Live Poster Session: Zoom Link
Thursday, July 30th 1:15-2:30pm EDT
Abstract: Today, 55 percent of the global population currently lives in cities and the UN estimates that this will rise to 68 percent over the next several decades. This makes understanding movement through cities of growing importance. Increasing urban populations cause more people to move through cities, leading to more congestion. Thus, understanding how congestion changes throughout the course of a day provides insight in how to travel efficiently. By analyzing the road speeds provided by Uber we characterize patterns in the congestion of cities. Uber Movement provides the aggregated data from over 10 billion trips, giving both dynamic travel time and road speed data. This data allowed us to create a metric for measuring the overall congestion on a network-wide level, as well as evaluate the changes in speed across individual roads over the course of a day. We found that congestion peaks at 10 am and 4 pm, with the least congested time being 5 am. This is not an unexpected result as these times roughly correspond with the beginning and end of a typical workday. Another result is the minute differences found between congestion of different road-types. The minimal presence of differences suggests that the choice of travel route is relatively balanced across the network. On a network-wide scale, congestion acts relatively predictably across road-type and day of the week.
Poster-3-Sam-EphronLive Poster Session: Zoom Link
Thursday, July 30th 1:15-2:30pm EDT