Platoon Optimization Based on Truck Pairs
Truck platooning technology allows trucks to drive at short headways to save fuel and associated emissions. However, fuel savings from platooning are relatively small, so forming platoons should be convenient and associated with minimum detours and delays. In this paper, we focus on developing optim...
Gespeichert in:
Veröffentlicht in: | INFORMS journal on computing 2023-11, Vol.35 (6), p.1242-1260 |
---|---|
1. Verfasser: | |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Zusammenfassung: | Truck platooning technology allows trucks to drive at short headways to save fuel and associated emissions. However, fuel savings from platooning are relatively small, so forming platoons should be convenient and associated with minimum detours and delays. In this paper, we focus on developing optimization technology to form truck platoons. We formulate a mathematical program for the platoon routing problem with time windows (PRP-TW) based on a time–space network. We provide polynomial-time algorithms to solve special cases of PRP-TW with two-truck platoons. Based on these special cases, we build several fast heuristics. An extensive set of numerical experiments shows that our heuristics perform well. Moreover, we show that simple two-truck platoons already capture most of the potential savings of platooning.
History:
Accepted by Pascal van Hentenryck, Area Editor for Computational Modeling: Methods and Analysis.
Funding:
This work was supported by the Netherlands Organization for Scientific Research (NWO) as part of the Spatial and Transport Impacts of Automated Driving [Grant 438-15-161] project.
Supplemental Material:
The software that supports the findings of this study is available within the paper and its Supplemental Information (
https://pubsonline.informs.org/doi/suppl/10.1287/ijoc.2020.0302
) as well as from the IJOC GitHub software repository (
https://github.com/INFORMSJoC/2020.0302
). The complete IJOC Software and Data Repository is available at
https://informsjoc.github.io/
. |
---|---|
ISSN: | 1091-9856 1526-5528 1091-9856 |
DOI: | 10.1287/ijoc.2020.0302 |