Learning more about how our roads are used today
By Chris Pangilinan, Head of Global Policy for Public Transportation
At Uber, we’re focused on reducing the need for private car ownership while expanding transportation access for all. Ten years and more than 15 billion trips into our journey, we’re building products to get people closer to where they want to be and eschew private car ownership altogether — be it via ridesharing and carpooling; electric bikes, scooters and integration into public transportation systems.
As we continue to grow in the communities we serve, it’s important to understand how roads are being used so we can continue to work together with cities to develop the right policies that expand mobility. That’s why we’re excited to share a study analyzing our and Lyft’s ride data to determine our combined contribution to overall vehicle miles traveled (VMT), a standard metric for vehicle activity in a region. This report, sponsored by us and Lyft, and conducted by transportation consultancy Fehr & Peers, is the first of its kind and uses our own and Lyft’s trip data as well as VMT data collected by federal, state, and local authorities.
This study found that overall VMT share at the metropolitan level and at the core county level consists overwhelmingly of non-Transportation Network Company (TNC, shorthand for Uber and Lyft) traffic — that is, personal and commercial vehicles for the six regions studied: Boston, MA; Chicago, IL; Los Angeles, CA; San Francisco, CA; Seattle, WA; Washington, DC. The research shows that despite tremendous growth over the past decade, TNC use still pales in comparison to all other traffic, and although TNCs are likely contributing to an increase in congestion, its scale is dwarfed by that of private cars and commercial traffic. Below are the study results for all six regions, and a more detailed figure for Boston. Complete figures for each city can be found at the end of this post.
At the metropolitan area level, the share of VMT from TNCs ranges from 1–3 percent, while private and commercial passenger and freight traffic make up the remaining 97–99 percent. When drilling down to the core county level, the county where the primary city is located, TNC VMT share is between 2–13 percent; private and commercial passenger and freight traffic is between 87–98 percent. Note that this counts all TNC mileage — even times when drivers are online but don’t have passengers in their cars (or are enroute to pick up passengers).
Economic and transportation activity is of course concentrated even further within the core counties themselves, such as within the central business district or other popular destinations. To get a sense of how concentrated Uber’s VMT are, we took the same data from September 2018 and examined our VMT split within the core counties in areas we deemed to be the “core of the core”. An example of the boundaries of these areas is shown below for Boston, and they are our rough estimations of the highest activity areas within each region’s core county. The remaining city maps can be found at the end of this post.
This analysis reveals that most of Uber’s VMT occurs outside of the core of the core areas. In San Francisco, for example, approximately 70 percent of Uber’s VMT is west of Van Ness Avenue and/or south of 16th Street, indicating that service is spread throughout the city, and not just concentrated in high activity areas. The numbers in Boston, Chicago, Los Angeles, Seattle, and Washington, DC tell a similar story.
As we move towards our vision of becoming a one-stop shop for transportation in your city, we’re focused on bringing you the right option available at your fingertips for every trip. We are excited to continue working with cities around the world to provide better mobility solutions, and we hope that the results of this study will inform future mobility policies at the local and regional level so we can do just that.
Study result figures for all six cities:
“Core of the core” boundary areas for all six cities (brown is the core county in the metropolitan region, yellow is the “core of the core”):