Access is thus a more encompassing (and complex) concept than mobility. It focuses less on the means and more on the ends (destinations) of travel. It is also a bigger challenge to measure and evaluate, in part because of its multifaceted nature. While mobility-based metrics focus on things like vehicle movements and traffic delays, they don’t consider the advantages of proximity. By contrast, analyzing a person’s access to education, employment, or health care entails, at a minimum, considering mobility, as well as proximity and connectivity.
While mobility, proximity, and connectivity combine to determine accessibility, there are typically trade-offs among these factors: More of one may diminish another. For example, when many origins and destinations are clustered together in dense urban districts, average travel distances are short, making it easier to walk, bike, and ride public transit to destinations. But such environments also tend to have less space available for driving and parking, so drivers frequently experience traffic delays during their trips and pricey parking at their destinations, which combine to inhibit their mobility (and, in turn, access) via car.
How easily people can reach desired destinations also varies by traveler attributes, such as whether one has access to a car, feels safe riding public transit, or has a disability that affects their ability to travel. More broadly, access is not simply an objective construct, but depends as well on travelers’ preferences, constraints, access to various means of travel, as well as perceptions of convenience, comfort, and available destinations. For instance, if a traveler is not aware of restaurant options in an unfamiliar neighborhood, her personal access to prepared food may be low, even if nearby restaurants are objectively plentiful.
Access also has a temporal aspect. People schedule their activities based on the time available to them. They typically sort flexible activities, like grocery shopping, into the times and locations available to them after performing activities with fixed times and locations, like working or going to school. The temporal availability of opportunities also affects access. You might crave pancakes at 3:00 a.m., and in a dense urban environment you are more likely to live near a 24-hour diner. But if your local diner closes at midnight, the fact that it is nearby doesn’t matter at 3:00 a.m.
Other factors, such as public transit reliability, the price of gas, transportation network delays, and policies (such as parking charges) affect access as well.
Figure 1 depicts many of the factors that go into determining access. Because of its overarching nature, access offers a powerful framework for us to think about the physical layout of cities and the opportunities they offer. At the same time, however, the multidimensional nature of access makes it harder to operationalize. We turn to this challenge next.
Figure 1. A conceptual model of the factors affecting accessibility of individuals
Access analysis metrics and tools can operationalize access in two ways: 1) the accessibility of places and 2) the accessibility of people. Place accessibility is generally the easier of the two to measure, and place-based measures are more common as a result. Place access considers primarily the spatial arrangement of potential trip origins and destinations (residences, jobs, etc.) and the transportation networks that link them. Place-based measures allow planners and engineers to analyze accessibility at various geographic scales, such as in larger-scale, longer-term metropolitan growth projections, or smaller-scale accessibility analyses of specific land development or transportation projects.
There are limits to this approach. When we speak of a neighborhood as having more or less access to, for example, health care, we tend to treat everyone in it the same. But health care access is also affected by whether someone has access to a car, health insurance, and so on. So health care access can vary dramatically from person to person, even among people living next door to one another.
To address this, people-based access measures include the attributes and attitudes of travelers, in addition to the place-based characteristics of where they live or work. They allow us to measure access equity across types of travelers, but typically require more data than measuring how access varies across places.
Most accessibility measures offer insight on how land use and transportation systems interact, usually by determining baseline accessibility levels and then analyzing how those levels would change if some aspect of the land use or transportation system changed — such as if a new apartment project were completed, or a new rail transit stop opened. Most measures can compare and contrast alternative future scenarios; the simplest ones count the number of available opportunities within a certain distance and/or travel time threshold (e.g., a person can reach 1,000 jobs in a 20-minute walk) and compare the result with some desired policy goal.
More sophisticated tools account for individual preferences and/or socioeconomic characteristics of travelers, and assign weights to destinations based on distance, and include the temporal dimensions of access as well. For example, if a household has two pharmacies nearby, one a 10-minute drive away, and a second one a 20-minute drive, the first will be weighted more heavily than the second (even though both are within a 20-minute drive).
These access measures allow analysts to examine how equity is affected by particular land use and transportation network configurations. For instance, while people with cars may easily travel to low-density suburbs where trip origins and destinations are dispersed, access to those same developments for those without cars is much lower. Most access measures allow us to analyze these varying effects. Planners can also use these measures to analyze how various land use and transportation configurations affect opportunities for social interaction.
Accessibility analyses of larger-scale, longer-term metropolitan growth scenarios in regional planning are gradually becoming more commonplace, while more microscale, project-level analyses of accessibility remain comparatively rare. Indeed, only a few of the measures we reviewed are intended for land development or transportation project evaluation.
The more dimensions an accessibility metric incorporates, the more data it needs. Measuring access, therefore, has been greatly helped by the increasing availability of new and innovative data sources with far more detailed and nuanced information on travel behavior and access to opportunities, including in real-time. It is now possible to track travelers’ movements in exquisite (and often invasive) detail with mobile device global positioning system (GPS) data. Using social media data, we can infer trip purposes and preferences. General transit feed specification (GTFS), automatic vehicle location (AVL), and automated passenger counter (APC) data provide us with detailed information on public transit service and use.
Despite this explosion of new data, many of the accessibility tools developed to date are still rather simplistic, evaluating only a particular trip purpose, a specific time of the day, or a single mode of travel. As Figure 2 shows, about one-third of the metrics we reviewed measure only accessibility to jobs (35.2%) and/or travel via motor vehicles (29.6%), though most of the commercial and open-source tools being gradually deployed in practice account for multiple means of travel.
Figure 2: Accessibility metrics and tools by means of travel, and trip purposes accounted for