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Research Projects

Scale-Dependent Observability of Emergent Dynamics: Application to Traffic Flow with Connected Vehicles

A single traffic flow model for 'any' spatiotemporal scale

Sponsor: National Science Foundation

Senior Investigator: Kshitij Jerath

Junior Investigator: Zhaohui (Brandon) Yang

Traffic flow modeling is typically performed at distinct scales: microscopic (that models individual vehicles), mesoscopic (that models clusters of vehicles) and macroscopic (that models traffic as a fluid flow). Creating a single modeling framework for traffic flow can not only simplify analysis and reduce computational effort, but it could also provide an opportunity to select the modeling scale that best fits a desired goal, such as prediction of congestion, platooning of connected autonomous vehicles or determining fuel efficient driving behaviors. Our physics-inspired work borrows from the field of statistical mechanics and **renormalization group theory**. We have shown that using just two vehicle-interaction and traffic flow parameters, we can perform systematic transformation from one scale to another while maintaining fidelity across multiple (but not arbitrarily large) spatial and time scales.
Rescaled models retain traffic behavior.png

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