@inproceedings{7ebfb5cd3655414692fb1cd46ec85faa,
title = "Integrated Framework of Vehicle Dynamics, Instabilities, Energy Models, and Sparse Flow Smoothing Controllers",
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.",
keywords = "automated vehicles, energy models, fuel economy, microsimulation, traffic control systems",
author = "Lee, {Jonathan W.} and George Gunter and Rabie Ramadan and Sulaiman Almatrudi and Paige Arnold and John Aquino and William Barbour and Rahul Bhadani and Joy Carpio and Chou, {Fang Chieh} and Marsalis Gibson and Xiaoqian Gong and Amaury Hayat and Nour Khoudari and Kreidieh, {Abdul Rahman} and Maya Kumar and Nathan Lichtl{\'e} and Sean Mcquade and Brian Nguyen and Megan Ross and Sydney Truong and Eugene Vinitsky and Yibo Zhao and Jonathan Sprinkle and Benedetto Piccoli and Bayen, {Alexandre M.} and Work, {Daniel B.} and Benjamin Seibold",
note = "Funding Information: The authors would like to thank Kenneth Butts (Toyota) for helpful discussions and comments. This material is based upon work supported by the National Science Foundation under Grants CNS-1837244/CNS-1837652/CNS-1837481/OISE-1743772. This material is based upon work supported by the U.S. Department of Energy{\textquoteright}s Office of Energy Efficiency and Renewable Energy (EERE) under the Vehicle Technologies Office award number CID DE–EE0008872. The views expressed herein do not necessarily represent the views of the U.S. Department of Energy or the United States Government. Funding Information: The authors would like to thank Kenneth Butts (Toyota) for helpful discussions and comments. This material is based uponwork supported by the National Science Foundation under Grants CNS-1837244/CNS-1837652/CNS-1837481/OISE-1743772. Publisher Copyright: {\textcopyright} 2021 Owner/Author.; 1st ACM Workshop on Data-Driven and Intelligent Cyber-Physical Systems, DICPS 2021 - Part of CPS-IoT Week 2021 ; Conference date: 18-05-2021",
year = "2021",
month = may,
day = "18",
doi = "10.1145/3459609.3460530",
language = "English (US)",
series = "DICPS 2021 - Proceedings of the ACM 1st Workshop on Data-Driven and Intelligent Cyber-Physical Systems, Part of CPS-IoT Week 2021",
publisher = "Association for Computing Machinery, Inc",
pages = "41--47",
booktitle = "DICPS 2021 - Proceedings of the ACM 1st Workshop on Data-Driven and Intelligent Cyber-Physical Systems, Part of CPS-IoT Week 2021",
}