Analysis of Lookout Activity in a Simulated Environment to Investigate Maritime Accidents Caused by Human Error
Maritime accidents remain a significant concern for the shipping industry, despite recent technological developments. In the Republic of Korea, the leading cause of maritime accidents is navigator error, particularly in collisions and groundings; this cause has led to 79% of maritime accidents, acco...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2018-12-01
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| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/9/1/4 |
| _version_ | 1819115919579807744 |
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| author | Ik-Hyun Youn Deuk-Jin Park Jeong-Bin Yim |
| author_facet | Ik-Hyun Youn Deuk-Jin Park Jeong-Bin Yim |
| author_sort | Ik-Hyun Youn |
| collection | DOAJ |
| description | Maritime accidents remain a significant concern for the shipping industry, despite recent technological developments. In the Republic of Korea, the leading cause of maritime accidents is navigator error, particularly in collisions and groundings; this cause has led to 79% of maritime accidents, according to a recent assessment. The reduction of navigator error is crucial for accident prevention; however, the lack of objective measures to monitor navigator error remains a challenge. The purpose of this study was to develop an objective classification of navigation behaviors in a simulated environment. The statistical model of classification of lookout activity was developed by collecting participants’ lookout behavior using a Kinect sensor within a given scenario. This classification model was validated in non-scenario experiments. The results showed that seven standard lookout activities during a lookout routine were accurately classified in both the model development and validation phases. The proposed model classification of lookout activity using an optical sensor is expected to provide a better understanding of how navigators behave to help prevent maritime accidents in practice. |
| first_indexed | 2024-12-22T05:08:51Z |
| format | Article |
| id | doaj.art-74404fef88d745e29458c0c07313f899 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-12-22T05:08:51Z |
| publishDate | 2018-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-74404fef88d745e29458c0c07313f8992022-12-21T18:38:02ZengMDPI AGApplied Sciences2076-34172018-12-0191410.3390/app9010004app9010004Analysis of Lookout Activity in a Simulated Environment to Investigate Maritime Accidents Caused by Human ErrorIk-Hyun Youn0Deuk-Jin Park1Jeong-Bin Yim2Division of Navigation & Information Systems, Mokpo National Maritime University, Mokpo 58628, KoreaDepartment of Maritime Transportation System, Mokpo National Maritime University, Mokpo 58628, KoreaDivision of Navigation Sciences, Korea Maritime and Ocean University, Busan 49112, KoreaMaritime accidents remain a significant concern for the shipping industry, despite recent technological developments. In the Republic of Korea, the leading cause of maritime accidents is navigator error, particularly in collisions and groundings; this cause has led to 79% of maritime accidents, according to a recent assessment. The reduction of navigator error is crucial for accident prevention; however, the lack of objective measures to monitor navigator error remains a challenge. The purpose of this study was to develop an objective classification of navigation behaviors in a simulated environment. The statistical model of classification of lookout activity was developed by collecting participants’ lookout behavior using a Kinect sensor within a given scenario. This classification model was validated in non-scenario experiments. The results showed that seven standard lookout activities during a lookout routine were accurately classified in both the model development and validation phases. The proposed model classification of lookout activity using an optical sensor is expected to provide a better understanding of how navigators behave to help prevent maritime accidents in practice.https://www.mdpi.com/2076-3417/9/1/4maritime accidentslookout behavior classificationoptical sensormachine learning modelsimulation environment |
| spellingShingle | Ik-Hyun Youn Deuk-Jin Park Jeong-Bin Yim Analysis of Lookout Activity in a Simulated Environment to Investigate Maritime Accidents Caused by Human Error Applied Sciences maritime accidents lookout behavior classification optical sensor machine learning model simulation environment |
| title | Analysis of Lookout Activity in a Simulated Environment to Investigate Maritime Accidents Caused by Human Error |
| title_full | Analysis of Lookout Activity in a Simulated Environment to Investigate Maritime Accidents Caused by Human Error |
| title_fullStr | Analysis of Lookout Activity in a Simulated Environment to Investigate Maritime Accidents Caused by Human Error |
| title_full_unstemmed | Analysis of Lookout Activity in a Simulated Environment to Investigate Maritime Accidents Caused by Human Error |
| title_short | Analysis of Lookout Activity in a Simulated Environment to Investigate Maritime Accidents Caused by Human Error |
| title_sort | analysis of lookout activity in a simulated environment to investigate maritime accidents caused by human error |
| topic | maritime accidents lookout behavior classification optical sensor machine learning model simulation environment |
| url | https://www.mdpi.com/2076-3417/9/1/4 |
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