Entry Date:
May 22, 2013

Real-Time Path Tracking/Predictions and On-Demand Route Guidance Under Uncertainty

Principal Investigator Patrick Jaillet

Co-investigator Daniela Rus


Algorithms that use real-time data from many heterogeneous sources in order to (i) track and predict paths in dynamic transportation networks, and (ii) provide on-demand route guidance under uncertainty, based on a combination of optimization, data-fusion, machine learning, and novel behavioral techniques.