability to reach destinations. 2.1.6 Logsums A logsum represents the value that people derive from the choices that are available to them. It can be represented in raw form or converted to a dollar amount and indicates the ease of reaching destinations. Figure 8 shows the distribution (as a smoothed frequency plot) of the monetized change in logsums that would result from a change in travel cost for different populations of travelers. Logsums are one of the most theoretically appealing approaches to accessibility measurement because they capture the value of many different destinations and travel options in one measure. They can be estimated using information embedded within travel demand models. Specifically, the denominator of choice models that take a multinomial logit form can be interpreted as a measure of accessibility. This denominator is known as a logsum because it is the logarithm of the sum of utility associated with all available alternatives (including all destinations and all travel modes available to an individual). Because of this formulation, logsums consider only the characteristics of available modes and desired destinations. If data are available describing other traveler characteristics that might affect accessibility, these can also be included in the logsum and reflected in the accessibility results. Logsums can be obtained from components of travel demand models including mode choice, location choice, destination choice, or any category of models that consider joint decisions (e.g., joint location-mode choice models). Logsum measures can be derived from traditional trans- portation demand models or more complex activity-based models. Like other modeled accessibility measures discussed above, logsums are limited by the under- lying assumptions and data. They capture the infrastructure characteristics and behaviors that are represented in the travel demand model. These models may not include characteristics of transportation systems that affect a traveler’s ability to reach destinations (e.g., unmeasured aspects of infrastructure quality and social and political barriers to travel, among others). Different formulations of the underlying models can also lead to differences in the results. Figure 8. Distribution of monetized change in the logsum that is expected to result from a reduction in travel cost for automobile and transit modes for low- and high-income travelers in the San Francisco Bay area (6).

14 Accessibility Measures in Practice: A Guide for Transportation Agencies 2.1.7 Conceptual When it is impossible or undesirable to estimate quantitative accessibility measures directly, it may still be worthwhile to consider the accessibility implications of different alternatives. Agencies with limited capacity still have to make transportation planning and programming decisions. They could infuse accessibility principles into their processes by thinking about and discussing how a decision is likely to affect accessibility outcomes. Fiscal constraints often necessitate prioritizing projects to receive available funding. Even if detailed quantitative accessibility analyses cannot be performed to support such prioritization, projects can be rated on the extent to which they would enhance or degrade accessibility for different travel modes. These ratings can subsequently be used in the decision-making process. For example: • While roadway expansion projects are likely to improve access by automobile in the short run, they may degrade walking and bicycling access by making it less convenient or comfortable. • Road diets can increase accessibility for walking, bicycling, and public transit, while they may degrade automobile accessibility. • Land use changes that increase density may degrade automobile congestion while increasing overall multimodal accessibility because more destinations are reachable within a short time. • Converting a general-purpose travel lane to a bus-only lane may reduce automobile acces- sibility while it increases transit accessibility. One example that demonstrates the value of conceptual measures is provided by the Florida Department of Transportation (FDOT). Using proprietary tools, FDOT categorized neighbor- hoods within its District 5 into different traveler personas based on personal values, life stages, and socioeconomic characteristics. Each traveler persona is presented in the form of a relatable narrative. At a public meeting, FDOT engaged with the public and other stakeholders to consider transportation values and needs for each persona, with their geographic context, costs, flex- ibility, and travel behavior in mind. Examples of personas discussed at the meeting are shown in Figure 9. This type of representation can be used to highlight each type of traveler’s current and future accessibility experiences in the existing transportation and land use system or under various future planning scenarios. Figure 9. Two examples of traveler personas in FDOT District 5 based on Esri Tapestry Data (7).

