V2X Communication

V2X: Vehicle-to-Everything

Ask about this topic

Overview

V2X studies how vehicles exchange data with other vehicles, roadside infrastructure, networks, and vulnerable road users to improve connectivity and coordinate traffic. Work spans C-V2X and 5G NR resource allocation, beam management, handover, and safety-message delivery, as well as cooperative perception and driving that share sensor features, object lists, or driving intentions. Methods include radio scheduling and optimization, multi-agent reinforcement learning, and semantic compression, often evaluated on datasets such as OPV2V, DAIR-V2X, and V2X-Real or in SUMO and CARLA simulations. A central challenge is balancing communication bandwidth, latency, and reliability with useful perception and planning gains; packet loss, changing network conditions, and the gap between simulation and real-world validation remain important constraints.

Latest papers

CardsList

67 papers6 papers in the last four weeks, level with the four weeks before. 0.0% of all new papers.

  1. Open-Source Based and ETSI Compliant Cooperative, Connected, and Automated Mini-Cars

    Mar 6, 2026Lorenzo Farina, Federico Gavioli, Salvatore Iandolo +9Autonomous DrivingV2X Communication

    DEI, Università di Bologna, 40136 Bologna, Italy · National Laboratory of Wireless Communications (WiLab), CNIT, 40136 Bologna, Italy · DIEF, University of Modena and Reggio Emilia, 41125 Modena, Italy +2

  2. Digital-Twin Losses for Lane-Compliant Trajectory Prediction at Urban Intersections

    Mar 4, 2026Kuo-Yi Chao, Erik Leo Haß, Melina Gegg +3Multi-Agent Trajectory PredictionVehicle Trajectory Prediction

    * Chair of Robotics, Artificial Intelligence and Real-Time Systems Technical University of Munich, Munich, Germany · † BMW Group, Munich, Germany

  3. An Empirical Analysis of Cooperative Perception for Occlusion Risk Mitigation

    Feb 26, 2026Aihong Wang, Tenghui Xie, Fuxi Wen +1Autonomous Driving Safety EvaluationCooperative Perception

    School of Vehicle and Mobility, Tsinghua University, China.

  4. Multi-Agent Reinforcement Learning for V2X Resource Allocation: Disentangling MARL Challenges Through Benchmarking

    Feb 18, 2026Siyuan Wang, Lei Lei, Pranav Maheshwari +2RL BenchmarksReinforcement Learning

    College of Engineering, University of Guelph, Guelph, Ontario, Canada · College of Electrical Engineering and Computer Sciences, Ningbo University, Ningbo, 315211, China

  5. Spatiotemporal Semantic V2X Framework for Cooperative Collision Prediction

    Jan 23, 2026Murat Arda Onsu, Poonam Lohan, Burak Kantarci +3Intelligent Transportation SystemsSemantic Communication

    School of Electrical Engineering and Computer Science, University of Ottawa, Ottawa, ON, Canada. · Nokia Bell Labs, 600 March Road, Kanata, ON K2K 2E6, Canada.

  6. QuantV2X: A Fully Quantized Multi-Agent System for Cooperative Perception

    Sep 3, 2025Seth Z. Zhao, Huizhi Zhang, Zhaowei Li +11V2X CommunicationCooperative Perception

    UCLA · UW-Madison · NCSU +3

  7. Teleoperated Driving: a New Challenge for 3D Object Detection in Compressed Point Clouds

    Jun 13, 2025Filippo Bragato, Michael Neri, Paolo Testolina +23D Object DetectionLidar-Based 3D Object Detection

    Department of Information Engineering, University of Padova. Padova, Italy. · Faculty of Information Technology and Communication Sciences, Tampere University, Tampere, Finland · Institute for the Wireless Internet of Things, Northeastern University, Boston, MA, USA