EV adoption

This policy brief summarizes a series of recurring surveys that measure consumers' awareness and attitudes toward electric vehicles.

In this study, the researchers used a sample of California new electric vehicle buyers to understand if and how current adopters of new vehicle technologies will adopt automated vehicles.

This study aims to develop a prediction framework based on a Bidirectional Long Short-Term Memory Network model to suggest when battery electric vehicle drivers should charge their vehicles, in order to to provide a more accurate and precise method of predicting charging events than conventional machine learning models.

This policy brief summarizes findings from research that surveyed California PEV buyers 2–7 years after they first purchased their EV to understand whether they have continued to choose PEVs with subsequent purchases, and if not, what factors may have led to their discontinuance of the technology.