Accessibility Measurement Principles and Practices 15   2.1.8 Qualitative Many contextual factors that are difficult to measure affect an individual’s accessibility experi- ence. When these factors are important to capture, qualitative data collection is likely to be neces- sary. All travel modes have many unmeasured factors that can affect accessibility conditions. Often data capturing these factors are not available or are difficult to collect or obtain. These factors can include (but are not limited to): • Driving: pavement conditions, winter road maintenance, reliability, parking availability. • Public transit: crowding, vehicle or stop/station amenities, passenger comfort, ambient tem- perature and air quality, physical accessibility, police presence, driver or passenger attitudes, risk of assault or harassment at stops or on vehicles, first- and last-mile characteristics. • Bicycling: presence or absence of bicycle facilities, driver awareness and courtesy, ambient temperature and air quality, grade, repair facilities, presence of other cyclists, police presence, risk of assault or harassment, winter road maintenance, pavement condition. • Walking: sidewalk condition and presence of obstructions, presence of curb cuts, police pres- ence, ambient temperature and air quality, urban design features, grade, presence of other pedestrians, risk of assault or harassment, winter road maintenance. Each of these contextual factors can in turn affect a person’s perceived accessibility. For example, contextual factors can affect a person’s feelings of comfort or safety while traveling, affecting their perception of access. In some cases, the effect of contextual factors on a traveler’s experi- ence is a function of their identity or past experiences. For example, the risk of harassment on transit may be higher for female, genderqueer, or gender-nonconforming transit riders, and concerns about harassment may be greater for transit riders who have previously experienced harassment. In principle, these contextual factors and their effects on travelers’ perceptions and experi- ences can be evaluated and incorporated into impedance estimates but, in practice, this is rarely done. This stems in part from the fundamentally different measurement units inherent in tra- ditional impedance measures (e.g., travel time and cost) and those required to capture other qualitative characteristics. One example of a qualitative accessibility measurement tool designed to capture people’s percep- tions and experiences of accessibility is the Qualitative Pedestrian Environments Data (QPED) Toolkit developed by researchers at the University of Arizona. The QPED Toolkit can be used to generate qualitative information about pedestrians’ experiences using short interviews with pedestrians. One study employed the QPED Toolkit to examine differences in perceptions of walkability in predominantly Mexican-American and non-Hispanic white neighborhoods in Tucson, Arizona (8). Figure 10 shows that general perceptions of walkability did not differ much between the two neighborhoods, except for the sense of safety when walking in the evening. Other results demonstrated that those walking in Mexican-American neighborhoods were more likely to cite available destinations and elements of the social environment as positives. Pedes- trians in non-Hispanic white neighborhoods were more likely to cite calm/quiet and aesthetics. These qualitative differences could be captured in accessibility metrics applied in tandem across different contexts. 2.1.9 Other In addition to the accessibility measures described here, agencies and other stakeholders may experiment with new measures or other combinations not previously imagined. These measures could be geared toward capturing elements of the other measures that appear to be missing or inadequate. For example, weighted accessibility indices or combined measures can bring together different types of accessibility or different elements of a traveler’s experience into a single

16 Accessibility Measures in Practice: A Guide for Transportation Agencies measure. If different mode-specific measures are combined, weights could account for observed mode shares, trip counts by mode, or population-weighted mode availability. Measures designed to better capture travelers’ experiences could weight trip components as needed, for example by weighting out-of-vehicle time more heavily than in-vehicle time when assessing transit accessibility. 2.1.10 Conclusion Possible accessibility measures are numerous, and different measures capture different aspects of individual experiences and system-level performance. It is likely that efforts that take care to match analysis needs with specific measurement approaches and experiment with alternative formulations will yield more meaningful results than those that rely upon a single measure defined in advance. 2.2 Common Uses for Accessibility Measures Many state DOTs, MPOs, and transit agencies use accessibility measures in public-facing and internal analyses. Many others have expressed interest in using such measures in the future. The measures employed by agencies are almost always based on either proximity or access to oppor- tunities. Some agencies also use their travel demand models to summarize trip characteristics, although measures of trip characteristics are generally not interpreted as accessibility and are instead typically presented alongside traditional transportation performance measures associ- ated with delay and congestion. Travel forecasting procedures that include choice models can produce logsums that can be used to estimate the accessibility effects of a proposed transportation investment. However, more technically demanding measures (e.g., logsums, competitive measures, and potential path areas) are rarely presented to the public. Agencies commonly use accessibility measurement in a wide range of transportation plan- ning applications, as described in the following. 2.2.1 Corridor Planning Accessibility measures can capture the transportation benefits of both motorized and non- motorized travel modes. Practitioners reported that accessibility measures tell a more complete Figure 10. Differences in the perception of walking environments in predominantly Mexican-American and non-Hispanic white neighborhoods in Tucson, Arizona. Note **refers to the results of a statistically significant t-test (p < 0.05) (8).

