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Date

1-24-2019

Description

Although connected vehicles (CVs) will soon go beyond testbeds, CVs and human-driven vehicles (HVs) will co-exist over a long period. Hence, it is critical to consider the interactions between these two types of vehicles in traffic flow modeling. In this study, we aim to develop a macroscopic model to understand how CVs would impact HVs in the traffic stream. Grounded on the second-order traffic flow model, we study the relationships among flow, density, and speed by two sets of formulations for the groups of CVs and HVs, respectively. A set of friction factors, which indicate CVs' impact to HVs, are introduced to the speed equation for accounting CV speed impacts. Then extended Kalman Filter is employed to update both model parameters and friction factors in real-time. By using CVs trajectory data as measurements, the difference between CV average speed and overall traffic mean speed will be fully accounted. The proposed model will serve as a basis for designing CV-based traffic control function, such as speed harmonization, on highways.

This webinar is based on a study funded by the National Institute for Transportation and Communities (NITC) and conducted at the University of Utah. Read more about the research: Vehicle Sensor Data (VSD) Based Traffic Control in Connected Automated Vehicle (CAV) Environment.

Biographical

Dr. Yang is an Assistant Professor in Transportation Engineering at the University of Utah. He received his Ph.D. and M.S. degrees in Civil Engineering from University of Maryland, College Park. His current research areas include traffic operations with connected automated vehicles, evacuation planning and operation, big data applications in transportation, traffic safety, and network flow modeling. His researches are sponsored by NSF, USDOT, UDOT, and MSHA. He is the member of TRB Traffic Signal System and Emergency Evacuations committees. He is also an editorial board member of ASCE Journal of Urban Planning and Development and panelist of NSF and NCHRP.

Subjects

Autonomous vehicles -- United States, Traffic Engineering, Transportation

Disciplines

Transportation | Transportation Engineering | Urban Studies | Urban Studies and Planning

Persistent Identifier

https://archives.pdx.edu/ds/psu/27616

Webinar: Modeling Freeway Traffic in a Mixed Environment: Connected and Human-Driven Vehicles

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