IDEaS Short Talks and Networking Social
“Real-Time Intelligence in Electric Vehicle Mobility” by Omar Asensio
Monday, October 22nd
Part of Two Short 30-MinuteTalks from 2-3 pm
Networking Social from 3-4 pm
Technology Square Research Building (TSRB) Auditorium
(You are welcome to attend any part of these events as your schedule permits.)
IDEaS is running a series of short talks to learn about research across the Georgia Tech campus. The presentations are from broadly different topics and accessible to those in other research areas.
Assistant Professor in the School of Public Policy
Georgia Institute of Technology
2:30 - 3:00 pm
Real-Time Intelligence in Electric Vehicle Mobility
Mobile apps have changed the scale and techniques by which individual mobility decisions can be analyzed. In this talk, I will discuss the use of real-time data from digital platforms as a means to discover social and behavioral mechanisms of energy use in emerging electric vehicle (EV) charging infrastructure. I will use data from the world’s most popular EV charging station locator app to evaluate consumer sentiment and test theoretical predictions about government service provision in public versus privately managed charging infrastructure—particularly in dealing with policy challenges such as charge rage, congestion and over-consumption. I will discuss the results of a real-time pricing experiment with a large U.S. automaker to examine whether behavioral “nudges” can motivate more efficient resource sharing among employees and peer groups as complements to price policies. I will then use neural network based language models to evaluate popular sentiment in 12,720 electric vehicle charging stations across 651 core-based statistical areas (CBSAs) in the United States from 2011-2015. Contrary to expectations, we find that nearly 40% of EV drivers have a poor experience at EV stations, a problem that needs to be fixed as the market expands.
Omar I. Asensio is an assistant professor and Class of 1969 teaching fellow in the School of Public Policy at Georgia Tech. His research focuses on the intersection of big data and public policy, with applications to energy systems and behavior, smart cities, vehicle electrification and applied machine learning in transportation and smart mobility. He is a faculty affiliate at the Institute for Data Engineering & Science (IDEaS), the Machine Learning Center, the Strategic Energy Institute, and the Climate and Energy Policy Laboratory. Dr. Asensio was recently awarded the 40 for 40 early career fellowship by the Association for Public Policy Analysis and Management.