A Survey of Collaborative Perception in Intelligent Vehicles at Intersections

As an important component of intelligent transportation systems, collaborative perception has made great progress in recent years. In collaborative perception, multiple devices rely on communication to interact and transfer perception information and use complementary information to overcome occlusion and long-distance perception problems. Although there have been some overviews and analyses of the development status and architecture design in this field, there has not been a comprehensive review of the specific task division and goals in perception and communication. In this paper, to facilitate the quick location of specific directions or tasks in vehicle-road collaboration, we first analyze the timing and role of each task in the workflow of cooperative perception. Then, based on perception goals, we divide perception tasks into detection, segmentation, and tracking and discuss communication tasks in terms of open issues such as delay robustness, communication bandwidth, positioning errors, countermeasures against attacks, and privacy preservation computation and comprehensively review the research in each task. We summarize research in downstream tasks of collaborative perception, which are important for safe decision-making and efficient operation of intelligent transportation. We summarize the domain-relevant datasets and discuss future research trends and challenges.