Project: #176 Mesoscopic car-truck flow modeling and simulation: theory and applications Progress Report - Reporting Period Ending: March 30, 2019 Principal Investigator: Sean Qian Status: Active Start Date: Aug. 7, 2018 End Date: June 30, 2019 Research Type: Applied Grant Type: Research Grant Program: FAST Act - Mobility National (2016 - 2022) Grant Cycle: 2018 Mobility21 UTC Progress Report (Last Updated: March 24, 2019, 9:36 p.m.) % Project Completed to Date: 90 % Grant Award Expended: 90 % Match Expended & Document: 90 USDOT Requirements Accomplishments 1. We improved the bi-modal traffic flow model, and integrated it in traffic simulation models for large-scale networks. We have developed a computational graph approach that substantially improved the simulation accuracy. This has been summarized in a manuscript submitted to a journal. 2. We improved the traffic simulation models for the Pittsburgh region, which supports decision making for traffic management and planning. Impacts 1. presented the work in meetings with PennDOT, the City of Pittsburgh, McKees Rocks. 2. Helped McKees Rocks to plan for traffic mitigation under the new CSX terminal 3. This research fundamentally enriched the way we understand truck flow in the regional transportation networks. 4. contributed to a software package MAC-POSTS (Mobility Data Analytics Center - Prediction, Optimization, and Simulation toolkit for Transportation Systems.) which is open sourced and shared in Github under MIT license. Other contributed to a software package MAC-POSTS (Mobility Data Analytics Center - Prediction, Optimization, and Simulation toolkit for Transportation Systems.) which is open sourced and shared in Github under MIT license. A large-scale network simulation models that encapsulates evolution of cars and trucks, as well as the respective software package A report that summarizes all findings from the case study of McKees Rocks Outcomes New Partners n/a Issues n/a