An Improved Ship Collision Risk Evaluation Method for Korea Maritime Safety Audit Considering Traffic Flow Characteristics
被引:14
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作者:
Yoo, Yunja
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机构:
Korea Maritime Inst, Maritime Safety Dept, Busan 49111, South KoreaKorea Maritime Inst, Maritime Safety Dept, Busan 49111, South Korea
Yoo, Yunja
[1
]
Kim, Tae-Goun
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机构:
Korea Maritime & Ocean Univ, Div Maritime Transportat Sci, Busan 49112, South KoreaKorea Maritime Inst, Maritime Safety Dept, Busan 49111, South Korea
Kim, Tae-Goun
[2
]
机构:
[1] Korea Maritime Inst, Maritime Safety Dept, Busan 49111, South Korea
[2] Korea Maritime & Ocean Univ, Div Maritime Transportat Sci, Busan 49112, South Korea
Ship collision accidents account for the majority of marine accidents. The collision risk can be even greater in ports where the traffic density is high and terrain conditions are difficult. The proximity assessment model of the Korea Maritime Safety Audit (KMSA), which is a tool for improving maritime traffic safety, employs a normal distribution of ship traffic to calculate the ship collision risk. However, ship traffic characteristics can differ according to the characteristics of the sea area and shipping route. Therefore, this study simulates collision probabilities by estimating the best-fit distribution function of ship traffic flow in Ulsan Port, which is the largest hazardous cargo vessel handling port in Korea. A comparison of collision probability simulation results using the best-fit function and the normal distribution function reveals a difference of approximately 1.5-2.4 times for each route. Moreover, the collision probability estimates are not accurate when the normal distribution function is uniformly applied without considering the characteristics of each route. These findings can be used to improve the KMSA evaluation method for ship collision risks, particularly in hazardous port areas.
机构:
Wuhan Univ Technol WUT, Sch Nav, Wuhan 430063, Peoples R China
Univ Calif Santa Barbara, Dept Geog, Santa Barbara, CA 93106 USAWuhan Univ Technol WUT, Sch Nav, Wuhan 430063, Peoples R China
Yu, Hongchu
Murray, Alan T.
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Univ Calif Santa Barbara, Dept Geog, Santa Barbara, CA 93106 USAWuhan Univ Technol WUT, Sch Nav, Wuhan 430063, Peoples R China
Murray, Alan T.
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机构:
Fang, Zhixiang
Liu, Jingxian
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Wuhan Univ Technol WUT, Sch Nav, Wuhan 430063, Peoples R ChinaWuhan Univ Technol WUT, Sch Nav, Wuhan 430063, Peoples R China
Liu, Jingxian
Peng, Guojun
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Univ Tennessee, Dept Geog, Knoxville, TN 37996 USAWuhan Univ Technol WUT, Sch Nav, Wuhan 430063, Peoples R China
Peng, Guojun
Solgi, Mohammad
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Univ Calif Santa Barbara, Dept Geog, Santa Barbara, CA 93106 USAWuhan Univ Technol WUT, Sch Nav, Wuhan 430063, Peoples R China
Solgi, Mohammad
Zhang, Weilong
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机构:
China Railway First Survey & Design Inst Grp Co L, Xian 710043, Peoples R ChinaWuhan Univ Technol WUT, Sch Nav, Wuhan 430063, Peoples R China