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Related papers: Towards Vehicle-to-everything Autonomous Driving: …

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Vehicle-to-everything-aided autonomous driving (V2X-AD) has a huge potential to provide a safer driving solution. Despite extensive researches in transportation and communication to support V2X-AD, the actual utilization of these…

Computer Vision and Pattern Recognition · Computer Science 2025-04-10 Genjia Liu , Yue Hu , Chenxin Xu , Weibo Mao , Junhao Ge , Zhengxiang Huang , Yifan Lu , Yinda Xu , Junkai Xia , Yafei Wang , Siheng Chen

Vehicle-to-Vehicle (V2V) cooperative perception has great potential to enhance autonomous driving performance by overcoming perception limitations in complex adverse traffic scenarios (CATS). Meanwhile, data serves as the fundamental…

Autonomous driving relies on accurate perception to ensure safe driving. Collaborative perception improves accuracy by mitigating the sensing limitations of individual vehicles, such as limited perception range and occlusion-induced blind…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-01-21 Hui Zhang , Yuquan Yang , Zechuan Gong , Xiaohua Xu , Dan Keun Sung

LiDAR-based Vehicle-to-Everything (V2X) cooperative perception has demonstrated its impact on the safety and effectiveness of autonomous driving. Since current cooperative perception algorithms are trained and tested on the same dataset,…

Computer Vision and Pattern Recognition · Computer Science 2025-03-20 Baolu Li , Zongzhe Xu , Jinlong Li , Xinyu Liu , Jianwu Fang , Xiaopeng Li , Hongkai Yu

Cooperative perception enabled by Vehicle-to-Everything (V2X) communication enhances autonomous driving safety by creating a unified environmental representation through shared sensory data. While recent works have advanced multi-agent…

Computer Vision and Pattern Recognition · Computer Science 2026-05-21 Abhishek Dinkar Jagtap , Sanath Tiptur Sadashivaiah , Andreas Festag

Perception for automated driving is largely based on onboard environmental sensors, such as cameras and radar, which are cost-effective but limited by line-of-sight and field-of-view constraints. These inherent limitations may cause onboard…

Computer Vision and Pattern Recognition · Computer Science 2026-05-04 Lukas Ostendorf , Lennart Reiher , Onn Haran , Lutz Eckstein

This paper presents a comprehensive end-to-end evaluation of an infrastructure-assisted collective perception (ICP) system deployed on a highway using ITS-G5 technology. Open-road tests were conducted in the Bizkaia Connected Corridor…

Networking and Internet Architecture · Computer Science 2026-04-23 Jon Ander Iñiguez de Gordoa , Iker Alkorta , Itziar Urbieta , Gorka Velez , Andoni Mujika

Existing Vehicle-to-Everything (V2X) cooperative perception methods rely on accurate multi-agent 3D annotations. Nevertheless, it is time-consuming and expensive to collect and annotate real-world data, especially for V2X systems. In this…

Computer Vision and Pattern Recognition · Computer Science 2025-06-19 Seth Z. Zhao , Hao Xiang , Chenfeng Xu , Xin Xia , Bolei Zhou , Jiaqi Ma

Perception of the driving environment is critical for collision avoidance and route planning to ensure driving safety. Cooperative perception has been widely studied as an effective approach to addressing the shortcomings of single-vehicle…

Computer Vision and Pattern Recognition · Computer Science 2023-12-19 Chenguang Liu , Jianjun Chen , Yunfei Chen , Ryan Payton , Michael Riley , Shuang-Hua Yang

Cooperative perception, leveraging shared information from multiple vehicles via vehicle-to-vehicle (V2V) communication, plays a vital role in autonomous driving to alleviate the limitation of single-vehicle perception. Existing works have…

Computer Vision and Pattern Recognition · Computer Science 2025-05-07 Chenguang Liu , Jianjun Chen , Yunfei Chen , Yubei He , Zhuangkun Wei , Hongjian Sun , Haiyan Lu , Qi Hao

