Container Port Performance Measurement and Comparison Leveraging Ship GPS Traces and Maritime Open Data

Container ports are generally measured and compared using performance indicators such as container throughput and facility productivity. Being able to measure the performance of container ports quantitatively is of great importance for researchers to design models for port operation and container logistics. Instead of relying on the manually collected statistical information from different port authorities and shipping companies, the authors propose to leverage the pervasive ship GPS traces and maritime open data to derive port performance indicators, including ship traffic, container throughput, berth utilization, and terminal productivity. These performance indicators are found to be directly related to the number of container ships arriving at the terminals and the number of containers handled at each ship. Therefore, the authors propose a framework that takes the ships' container-handling events at terminals as the basis for port performance measurement. With the inferred port performance indicators, the authors further compare the strengths and weaknesses of different container ports at the terminal level, port level, and region level, which can potentially benefit terminal productivity improvement, liner schedule optimization, and regional economic development planning. In order to evaluate the proposed framework, the authors conduct extensive studies on large-scale real-world GPS traces of container ships collected from major container ports worldwide through the year, as well as various maritime open data sources concerning ships and ports. Evaluation results confirm that the proposed framework not only can accurately estimate various port performance indicators but also effectively produces port comparison results such as port performance ranking and port region comparison.


  • English

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  • Accession Number: 01601109
  • Record Type: Publication
  • Files: TLIB, TRIS
  • Created Date: May 3 2016 9:06AM