Maritime shipping is the primary means connecting countries and global economies, with ports serving as critical logistics hubs in the supply chain. In recent decades, international conflicts and economic disruptions have increasingly stressed maritime transport, highlighting the need to focus more on terminal performance. This paper presents a methodology to evaluate port traffic conditions using data from open Automatic Identification System (AIS) repositories. A rule-based approach is applied to segment the vessel trajectories into underway, anchoring, and berth operations, allowing the assessment of all stages that characterize a port call and the calculation of the vessel turnaround time. The methodology is demonstrated in the Port of Los Angeles, the busiest container hub on the United States West Coast. Historical AIS data are analyzed to obtain traffic conditions, and a set of key performance indicators is computed to quantify terminal operations and docks utilization during the observation period. The proposed framework provides a scalable tool for maritime traffic monitoring and decision support in port management.

Times of ships in container ports: automatic identification system data for analyzing traffic conditions at a maritime terminal

Belcore O. M.
;
Polimeni A.
2026-01-01

Abstract

Maritime shipping is the primary means connecting countries and global economies, with ports serving as critical logistics hubs in the supply chain. In recent decades, international conflicts and economic disruptions have increasingly stressed maritime transport, highlighting the need to focus more on terminal performance. This paper presents a methodology to evaluate port traffic conditions using data from open Automatic Identification System (AIS) repositories. A rule-based approach is applied to segment the vessel trajectories into underway, anchoring, and berth operations, allowing the assessment of all stages that characterize a port call and the calculation of the vessel turnaround time. The methodology is demonstrated in the Port of Los Angeles, the busiest container hub on the United States West Coast. Historical AIS data are analyzed to obtain traffic conditions, and a set of key performance indicators is computed to quantify terminal operations and docks utilization during the observation period. The proposed framework provides a scalable tool for maritime traffic monitoring and decision support in port management.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11570/3347370
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