CPS: Synergy: Collaborative Research: Design and Control of High-performance Provably-safe Autonomy-enabled Dynamic Transportation Networks

CPS：协同：协作研究：高性能、可证明安全、支持自主的动态运输网络的设计和控制

• 批准号: 1544413
• 负责人: Sertac Karaman
• 金额: $ 60.08万
• 依托单位: Massachusetts Institute of Technology
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-15 至 2019-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1544413&HistoricalAwards=false
• 关键词: CPS; Synergy; Collaborative; Research; Design

During the last decade, we have witnessed a rapid penetration of autonomous systems technology into aerial, road, underwater, and sea vehicles. The autonomy assumed by these vehicles holds the potential to increase performance significantly, for instance, by reducing delays and increasing capacity, while enhancing safety, in a number of transportation systems. However, to exploit the full potential of these autonomy-enabled transportation systems, we must rethink transportation networks and control algorithms that coordinate autonomous vehicles operating on such networks. This project focuses on the design and operation of autonomy-enabled transportation networks that provide provable guarantees on achieving high performance and maintaining safety at all times. The foundational problems arising in this domain involve taking into account the physics governing the vehicles in order to coordinate them using cyber means. This research effort aims to advance the science of cyber-physical systems by following a unique and radical approach, drawing inspiration and techniques from non-equilibrium statistical mechanics and self-organizing systems, and blending this inspiration with the foundational tools of queueing theory, control theory, and optimization. This approach may allow orders of magnitude improvement in the servicing capabilities of various transportation networks for moving goods or people. The applications include the automation of warehouses, factory floors, sea ports, aircraft carrier decks, transportation networks involving driverless cars, drone-enabled delivery networks, air traffic management, and military logistics networks. The project also aims to start a new wave of classes and tutorials that will create trained engineers and a research community in the area of safe and efficient transportation networks enabled by autonomous cyber-physical systems.

在过去的十年中，我们目睹了自主系统技术快速渗透到空中、公路、水下和海上车辆中。这些车辆的自主性有可能显着提高性能，例如，通过减少延误和增加运力，同时提高许多交通系统的安全性。然而，为了充分发挥这些自主交通系统的潜力，我们必须重新思考交通网络和协调在此类网络上运行的自动驾驶车辆的控制算法。该项目专注于自主交通网络的设计和运营，为实现高性能和始终保持安全提供可证明的保证。该领域出现的基本问题涉及考虑控制车辆的物理原理，以便使用网络手段协调它们。这项研究工作旨在通过遵循独特而激进的方法，从非平衡统计力学和自组织系统中汲取灵感和技术，并将这种灵感与排队论、控制等基础工具相结合，来推进网络物理系统的科学发展。理论、优化。这种方法可以使各种运输网络运输货物或人员的服务能力得到数量级的提高。这些应用包括仓库、工厂车间、海港、航空母舰甲板、涉及无人驾驶汽车的运输网络、无人机交付网络、空中交通管理和军事物流网络的自动化。该项目还旨在启动新一波的课程和教程，在自主网络物理系统支持的安全高效的交通网络领域培养训练有素的工程师和研究社区。