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

Zhiying Song, Tenghui Xie, Fuxi Wen, Jun Li

TL;DR

This survey reframes cooperative perception through the lens of V2X as an information sensor, addressing three pillars: information representation, fusion, and large-scale deployment. It categorizes CPM into data-, feature-, and object-level representations and analyzes fusion under ideal and non-ideal conditions, emphasizing heterogeneity, latency, and pose errors. The paper surveys architectural and scheduling approaches for scalability, including edge-assisted and hybrid networks, and highlights limitations such as task-specific designs and a lack of standardized benchmarks. The work provides guidance for designing robust, scalable cooperative perception systems suitable for real-world intelligent transportation systems and outlines directions for future research and dataset development.

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.

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

TL;DR

This survey reframes cooperative perception through the lens of V2X as an information sensor, addressing three pillars: information representation, fusion, and large-scale deployment. It categorizes CPM into data-, feature-, and object-level representations and analyzes fusion under ideal and non-ideal conditions, emphasizing heterogeneity, latency, and pose errors. The paper surveys architectural and scheduling approaches for scalability, including edge-assisted and hybrid networks, and highlights limitations such as task-specific designs and a lack of standardized benchmarks. The work provides guidance for designing robust, scalable cooperative perception systems suitable for real-world intelligent transportation systems and outlines directions for future research and dataset development.

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.
Paper Structure (12 sections, 1 figure)

This paper contains 12 sections, 1 figure.

Table of Contents

  1. Introduction
  2. Information Representation
  3. Abstracting the World
  4. Reducing Information Volume
  5. Compressing and Conveying the Messages
  6. Information Fusion
  7. Ideal Condition
  8. Heterogeneity
  9. Imperfect Communications
  10. Pose Errors
  11. Large-scale Deployment
  12. Conclusion

Figures (1)

  • Figure 1: Comparison of key characteristics between onboard sensors and information sensors.