Waymo联手DeepMind打造世界模型：基于Genie 3，让自动驾驶「脑补」罕见场景

Core Insights - Waymo has launched the Waymo World Model, a new standard in large-scale, hyper-realistic autonomous driving simulation, built on DeepMind's Genie 3 [1][4] - The model can generate highly realistic and interactive 3D environments tailored for the strict requirements of autonomous driving [4][8] - Waymo Driver has completed nearly 200 million miles of fully autonomous driving, enhancing road safety through extensive virtual world training [4][28] Group 1: Model Capabilities - Waymo World Model leverages Genie 3's extensive world knowledge to simulate rare events that are difficult to replicate in real life, such as tornadoes and encounters with elephants [4][9] - The model supports high-fidelity, multi-sensor data generation, including camera images and LiDAR point clouds, providing a comprehensive training and testing environment for autonomous systems [4][8] - The simulation allows for real-time adjustments through simple language prompts, driving inputs, or scene layouts, enhancing the model's adaptability [4][11][16] Group 2: Simulation Control Mechanisms - The model features three main control mechanisms: driving behavior control, scene layout control, and language control, enabling the simulation of various driving scenarios [11][13][16] - Driving behavior control allows for the simulation of counterfactual events, assessing how the Waymo Driver would respond under specific conditions [11] - Scene layout control enables customization of road layouts and traffic signals, while language control provides flexibility in adjusting time of day and weather conditions [13][16] Group 3: Realism and Accuracy - Waymo World Model can convert real-world videos into multi-modal simulations, achieving high levels of realism and factual accuracy [22] - The model's efficient variants allow for long-duration simulations while maintaining high fidelity, supporting large-scale testing [24] - By simulating rare scenarios, Waymo Driver prepares for complex driving situations, setting a higher safety benchmark for autonomous systems [28]