Vulnerable Road Users & Transportation Equity
Analyzing transportation infrastructure & demographics to make data-driven community planning decisions.
Who are vulnerable road users?
Vulnerable road users broadly refer to individuals using transportation networks in a non-singular occupancy vehicle capacity. When it comes to analyzing transportation network safety and equity for these groups, pedestrians, elderly individuals, cyclists, individuals with disabilities, and similar distinctions are often the focus. The Federal Highway Administration's full technical definition of a vulnerable road user can be found here .
While the official use of the term 'vulnerable road user' is still relatively new, US government agencies have long been implementing transportation safety measures in order to protect pedestrians and reduce traffic-related fatalities. In fact, the First National Conference on Street and Highway Safety was held in 1924 as the increase in automobile ownership and inadequate infrastructure led to rising pedestrian-involved traffic accidents.
There are various types of infrastructure designed to meet the specific needs of different vulnerable road users, and it's important to note that transportation equity for these individuals means not only making infrastructure safe, but also available and accessible.
For example, an important part of transportation equity is ensuring all community members have access to pedestrian features like sidewalks or bike lanes in order to encourage healthy lifestyles, provide safer options, and improve the quality of life for residents. These are often referred to as pedestrian access routes.
Making sure these features are accessible to all, including those living with disabilities, is also critically important. For more than 30 years, the US government has been supporting expansion in transportation infrastructure accessibility, most notably through the passage of the Americans with Disabilities Act (ADA) in 1990. For example, sidewalks must be at least 3 feet wide to be considered ADA compliant, and later Public Right-of-Way Accessibility Guidelines (PROWAG) established by the US Access Board recommend that sidewalks be at least 4 feet wide to accommodate a more diverse group of vulnerable road users.
Below is a brief timeline of major accessibility milestones in the US. These milestones have resulted in authoritative guidelines in order to ensure the accessibility of new and existing transportation infrastructure, which organizations are increasingly turning to geospatial analysis and mapping to achieve.
Leveraging land cover data to understand transportation equity
Understanding accessibility guidelines is just the first step in fostering an equitable society. To truly enact change, metropolitan planning organizations (MPOs) and departments of transportation (DOTs) must analyze their exiting infrastructure for compliance and then develop strategic plans for expanding availability and accessibility. Traditional methods for conducting this type of project would involve manually surveying and digitizing entire communities to understand where certain types of transportation infrastructure exist and how accessible they are to all types of users, an extremely resource-intensive and time-consuming process.
Thankfully, geospatial data and AI-powered mapping technology has delivered an efficient and accurate alternative for transportation planners. Land cover vector features extracted from geospatial imagery provide MPOs and DOTs with a digital source of truth for the real world, enabling them to easily locate gaps in transportation availability. This artificial intelligence (AI)-based mapping approach also classifies each feature into distinct features types and appends them with critical accessibility information, such as sidewalk width or curb height. When layered with demographic data related to income, population living with disabilities, and more, this mapping data gives planners the information they need to make transportation networks safe, accessible, and equitable throughout their community.
Case study: transportation equity for vulnerable road users in Baltimore, Marlyand
At Ecopia AI (Ecopia) we work closely with MPOs and DOTs across the US to improve transportation mapping with comprehensive, accurate, and up-to-date data. In this case study, we will explore how demographic data from the US Census Bureau can be combined with Advanced Transportation Feature data to better understand transportation equity across an entire community.
While our analysis will examine the greater Baltimore area, we will pay particular attention to the City of Baltimore itself, the boundaries of which can be seen to the left overlaid on census tracts.
The Baltimore region contains over 700 miles of sidewalks, crosswalks, pedestrian bridges, and ADA curb ramp warning pads - all critical infrastructure for understanding transportation equity.
Visualizing the entire transportation network with data from Ecopia and the Maryland DOT, we can see some patterns in geographic distribution, but no real insights into what that means for vulnerable road users.
With this data, we can calculate the following stats to get a better picture of transportation equity in the region:
Average percent per census tract of transportation safety features
Average count per census tract of transportation safety features & demographic characteristics
However, these stats only scratch the surface and do not provide actionable insights for MPOs and DOTs to leverage in their planning. To truly understand the transportation equity for vulnerable road users, we need to experiment with different ways of visualizing and normalizing both infrastructure and demographic data. This will enable us to narrow down where inequity exists and why, which can inform future planning projects.
