Collaborative Research: CCRI: New: An Open Source Simulation Platform for AI Research on Autonomous Driving

合作研究：CCRI：新：自动驾驶人工智能研究的开源仿真平台

• 批准号: 2235013
• 负责人: Trevor Darrell
• 金额: $ 90万
• 依托单位: University of California-Berkeley
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-03-15 至 2026-02-28
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2235013&HistoricalAwards=false
• 关键词: Collaborative; Research; CCRI; New; Open

Autonomous driving is transforming daily life and economy, with promised benefits like safe transportation and efficient mobility. Much of today’s research on autonomous driving experiments on expensive commercial vehicles. It is costly and risky to evaluate AI and machine learning methods on physical vehicles in real world. Driving simulator provides a cost-effective and safe alternative for the development and evaluation of new AI algorithms. However, existing driving simulators with limited assets and complexity cannot accommodate the needs of the rapidly progressing AI fields. This project aims to develop an open-ended driving simulation platform that fosters innovations in various aspects of autonomous driving from perception to decision-making. This platform will support realistic driving simulation with a diverse range of traffic assets and scenarios imported from real world. It will become a common experimental ground for researchers in academia and industry to develop new AI methods, share data and models, and benchmark the progress. The platform will grow into a community research infrastructure and have significant impacts on the blooming autonomous driving industry. Additionally, it will provide interactive teaching toolkits for STEM education, particularly for students from underserved communities. In this project, investigators will develop an open-source simulation platform called MetaDriverse for AI research on autonomous driving. This platform will serve as a research infrastructure and facilitate compelling research opportunities in various disciplines, including computer vision, computer graphics, machine learning, and human-machine interaction. MetaDriverse will feature realistic visual appearance, interactive real-world scenarios and assets, and intuitive human control interface, allowing for the simulation of real-world driving experiences. It will also provide a wide range of tasks and benchmarks and the flexibility to design new ones, which will gauge the community’s collective effort and accelerate the research progress. The key features and capabilities of the platform include (i) realistic visual perception and neural rendering, (ii) interactive simulation of real-world traffic scenarios, (iii) comprehensive benchmarks and model zoo, and (iv) community’s collective effort. This infrastructure will foster a wide range of opportunities and collaborations in the autonomous driving and intelligent transportation industries and bring significant societal and economic impacts.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

自主驾驶正在改变日常生活和经济，并具有安全的运输和有效的流动性等承诺的好处。当今关于昂贵商用车的自动驾驶实验的大部分研究。评估现实世界中物理车辆的AI和机器学习方法是昂贵和风险的。驾驶模拟器为开发和评估新的AI算法提供了一种经济高效且安全的替代方案。但是，现有资产和复杂性有限的驾驶模拟器无法满足快速进步的AI领域的需求。该项目旨在开发一个开放式驾驶模拟平台，该平台在自主驾驶从感知到决策的各个方面促进创新。该平台将支持现实的驾驶模拟，并使用从现实世界中进口的各种交通资产和场景范围。这将成为学术界和行业研究人员开发新的AI方法，共享数据和模型并基准进步的共同实验基础。该平台将成长为社区研究基础设施，并对开花的自动驾驶行业产生重大影响。此外，它将为STEM教育提供互动的教学工具包，特别是对于服务不足社区的学生。在该项目中，调查人员将开发一个名为Metadriverse的开源模拟平台，用于自动驾驶的AI研究。该平台将作为研究基础设施和设施在各种学科中引人入胜的研究机会，包括计算机视觉，计算机图形，机器学习和人机互动。 Metadriverse将具有逼真的视觉外观，交互式现实世界的场景和资产以及直观的人类控制界面，从而允许模拟现实世界的驾驶体验。它还将提供广泛的任务和基准，并具有设计新任务的灵活性，这将评估社区的集体努力并加速研究的进度。该平台的关键功能包括（i）现实的视觉感知和中性渲染，（ii）对现实世界流量方案的交互式模拟，（iii）全面的基准和模型动物园，以及（iv）社区的集体工作。该基础设施将在自动驾驶和智能运输行业中促进广泛的机遇和合作，并带来重大的社会和经济影响。该奖项反映了NSF的法定任务，并被认为是通过基金会的智力优点和更广泛的影响来通过评估来获得的支持。