Study on the Analysis of Near-Miss Ship Collisions Using 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.