Abstract
The Internet of Vehicles (IoV) is a transformative technology that underpins the development of intelligent transportation systems, facilitating enhanced data management and traffic safety. This systematic review seeks to examine the current state of the art in blockchain-based systems for handling unstructured vehicle data in the IoV domain, as well as to investigate feature engineering techniques for forecasting road transportation scenarios and AI-based approaches for traffic prediction and vehicle safety measures. The review is structured into four distinct sections: (1) Blockchain-based Data Sharing, (2) Driver Behavior Analysis, (3) Collision, Hazard, and Accident Prediction, and (4) AI-based Approaches for Traffic Safety. The primary goal of this review is to present a comprehensive analysis of the contemporary research landscape, outlining the potential benefits and challenges associated with the integration of blockchain and AI technologies in the IoV context. Through this detailed examination, we aim to pinpoint areas of opportunity for future research and development, ultimately paving the way for the creation of more secure, efficient, and intelligent transportation systems. The insights derived from this review will be of value to researchers, policymakers, and practitioners in the transportation and technology sectors, as they work together to shape the future of the IoV ecosystem.
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