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

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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.