Title: Mitigating Freeway Congestion at Bottlenecks through Variable Speed Limit Control in Connected Autonomous Vehicle Environment
Speaker: Dr. Wei Fan
Date: Friday, May 28, 2021
SYNOPSIS
This study presents an optimal variable speed limit (VSL) strategy in a connected autonomous vehicle (CAV) environment for a freeway corridor with multiple bottlenecks. The VSL control is developed by using an extended cell transmission model (CTM) which takes into account capacity decrease and mixed traffic flow, including traditional human-driven cars and heavy vehicles, and autonomous vehicles (AVs). A multiple-objective function is formulated which aims to improve the operational efficiency and smooth the speed transition. A genetic algorithm (GA) is developed to solve the integrated VSL control problem. A real-world freeway stretch is selected to test the designed control framework. Sensitivity analyses are performed to investigate impacts of both the penetration rate of CAVs and communication range. Simulation performances demonstrate that the developed VSL control not only improves the overall efficiency but also reduces tailpipe emission rate. Simulation results also show that the VSL control integrating vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I), and infrastructure-to-vehicle (I2V) communication outperforms the VSL control only. In addition, as the penetration rate of CAVs increases, better performance can be achieved.
ABOUT THE SPEAKER
Dr. Wei (David) Fan currently serves as a full professor in the Department of Civil and Environmental Engineering (CEE) at The University of North Carolina at Charlotte (UNCC). He is the Director of the USDOT University Transportation Center for Advanced Multimodal Mobility Solutions and Education. Dr. Fan holds a Ph.D. (May 2004) in Civil Engineering – Transportation from the University of Texas at Austin (Hook ’em Horns!). He was a Senior Analytical Optimization Software Developer for the R&D Department at SAS Institute Inc. located in Cary, North Carolina from June 2004 – August 2006.
Dr. Fan’s primary research interests include big data analytics for transportation (machine learning, artificial intelligence, travel demand analysis, transportation safety data analysis, and discrete choice modeling); connected and autonomous vehicles (technologies, impact analysis, simulation and modeling, optimization and control); shared mobility and multimodal transportation (carsharing, bike-sharing, public transit, and non-motorized transportation (bicycle and pedestrian) systems planning and operations); traffic system operation and control (traffic simulation, and active traffic management including variable speed limits and managed lanes); transportation system analysis and network modeling (equilibrium-based traffic assignment, network design and highway improvements, travel time reliability, freeway bottleneck identification and mitigation, and congestion pricing); operations research; and computer software development.
Dr. Fan has been and is involved in many sponsored projects (with a total of over 17.0 million dollars in funding and about 7.2 million dollars of them being my share), having been a principal or co-principal investigator on many research studies for the U. S. Department of Transportation (USDOT), Federal Highway Administration (FHWA), NCHRP, SHRP2 Education Connection, Texas Department of Transportation (TxDOT) and North Carolina Department of Transportation (NCDOT). He had published 99 journal articles thus far, and many proceeding papers and technical reports on big data analytics for transportation, connected and autonomous vehicles, shared mobility and multimodal transportation, traffic system operation and control, and transportation system analysis and network modeling. He is a registered professional engineer in Texas.