A Deep Learning Approach for Macroscopic Energy Consumption Prediction with Microscopic Quality for Electric Vehicles

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.

Decision Making Feature Engineering +2

A Real-Time Energy and Cost Efficient Vehicle Route Assignment Neural Recommender System

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.

Recommendation Systems

Explainable AI for a No-Teardown Vehicle Component Cost Estimation: A Top-Down Approach

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.