Pedestrian route accessibility
First, we visualize the relationship between total road mileage and total pedestrian access route mileage by census tract. Pedestrian access routes include sidewalks, high visibility crosswalks, and marked crosswalks.
This visualization helps us see that the Baltimore area tends to have more pedestrian access routes in urban areas and more traditional roads in rural areas, while suburban areas have more of a mix of the two.
Generally speaking, this is what the distribution of routes looks like in US cities, so this visualization alone does not provide much new insight for planning.
Next we normalize that data by total census tract population to better understand what that accessibility distribution looks like. In other words, this visualization shows the relationship between total road mileage and total pedestrian access route mileage per person by census tract.
Using this method, we can start to see some areas of disparities, particularly in urban areas. This provides more real-world context for planning decisions by indicating where pedestrian access routes and roadways are in relation to the area's population, but we can still layer in more information for deeper insights.
We then switch the normalization method to account for median household income instead of population, as higher income is positively correlated with the tendency to use a vehicle and not be as reliant on pedestrian access routes.
With this normalization, we can see some hot spots of inequality, particularly in outer city neighborhoods and inner suburbs.
These insights can be used to determine where to allocate planning resources, but can also be augmented with other data.
The US Census Bureau does collect data that represents the number of households without access to a vehicle in a census tract, but there are some data gaps to consider.
Additionally, it is important to remember that there can be high income households within urban areas that do not have vehicles, so this is not always the best variable to use in an analysis.
This variety in data visualizations shows how important it is to conduct a multivariate analysis when identifying geographic trends.
Overall, normalizing by population and income provides the most reliable method of identifying underserved areas. The data shows that outer neighborhoods of the city, as well as inner suburbs, have the most transportation inequality, so would be ideal areas to allocate funding for improvement projects.
Crosswalk safety equity
Crosswalks are another important element to understanding transportation equity for vulnerable road users.
Leveraging Ecopia's topologically connected crosswalk data across the region, we plot crosswalks as points and symbolize them based on safety classifications to identify any regional disparities, and quantify how many unsafe crosswalks a vulnerable road user would have to traverse over a given routable network.
We can then aggregate this crosswalk safety data by census tract to see how different areas and populations are impacted by variations in crosswalk visibility.
Visibility is top of mind for many regions when analyzing transportation routes, as 77% of pedestrian-involved traffic incidents in 2021 occurred at night, when visibility is poor ( NHSTA ).
Predictably, this visualization shows that in the Baltimore region, the highest visibility crosswalks are in the downtown core of the city.
If we normalize this data by population, there is a much less clear trend throughout the region. It appears there are the most inequities in suburban areas.
Normalizing by both population and income, the same areas of inequality we identified as underserved in our pedestrian access route analysis are highlighted.
This reaffirms the need to allocate resources to these areas to increase transportation equity for vulnerable road users.
If we normalize by households without access to a vehicle (hypothesizing that these areas are likely to have more pedestrians) we can again see the same underserved areas.
These areas are highlighted again when we visualize and normalize by population living with a visual or ambulatory disability (those who are most vulnerable when using unsafe crosswalks), although even more pronounced in the city and some rural areas.
Adding income into this analysis to account for people living with a disability who are more likely to be a pedestrian, we see the same vulnerable areas: outer city neighborhoods and inner suburbs.
Looking at the locations of high visibility crosswalks themselves, we can see there is a relatively low concentration region-wide, even along urban arterials.
Symbolizing by crosswalk length and average daily traffic passing these crosswalks, we can see where pedestrians are most exposed to vehicle traffic and associated dangers.
Suburban arterials show up as potential problem areas due to the longer lengths of pedestrian exposure, despite the lower average daily traffic compared to crosswalks in more urban areas.
The same visualization method and analysis for standard crosswalks shows a clearer trend along principal regional arterials.
This is a useful input to vulnerable road user assessment, as upgrading standard crosswalks to high visibility crosswalks is a high impact, relatively low cost improvement MPOs and DOTs can make.
For example, high visibility crosswalks add multiple seconds to driver reaction time on a high speed route.
Performing this analysis for unmarked crosswalks reveals a similar trend along principal regional arterials, but with particular risk in areas with very high volume, high speed roads that funnel into dense urban areas.
