Integrated Framework of Vehicle Dynamics, Instabilities, Energy Models, and Sparse Flow Smoothing Controllers

Jonathan W. Lee, George Gunter, R. Ramadan, Sulaiman Almatrudi, Paige Arnold, John Aquino, William Barbour, R. Bhadani, Joy Carpio, Fang-Chieh Chou, Marsalis Gibson, Xiaoqian Gong, Amaury Hayat, Nour Khoudari, Abdul Rahman Kreidieh, Maya Kumar, Nathan Lichtlé, Sean T. McQuade, Brian Q. Nguyen, Megan Ross, S. Trương, Eugene Vinitsky, Yibo Zhao, J. Sprinkle, B. Piccoli, A. Bayen, D. Work, Benjamin Seibold
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引用次数: 13

Abstract

This work presents an integrated framework of: vehicle dynamics models, with a particular attention to instabilities and traffic waves; vehicle energy models, with particular attention to accurate energy values for strongly unsteady driving profiles; and sparse Lagrangian controls via automated vehicles, with a focus on controls that can be executed via existing technology such as adaptive cruise control systems. This framework serves as a key building block in developing control strategies for human-in-the-loop traffic flow smoothing on real highways. In this contribution, we outline the fundamental merits of integrating vehicle dynamics and energy modeling into a single framework, and we demonstrate the energy impact of sparse flow smoothing controllers via simulation results.
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车辆动力学、不稳定性、能量模型和稀疏流平滑控制器的集成框架
这项工作提出了一个综合框架:车辆动力学模型,特别关注不稳定性和交通波动;车辆能量模型,特别注意强不稳定驾驶剖面的准确能量值;和稀疏拉格朗日控制通过自动车辆,重点是控制可以通过现有的技术,如自适应巡航控制系统执行。该框架可作为开发真实高速公路上人在环路交通流平滑控制策略的关键构建块。在本文中,我们概述了将车辆动力学和能量建模集成到单个框架中的基本优点,并通过仿真结果展示了稀疏流平滑控制器的能量影响。
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