Accessibility Measurement Principles and Practices 17   and personalized story of conditions at the corridor level than mobility-related measures, such as level of service or travel-time savings. Accessibility can be used to demonstrate the benefits of public transit, walking, and cycling modes during corridor planning efforts. 2.2.2 Project Prioritization and Selection The concept of accessibility captures the fundamental benefit of transportation systems and can be used to identify projects that improve transportation system outcomes. Project prioritiza- tion and selection can include accessibility among the measures used in an evaluation. The expected performance of a project is reflected in these measures, which can be combined to facilitate comparisons among alternatives using multicriteria analysis. 2.2.3 Equity Analysis Equity analysis generally includes evaluating the distribution of transportation burdens and benefits across populations and space. Equity analysis can also be used to capture quality-of-life and transportation-justice goals. Practitioners often cite equity analysis requirements related to Title VI of the Civil Rights Act of 1964 and/or environmental justice (EJ) regulations as motivating factors for computing accessibility measures. Equity analyses can evaluate existing gaps and defi- ciencies, or they can be used to look at the effects of proposed system changes. 2.2.4 Transit Planning Accessibility measures can capture the effects of land use and public transit level of service on the ability of transit travelers to reach destinations. Accordingly, accessibility measures are often used to support transit-related decision-making. Observed or projected ridership provides an important measure of system use but says little about the opportunities the transit system provides. Both ridership and accessibility should be evaluated simultaneously. 2.2.5 Long-Range Planning and Scenario Performance Analysis Accessibility measures can be used in many ways to support long-range planning: to track changes in systemwide performance, identify needs, and model potential land use and transporta- tion scenarios. Again, accessibility measures can provide different insights than congestion- and mobility-focused measures. 2.2.6 Nonmotorized Planning Accessibility measures can capture transportation system outcomes related to walking and bicycling. These modes are also relevant to public transit trips and often serve the first and last mile. Highway level-of-service and travel-time savings are largely irrelevant to nonmotorized planning. These measures may worsen in response to nonmotorized improvements as acces- sibility increases. The ability to capture transportation system outcomes related to walking and bicycling has been highlighted as particularly important in several regions with multimodal regional transportation goals. 2.3 Implementation Challenges and Gaps Three types of gaps reflect barriers to broader and more meaningful application of accessibility concepts and measures at transportation agencies across the United States: conceptual gaps, data gaps, and implementation gaps. These gaps can all be remedied with attention to detail and thoughtful analysis choices.

