Abstract

A truck platoon is a set of virtually linked trucks that travel in tandem with small intervehicle distances. Several studies have proved that traveling in platoons can significantly improve fuel economy due to the reduced aerodynamic drag. However, most literature only provides scattered pieces of information regarding fuel economy in truck platoons. Therefore, a literature survey is needed to understand what has been studied and what problems remain to be further addressed. This paper presents an overview of existing studies to illustrate the state of the art about fuel savings for truck platooning. Specifically, it summarized the methodologies, the contributing factors of fuel consumption, the coordination methods to improve the platooning rate, and the look-ahead control strategies to generate fuel-efficient speed profiles for each vehicle driving in a platoon over different road grades. After that, the autonomous truck platooning was introduced, and we raised and discussed a couple of outstanding questions to be addressed in future work.

Document type: Article

Full document

The PDF file did not load properly or your web browser does not support viewing PDF files. Download directly to your device: Download PDF document

Original document

The different versions of the original document can be found in:

http://downloads.hindawi.com/journals/jat/2020/2604012.xml,
http://dx.doi.org/10.1155/2020/2604012 under the license http://creativecommons.org/licenses/by/4.0
https://doaj.org/toc/0197-6729,
https://doaj.org/toc/2042-3195 under the license http://creativecommons.org/licenses/by/4.0/
http://downloads.hindawi.com/journals/jat/2020/2604012.pdf,
https://jglobal.jst.go.jp/en/detail?JGLOBAL_ID=202002281888488112,
https://academic.microsoft.com/#/detail/2997385668
Back to Top

Document information

Published on 01/01/2020

Volume 2020, 2020
DOI: 10.1155/2020/2604012
Licence: Other

Document Score

0

Views 9
Recommendations 0

Share this document

claim authorship

Are you one of the authors of this document?