no code implementations • 25 Nov 2021 • Ayman Moawad, Krishna Murthy Gurumurthy, Omer Verbas, Zhijian Li, Ehsan Islam, Vincent Freyermuth, Aymeric Rousseau
For this work, we leveraged a high-performance, agent-based transportation tool to model trips that occur in the Greater Chicago region under various scenario changes, along with physics-based modeling and simulation tools to provide high-fidelity energy consumption values.
no code implementations • 21 Oct 2021 • Ayman Moawad, Zhijian Li, Ines Pancorbo, Krishna Murthy Gurumurthy, Vincent Freyermuth, Ehsan Islam, Ram Vijayagopal, Monique Stinson, Aymeric Rousseau
This paper presents a neural network recommender system algorithm for assigning vehicles to routes based on energy and cost criteria.
no code implementations • 15 Jun 2020 • Ayman Moawad, Ehsan Islam, Namdoo Kim, Ram Vijayagopal, Aymeric Rousseau, Wei Biao Wu
The broader ambition of this article is to popularize an approach for the fair distribution of the quantity of a system's output to its subsystems, while allowing for underlying complex subsystem level interactions.