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superciliously    
ad. 高傲地

高傲地

superciliously
adv 1: with a sneer; in an uncomplimentary sneering manner; "`I
don't believe in these customs,' he said sneeringly"
[synonym: {sneeringly}, {superciliously}, {snidely}]


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  • 真实闭环拉满！浙大 华为发布全新闭环仿真工具HUGSIM - 知乎
    这推动了HUGSIM的发展，这是一个闭环、真实和实时的仿真器，用于评估自动驾驶算法。 我们通过 3DGS 将捕获的2D RGB图像提升到3D空间，提高闭环场景的渲染质量，并构建闭环环境来实现这一目标。 在渲染方面，我们解决了闭环场景中新视图合成的挑战，包括视点外推和360度车辆渲染。 除了新视图合成外，HUGSIM还实现了全闭环仿真循环，根据控制命令动态更新自车和行为者状态和观察结果。 此外，HUGSIM为 KITTI-360 、Waymo、nuScenes和 PandaSet 的70多个序列以及400多个不同的场景提供了全面的基准，为现有的自动驾驶算法提供了一个公平和现实的评估平台。 HUGSIM不仅是一个直观的评估基准，还释放了在真实的闭环环境中微调自动驾驶算法的潜力。
  • [2408. 00415] DriveArena: A Closed-loop Generative Simulation Platform . . .
    This paper presented DriveArena, the first high-fidelity closed-loop simulation system designed for driving agents navigating in real scenarios
  • DrivingSphere: Building a High-fidelity 4D World for Closed-loop Simulation
    We introduce DrivingSphere, a novel geometry-aware closed-loop simulation framework that captures 2D visual and 3D geometric properties while seamlessly integrating with vision-based end-to-end driving agents
  • HUGSIM - xdimlab. github. io
    We present HUGSIM, a real-time, photo-realistic and closed-loop simulator for autonomous driving HUGSIM enables the full closed simulation loop, dynamically updating the ego and actor positions and observations based on control commands
  • GitHub - hyzhou404 HUGSIM: Official implementation of the paper HUGSIM . . .
    The dependencies for NAVSIM are already specified as the pixi environment file, so you don't need to manually install the dependencies In closed_loop py, we automatically launch autonomous driving algorithms Paths in configs sim *_base yaml should be updated as paths on your machine
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    因此，我们推出了DRIVEARENA，一个基于条件生成模型的先驱性闭环模拟器，用于训练和测试驾驶代理。 具体而言，DRIVEARENA提供了一个灵活的平台，可与任何基于摄像头输入的驾驶代理集成。 它采用模块化设计，自然支持各模块的迭代升级。 DRIVEARENA由交通管理器（Traffic Manager）和世界梦想家（World Dreamer，基于自回归生成）组成。 交通管理器可以在全球任何道路网络上生成逼真的交互式交通流，而世界梦想家则是一个具有无限自回归能力的高保真条件生成模型。 驾驶代理通过与环境交互来学习，在DRIVEARENA中，这种交互是通过驾驶代理接收来自环境的图像和状态信息，并基于这些信息执行驾驶操作来实现的。
  • Do Open-Loop Metrics Predict Closed-Loop Driving? A Cross-Benchmark . . .
    But closed-loop performance depends on whether those predictions, when used as actual driving commands, lead to safe and effective driving The gap emerges because errors compound in closed-loop scenarios—a small prediction mistake can cascade into a poor decision that the environment immediately punishes
  • From Urban Data to City‐Scale Models: A Review of Traffic Simulation . . .
    By reviewing more than 60 case studies from 23 countries, we identify trends and best practices in the design and development of city-wide traffic simulations, as well as formulate the current challenges and gaps that need to be addressed
  • DriveArena: A Closed-loop Generative Simulation Platform for Autonomous . . .
    This paper introduces DRIVEARENA, the first high-fidelity closed-loop simulation system designed for driving agents navigating real-world scenarios





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