Deep learning is a rapidly advancing technology with the potential to revolutionize the field of autonomous electric vehicles (AEVs). This article presents an overview of the emergent trends in deep learning applications for AEVs over the past five years. The study employs a comprehensive literature review of research studies (sourced from three scientific databases, Scopus, Web of Science, and IEEE Xplore) to map the evolution of these trends from 2019 to 2024. The findings reveal five key areas of deep learning application: collision avoidance, energy management, electric vehicle charging, connected vehicles (V2V and V2I), and eco-driving. Each area is discussed in detail, providing insights into existing applications and research developments in each field.