Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition
Hao, Ruiyang Yu, Haibao Zhong, Jiaru Wang, Chuanye Wang, Jiahao Kan, Yiming Yang, Wenxian Fan, Siqi Yin, Huilin Qiu, Jianing
Hao, Ruiyang
Yu, Haibao
Zhong, Jiaru
Wang, Chuanye
Wang, Jiahao
Kan, Yiming
Yang, Wenxian
Fan, Siqi
Yin, Huilin
Qiu, Jianing
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Abstract
With the rapid advancement of autonomous driving technology, vehicle-to-everything (V2X) communication has emerged as a key enabler for extending perception range and enhancing driving safety by providing visibility beyond the line of sight. However, integrating multi-source sensor data from both ego-vehicles and infrastructure under real-world constraints, such as limited communication band-width and dynamic environments, presents significant tech-nical challenges. To facilitate research in this area, we organized the End-to-End Autonomous Driving through V2X Cooperation Challenge, which features two tracks: cooperative temporal perception and cooperative end-to-end plan-ning. Built on the UniV2Xframework and the V2X-Seq-SPD dataset, the challenge attracted participation from over 30 teams worldwide and established a unified benchmark for evaluating cooperative driving systems. This paper describes the design and outcomes of the challenge, highlights key research problems including bandwidth-aware fusion, robust multi-agent planning, and heterogeneous sensor integration, and analyzes emerging technical trends among top-performing solutions. By addressing practical constraints in communication and data fusion, the challenge contributes to the development of scalable and reliable V2X-cooperative autonomous driving systems.
Citation
R. Hao, H. Yu, J. Zhong, C. Wang, J. Wang, Y. Kan , et al., "Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition," 2026, pp. 1849-1860.
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Conference
2025 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW)
Keywords
40 Engineering, 46 Information and Computing Sciences, 4602 Artificial Intelligence, 4605 Data Management and Data Science
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2025 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW)
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IEEE