Evaluation and prediction of punctuality of vessel arrival at port: a case study of Hong Kong

The punctuality of vessel arrival at port is a crucial issue in contemporary port operations. Uncertainties in vessel arrival can lead to port handling inefficiency and result in economic losses. Although vessels typically report their estimated time of arrival (ETA) en-route to the destination port...

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Main Authors: Chu, Zhong, Yan, Ran, Wang, Shuaian
Other Authors: School of Civil and Environmental Engineering
Format: Article
Language:English
Published: 2023
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Online Access:https://hdl.handle.net/10356/170044
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1700442023-08-22T06:55:39Z Evaluation and prediction of punctuality of vessel arrival at port: a case study of Hong Kong Chu, Zhong Yan, Ran Wang, Shuaian School of Civil and Environmental Engineering Engineering::Civil engineering Maritime Transport Port Management The punctuality of vessel arrival at port is a crucial issue in contemporary port operations. Uncertainties in vessel arrival can lead to port handling inefficiency and result in economic losses. Although vessels typically report their estimated time of arrival (ETA) en-route to the destination port, their actual time of arrival (ATA) often differs from the reported ETA due to various factors. To address this issue and enhance terminal operational efficiency, we first quantitatively evaluate vessel arrival uncertainty in different time slides prior to arrival at the port using 2021 vessel arrival data for Hong Kong port (HKP). Our results confirm that the overall vessel arrival uncertainty decreases as vessels approach the HKP. Then, we implement a random forest (RF) approach to predict vessel arrival time. Our model reduces the error in ship ATA data prediction by approximately 40% (from 25.5 h to 15.5 h) using the root mean squared error metric and 20% (from 13.8 h to 11.0 h) using the mean absolute error metric compared with the reported ETA data. The proposed vessel arrival time evaluation and prediction models are applicable to port management and operation, laying the foundation for future research on port daily operations. Nanyang Technological University The work was supported by the Nanyang Technological University [start-Up grant]; National Natural Science Foundation of China [71831008]. 2023-08-22T06:55:38Z 2023-08-22T06:55:38Z 2023 Journal Article Chu, Z., Yan, R. & Wang, S. (2023). Evaluation and prediction of punctuality of vessel arrival at port: a case study of Hong Kong. Maritime Policy and Management. https://dx.doi.org/10.1080/03088839.2023.2217168 0308-8839 https://hdl.handle.net/10356/170044 10.1080/03088839.2023.2217168 2-s2.0-85160531531 en Maritime Policy and Management © 2023 Informa UK Limited, trading as Taylor & Francis Group. All rights reserved.
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Civil engineering
Maritime Transport
Port Management
spellingShingle Engineering::Civil engineering
Maritime Transport
Port Management
Chu, Zhong
Yan, Ran
Wang, Shuaian
Evaluation and prediction of punctuality of vessel arrival at port: a case study of Hong Kong
description The punctuality of vessel arrival at port is a crucial issue in contemporary port operations. Uncertainties in vessel arrival can lead to port handling inefficiency and result in economic losses. Although vessels typically report their estimated time of arrival (ETA) en-route to the destination port, their actual time of arrival (ATA) often differs from the reported ETA due to various factors. To address this issue and enhance terminal operational efficiency, we first quantitatively evaluate vessel arrival uncertainty in different time slides prior to arrival at the port using 2021 vessel arrival data for Hong Kong port (HKP). Our results confirm that the overall vessel arrival uncertainty decreases as vessels approach the HKP. Then, we implement a random forest (RF) approach to predict vessel arrival time. Our model reduces the error in ship ATA data prediction by approximately 40% (from 25.5 h to 15.5 h) using the root mean squared error metric and 20% (from 13.8 h to 11.0 h) using the mean absolute error metric compared with the reported ETA data. The proposed vessel arrival time evaluation and prediction models are applicable to port management and operation, laying the foundation for future research on port daily operations.
author2 School of Civil and Environmental Engineering
author_facet School of Civil and Environmental Engineering
Chu, Zhong
Yan, Ran
Wang, Shuaian
format Article
author Chu, Zhong
Yan, Ran
Wang, Shuaian
author_sort Chu, Zhong
title Evaluation and prediction of punctuality of vessel arrival at port: a case study of Hong Kong
title_short Evaluation and prediction of punctuality of vessel arrival at port: a case study of Hong Kong
title_full Evaluation and prediction of punctuality of vessel arrival at port: a case study of Hong Kong
title_fullStr Evaluation and prediction of punctuality of vessel arrival at port: a case study of Hong Kong
title_full_unstemmed Evaluation and prediction of punctuality of vessel arrival at port: a case study of Hong Kong
title_sort evaluation and prediction of punctuality of vessel arrival at port: a case study of hong kong
publishDate 2023
url https://hdl.handle.net/10356/170044
_version_ 1779156561576329216