Bandwidth-Adaptive Feature Sharing for Cooperative LIDAR Object Detection

Marvasti, Ehsan Emad; Raftari, Arash; Marvasti, Amir Emad; Fallah, Yaser P.

doi:10.1109/cavs51000.2020.9334618

Cited by 7 publications

(1 citation statement)

References 12 publications

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“…The method employs optimization algorithms to select optimal information, determine the optimal information compression, transmission and fusion mode within limited communication channels. Some studies have implemented confidence evaluation [ 44 ], and graph theory [ 45 ] to reduce information redundancy, while others have explored information compression [ 46 ], variable frequency communication, and special data formats to maximize the use of the limited communication bandwidth.…”

Section: Introductionmentioning

confidence: 99%

Perception Methods for Adverse Weather Based on Vehicle Infrastructure Cooperation System: A Review

Wang,

Wu,

Liang

et al. 2024

Sensors

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Environment perception plays a crucial role in autonomous driving technology. However, various factors such as adverse weather conditions and limitations in sensing equipment contribute to low perception accuracy and a restricted field of view. As a result, intelligent connected vehicles (ICVs) are currently only capable of achieving autonomous driving in specific scenarios. This paper conducts an analysis of the current studies on image or point cloud processing and cooperative perception, and summarizes three key aspects: data pre-processing methods, multi-sensor data fusion methods, and vehicle–infrastructure cooperative perception methods. Data pre-processing methods summarize the processing of point cloud data and image data in snow, rain and fog. Multi-sensor data fusion methods analyze the studies on image fusion, point cloud fusion and image-point cloud fusion. Because communication channel resources are limited, the vehicle–infrastructure cooperative perception methods discuss the fusion and sharing strategies for cooperative perception information to expand the range of perception for ICVs and achieve an optimal distribution of perception information. Finally, according to the analysis of the existing studies, the paper proposes future research directions for cooperative perception in adverse weather conditions.

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Section: Introductionmentioning

confidence: 99%

Perception Methods for Adverse Weather Based on Vehicle Infrastructure Cooperation System: A Review

Wang,

Wu,

Liang

et al. 2024

Sensors

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Collaborative Perception for Autonomous Driving: Current Status and Future Trend

Ren

Chen

Zhang

2022

Lecture Notes in Electrical Engineering

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Perception is one of the crucial module of the autonomous driving system, which has made great progress recently. However, limited ability of individual vehicles results in the bottleneck of improvement of the perception performance. To break through the limits of individual perception, collaborative perception has been proposed which enables vehicles to share information to perceive the environments beyond line-of-sight and field-of-view. In this paper, we provide a review of the related work about the promising collaborative perception technology, including introducing the fundamental concepts, generalizing the collaboration modes and summarizing the key ingredients and applications of collaborative perception. Finally, we discuss the open challenges and issues of this research area and give some potential further directions.

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