Sivaranjani Seetharaman

University of Notre Dame

Position: PhD Candidate
Rising Stars year of participation: 2018
Bio

Sivaranjani Seetharaman is a doctoral candidate in the Department of Electrical Engineering at the University of Notre Dame. She obtained her undergraduate and Master’s degrees in Electrical Engineering from the PES Institute of Technology and the Indian Institute of Science in 2011 and 2013 respectively. Sivaranjani’s research interests are in the area of distributed control for large-scale infrastructure networks with an emphasis on transportation networks and power grids. She is a recipient of the prestigious international Schlumberger Foundation Faculty for the Future fellowship (2015-present) and the Zonta International Amelia Earhart fellowship (2015-2016). She was also a Notre Dame (NSF) Ethical Leaders in STEM fellow for the year 2016-17.

Congestion in Large-Scale Transportation Networks: Analysis and Control Perspectives

Congestion in Large-Scale Transportation Networks: Analysis and Control Perspectives
Fluid-like models and their discretizations like the Cell Transmission Model have proven successful in modeling traffic networks. However, given the complexity of the dynamics, it is not surprising that the dynamical properties of these models, especially in congested regimes, are not yet well characterized. My research addresses this gap by proposing a new modeling paradigm where an analogy between discetized fluid-like traffic flow models and a class of chemical reaction networks is constructed by suitable relaxations of key conservation laws. This framework allows us to draw upon powerful structural results from chemical reaction network theory to study the existence and stability of congested steady states in large-scale transportation networks. Using these models, we also propose control techniques that optimally utilize the vast quantities of real-time data such as density estimates and measurements obtained from mobile devices and smart infrastructure to design and implement both macroscopic (network-level) and microscopic (vehicle-level) real-time control actions that provide provable guarantees on congestion mitigation in large-scale traffic networks.