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With the tremendous advancement of deep learning and communication technology, Vehicle-to-Everything (V2X) cooperative perception has the potential to address limitations in sensing distant objects and occlusion for a single-agent…

Artificial Intelligence · Computer Science 2025-09-30 An Guo , Shuoxiao Zhang , Enyi Tang , Xinyu Gao , Haomin Pang , Haoxiang Tian , Yanzhou Mu , Wu Wen , Chunrong Fang , Zhenyu Chen

Vehicle-to-everything (V2X) autonomous driving opens up a promising direction for developing a new generation of intelligent transportation systems. Collaborative perception (CP) as an essential component to achieve V2X can overcome the…

Computer Vision and Pattern Recognition · Computer Science 2023-09-01 Si Liu , Chen Gao , Yuan Chen , Xingyu Peng , Xianghao Kong , Kun Wang , Runsheng Xu , Wentao Jiang , Hao Xiang , Jiaqi Ma , Miao Wang

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…

Other Computer Science · Computer Science 2025-05-05 Zhiying Song , Tenghui Xie , Fuxi Wen , Jun Li

Sharing and joint processing of camera feeds and sensor measurements, known as Cooperative Perception (CP), has emerged as a new technique to achieve higher perception qualities. CP can enhance the safety of Autonomous Vehicles (AVs) where…

Computer Vision and Pattern Recognition · Computer Science 2024-04-15 Ahmad Sarlak , Hazim Alzorgan , Sayed Pedram Haeri Boroujeni , Abolfazl Razi , Rahul Amin

Autonomous Vehicles (AVs) rely on individual perception systems to navigate safely. However, these systems face significant challenges in adverse weather conditions, complex road geometries, and dense traffic scenarios. Cooperative…

Robotics · Computer Science 2025-03-25 Ahmad Sarlak , Rahul Amin , Abolfazl Razi

In this paper, we investigate the application of Vehicle-to-Everything (V2X) communication to improve the perception performance of autonomous vehicles. We present a robust cooperative perception framework with V2X communication using a…

Computer Vision and Pattern Recognition · Computer Science 2022-08-09 Runsheng Xu , Hao Xiang , Zhengzhong Tu , Xin Xia , Ming-Hsuan Yang , Jiaqi Ma

Vehicle-to-everything (V2X) communication techniques enable the collaboration between vehicles and many other entities in the neighboring environment, which could fundamentally improve the perception system for autonomous driving. However,…

Computer Vision and Pattern Recognition · Computer Science 2022-07-19 Yiming Li , Dekun Ma , Ziyan An , Zixun Wang , Yiqi Zhong , Siheng Chen , Chen Feng

As a pivotal technology for autonomous driving, collaborative perception enables vehicular agents to exchange perceptual data through vehicle-to-everything (V2X) communications, thereby enhancing perception accuracy of all collaborators.…

Systems and Control · Electrical Eng. & Systems 2025-09-23 Guowei Liu , Le Liang , Chongtao Guo , Hao Ye , Shi Jin

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

Accurate 3D object detection is essential for ensuring the safety of autonomous vehicles. Cooperative perception, which leverages vehicle-to-everything (V2X) communication to share perceptual data, enhances detection but is vulnerable to…

Computer Vision and Pattern Recognition · Computer Science 2026-05-05 Xi Zhou , Tao Huang , Qing-Long Han , Rana Abbas , Mostafa Rahimi Azghadi

Infrastructure sensors installed at elevated positions offer a broader perception range and encounter fewer occlusions. Integrating both infrastructure and ego-vehicle data through V2X communication, known as vehicle-infrastructure…

Robotics · Computer Science 2024-08-21 Jiaru Zhong , Haibao Yu , Tianyi Zhu , Jiahui Xu , Wenxian Yang , Zaiqing Nie , Chao Sun

Autonomous driving has attracted significant attention from both academia and industries, which is expected to offer a safer and more efficient driving system. However, current autonomous driving systems are mostly based on a single…

Computer Vision and Pattern Recognition · Computer Science 2025-04-16 Senkang Hu , Zhengru Fang , Yiqin Deng , Xianhao Chen , Yuguang Fang

Perceiving the complex driving environment precisely is crucial to the safe operation of autonomous vehicles. With the tremendous advancement of deep learning and communication technology, Vehicle-to-Everything (V2X) collaboration has the…

Software Engineering · Computer Science 2024-08-30 An Guo , Xinyu Gao , Zhenyu Chen , Yuan Xiao , Jiakai Liu , Xiuting Ge , Weisong Sun , Chunrong Fang

Occlusion is a major challenge for LiDAR-based object detection methods. This challenge becomes safety-critical in urban traffic where the ego vehicle must have reliable object detection to avoid collision while its field of view is…

Robotics · Computer Science 2023-09-20 Minh-Quan Dao , Julie Stephany Berrio , Vincent Frémont , Mao Shan , Elwan Héry , Stewart Worrall

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

Cooperative perception of connected vehicles comes to the rescue when the field of view restricts stand-alone intelligence. While raw-level cooperative perception preserves most information to guarantee accuracy, it is demanding in…

Information Theory · Computer Science 2023-02-28 Yukuan Jia , Ruiqing Mao , Yuxuan Sun , Sheng Zhou , Zhisheng Niu

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

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…

In recent years, autonomous driving has garnered significant attention due to its potential for improving road safety through collaborative perception among connected and autonomous vehicles (CAVs). However, time-varying channel variations…

Computer Vision and Pattern Recognition · Computer Science 2024-03-05 Yuang Zhang , Haonan An , Zhengru Fang , Guowen Xu , Yuan Zhou , Xianhao Chen , Yuguang Fang

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
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