Smart Electric Vehicle Charging: Modeling Drivers’ Choices and Autonomous Vehicles’ Strategies

As transportation is increasingly electrified, understanding travel and charging choices of electric vehicle drivers and users of shared electric mobility systems is crucial for service planning and operations. Ultimately, quantitative models of users’ behavior enable the estimation of local and regional demand impinging on transportation and electricity networks and the development of approaches to manage the demand so that such networks can operate efficiently. Developing realistic models of individual behavior to use as “users’ digital twins” in planning and operations is challenging enough, due to the inherent uncertainties of how individuals make everyday choices and their heterogeneity in approaching decisions. Even more challenging is to attempt to anticipate how users might respond to new technologies and changes in infrastructure or services. In this case choice data from systems’ operations or “revealed preference” users’ surveys may not exist, be available only from early adopters, or relate to the system before the change. In this case, often the only option available is to generate new data using choice experiments. In the first part of this seminar, Dr. Daina will present pioneering work adopting these techniques to model electric vehicles driver’s charging choices under smart charging. While in the near term e-mobility is and will be dominated by human drivers, on demand e-mobility services delivered by fleets of autonomous vehicles are on the horizon. Therefore, in the second part of this talk, he will present recent work on reinforcement learning approaches to smart charging management of shared autonomous electric vehicle fleets.

Dr. Nicolò Daina is a Research Scientist in the Department of Civil Engineering and Engineering Mechanics and a Research Scholar at the Center on Global Energy Policy at Columbia University. Using data science approaches, econometric techniques and experimentation Dr. Daina seeks to characterize and model the behavior of users of integrated transportation and energy systems. By developing realistic behavioral models and embedding them in systems’ simulation and optimization, Dr. Daina’s research aims to harness the flexibility and the cooperation of end users in both planning and operations of integrated transportation and energy systems as they transition to net-zero. Dr. Daina obtained his PhD in Transport from Imperial College London in 2014. Following his PhD, he worked at Imperial College London’s Department of Civil and Environmental Engineering first as a postdoctoral research associate then as a research fellow. Before moving to Columbia University, Dr. Daina was appointed as a faculty (Chancellor’s Fellow and Lecturer in Transport Policy) at the University of Strathclyde, Glasgow in the United Kingdom. Dr. Daina is currently an Honorary Lecturer in the School of Government and Public Policy of the University of Strathclyde. He is also a member of the US’ Transportation Research Board’s Standing Committee on Alternative Fuels and Technologies.