Abstract

The continuous development of maritime trade over the last decades has led to a significant growth of needs in
every section of maritime transport and port operations. During the next 5 years the annual volume at global
container terminals will rise significantly, making terminal utilization rates higher than the ones where the
systems operate optimally. There is a need for finding more efficient, quick and economic ways of transporting,
handling and storing goods as well as seeking more productive strategies for yard management and terminal
operation. Inspired by markets’ growing demands and the possibilities of transforming conventional vehicles
into automatic ones, an algorithm for smart job allocation and routing of automated vehicles (Straddle Carriers)
in terminals is presented in this paper. A management strategy for handling a fleet of autonomous straddle
carriers in port yard areas aiming at minimizing the energy consumption while maintaining the performance of
the port operations is developed. The strategy is based on a three-layer approach, with job assignment and
individual routing at the first two levels and conflict resolution at the last layer, aiming at providing collisionfree
trajectories and speed profiles. The algorithm is integrated into the terminal operating system of the port and
constitutes a complete solution for small-medium sized ports.


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

https://zenodo.org/record/3540586 under the license http://creativecommons.org/licenses/by/4.0/legalcode
http://dx.doi.org/10.5281/zenodo.1445878 under the license http://creativecommons.org/licenses/by-nc-nd/4.0/legalcode
http://dx.doi.org/10.5281/zenodo.1445879 under the license http://creativecommons.org/licenses/by-nc-nd/4.0/legalcode
http://dx.doi.org/10.5281/zenodo.3540585 under the license http://creativecommons.org/licenses/by/4.0/legalcode



DOIS: 10.5281/zenodo.3540586 10.5281/zenodo.3540585 10.5281/zenodo.1445879 10.5281/zenodo.1445878

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Published on 01/01/2018

Volume 2018, 2018
DOI: 10.5281/zenodo.3540586
Licence: Other

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