18 Accessibility Measures in Practice: A Guide for Transportation Agencies 2.3.1 Conceptual Gaps Multiple conceptual gaps need to be addressed to ensure that accessibility measures capture important dimensions of traveler experiences and foster broader public acceptance and com- prehension. These gaps include • Misunderstanding accessibility as mobility. • Narrowly focusing accessibility measures on network and location characteristics. • Difficulty characterizing unmet travel needs or missed trips. • Limited consideration of virtual access. • Challenges applying accessibility measures across different contexts. 2.3.1.1 Misunderstanding Accessibility as Mobility Accessibility is sometimes included as one of many measures that improves when congestion is mitigated. Because local jurisdictions control land use, transportation agencies often lack land use professionals. This absence often results in a singular focus on accessibility’s transportation-related elements rather than a view that encompasses both its transportation and land use components. Accessibility measures are unique in quantifying the relationships between land use and trans- portation systems by accounting for opportunity density and travel speed. While accessibility can be improved through congestion mitigation, accessibility measures provide an opportunity to communicate the fundamental objective of transportation systems—connecting people to opportunities they value. Accessibility measures can also capture transportation system benefits for drivers, transit users, cyclists, and pedestrians. Remedy → Focus on accessibility changes that arise from shifts in land use or from enhancing public transit, walking, and cycling level of service. 2.3.1.2 Narrowly Focusing Accessibility Measures on Network and Location Characteristics Accessibility descriptions and measures often emphasize the location of people, destinations, and infrastructure but rarely include social and historical factors or unique traveler experiences that can affect accessibility. For example, accessibility measures rarely address the needs of people with disabilities or differences in people’s perceptions of safety as they relate to collision risk, crime, concerns about over policing, and harassment. In general, capturing the relationship between travelers and the characteristics of opportunities at destinations can render accessibility mea- sures more meaningful. For example, measures can consider the match between job seekers and the education and skills demanded by particular employment opportunities or the relationship between prices charged at grocery stores and traveler income. Remedy → Match accessibility measures to specific people or groups and seek to incorporate key elements of their travel experience into the analysis. 2.3.1.3 Difficulty Characterizing Unmet Travel Needs or Missed Trips Many commonly used accessibility measures focus on quantifying available opportunities (e.g., access to opportunities). If these measures indicate low accessibility, residents are likely to experience unmet travel needs. Nonetheless, even residents in high-accessibility locations can experience unmet needs if they cannot travel to apparently available opportunities because the opportunities are not suitable for them or they face other barriers, like mode availability. From this perspective, it is important to understand trips that people actually make, for example by using trip characteristics. At the same time, measures of actual travel on their own also do not capture unmet needs. Hybrid approaches to accessibility measurement can combine information about

Accessibility Measurement Principles and Practices 19   opportunity and actual travel to better address unmet needs; modeled scenarios can be used that show how travel changes when barriers are eased. For example, insights from measures of trip characteristics and access to opportunities can be combined to identify populations with high access and low mobility who may have unmet travel needs. Logsum measures are also based on information about actual travel and opportunities for travel. Remedy → Combine information about revealed (observed) behavior and available opportunities to understand how unmet needs may affect individual experiences of accessibility. 2.3.1.4 Limited Consideration of Virtual Access Virtual accessibility, or the ability to access opportunities without traveling, and broadband access are becoming increasingly important as nearly all daily activities either require or can be facilitated using the internet. Although virtual accessibility varies widely across the country— and some communities lack access because of “virtual redlining”—it is understudied in the academic literature and is rarely considered in practice. Further, the ability to take advantage of virtual accessibility by telecommuting, ordering food and consumer goods for delivery, or undertaking leisure activities online is likely to vary substantially by socioeconomic status and profession. Remedy → Understand how virtual access affects accessibility by including appropriate questions on regional or statewide travel and activity surveys. 2.3.1.5 Challenges Applying Accessibility Measures Across Different Contexts Rural land use conditions can render commonly employed accessibility measures less mean- ingful than they would be otherwise. For example, accessibility to total jobs is likely to be low in rural areas compared to urban areas, regardless of transportation and land use interventions. In any context, it is important to ensure that the measures used are tied to the region’s context and objectives. This can be particularly challenging—but not impossible—in rural areas. In some rural areas, it may be important to distinguish between access to jobs in urban areas and access to non-work destinations in smaller communities. Remedy → Ensure that applications of accessibility measures are tailored to and reflect local context and needs. 