6 citations · 11 across the 18 of their papers we have counts for
18 papers
Real-Time In-Domain Congestion Control for the LWR Traffic Model via Control Barrier Functions
Zehang Zhu, Brian Block, Stephanie Stockar
This paper presents a control barrier function-based method for real-time in-domain congestion control of the Lighthill-Whitham-Richards traffic model. Traffic congestion is formul…
A Continuification Approach to CAV Control in Mixed Traffic via Variable Speed Limits
Brian Block, Cecilia Pasquale, Silvia Siri +2
This paper presents a method for controlling traffic via the use of connected and automated vehicles (CAVs) acting as moving bottlenecks. Current methods for moving bottleneck cont…
Optimal Finite-Horizon LQR Control for Traffic Flow via Variable Speed Limits
Brian Block, Stephanie Stockar
This article presents a finite-horizon linear quadratic regulator for the control of the first-order Lighthill-Whitham-Richards traffic model with a triangular fundamental diagram.…
Sensitivity Analysis of Performance-Based Partitioning in District Heating Networks
Audrey Blizard, Stephanie Stockar
The paper presents a sensitivity analysis of the factors affecting the optimal partitioning of a district heating network for distributed control. Leveraging a physics-based, distr…
Constrained Control of PDE Traffic Flow via Spatial Control Barrier Functions
Brian Block, Stephanie Stockar
In this paper, a constrained control approach to variable speed limit (VSL) control for macroscopic partial differential equations (PDE) traffic models is developed. Control Lyapun…
Traffic-Aware Eco-Driving Control in CAVs via Learning-based Terminal Cost Model
Mehmet Fatih Ozkan, Dennis Kibalama, Jacob Paugh +2
Connected and Automated Vehicles (CAVs) offer significant potential for improving energy efficiency and lowering vehicle emissions through eco-driving technologies. Control algorit…
Optimality Loss Minimization in Distributed Control with Application to District Heating
Audrey Blizard, Stephanie Stockar
This paper presents a novel partitioning method designed to minimize control performance degradation resulting from partitioning a system for distributed control while maintaining…
Koopman-Based Methods for EV Climate Dynamics: Comparing eDMD Approaches
Luca Meda, Stephanie Stockar
In this paper, data-driven algorithms based on Koopman Operator Theory are applied to identify and predict the nonlinear dynamics of a vapor compression system and cabin temperatur…
Modeling Driver Behavior in Speed Advisory Systems: Koopman-based Approach with Online Update
Mehmet Fatih Ozkan, Jeff Chrstos, Marcello Canova +1
Accurate driver behavior modeling is essential for improving the interaction and cooperation of the human driver with the driver assistance system. This paper presents a novel appr…
Communication-Based Distributed Control of Large-Scale District Heating Networks
Audrey Blizard, Stephanie Stockar
This paper presents a non-cooperative distributed model predictive controller for the control of large-scale District Heating Networks. To enable the design of this controller a no…
Data-Driven Personalized Energy Consumption Range Estimation for Plug-in Hybrid Electric Vehicles in Urban Traffic
Mehmet Fatih Ozkan, James Farrell, Marcello Telloni +5
In urban traffic environments, driver behaviors exhibit considerable diversity in vehicle operation, encompassing a range of acceleration and braking maneuvers as well as adherence…
Using Flexibility Envelopes for the Demand-Side Hierarchical Optimization of District Heating Networks
Audrey Blizard, Colin N. Jones, Stephanie Stockar
The demand-side control of district heating networks is notoriously challenging due to the large number of connected users and the high number of states to be considered. To overco…
LQ Control of Traffic Flow Models via Variable Speed Limits
Brian Block, Stephanie Stockar
In this paper, an extension of a linear control design for hyperbolic linear partial differential equations is presented for a first-order traffic flow model. Starting from the Lig…
Eco-Driving Control of Connected and Automated Vehicles using Neural Network based Rollout
Jacob Paugh, Zhaoxuan Zhu, Shobhit Gupta +2
Connected and autonomous vehicles have the potential to minimize energy consumption by optimizing the vehicle velocity and powertrain dynamics with Vehicle-to-Everything info en ro…
A Graph-Based Technique for the Automated Control-Oriented Modeling of District Heating Networks
Audrey Blizard, Stephanie Stockar
Advanced control strategies for delivering heat to users in a district heating network have the potential to improve performance and reduce wasted energy. To enable the design of s…
A Dynamically Similar Lab-Scale District Heating Network via Dimensional Analysis
Audrey Blizard, Stephanie Stockar
Strict user demands and large variability in external disturbances, along with limited richness in the data collected on the daily operating conditions of district heating networks…
Data-driven Driver Model for Speed Advisory Systems in Partially Automated Vehicles
Olivia Jacome, Shobhit Gupta, Stephanie Stockar +1
Vehicle control algorithms exploiting connectivity and automation, such as Connected and Automated Vehicles (CAVs) or Advanced Driver Assistance Systems (ADAS), have the opportunit…
Model Predictive Control for Automotive Climate Control Systems via Value Function Approximation
Dennis Kibalama, Yuxing Liu, Stephanie Stockar +1
Among the auxiliary loads in light-duty vehicles, the air conditioning system is the single largest energy consumer. For electrified vehicles, the impact of heating and cooling loa…