2025/02/11 by Z. Wu, Wu, Ziyong, Lei Yu +2 · 1 citation
Computer Science · Decision Sciences · #E-Learning and Knowledge Management #FOS: Computer and information sciences #Multiagent Systems (cs.MA) #Online Learning and Analytics #Personal Information Management and User Behavior
paper · pdf · doi:10.48550/arxiv.2502.07852
openalex publication_date 2025/02/11 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/01
Collaborative perception is a cornerstone of intelligent connected vehicles, enabling them to share and integrate sensory data to enhance situational awareness. However, measuring the impact of high transmission delay and inconsistent delay on collaborative perception in real communication scenarios, as well as improving the effectiveness of collaborative perception under such conditions, remain significant challenges in the field. To address these challenges, we incorporate the key factor of information freshness into the collaborative perception mechanism and develop a model that systematically measures and analyzes the impacts of real-world communication on collaborative perception performance. This provides a new perspective for accurately evaluating and optimizing collaborative perception performance. We propose and validate an Age of Information (AoI)-based optimization framework that strategically allocates communication resources to effectively control the system's AoI, thereby significantly enhancing the freshness of information transmission and the accuracy of perception. Additionally, we introduce a novel experimental approach that comprehensively assesses the varying impacts of different types of delay on perception results, offering valuable insights for perception performance optimization under real-world communication scenarios.