Over the years, we’ve learned a lot about urban mobility and what it means for cities and the people who live in them. We’ve gotten consistent feedback from cities we partner with that access to our aggregated data will inform decisions about how to adapt existing infrastructure and invest in future solutions to make our cities more efficient. We hope Uber Movement can play a role in helping cities grow in a way that works for everyone.
Uber Movement will only work in cities where we operate. Over time, we’ll be expanding Movement to include data from many more of those cities. Join our Newsletter to stay tune, or Contact us if you have a recommendation of where we should roll out to next.
Preserving rider and driver privacy is our #1 priority. All data is anonymized and aggregated to ensure no personally identifiable information or user behavior can be surfaced through the Movement tool. All data shared through Movement adheres to Uber’s privacy policy. At no point will Movement provide a means for users to access individual user details. For in-depth details of how we're ensuring this in specific Movement solution, read the methodology whitepaper for the given solution.
Yes! We’re continually iterating on Movement in collaboration with government experts, transportation professionals, and academic organizations around the globe. We’re always interested in discussing feature requests and soliciting feedback on our product, Contact us
We regularly partner with academic organizations around the globe, and are always interested in discussing research opportunities and soliciting feedback. Contact us regarding your specific case.
If Movement data are used in a paper, the following should be included in your acknowledgements section: “Data retrieved from Uber Movement, (c) 2023 Uber Technologies, Inc., https://movement.uber.com.” For Travel Times data, you may also need to provide appropriate attribution according to the Provider Attribution details here: Data Provider Attribution
Travel Times values are derived from anonymized and aggregated trip location data across the zones. For more details, see the methodology whitepaper below.
No. Travel Times data is available under a Creative Commons, Attribution Non-Commercial license.
Travel times data is available in a machine readable, csv format. For use in geospatial applications, travel times data may need to be joined with the geo boundaries geojson file, available via the download interface.
Movement Travel Times data isn’t available programmatically at this time. If you have a use case requiring time series data at hourly granularity, over a span of time greater than that available in the tool, or similar, there is a possibility we can assist. Please Contact us.
Speed values are derived from average speed readings from on-trip Uber data across the street segments. For more details, see the methodology whitepaper below.
Free-flow speed is the term used to describe the average speed of traffic in the absence of congestion or other adverse conditions (such as bad weather). We estimate the free-flow as the 85th percentile of all speed values observed on a segment during the earliest quarter into which your filtered time range falls. In the future, we’re hoping to refine this approach and develop a more accurate representation of free-flow speeds that our users can leverage.
Many cities do not have detailed speed limit data coverage for the entire city. We decided to approximate the prevailing traffic speed with the free-flow (P85) value, as this approximation is commonly used in both research and in regulations to set speed limits (source1, source2. We know that there are a number of inputs that go into roadway design and setting the speed limit. We hope that the data provided via Uber Movement can contribute to these conversations and help cities, engineers and others have more informed conversations about how infrastructure can positively impact road safety.
Speeds data is downloadable in machine readable, .csv format. For certain geospatial applications, Speeds data may need to be joined with other data sets. On the Download Page we provide tools to facilitate working with the data and interoperability with the other data formats. If you have a specific geospatial need not handled by the tool, we always welcome feedback to improve the product. Contact us.
The goal of Movement is to provide data that is valuable to stakeholders and an accurate representation of overall road and traffic conditions, not simply Uber behavior. In order to ensure validity of the data, we set a minimum threshold of observations necessary to render data.
No. Speeds data is available under a Creative Commons, Attribution Non-Commercial license.
No, Movement Speeds are aggregated values calculated from GPS pings along street segments from a variety of trips and drivers as a ratio of the traveled distance over time. This means that individual driving behavior cannot be identified and more information is needed to infer more general safety conditions on road segments (e.g. the volume of traffic, roadway design, or how the posted limit was set). For more information, please refer to the safety section of the Uber Movement: Speeds Calculation Methodology document.
While the data is public, this tool is not designed for enforcement. This tool is designed to provide helpful and contextual information about behavior on the streets for planning and analysis. Our goal is to contribute to data driven conversations about what’s happening on our streets and the overall transportation network when it comes to speed. We hope this data drives this and other conversations focused on safer roadways for all people.
Let us know! We appreciate the feedback. This is an enormous amount of data to release and while we make strong efforts to clean and validate this data, there will inevitably be outliers or times where there are biases in the data. See something strange? Say something. We will investigate and get back to you. You can reach us at movement-research@uber.com.
We believe that our users have the right to their mobility privacy which is why we take detailed care in protecting it when publishing data. For more information, read our whitepaper methodology.