Experiments in Traffic Flow Control with Low and High Density of Autonomous Vehicles
This talk describes two experiments in traffic flow control that involve the University of Arizona CAT Vehicle Testbed. The first experiment explores how to dampen emerging waves in traffic that are due to congestive effects. This experiment grew out of theory of how traffic flow could be improved through sparse velocity control (e.g., ~5% of the vehicles) in the flow. The second experiment examines an analogous case, where 100% of the vehicles are controlled, though this time using off-the-shelf (rather than customized) cruise control algorithms. The talk will examine the hypotheses, methods, and results of these experiments, and explore the theory and motivation for the research as a means to provide insights into the obtained results. The talk will discuss how some results promise the potential for tremendous societal reduction in stress and in fuel used, and how other results indicate the need for more research to determine whether deployment at a societal scale of the available technology would result in positive, or negative, benefits in terms of safety and congestion. The research was sponsored by the National Science Foundation under award CNS-1446435, and is collaborative work with Benedetto Piccoli, Benjamin Seibold, and Dan Work.