A broad API will be developed to handle interfacing any simulation with a multi-agent demand simulator. This will be tested...
Read MoreDr. Ban’s research interests are in transportation network system modeling and simulation, urban traffic system modeling and operations, and Intelligent Transportation Systems (ITS). He develops modeling tools to study dynamic transportation networks with emerging technologies and systems such as connected/automated vehicles and shared mobility. He also works on urban traffic system state estimation/prediction using mobile sensing data. He is the recipient of the NSF CAREER Award, and the New Faculty Award by the Council of University Transportation Centers and American Road & Transportation Builders Association. His research has been funded by the NSF, US DOT, NCFRP, Volvo Foundation, among others. He joined UW as an Associate Professor in the Fall 2016. Prior to this appointment, he was an Associate Professor of the Department of Civil and Environmental Engineering at the Rensselaer Polytechnic Institute.
Dr. Ban serves on the Network Modeling Committee (ADB30) and the Vehicle Highway Automation Committee (AHB30) of Transportation Research Board (TRB) of the National Academies. He was the elected Vice Chair (2010-2011) and Chair (2012-2013) of the ITS SIG (cluster) under Transportation Science and Logistics (Society) of INFORMS. He currently directs the intelligent Urban Transportation Systems (iUTS) lab at UW. He is an Associate Editor of IEEE Transactions on Intelligent Transportation Systems, Journal of Intelligent Transportation Systems, Networks and Spatial Economic, and Transportmetrica B: Dynamics, and serves on the editorial board of Transportation Research Part B, Part C. His research has produced more than 100 papers in refereed journals and conference proceedings.
C2SMART Projects
Crowdsourcing Parking Data for Micromobility Vehicles
This project will develop a mobile app that streamlines the reporting of mis-parked dockless scooters and bikes, relaying data to...
Read MoreResearch and Field Testing of Vehicle-Traffic Control with Limited-Capacity Connected/Automated Vehicles
This project aims to extend and field-test CAV-based traffic signal/vehicle control methods developed by the research team in previous projects...
Read MoreAn Artificial Intelligence Platform for Network-wide Congestion Detection and Prediction Using Multi-source Data
The research team has already established an online transportation platform, named the Digital Roadway Interactive Visualization and Evaluation Network (DRIVE...
Read MoreModeling and Optimizing Ridesourcing Services in Connected and Automated Cities
This research aims to develop modeling and analysis methods to capture the key behaviors and intersections of the major players...
Read MoreA Multiscale Simulation Platform for Connected and Automated Transportation Systems
Traffic simulation is an important tool that can assist researchers, analysts, and policymakers to test vehicle/traffic control algorithms, gain insights...
Read MoreTraffic Signal Optimization and Coordination in Connected Cities
This research aims to explore the basic research on developing signal control and coordination methods under the CV environment, develop...
Read MoreIntegrative Vehicle-Traffic Control in Connected/Automated Cities
In this project, the research team built on work done in a Year 1 C2SMART project, in which a decomposition...
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