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While Vehicle-to-Vehicle (V2V) collaboration extends sensing ranges through multi-agent data sharing, its reliability remains severely constrained by ground-level occlusions and the limited perspective of chassis-mounted sensors, which…

Computer Vision and Pattern Recognition · Computer Science 2026-03-17 Xianke Wu , Songlin Bai , Chengxiang Li , Zhiyao Luo , Yulin Tian , Fenghua Zhu , Yisheng Lv , Yonglin Tian

Modern perception systems of autonomous vehicles are known to be sensitive to occlusions and lack the capability of long perceiving range. It has been one of the key bottlenecks that prevents Level 5 autonomy. Recent research has…

Computer Vision and Pattern Recognition · Computer Science 2023-03-21 Runsheng Xu , Xin Xia , Jinlong Li , Hanzhao Li , Shuo Zhang , Zhengzhong Tu , Zonglin Meng , Hao Xiang , Xiaoyu Dong , Rui Song , Hongkai Yu , Bolei Zhou , Jiaqi Ma

Cooperative perception has been widely used in autonomous driving to alleviate the inherent limitation of single automated vehicle perception. To enable cooperation, vehicle-to-vehicle (V2V) communication plays an indispensable role. This…

Signal Processing · Electrical Eng. & Systems 2023-11-20 Chenguang Liu , Yunfei Chen , Jianjun Chen , Ryan Payton , Michael Riley , Shuang-Hua Yang

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…

The paper addresses the vehicle-to-X (V2X) data fusion for cooperative or collective perception (CP). This emerging and promising intelligent transportation systems (ITS) technology has enormous potential for improving efficiency and safety…

Multi-agent collaborative perception could significantly upgrade the perception performance by enabling agents to share complementary information with each other through communication. It inevitably results in a fundamental trade-off…

Computer Vision and Pattern Recognition · Computer Science 2022-09-27 Yue Hu , Shaoheng Fang , Zixing Lei , Yiqi Zhong , Siheng Chen

Vehicle-to-Infrastructure (V2I) collaborative perception leverages data collected by infrastructure's sensors to enhance vehicle perceptual capabilities. LiDAR, as a commonly used sensor in cooperative perception, is widely equipped in…

Computer Vision and Pattern Recognition · Computer Science 2025-03-06 Xinxin Feng , Haoran Sun , Haifeng Zheng

Achieving fully autonomous driving with enhanced safety and efficiency relies on vehicle-to-everything cooperative perception, which enables vehicles to share perception data, thereby enhancing situational awareness and overcoming the…

Computer Vision and Pattern Recognition · Computer Science 2025-09-03 Tao Huang , Jianan Liu , Xi Zhou , Dinh C. Nguyen , Mostafa Rahimi Azghadi , Yuxuan Xia , Qing-Long Han , Sumei Sun

Connected Autonomous Vehicles (CAVs) benefit from Vehicle-to-Everything (V2X) communication, which enables the exchange of sensor data to achieve Collaborative Perception (CP). To reduce cumulative errors in perception modules and mitigate…

Computer Vision and Pattern Recognition · Computer Science 2025-12-09 Lei Wan , Hannan Ejaz Keen , Alexey Vinel

Cooperative perception among autonomous agents overcomes the limitations of single-agent sensing, but bandwidth constraints in vehicle-to-everything (V2X) networks require efficient communication policies. Existing approaches rely on…

Multiagent Systems · Computer Science 2026-03-24 Aayam Bansal , Ishaan Gangwani

Collaborative autonomous driving with multiple vehicles usually requires the data fusion from multiple modalities. To ensure effective fusion, the data from each individual modality shall maintain a reasonably high quality. However, in…

Artificial Intelligence · Computer Science 2024-08-02 Zhe Huang , Shuo Wang , Yongcai Wang , Wanting Li , Deying Li , Lei Wang

The emergence of 6G wireless networks promises to revolutionize vehicular communications by enabling ultra-reliable, low-latency, and high-capacity data exchange. In this context, collaborative perception techniques, where multiple vehicles…

Signal Processing · Electrical Eng. & Systems 2025-06-26 Soheyb Ribouh , Osama Saleem , Mohamed Ababsa

Cooperative perception enabled by Vehicle-to-Everything (V2X) communication holds significant promise for enhancing the perception capabilities of autonomous vehicles, allowing them to overcome occlusions and extend their field of view.…

Computer Vision and Pattern Recognition · Computer Science 2025-03-14 Hao Xiang , Zhaoliang Zheng , Xin Xia , Seth Z. Zhao , Letian Gao , Zewei Zhou , Tianhui Cai , Yun Zhang , Jiaqi Ma

Recent advancements in Vehicle-to-Everything communication technology have enabled autonomous vehicles to share sensory information to obtain better perception performance. With the rapid growth of autonomous vehicles and intelligent…

Computer Vision and Pattern Recognition · Computer Science 2023-03-15 Hao Xiang , Runsheng Xu , Xin Xia , Zhaoliang Zheng , Bolei Zhou , Jiaqi Ma

Multi-agent collaboration enhances the perception capabilities of individual agents through information sharing. However, in real-world applications, differences in sensors and models across heterogeneous agents inevitably lead to domain…

Computer Vision and Pattern Recognition · Computer Science 2025-11-04 Junfei Zhou , Penglin Dai , Quanmin Wei , Bingyi Liu , Xiao Wu , Jianping Wang

Cooperative perception, offering a wider field of view than standalone perception, is becoming increasingly crucial in autonomous driving. This perception is enabled through vehicle-to-vehicle (V2V) communication, allowing connected…

Information Theory · Computer Science 2024-09-17 Yucheng Sheng , Le Liang , Hao Ye , Shi Jin , Geoffrey Ye Li

Cooperative sensing and heterogeneous information fusion are critical to realize vehicular cyber-physical systems (VCPSs). This paper makes the first attempt to quantitatively measure the quality of VCPS by designing a new metric called Age…

Networking and Internet Architecture · Computer Science 2023-01-30 Xincao Xu , Kai Liu , Penglin Dai , Ruitao Xie , Jingjing Cao , Jiangtao Luo

Recent advancements in Vehicle-to-Everything (V2X) technologies have enabled autonomous vehicles to share sensing information to see through occlusions, greatly boosting the perception capability. However, there are no real-world datasets…

Computer Vision and Pattern Recognition · Computer Science 2024-12-18 Hao Xiang , Zhaoliang Zheng , Xin Xia , Runsheng Xu , Letian Gao , Zewei Zhou , Xu Han , Xinkai Ji , Mingxi Li , Zonglin Meng , Li Jin , Mingyue Lei , Zhaoyang Ma , Zihang He , Haoxuan Ma , Yunshuang Yuan , Yingqian Zhao , Jiaqi Ma

In V2X collaborative perception, the domain gaps between heterogeneous nodes pose a significant challenge for effective information fusion. Pose errors arising from latency and GPS localization noise further exacerbate the issue by leading…

Computer Vision and Pattern Recognition · Computer Science 2025-01-28 Sichao Wang , Ming Yuan , Chuang Zhang , Qing Xu , Lei He , Jianqiang Wang

Vehicle-to-Everything (V2X) communications enable the exchange of information among vehicles to improve road safety and traffic efficiency. As V2X deployments progress, vehicles are expected to support an increasing number of V2X services,…

Networking and Internet Architecture · Computer Science 2026-03-03 Miguel Sepulcre , Javier Tortosa-Garcia , Javier Gozalvez