ISyE Seminar: “Map Technologies for Ride-Sharing”

Please join us for our next seminar via Zoom. This analytics-focused seminar will feature Dawn Woodard from Uber who will discuss map technologies for ride-sharing.

3:30 - Graduate seminar
4:30 p.m. - Reception
Zoom link
Password: ISyE2021

*Required attendance for students in IE 5773, 8773, and 8774

About the Seminar

Extensive literature now exists on methods for pricing and matching in ride-sharing platforms, such as Uber, Lyft, Didi Chuxing, and Ola. However, less attention has been paid to the complex geospatial inputs required for these systems. For example, carpool matching methods require accurate predictions of the time required to travel between any two locations in the road network. Woodard and her team describe geospatial (map) technologies, including those for travel time prediction and route optimization, that can be used in the context of such large-scale vehicle decision systems. The researchers showcase the challenges, such as data sparsity on parts of the road network, and the fact that highly accurate predictions need to take into account the detailed dynamics of a physical system (traffic patterns in a road network). They also compare several common approaches for travel time prediction, and provide rigorous theoretical results showing that one class of approaches has higher accuracy than alternatives.

About the Speaker

Dawn Woodard leads modeling and data analytics for platforms including Uber Maps, which is the mapping platform used in Uber’s user interfaces and decision systems. The team’s technologies include road map and points of interest definition, map search, route optimization, travel time prediction, and navigation.