Curb space in city centers is a scarce resource. And as demand for this space increases — with the rise of urban deliveries, shared mobility services, and, ultimately, autonomous vehicles — things will only get more challenging. Cities around the world are looking for ways to make curb space safer, more efficient, and more productive.
That’s why we commissioned a study with Fehr & Peers Transportation Consultants that analyzed a combination of rideshare pickup and dropoff activity data, traffic count data, and video and photo content to develop broad design strategies others can use when contemplating how to get more out of their curbs. You can see the full report here.
Building on a growing body of policy, planning, and engineering studies from organizations like NACTO and the ITF, we worked with Fehr & Peers to select five different blocks in San Francisco representing a range of different neighborhood characteristics. All five locations experience high levels of rideshare passenger loading activity and are broadly comparable to other similar urban environments across the country. For each location, Fehr & Peers collected, observed, and analyzed traffic count data, video, photography, and Uber activity data to quantify passenger loading demand as well as interactions and behaviors at the curb.
A New Metric for Curbside Productivity
The first step in solving any problem at scale is having a consistent tool for measurement. We worked with Fehr & Peers to develop just such a tool — the Curb Productivity Index. The Index calculates the amount of passenger activity — the number of people using the curb — per hour, per 20 feet of curb, which is about the size of a typical on-street parking space.
For example, if a bus stop serves 100 passengers in 4 hours, and the bus stop is 80 feet long, the curb productivity would be:
100 passengers / 4 hours x 80 feet =0.3125
0.3125 x 20 feet= 6.25 passengers served per hour per 20 feet of curb
To put this into perspective, if a single car carrying two people is parked in an on-street parking space for the same four hours, that space served 2 passengers in 4 hours over 20 feet — or 0.5 passengers per hour per 20 feet of curb. In this example, the bus stop is about 12 times more productive than the on-street parking space. This isn’t surprising, since high-capacity transit is the most efficient way to move people in a city. Based on Fehr & Peers’ observations of the selected streets in San Francisco, passenger pickup and dropoff zones tended to rank somewhere in between.
However, as shown in the graphic below, the actual space allocation of the curb often isn’t optimized for the most productive uses. In many cases, the less productive uses claim the vast majority of curbside real estate and, as a result, other users of the road — from commercial delivery to passenger loading — can spill over into traffic and bike lanes, causing delays and unsafe vehicle interactions.
Three Strategies to Improve Curb Productivity
So what’s the path forward?
First, we know we can leverage our technology to make improvements ourselves — we’re working to ensure we get best in class information to our drivers on how to safely pick up riders, and we’re designing features to help communicate the best and safest spots to request a ride. We’re also working to improve the experience in areas of particular high density — airports, transit hubs, and large event centers — designing new in-app features that make it easier and more intuitive for riders and drivers to find each other and safely be on their way.
Beyond digital infrastructure, we’ve heard directly from cities and governments that they are looking for strategies to design the future of curb space. That’s why, in addition to the Curb Productivity Index, Fehr & Peers developed three broad strategies to help improve curb productivity and efficiency based on their observations and analysis for each study location.
Leveraging these strategies — relocation, conversion, and flexibility — the report develops a set of design templates for each of the five study locations illustrating how the strategies might be applied to a typical street. Below are design recommendations for a busy commercial street surrounded by medium density residential, based on observations and data collected on Hayes Street in San Francisco:
This study benefited from high quality data collected from across San Francisco, including data from Uber. As cities face the tough challenge of reimagining their curbs and streets, we know they’ll need up-to-date data about existing curbside activity. That’s why we’re pleased to be partnering with the non-profit SharedStreets. We’re working to build tools and methods to share data on curb use, and we’re also announcing our intention to expand our Movement product to include granular street segment-level speed data. Informed by our conversations with city agencies and urban planners, these data resources are designed to make it easier and more intuitive to measure the success of new methods of managing curb space.
In addition to sharing data, we’re also focused on improving our product to enable smarter, safer, more efficient pickups and dropoffs. We know there are places where rideshare passenger loading and unloading don’t belong — bike lanes, bus stops, and streets heavily traversed by transit — and we’re committed to working with cities and communities to get this right.
We’re excited to continue our work with SharedStreets to build standards and tools for public-private data sharing. We hope our work with Fehr & Peers proves useful in cities’ efforts to make their curbs safer and more efficient and we look forward to continuing our efforts to partner with cities to encourage shared mobility adoption, rethink curb space, and prioritize the most efficient uses of our limited urban space.