CPS: Small: Cyber-Physical Phases of Mixed Traffic with Modular & Autonomous Vehicles: Dynamics, Impacts and Management

CPS：小型：模块化混合流量的网络物理阶段

• 批准号: 2313578
• 负责人: Xiaopeng Li
• 金额: $ 50万
• 依托单位: University of Wisconsin-Madison
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-10-01 至 2025-03-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2313578&HistoricalAwards=false
• 关键词: CPS; Small; Cyber; Physical; Phases

Emerging technologies in communications and vehicle technologies will allow future autonomous vehicles to be platooned together with wireless communications (cyber-connected) or physically forming an actual train (physically-connected). When physically connected, vehicles may dock to and undock from each other en-route when vehicles are still moving. While such platooning can potentially offer substantial societal benefits in safety, mobility and environmental friendliness, their emergence also challenges the classic traffic flow models that do not account for the state that vehicles can have very short to no gaps from each other. And yet, classic traffic flow models are being used for all traffic simulations for assessment on safety, mobility and environment. This project aims to expand classic highway traffic flow models to account for states where vehicles can be very close to or even physically connected with each other. These new models will help stakeholders plan and manage future transportation systems and supply the engineering curriculum with new methods, tools, and experimental platforms oriented towards future smart urban systems. The objectives of this research are (1) to gain new knowledge on the impacts of the emerging new states in highway traffic dynamics in both ideal (e.g., with zero sensor errors and delay, infinite communication range, and infinite computational power ) and realistic ( e.g., with sensor noise, communication delay and computational limits) operational conditions, (2) to devise mechanisms and managing strategies to properly regulate the multi-state mixed traffic for its best performance, and (3) to quantify the key components of the models and systems via both full-scale and reduced-scale testbeds. These models will provide theoretical insights on the upper-bound performance of a mixed traffic system in ideal operational conditions. Then realistic cyber-physical constraints will be incorporated into the highway system and agent-based simulations will be conducted to understand how the system performance will be compromised due to these real-world cyber-physical constraints. Various management strategies will also be explored via both decentralized (e.g., each individual vehicle making decisions on its own) and centralized (e.g., all vehicles controlled or coordinated by a central operator) control strategies for offsetting the performance of a transportation system closer to the theoretical upper bound. Finally, field experiments on both multi-scale testbeds will be conducted to validate the key components of the theorems and models.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.

通信和车辆技术领域的新兴技术将使未来的自动驾驶车辆能够通过无线通信（网络连接）编排在一起，或在物理上形成真正的列车（物理连接）。当物理连接时，当车辆仍在移动时，车辆可以在途中相互对接和脱离。虽然这种队列行驶可能会在安全性、机动性和环境友好性方面带来巨大的社会效益，但它们的出现也对传统的交通流模型提出了挑战，这些模型没有考虑到车辆之间可以有非常短的间隙甚至没有间隙的情况。然而，经典的交通流模型正在用于所有交通模拟，以评估安全性、流动性和环境。该项目旨在扩展经典的高速公路交通流模型，以考虑车辆可以非常接近甚至物理上相互连接的状态。这些新模型将帮助利益相关者规划和管理未来的交通系统，并为工程课程提供面向未来智能城市系统的新方法、工具和实验平台。 这项研究的目标是（1）获得关于公路交通动态中新兴新状态的影响的新知识，包括理想（例如，零传感器误差和延迟、无限通信范围和无限计算能力）和现实（例如，在传感器噪声、通信延迟和计算限制的情况下）操作条件，(2) 设计机制和管理策略以正确调节多状态混合流量以获得最佳性能，以及 (3) 量化模型的关键组成部分和系统通过两者全尺寸和缩小尺寸的试验台。这些模型将为理想运行条件下混合交通系统的上限性能提供理论见解。然后，将现实的网络物理约束纳入高速公路系统，并进行基于代理的模拟，以了解这些现实世界的网络物理约束将如何影响系统性能。还将通过分散式（例如，每个单独的车辆自行做出决策）和集中式（例如，所有车辆由中央操作员控制或协调）控制策略来探索各种管理策略，以抵消交通系统的性能更接近于实际情况。理论上限。最后，将在两个多尺度测试平台上进行现场实验，以验证定理和模型的关键组成部分。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。