Ford, Uber & Lyft Sign Agreement to Share Data to Help Reduce Traffic in Cities

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【Summary】The Ford Motor Company and ride-hailing companies Uber and Lyft announced an unprecedented commitment to SharedStreets, a new data platform designed to make it easier for the private sector to work with cities by agreeing to share data that might help everyone get around cities more easily.

Eric Walz    Nov 02, 2018 12:20 PM PT
Ford, Uber & Lyft Sign Agreement to Share Data to Help Reduce Traffic in Cities

NEW YORK — Hailing a ride with Uber and then getting stuck in traffic on the way to your destination is frustrating. But with an ever increasing number of ride-hailing vehicles operating on city streets the problem might only get worse, until city planners have access their own detailed traffic data so they can begin to work on a solution to reduce congestion and greenhouse gases.

A new partnership with The Ford Motor Company and the two largest ride-hailing companies is addressing this problem—by agreeing to share data that might help everyone get around cities more easily.

The Ford Motor Company, along with Uber and Lyft, have announced an unprecedented commitment to SharedStreets, a new data platform designed to make it easier for the private sector to work with cities around the world and leverage data to improve urban mobility and help make traffic move more efficiently.

This collaborative effort was announced by Jim Hackett, CEO of Ford Motor Company, Dara Khosrowshahi, CEO of Uber, and John Zimmer, Co-founder and President of Lyft, at the second annual Bloomberg Global Business Forum held in New York City.

"This is a once in a lifetime opportunity for business and government to work together to rethink transportation," said Jim Hackett, president and CEO, Ford Motor Company. "Collaborating through initiatives such as Shared Streets will enable us to use vehicles, road systems and data together to create a new roadmap for mobility. We are working toward a future where all cities are smart and curb space is actively managed, increasing efficiency and safety, while reducing driver stress and pollution."

New Tools to Reduce Traffic and Emissions

The data sets pledged by the companies will provide the public and private sectors with new tools to manage curb space in order to reduce congestion, accidents and greenhouse emissions, while and making it easier for everyone to get around in city traffic.

The public-private partnership is the result of a collaboration with the National Association of City Transportation Officials (NACTO), the Open Transport Partnership and Bloomberg Philanthropies, the consortium behind the innovative SharedStreets data platform.

NACTO represents 74 cities and transit agencies across North America, formally endorsed the data sharing policies of SharedStreets and is committed to working collaboratively with the private sector.  

The partnership gives city mayors unprecedented access to detailed road traffic data, such as exact locations of daily traffic congestion, allowing them to make better city planning and infrastructure investment decisions, as shared and autonomous mobility services arrive in their cities.

For mobility companies, the agreement provides a common standard for sharing specific data across all cities, where local requirements vary widely.


Launched earlier this year with funding from Bloomberg Philanthropies, SharedStreets is a universal data language for sharing detailed information about city streets. The platform serves as a launching pad for public-private collaboration to manage streets.

SharedStreets is already operating in over 30 cities around the world, the SharedStreets platform and this new partnership will provide city leaders with far better tools for managing their transportation networks.

For its part in the collaboration, Ford will develop a universal data standard for real-time curb demand and availability. With this tool, cities will be able to manage, or price curb space in real-time, for the first time. It will help cities encourage sustainable transportation choices and reallocate available road space.

Uber will contribute a global data set of vehicle driving speeds, to help cities identify areas where drivers frequently travel above the speed limit. With this critical data, cities can identify where exactly on their streets people are driving too fast, so that they can redesign streets, such as adding curb extensions or reducing speed limits in certain areas.

Uber will include this speed data in an update of its open-source tool, a web application which is available on GitHub. The software providing cities with tools for data visualization and information sharing. Uber rival Lyft will follow with a release its own city speed data set.

"The private and public sectors need to come together and collaborate on ways to create smarter, safer and more efficient transportation systems," said Dara Khosrowshahi, CEO, Uber. "It's the responsibility of companies like ours to step up and support cities in every way we can—whether that's through data sharing, urban planning research, funding for nonprofits, or even through the introduction of new and more efficient forms of transportation like electric bicycles."

Lyft will join SharedStreets and Uber to produce a universal framework for sharing curbside pick-up/drop-off counts. Building on an early SharedStreets feature first announced with Uber, Lyft will also provide curb usage data to leading cities everywhere, to help cities identify demand for rides.

With this data, city leaders can understand locations and times where ride-hailing trips are in the greatest demand, so that they can reduce congestion and make pickups and dropoffs areas easier for drivers to reach or exit from.

First funded by Bloomberg Philanthropies and developed by NACTO and the Open Transport Partnership, the SharedStreets is a neutral, anonymized clearinghouse for data collected by transportation providers, private companies and government agencies, as well as a hub for industry-leading data analysis, traffic planning, street design and development of new technologies.

"Ride-share and auto companies have been gathering an enormous amount of data on transportation and traffic. Now, cities will be able use it to find new ways to manage congestion, reduce carbon emissions, prevent traffic crashes, and prepare for the arrival of autonomous vehicles," said Michael R. Bloomberg the founder of Bloomberg Philanthropies. "It's a great example of how governments and businesses can work together to solve tough problems and build a better world - and I want to thank all the companies that are taking part."

Uber & Lyft Being Blamed for an Increase in City Traffic

Ride-hailing companies like Uber are under increasing pressure from cities such as New York, where the city council voted in August to cap the number of licensed Uber drivers that can operate in the city. City officials have blamed Uber and other ride-hailing operators for an increase in traffic, especially in popular areas of midtown Manhattan, where city streets are often clogged with thousands of Uber vehicles during peak times.

Bruce Schaller, a transit consultant who served as deputy commissioner for traffic and planning in New York City, released a new report in July examining the effect ride-hailing companies on city traffic nationwide. The report alleges that Lyft and Uber are responsible to a 180 percent increase in traffic in major markets where the companies operate, including San Francisco, Philadelphia, Seattle, Los Angeles and Chicago.

The partnership between the companies is the first formal step in addressing traffic problems in major cities, as well as providing a way for cities to plan for the upcoming wave of autonomous driving and mobility services that will change how people move and reduce personal car ownership.

In addition, the platform overcomes long-standing legal, regulatory and technical challenges of data sharing between the public and private sectors by converting huge amounts of disparate transportation data sources into a readable, global standard for the first time.

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