Robust Car-Following Control of Connected and Autonomous Vehicles: A Stochastic Model Predictive Control Approach-Reference-Cited by-同舟云学术

Robust Car-Following Control of Connected and Autonomous Vehicles: A Stochastic Model Predictive Control Approach

Published:2023-10-30 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the Int'l ACM Symposium on Design and Analysis of Intelligent Vehicular Networks and Applications
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Author:

Zhang Peiyu¹^ORCID,Zhou Jianshan¹^ORCID,Tian Daxin¹^ORCID,Duan Xuting¹^ORCID,Qu Kaige²^ORCID,Zhao Dezong³^ORCID,Sheng Zhengguo⁴^ORCID,Cai Pinlong⁵^ORCID,Leung Victor C.M.⁶^ORCID

Affiliation:

1. Beihang University, Beijing, China

2. University of Waterloo, Waterloo, Canada

3. University of Glasgow, Glasgow, United Kingdom

4. University of Sussex, Sussex, United Kingdom

5. Shanghai Artificial Intelligence Laboratory, Shanghai, China

6. Shenzhen University & The University of British Columbia, Shenzhen, China

Funder

the National Natural Science Foundation of China

the National Key Research and Development Program of China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3616392.3623420

Reference20 articles.

1. Constrained optimization and distributed computation based car following control of a connected and autonomous vehicle platoon

2. A Comparative Study of Stochastic Model Predictive Controllers

3. Jacopo Guanetti , Yeojun Kim , and Francesco Borrelli . 2018. Control of connected and automated vehicles: State of the art and future challenges. Annual reviews in control 45 ( 2018 ), 18--40. Jacopo Guanetti, Yeojun Kim, and Francesco Borrelli. 2018. Control of connected and automated vehicles: State of the art and future challenges. Annual reviews in control 45 (2018), 18--40.

4. Stochastic model predictive control — how does it work?

5. Fuel Economy-Oriented Vehicle Platoon Control Using Economic Model Predictive Control