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车辆能够通过无线通信（网络连接）或物理方式形成实际列车（物理连接）。当物理连接时，当车辆仍在移动时，车辆可以在途中彼此对接和解除对接。虽然这种排队可能会在安全性，机动性和环境友好性方面带来巨大的社会效益，但它们的出现也挑战了经典的交通流模型，这些模型没有考虑到车辆彼此之间可能有很短的间隙。然而，经典的交通流模型被用于所有的交通模拟，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，以考虑车辆可能非常接近甚至相互物理连接的状态。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。 本研究的目的是（1）获得新的知识，在公路交通动力学中出现的新状态的影响，在两个理想的（例如，具有零传感器误差和延迟、无限通信范围和无限计算能力）和现实的（例如，具有传感器噪声、通信延迟和计算限制）操作条件，（2）设计机制和管理策略以适当地调节多状态混合业务以获得其最佳性能，以及（3）通过全尺寸和缩小尺寸的测试床来量化模型和系统的关键组件。这些模型将提供理论上的见解，在理想的运行条件下的混合交通系统的上限性能。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。还将通过权力下放（例如，每个单独的车辆自己做出决定）和集中式（例如，由中央操作员控制或协调的所有车辆）控制策略，用于使运输系统的性能偏移到更接近理论上界。最后，将在两个多尺度试验台上进行现场实验，以验证理论和模型的关键组成部分。该奖项反映了NSF的法定使命，并被认为值得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。

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.