Uber Movement provides anonymised data from Uber rides to help urban planning

Uber has released data from over two billion rides to help urban planners. The GPS based data is collected from Uber rides, and contains information on the movement of traffic within the city, The data is stripped of all personally identifiable information. Analytics tools provided for the data allows users to get meaningful insights from the data. Daily and weekly travel times between two points in the city can be tracked. The patterns in the traffic conditions can be seen over days, weeks and years. The impact of rush hours, events and road closures can be tracked. The data is meant to help city officials, urban planners and policy makers take better decisions, but is available to the general public as well. The detailed historical data allows for better choices to be made for future infrastructure investments.

In the US, Uber was able to tract the effects of a series of maintenance based shutdowns to the DC Metrorail system in Washington DC. This is an example of how Uber can find out the impact of local events on traffic. The outages saw an increase in congestion, particularly in the busy areas of the city. When only a part of the line was shut down for maintenance, a more localised form of the congestion was seen, only in the areas serviced by the line. Travel times increased dramatically during the shutdown. Muriel Bowser, Mayor of Washington DC says “Smart technology and intelligent use of data are critical to the success of the nation’s cities, and the District of Columbia is committed to using these tools to keep pace with the rapid growth of our neighborhoods. We’re excited to be one of the early partners with Uber on this new platform. We want to employ as many data sources as possible to mitigate traffic congestion, improve infrastructure, and make our streets safer for every visitor and resident in the nation’s capital.” In Manila, Philippines, Uber Movement showed a spike in traffic over the course of the holiday season. The travel time to Ninoy Aquino International Airport from various points around the city was unpredictable. More passengers missed their flights, over the holiday season, because of the increased traffic on the roads. Analysing the data shows that the best times for travelling to the airport were early in the morning, or late in the evening. As of now, users can request access to the data by signing up with an email address. Uber plans to release the data to the public soon. The data is available under a Creative Commons, attribution, non commercial license.