Abstract
Understanding driving behavior has never been more important to intelligent transportation. It has a significant impact on the advancement of safe and sociable autonomous vehicles. With the advent of smartphones and intelligent connected vehicles, portable data acquisition and efficient driving data processing are enabled, providing unprecedented potential for comprehensive driving behavior analysis (DBA). This research benefits many industries, such as vehicle energy management, autonomous driving systems, advanced driver assistance systems, intelligent traffic systems, and environmental protection. In this study, we conduct a comprehensive literature investigation of the dataset and DBA model. The dataset is reviewed based on available datasets, and we also outline the evaluation metrics of the DBA model. We provide an overview of the DBA model separately, briefly discuss five DBA tasks, and focus on reviewing the smartphone-based DBA model. In addition, we analyze the key research challenges and prospects for future work, hoping to provide guidelines for related researchers.
Published Version
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