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JACIII Vol.21 No.3 pp. 467-473
doi: 10.20965/jaciii.2017.p0467
(2017)

Paper:

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Study on the Analysis of Near-Miss Ship Collisions Using Logistic Regression

Kwang-Il Kim*, Jung Sik Jeong*, and Byung-Gil Lee**

*International Maritime Transportation Science, Mokpo National Maritime University
91 Haeyangdaehag-ro, Mokpo, Jeon-Nam 58628, Republic of Korea

**Electronics and Telecommunications Research Institute
218 Gajeong-ro, Yuseong-gu, Daejeon 34129, Republic of Korea

Received:
March 20, 2016
Accepted:
January 4, 2017
Online released:
May 19, 2017
Published:
May 20, 2017
Creative Commons License
Keywords:
ship encounter variables, near-miss ship collision, logistic regression
Abstract
Generally, risk assessment for a ship collision can be performed by analyzing the trajectories of two ships as they get close to each other. A near-miss collision between ships is an undesired event that did not result in collision, but had a high risk of doing so. Due to the high frequency of these occurrences, many actual accident data samples can be obtained. In this paper, we extract various variables related to near-miss collisions from this data, such as Distance to Closest Point of Approach (DCPA), Time to Closest Point of Approach (TCPA) and Collision Avoidance Variance (CAV). To assess near-miss collision risk, logistic regression analysis is performed by categorizing encounter types based on ship trajectories collected over 4 months in coastal water areas.
Cite this article as:
K. Kim, J. Jeong, and B. Lee, “Study on the Analysis of Near-Miss Ship Collisions Using Logistic Regression,” J. Adv. Comput. Intell. Intell. Inform., Vol.21 No.3, pp. 467-473, 2017.
Data files:
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