The New Traffic Microscope- Measuring Microscopic Traffic Dynamics to Model and Control Freeway Traffic Congestion

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This NSF grant will produce a deeper understanding of freeway traffic dynamics that will be used develop the next generation of traffic models and ultimately targeted interventions to reduce the negative impacts of traffic congestion. Traffic congestion was estimated to cost the US $179 Billion in 2017. If this research can reduce those costs by only a few percent it will have a high payoff with a broad impact to society. Traffic is inherently difficult to study because one needs fine measurements over a large scale, somewhat akin to being able to read a newspaper in a satellite photo of an entire city. The current state of the art in traffic dynamics and control is based on low resolution data that only provide information about the "average vehicle." Recent results from NSF sponsored research has shown that it is critical to push to higher resolution and understand the individual vehicle interactions to advance both theory and control. This research will (1) essentially develop a "microscope" to see these individual vehicle interactions across large scale empirical data sets, (2) use the newfound dynamics to improve or replace current traffic flow models, and (3) use these traffic flow models to develop targeted interventions that will improve the effectiveness of traffic control.The microscopic details of freeway traffic dynamics are below the resolution of conventional vehicle detectors. This research will use new measurement techniques to empirically study the microscopic nature of how traffic actually flows, with the ultimate goal of building more robust traffic flow models and more effective traffic controls. The new measurement techniques extract microscopic relationships from common loop detectors, thereby using a collection of old sensors in new ways to achieve a level of resolution is unrivaled at this scale. The massive amount of high resolution data allow the research to isolate microscopic traffic dynamics that heretofore were obscured by noise. With the new clarity the microscopic relationships will lead to fundamental discoveries. The research will progress on three levels: (i) Empirically investigate suspected deficiencies of conventional traffic flow models. (ii) For the deficiencies explore the bounds of influence and the structure of the underlying mechanisms to develop a deeper understanding of the dependencies and how they impact traffic dynamics. (iii) Finally, act on the findings by developing traffic flow models to accurately capture the dynamics and explore ways in which these insights can be used to improve traffic control.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.