A review of collaborative intelligent perception methods for vehicle-road systems

HONG Dongyang; ZHANG Hui; ZHANG Yiyun; WANG Yutong; HAN Yushan; CAO Yuanzhouhan; LI Yidong

doi:10.11959/j.issn.2096-6652.202528

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A review of collaborative intelligent perception methods for vehicle-road systems

Surveys and Prospectives | 更新时间：2025-07-21

- A review of collaborative intelligent perception methods for vehicle-road systems
- Chinese Journal of Intelligent Science and Technology Vol. 7, Issue 2, Pages: 143-164(2025)
- 作者机构：
  
  1.北京交通大学计算机科学与技术学院，北京100044
  2.中国科学院自动化研究所复杂系统管理与控制国家重点实验室，北京 100190
- 作者简介：
- 基金信息：
  
  Fundamental Research Funds for the Central Universities(2024JBMC045);Youth Fund of The National Natural Science Foundation of China(62203040)
- DOI：10.11959/j.issn.2096-6652.202528
  CLC： TP39
- Received：07 March 2025，
  
  Revised：2025-06-09，
  
  Published：15 June 2025
- 稿件说明：
移动端阅览
洪东洋,张慧,张译匀等.车路群智协同感知方法综述[J].智能科学与技术学报,2025,07(02):143-164.

HONG Dongyang,ZHANG Hui,ZHANG Yiyun,et al.A review of collaborative intelligent perception methods for vehicle-road systems[J].Chinese Journal of Intelligent Science and Technology,2025,07(02):143-164.
洪东洋,张慧,张译匀等.车路群智协同感知方法综述[J].智能科学与技术学报,2025,07(02):143-164. DOI： 10.11959/j.issn.2096-6652.202528.

HONG Dongyang,ZHANG Hui,ZHANG Yiyun,et al.A review of collaborative intelligent perception methods for vehicle-road systems[J].Chinese Journal of Intelligent Science and Technology,2025,07(02):143-164. DOI： 10.11959/j.issn.2096-6652.202528.

摘要

单车智能系统在感知层面存在一定的局限性，如超视距感知能力不足、缺乏全局环境感知视角、在极端场景下的感知稳定性受限等。为提升车辆感知能力，车路群智协同感知技术应运而生。该技术通过多个智能体（如车辆、基础设施等）共享感知信息，并对信息进行整合和分析，获取更全面、准确的环境认知。聚焦于车路群智协同感知方法的最新进展：首先，介绍车路群智协同感知方法的基础技术支撑；其次，根据数据处理和交互方法，将其划分为4类协同模式；然后，深入探讨了3种主要的协同感知方法以及常用的大规模协同感知数据集；最后，讨论了车路群智协同感知技术面临的挑战和未来研究展望。车路群智协同感知方法有助于弥补单一智能体感知的不足，实现对环境的全面感知。

Abstract

The intelligent system of a single vehicle has certain perception limitations

such as the inability to perceive beyond visual range

the lack of global perception capabilities

and restricted perception capabilities in extreme situations. To enhance vehicle perception capabilities

vehicle-road collaborative intelligent perception technology has emerged. This technology enables multiple intelligent agents (such as vehicles

infrastructure

etc.) to share perceived information

integrate and analyze it

and thereby gain a more comprehensive and accurate understanding of the environment. This paper focuses on the latest developments in vehicle-road collaborative intelligent perception methods. Firstly

it introduces the fundamental technological support for vehicle-road collaborative intelligent perception methods. Secondly

it categorizes collaborative modes into four types based on data processing and interaction methods. Then

it delves into three primary collaborative perception methods and commonly used large-scale collaborative perception datasets. Finally

it discusses the challenges faced by vehicle-road collaborative intelligent perception technology and the outlook for future research. Vehicle-road collaborative intelligent perception methods help to compensate for the deficiencies of single-agent perception and achieve comprehensive environmental perception.

关键词

Keywords

references

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