将车联网通信视为信息传感器，提升自动驾驶协同感知能力
Wireless Communication as an Information Sensor for Multi-agent Cooperative Perception: A Survey
- 把车联通信看作动态信息传感器，解决数据异构与传输受限问题
- 提出三类信息表示方法，压缩消息量以适应有限带宽
- 适合智能交通系统研发者与协同感知算法研究者阅读
协同感知通过车联通信（V2X）实现多智能体间信息共享，拓展自动驾驶车辆的感知范围。与传统车载传感器不同，V2X作为动态‘信息传感器’具有通信受限、异构性、移动性与可扩展性等特点。本文从信息中心视角综述近年进展，聚焦三个维度：信息表征、信息融合与大规模部署。信息表征分为数据级、特征级与目标级三类，重点介绍在通信约束下降低数据量与压缩消息的新方法。信息融合涵盖理想与非理想条件下的技术，包括处理异构性、定位误差、延迟与丢包等问题。最后总结支持密集交通场景下可扩展性的系统级方案。相比已有综述，本文首次将V2X视为信息传感器，强调其实用化部署中的挑战。
原文摘要 · Abstract (English)
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.
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