2.3.2 Data Gaps The ability to measure accessibility often depends on the available data. Higher-quality data can improve measure accuracy or open up analytical possibilities, but they are often unavailable or expensive. This gap is particularly acute for nonmotorized data; comprehensive pedestrian and cyclist travel and network information are difficult to obtain. Similarly, the challenges of capturing unique traveler experiences that affect accessibility perceptions can stem from a lack of readily available data. Real-time data on public transit arrivals can be used to assess how reli- ability affects accessibility, but reliability data standards and availability are inconsistent across the country. Although mobile device tracking data are sometimes used to generate detailed information about transportation systems, these data are better suited for capturing traffic char- acteristics (such as travel speed or delay) than travel behavior or trip characteristics because they are not representative of all travelers and may not include socioeconomic information. Imperfect data are not necessarily a barrier to accessibility measurement. When data are unavailable or insufficient, an analyst may collect new data, improve existing data, use data from a similar region, assess accessibility qualitatively or conceptually, and/or communicate data

20 Accessibility Measures in Practice: A Guide for Transportation Agencies shortcomings when interpreting results. A lack of data should not preclude the consideration of accessibility in transportation decision-making. Remedy → Understand the limitations associated with existing data sources, but do not let a lack of perfect data stop accessibility measurement efforts. Communicate any limitations. If possible, collect new or improved data or assess accessibility qualitatively or conceptually. 2.3.3 Implementation Gaps Implementation gaps differ depending on an agency’s familiarity with accessibility concepts and measures. The interviews with transportation agency staff conducted for this research demonstrate that some agencies want to consider accessibility but do not due to a lack of staff knowledge and capacity, while other agencies consider accessibility regularly and wish to expand their assessment by developing more accurate or sophisticated measures or considering acces- sibility in new application areas. Finally, some agencies do not consider accessibility due to a lack of interest or a perception that it does not apply to their context. At the same time, technical barriers are low for many organizations as many existing datasets, software packages, and tools can be used to calculate and apply accessibility measures. Agencies can bridge knowledge and capacity gaps by hiring and retaining staff and/or consultants with expertise in geographic infor- mation systems, travel demand modeling, and data visualization. Remedy → Use the resources contained in this guide to aid with accessibility implementation efforts. Recognize that the concept is applicable across all agency contexts. 2.4 Opportunities to Use Accessibility in Practice Are Within Reach Although there are a number of gaps between the state of the art and the state of the practice of accessibility measurement, there are many promising avenues to close these gaps. Opportunities exist for those who have never used accessibility as well as for those who use accessibility regularly and wish to improve or expand their use. First and foremost, there is no need to limit use of accessibility measures because a perfect mea- sure is not available or desired data are missing. Accessibility measures can be used to highlight dimensions of transportation system performance and individual traveler experiences relevant to meeting travel needs that mobility measures alone do not capture. Using the concept of acces- sibility to think deeply about the relationship between transportation and land use and its effect on transportation system performance can be valuable regardless of the measure used. Although tradeoffs exist between the ease of estimating and communicating measures and their accuracy and comprehensiveness, using accessibility measures that are easy to estimate and communicate can be informative. Multiple off-the-shelf data and software tools are available to help lower-resourced agencies quantify accessibility. Where accessibility measures fail to capture important features of transportation and land use systems or traveler experiences, users of these measures should be transparent and honest about those shortcomings. However, even in such a case, the results can be informative if placed in the appropriate context. For agencies lacking the resources to measure accessibility quantitatively, the concept of accessibility can still be powerful even in the absence of a quantitative measure. Calculating multiple different accessibility measures and comparing the results can also provide planners, engineers, decision-makers, and the public with better information about existing con- ditions or the impacts of a project or plan. If calculated indicators all point in the same direction, then the results can be considered stable and robust. If different measures paint a different picture of current conditions and impacts, then caution and further analysis are warranted.

Accessibility Measurement Principles and Practices 21   Agencies that can quantify accessibility may want to broaden their applications with more accurate and comprehensive accessibility measures while clearly interpreting and communi- cating results. There have also been advances in the ability to capture accessibility dimensions that were previously difficult to measure, including improvements in nonmotorized data collec- tion, among other areas. Agencies can collaborate with other stakeholders to share accessibility measures and outcomes across plans and programs, helping to maintain accountability and consistency.