Abstract
This article provides an overview of the classical and new techniques in traffic flow control and estimations. The overview begins with a description of the most used traffic flow models for estimation and control. Then, it shifts towards using those models for traffic flow estimation using physics-informed machine learning techniques. Lastly, it focuses on traffic flow control describing the most classical techniques and the new advancement in traffic control using autonomous vehicles.
| Original language | English (US) |
|---|---|
| Title of host publication | 2022 IEEE 61st Conference on Decision and Control, CDC 2022 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 6910-6925 |
| Number of pages | 16 |
| ISBN (Electronic) | 9781665467612 |
| DOIs | |
| State | Published - 2022 |
| Event | 61st IEEE Conference on Decision and Control, CDC 2022 - Cancun, Mexico Duration: Dec 6 2022 → Dec 9 2022 |
Publication series
| Name | Proceedings of the IEEE Conference on Decision and Control |
|---|---|
| Volume | 2022-December |
| ISSN (Print) | 0743-1546 |
| ISSN (Electronic) | 2576-2370 |
Conference
| Conference | 61st IEEE Conference on Decision and Control, CDC 2022 |
|---|---|
| Country/Territory | Mexico |
| City | Cancun |
| Period | 12/6/22 → 12/9/22 |
Bibliographical note
Publisher Copyright:© 2022 IEEE.