XPENG和北京大学创建了FastDriveVLA,这是一个效率更高的自动驾驶汽车自动驾驶系统,在保持高度准确性的同时,将处理负荷削减了7.5倍。 XPENG and Peking University created FastDriveVLA, a more efficient AI system for self-driving cars, cutting processing load by 7.5 times while keeping high accuracy.

XPENG与北京大学合作开发了FastDriveVLA(Fast DriveVLA),这是2026年世界最大的AI会议之一AAAI(AAAI 2026)所接受的自主驾驶AI的视觉标志性运行框架。 XPENG, with Peking University, has developed FastDriveVLA, a visual token pruning framework for autonomous driving AI accepted at AAAI 2026, one of the world’s top AI conferences. 该系统以车辆和车道等关键视觉要素为重点,将标牌从3 249个切到812个,同时保持nuScenes基准的高度准确性,从而将计算负荷减少近7.5倍。 The system reduces computational load by nearly 7.5 times by focusing on key visual elements like vehicles and lanes, cutting tokens from 3,249 to 812 while maintaining high accuracy on the nuScenes benchmark. 在人类关注的启发下,它使用基于重建的方法来提高端对端驾驶系统的效率。 Inspired by human attention, it uses a reconstruction-based method to improve efficiency in end-to-end driving systems. 这标志着XPENG在2025年继CVPR WAD演示和VLA 2.0推出之后,第二次对AI的承认,展示了XPENG在推进L4自主驾驶方面全方位的AI能力。 This marks XPENG’s second major AI recognition in 2025, following a CVPR WAD presentation and the launch of VLA 2.0, showcasing its full-stack AI capabilities in advancing L4 autonomous driving.