Collaborative Sensing and Communication for Intelligent Connected Vehicles: A Comprehensive Survey

Intelligent Connected Vehicles (ICVs) enable collaborative perception by integrating sensing and communication modules, which are critical for addressing safety challenges in autonomous driving and modern transportation systems. While prior studies have explored collaborative perception, there remains a lack of comprehensive reviews from the perspective of both sensing and communication, especially in relation to the practical needs of the Internet of Vehicles (IoVs). This paper focuses on the integration of sensing and communication within collaborative perception systems, offering a detailed examination of perception mechanisms, collaboration strategies, and applications in the context of IoVs. Specifically, we begin by introducing commonly used sensing and communication technologies in automotive network applications. We then systematically discuss the fundamental components of a collaborative perception system, including sensor data processing, collaboration mechanisms, and the assessment of perception quality. Next, we address the challenges associated with sensing, collaboration, and security in perception systems, and explore potential solutions. Additionally, we review specific perception applications and discuss methods for evaluating algorithm performance using existing tools, as well as global practices in collaborative perception. Finally, we identify several open research issues and propose directions for future studies to advance the field.