Team: Sean Qian (PI, CMU), Pinchao Zhang (CMU), Wei Ma (CMU)
Funding source: PennDOT, T-SET, Traffic 21
Start/End Time:  2014-2015

The Philadelphia Metropolitan Region is traffic data rich comparing to other metropolitan areas in the U.S. Various data sets in the Philadelphia region, including traditional traffic sensors (loops, cameras, etc.) and cutting-edge sensors (Bluetooth, GPS probe, parking, etc.), are available and have been archived for a decade. The rich data sets allow us to learn travelers’ behavior accurately and develop an in-depth understanding of non-recurrent traffic in large-scale networks. This research develops a regional dynamic network model that simulates millions of trips in the Philadelphia Metropolitan Region and captures those travelers’ travel behavior. It can be applied directly to predict traffic impact of planned and unplanned incidents, and provide real-time decision making for traffic operations. The regional model will also be tested as a real-time traffic management tool for two planned incidents, I-95 closures and Center City bridge closures.