Traffic Signal Detection and Recognition Algorithms for Autonomous Vehicles: A Brief Review

In this paper, we present a brief review of the most prevalent computer vision–based traffic signal recognition studies in the literature. Based on the adopted computer vision approaches, we classify the traffic signal recognition studies into three categories: model-based, classical machine learning–based, and deep learning–based methods. Additionally, we include an extensive analysis of the traffic signal data sets used for training and evaluating traffic signal recognition deep learning models. This paper provides researchers and practitioners with insight into the research trends in traffic signal recognition used in vehicle perception, emphasizing various adopted methodologies and their detailed performance parameters.