Wireless Communication as an Information Sensor for Multi-agent Cooperative Perception: A Survey

TL;DR

This survey reviews how V2X communication acts as an information sensor to enhance multi-agent cooperative perception in autonomous vehicles, focusing on information representation, fusion, and large-scale deployment challenges.

Contribution

It introduces a novel perspective by treating V2X communication as an information sensor and emphasizes real-world deployment challenges in cooperative perception.

Findings

Categorization of information representation schemes

Analysis of data reduction and compression methods

Discussion of fusion techniques under realistic conditions

Abstract

Cooperative perception extends the perception capabilities of autonomous vehicles by enabling multi-agent information sharing via Vehicle-to-Everything (V2X) communication. Unlike traditional onboard sensors, V2X acts as a dynamic "information sensor" characterized by limited communication, heterogeneity, mobility, and scalability. This survey provides a comprehensive review of recent advancements from the perspective of information-centric cooperative perception, focusing on three key dimensions: information representation, information fusion, and large-scale deployment. We categorize information representation into data-level, feature-level, and object-level schemes, and highlight emerging methods for reducing data volume and compressing messages under communication constraints. In information fusion, we explore techniques under both ideal and non-ideal conditions, including those addressing heterogeneity, localization errors, latency, and packet loss. Finally, we summarize system-level approaches to support scalability in dense traffic scenarios. Compared with existing surveys, this paper introduces a new perspective by treating V2X communication as an information sensor and emphasizing the challenges of deploying cooperative perception in real-world intelligent transportation systems.