Ship path planning is crucial for the shipping industry, especially for the development of autonomous ships. Many algorithms have been developed over the last few decades to solve the ship path planning problem. However, it is still challenging for ship path planning in an inland waterway. In this paper, an improved RRT algorithm for ship path planning in complex inland waterways is proposed. The improved algorithm has a path shearing and smoothing module, and the function of keeping a safe distance between a moving ship and obstacles. In addition, the algorithm has been tested in two inland waterway scenarios, and the results have confirmed its feasibility and reliability. The path planning algorithm proposed in this research seeks to reduce the risks faced by ship navigation in inland water. It has theoretical and practical significance in improving navigation safety in complex inland waters.

The causes of maritime accidents are complex, mostly due to the coupling of four types of factors: human-ship-environmental-management. To effectively analyze the causes of maritime accidents in China, and reveal the risk coupling characteristics of accidents, this paper establishes the N-K model of maritime accident, and calculates and analyzes the four types of coupling of risk factors affecting safety in maritime traffic. This paper collects 922 maritime accidents that occurred in China from 2000 to 2020, and analyzes the location, type, and level of accidents and uses the trigger principle to describe the process of accidents. For marine and inland river accidents, this paper calculates the four types of coupling values of risk factors (single-factor coupling, two-factor coupling, three-factor coupling, four-factor coupling) for comparison and analysis. In addition, this paper calculates the coupling values of six typical maritime accidents of collision, sinking, contact, fire/explosion, stranding, grounding. According to the coupling values and the frequency of sub-factors, this paper analyzes the coupling characteristics of maritime accidents. The results show that in maritime accidents, as the number of risk factors participating in the coupling increases, the coupling value increases, and the multi-factor coupling is more likely to cause accidents. The overall situation of risk coupling causes of maritime accidents is basically consistent with inland river accidents, but they have their own characteristics in the specific degree of risk coupling and the dominant risk elements. In different types of maritime accidents, the risk coupling has different characteristics, and the dominant risk factors are also different.

Accurate vessel traffic flow prediction is significant for maritime traffic guidance and control. According to the characteristics of vessel traffic flow data, a new hybrid model, named DWT–Prophet, is proposed based on the discrete wavelet decomposition and Prophet framework for the prediction of vessel traffic flow. First, vessel traffic flow was decomposed into a low-frequency component and several high-frequency components by wavelet decomposition. Second, Prophet was trained to predict the components, respectively. Finally, the prediction results of the components were reconstructed to complete the prediction. The experimental results demonstrate that the hybrid DWT–Prophet outperformed the single Prophet, long short-term memory, random forest, and support vector regression (SVR). Moreover, the practicability of the new forecasting method was improved effectively.

There is a need to study the evolutionary laws of the risks in the navigation environments of complex marine areas. This can promote shipping safety using an early-warning system. The present study determines shipping flows and meteorological conditions in a marine area on the basis of meteorological and automatic identification system (AIS) data. It also determines the uncertainty evolution law of the navigation environment’s influencing factors. Moreover, a navigation risk evolution system for ships in complex marine areas was developed. A case study was carried out in a coastal area of China on the basis of the determined evolutionary laws. Evolution in the navigational environment risk within the case study area was analyzed. The results showed that the hydrometeorology wind factor has the greatest impact on the risk of ship collisions. This work was not only able to show advances in navigational collision environmental evolution laws but also provides a theoretical reference for the evaluation and early warning of risks in shipping environments.