Abstract
Port traffic is affected by many factors, which may lead to certain problems in terms of maritime traffic safety and efficiency. To further study the maritime traffic flow of ships under the influence of multiple factors, our work combines artificial intelligence and an agent-based architecture to carry out port traffic flow simulation research. Moreover, considering an actual situation, a theoretical research method is used to analyze the feasibility of cellular automata combined with an agent architecture, and the basic framework is constructed. Simultaneously, in order to improve the computational efficiency, a system framework based on the Internet of Things structure is constructed, and the authenticity of the simulation process is improved. In addition, through a field investigation, the corresponding cellular automata model is established, and the cellular automata model and agent architecture are combined to establish the port traffic flow simulation model. Finally, the actual port operational data are collected to simulate various conditions, and the simulation results are obtained. The research shows that the model constructed in this paper has certain effects on the study of ship behavior in ports and can provide a theoretical reference for subsequent related research.
Highlights
When passing through port segments, ships often need to line up and comply with corresponding navigation rules and dispatch commands
According to the simulation model of the cellular automata and Agent proposed in the previous section, the port traffic flow simulation is realized through system programming
The behavioral characteristics and ship dynamics can be quantitatively or visually analyzed, which provides a powerful method for evaluating the passage capacity, navigation risk, and organizational and management effectiveness of the navigation channel
Summary
When passing through port segments, ships often need to line up and comply with corresponding navigation rules and dispatch commands This increases the navigation time and causes frequent maritime traffic accidents and leads to loss of life and property as well as environmental pollution and damage. Reducing such accidents, evaluating the safety risks, and determining how to increase the passage capacity of waterways and effectively organize and manage maritime transportation are problems that maritime departments and scientific and technical personnel need to think about and study [1]. Intelligent methods are needed for processing to effectively simulate the actual operating conditions [2]
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