Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/209372
Authors: 
Bierwirth, Benjamin
Schwanecke, Ulrich
Gietzen, Thomas
Lopéz, Daniel Andrés
Brylka, Robert
Year of Publication: 
2019
Citation: 
[Editor:] Kersten, Wolfgang [Editor:] Blecker, Thorsten [Editor:] Ringle, Christian M. [Title:] Artificial Intelligence and Digital Transformation in Supply Chain Management: Innovative Approaches for Supply Chains. Proceedings of the Hamburg International Conference of Logistics (HICL), Vol. 27 [ISBN:] 978-3-7502-4947-9 [Pages:] 151-185
Abstract: 
Purpose: SmartAirCargoTrailers improve short-distance air cargo transports within airport premises. They create real-time-transparency between the partners in the transport chain and thereby reduces waiting times while at the same time increasing equipment utilization. An autonomous truck with swap bodies facilitates these short-distance transports. Methodology: The SmartAirCargoTrailer system consist of an autonomous truck with swap trailers which is controlled by a cloud platform. To allow for real-timetransparency all shipments loaded onto the trailer are detected by a camera-based system. Findings: To enable reliable scannings of AirwayBill numbers (AWBs) a system of multiple cameras was developed. Challenges arose from the big variationin shipment size and scanning in motion. While the truck could be triggered automatically based on time or filling level, also human interaction had to be integrated. Originality: The system introduces a combined push-pull-algorithm to optimize the utilization of the autonomous trucks. The camera-based barcode scanning allows for shipment identification without interrupting the loading process. Autonomous driving in the mixed traffic environments of the landside airport premises is another innovative part of the project.
Subjects: 
Air cargo
Camera-based barcode detection
Neural networks
Autonomous transports
Persistent Identifier of the first edition: 
Creative Commons License: 
https://creativecommons.org/licenses/by-sa/4.0/
Document Type: 
Conference Paper

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