Prnewswire·2025-12-29 05:35Core Insights - XPENG, in collaboration with Peking University, has developed FastDriveVLA, a novel visual token pruning framework for autonomous driving AI, which has been accepted at AAAI 2026, a prestigious AI conference with an acceptance rate of 17.6% [1][10]. Technology Development - FastDriveVLA focuses on efficient visual token pruning, allowing AI to prioritize essential visual information while filtering out irrelevant data, thereby enabling autonomous driving systems to "drive like a human" [2][4]. - The framework employs an adversarial foreground-background reconstruction strategy to enhance the model's ability to retain valuable tokens, achieving a significant reduction in computational load [5]. Performance Metrics - On the nuScenes autonomous driving benchmark, FastDriveVLA demonstrated state-of-the-art performance, achieving a nearly 7.5x reduction in computational load when visual tokens were reduced from 3,249 to 812, while maintaining high planning accuracy [5]. Industry Recognition - This marks the second recognition for XPENG at a top-tier global AI conference in 2025, following its participation in CVPR WAD, where it presented advancements in autonomous driving foundation models [6]. - XPENG's commitment to achieving L4 level autonomous driving is underscored by its full-stack in-house capabilities, which encompass model architecture design, training, and vehicle deployment [7]. Company Overview - XPENG is positioned as a leader in future mobility transformation, with R&D centers across China and a global strategy for research, development, and sales, including a presence in the United States and Europe [8][9].