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

通信和车辆技术的新兴技术将使未来的自动驾驶汽车与无线通信（网络连接）并列，或形成实际的列车（物理连接）。当物理连接时，车辆可以在车辆仍在行驶时在途中相互停靠和分离。虽然这样的队列可以在安全、机动性和环境友好性方面提供巨大的社会效益，但它们的出现也挑战了传统的交通流模型，这些模型没有考虑到车辆之间可以有很短甚至没有间隔的状态。然而，经典的交通流模型正在被用于所有的交通模拟，以评估安全性、移动性和环境。该项目旨在扩展经典的高速公路交通流模型，以考虑车辆之间非常接近甚至物理连接的状态。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。本研究的目标是：(1)在理想（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（如有传感器噪声、通信延迟和计算限制）运行条件下，获得有关新兴状态对公路交通动力学影响的新知识；(2)设计适当调节多状态混合交通的机制和管理策略，使其达到最佳性能。(3)通过全尺寸和缩小尺寸的试验台对模型和系统的关键部件进行量化。这些模型将为混合交通系统在理想运行条件下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，以了解由于这些现实世界的网络物理约束，系统性能将如何受到损害。各种管理策略也将通过分散（例如，每辆车自己做决定）和集中（例如，所有车辆由中央操作员控制或协调）控制策略进行探索，以抵消更接近理论上限的运输系统的性能。最后，将在两个多尺度试验台上进行现场实验，以验证定理和模型的关键组成部分。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

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.