Research of AIS Data-Driven Ship Arrival Time at Anchorage Prediction

Abstract

In today's time, maritime transport is becoming the mainstream. Ports have the problems of inefficient berthing and unreasonable allocation of shore and bridge resources. In this article, we propose a model to predict the ship arrival time based on automatic identification system (AIS) data and trajectory inflexion points to predict the anchor arrival time, aiming to solve the problems of low berthing efficiency and unreasonable allocation of shore and bridge resources. Experiments show that the minimum prediction error of the model is 8 min, the maximum error is 1 h, and the average error is 30 min; compared with the ship schedule data, the maximum error is seven days, the minimum error is one day, and the average error is 2.75 days, so the time got from this model is better than the ship schedule, which can effectively improve the berthing efficiency of the port and the reasonable allocation of shore and bridge resources. The model has good accuracy and effectiveness.