Collective Perception (CP) has emerged as a promising approach to overcome the limitations of individual perception in the context of autonomous driving. Various approaches have been proposed to realize collective perception; however, the…

Computer Vision and Pattern Recognition · Computer Science 2025-09-30 Sven Teufel , Jörg Gamerdinger , Oliver Bringmann

Environmental perception in Automated Valet Parking (AVP) has been a challenging task due to severe occlusions in parking garages. Although Collaborative Perception (CP) can be applied to broaden the field of view of connected vehicles, the…

Robotics · Computer Science 2024-03-25 Yukuan Jia , Jiawen Zhang , Shimeng Lu , Baokang Fan , Ruiqing Mao , Sheng Zhou , Zhisheng Niu

Urban intersections, dense with pedestrian and vehicular traffic and compounded by GPS signal obstructions from high-rise buildings, are among the most challenging areas in urban traffic systems. Traditional single-vehicle intelligence…

Robotics · Computer Science 2025-06-12 Qianxin Qu , Xinyu Zhang , Yifan Cheng , Yijin Xiong , Chen Xia , Qian Peng , Ziqiang Song , Kang Liu , Xin Wu , Jun Li

Collaborative perception enables vehicles to overcome individual perception limitations by sharing information, allowing them to see further and through occlusions. In real-world scenarios, models on different vehicles are often…

Computer Vision and Pattern Recognition · Computer Science 2025-09-12 Hao Si , Ehsan Javanmardi , Manabu Tsukada

Vehicle-to-Everything (V2X) network has enabled collaborative perception in autonomous driving, which is a promising solution to the fundamental defect of stand-alone intelligence including blind zones and long-range perception. However,…

Computer Vision and Pattern Recognition · Computer Science 2024-10-01 Ruiqing Mao , Jingyu Guo , Yukuan Jia , Yuxuan Sun , Sheng Zhou , Zhisheng Niu

Modern autonomous vehicle perception systems are often constrained by occlusions, blind spots, and limited sensing range. While existing cooperative perception paradigms, such as Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I),…

Computer Vision and Pattern Recognition · Computer Science 2026-03-27 Weijia Li , Haoen Xiang , Tianxu Wang , Shuaibing Wu , Qiming Xia , Cheng Wang , Chenglu Wen

Optical sensors and learning algorithms for autonomous vehicles have dramatically advanced in the past few years. Nonetheless, the reliability of today's autonomous vehicles is hindered by the limited line-of-sight sensing capability and…

Computer Vision and Pattern Recognition · Computer Science 2022-11-21 Jiaxun Cui , Hang Qiu , Dian Chen , Peter Stone , Yuke Zhu

As self-driving cars increasingly penetrate our daily lives, vehicle-to-everything (V2X) communications are emerging as one of the key enabler technologies. However, the dynamicity of vehicles (one of whose causes is the mobility of…

Systems and Control · Electrical Eng. & Systems 2024-01-30 Dhruba Sunuwar , Seungmo Kim

Collaborative perception (CP) is a promising method for safe connected and autonomous driving, which enables multiple vehicles to share sensing information to enhance perception performance. However, compared with single-vehicle perception,…

Cryptography and Security · Computer Science 2025-02-13 Senkang Hu , Yihang Tao , Zihan Fang , Guowen Xu , Yiqin Deng , Sam Kwong , Yuguang Fang

Surrounding perceptions are quintessential for safe driving for connected and autonomous vehicles (CAVs), where the Bird's Eye View has been employed to accurately capture spatial relationships among vehicles. However, severe inherent…

Networking and Internet Architecture · Computer Science 2024-08-22 Zhengru Fang , Senkang Hu , Haonan An , Yuang Zhang , Jingjing Wang , Hangcheng Cao , Xianhao Chen , Yuguang Fang