These areas tend to be high-employment industrial and commercial areas, where employees are more likely to use public transit and pedestrian access routes to get to work.
Sidewalk safety equity
Sidewalks are also critical features of an equitable transportation network for vulnerable road users. ADA and PROWAG guidelines for sidewalk width are intended to enable individuals living with a disability to have access to sidewalks by making them wide enough to accommodate mobility devices.
This map visualizes sidewalks throughout the region by width, and indicates that Baltimore's downtown areas have the widest, most accessible sidewalks, while outer city neighborhood sidewalks are less accessible. Some suburban and rural areas don't have any sidewalks at all.
Aggregating this sidewalk data by census tract, we can see that Baltimore's downtown core does indeed have a high percentage of ADA and PROWAG compliant sidewalks, but other areas of the city have less accessible sidewalks.
Normalized by population, the same trends can be seen. However, there are some areas of high accessibility sidewalks and lower population, while higher population areas exist with more inaccessible sidewalks, highlighting areas of inequality.
Normalizing by both population and income, the same hotspots of inequality we previously identified in the inner suburbs and outer city neighborhoods are highlighted. These are areas with populations less likely to use a car, and more likely to use pedestrian access routes. However, sidewalks are less accessible here.
Factoring in population living with an ambulatory disability, those most likely to use a mobility device, there is a high rate of dispersion throughout the region.
Layering income data into this to understand areas more likely to rely on pedestrian access routes, we can see that individuals living with an ambulatory disability are less likely to have access to safe sidewalks in outer city neighborhoods and inner suburbs.
Curb ramp safety equity
Curb ramp warning pads are an integral part of an accessible transportation network as they enable vulnerable road users with a visual disability to better detect when they might be entering traffic. Warning pads for curb ramps tend to be a bright yellow or other highly contrasted color in the United States.
Visualizing the locations of these features, we can see that warning pads are most common in newly developed areas and along major routes. This generally aligns to nationwide trends of warning pads for curb ramps.
Visualized by census tract, there are a few outliers of accessibility, but no real insights for strategic planning or resource allocation.
Normalized by population, we can see that Baltimore's downtown core and areas with newer development have more curb ramp warning pads.
Layering in income data, the familiar trend of outer city neighborhoods having less accessible transportation features (in this case, curb ramp warning pads) becomes apparent, though much less pronounced than the crosswalk or sidewalk inequalities we identified earlier.
This is likely due to recent federal requirements to upgrade infrastructure to ADA standards when performing resurfacing on federal-aid roads.
Normalized by population living with a visual disability, inequality seems to be dispersed throughout the region.
This may be due to a lower sample size of visually impaired persons when compared to other disabilities (like the ambulatory disability stats we looked at earlier).
However, adding income into the analysis highlights the same areas of inequality despite the small sample size: outer city neighborhoods and inner suburbs.
Results
These multivariate maps highlight specific areas in the Baltimore region with transportation inequity concerns for vulnerable road users. Generally speaking, the outer neighborhoods of the City of Baltimore and the region's inner suburbs tend to have the highest levels of inequality when it comes to pedestrian safety and access features. However, this data and analysis is granular enough for planners to pinpoint specific inequities in each census tract, providing data-driven insights to support resource allocation for infrastructure improvements.
Harnessing AI to create high-precision transportation data for planning decisions
This case study shows just some of the actionable insights MPOs and DOTs can uncover when layering high-precision transportation feature data with demographics. At Ecopia, we've worked with over 26 MPOs across the US to create the first region-wide sidewalk databases serving those areas. Check out a sample of data created for the Baltimore region by Ecopia below:
Ecopia's AI-based mapping systems extract these high-precision transportation features at scale, enabling MPOs and DOTs to create and maintain a comprehensive, accurate, and up-to-date database of vector layers to fuel their accessibility and equity analyses. To learn more about Ecopia's work with transportation planning organizations, click here .
Funding opportunities for transportation planning data
At Ecopia, we know that many planning departments want to leverage high-precision data for these types of analyses, but struggle to find the funding to create or acquire it. We often work with MPOs and DOTs to source and apply for federal funding for these types of projects, and created a cheat sheet here for you to get started .
If you're ready to power in-depth spatial analytics of your community's transportation network, get in touch with Ecopia's public sector team - we're here to help!
