Platooning of Automated Ground Vehicles to Connect Port and Hinterland

A Multi-objective Optimization Approach

Conference paper (2020)

Authors

N. Pourmohammadzia Transport Engineering and Logistics - Mechanical, Maritime and Materials Engineering
F. Schulte Transport Engineering and Logistics - Mechanical, Maritime and Materials Engineering
D. Souravlias Transport Engineering and Logistics - Mechanical, Maritime and Materials Engineering
R.R. Negenborn Transport Engineering and Logistics - Mechanical, Maritime and Materials Engineering
Research Group
Transport Engineering and Logistics (Mechanical, Maritime and Materials Engineering) (TU Delft)
Copyright: © 2020 N. Pourmohammadzia, F. Schulte, D. Souravlias, R.R. Negenborn
DOI
help_outline
https://doi.org/10.1007/978-3-030-59747-4_28
Platooning Container terminals Automated ground vehicles Emission analysis Loading/unloading operations
More Info
expand_more

Published Date

2020

Language

English

Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Faculty

Mechanical, Maritime and Materials Engineering

Department

Marine and Transport Technology

Research Group

Transport Engineering and Logistics

Abstract

Automated ground vehicles (AGVs) are essential parts of container operations at many ports. Forming platoons—as conceptually established in trucking—may allow these vehicles to directly cater demand points such as dry ports in the hinterland. In this work, we aim to assess such AGV platoons in terms of operational efficiency and costs, considering the case of the Port of Rotterdam. We propose a multi-objective mixed-integer programming model that minimizes dwell and idle times, on the one hand, and the total cost of the system involving transportation, labor, and platoon formation costs, on the other hand. To achieve Pareto optimal solutions that capture the trade-offs between minimizing cost and time, we apply an augmented epsilon constraint method. The results indicate that all the containers are delivered by AGVs. This not only shortens the dwell time of the containers by decreasing loading/unloading processes and eliminating stacking but also leads to considerable cost savings.