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.

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

Crosswalk safety equity

Sidewalk safety equity

Curb ramp safety equity

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!

Average percent per census tract of transportation safety features

Average count per census tract of transportation safety features & demographic characteristics