Ningbo Zhoushan port handled 1.08 billion tons cargoes in 2018 which is considered as the one of biggest ports in the world. There are more than 1 000 ships enter or depart the port per day. Therefore, it is of importance to assess the collision risk for ships passing through the harbor area. In this paper, a novel approach is initially proposed to assess ship collision risk in the harbor area based on collision detection technology of ship domain using automatic identified system (AIS) data. This study aims to build a unified framework of collision risk assessment which does not need to build different models in accordance with the ship domain we selected. To clean the historical motion data of ships, a method for anomaly detection of ship static information based on autoencoder (AE) is proposed. Based on the above proposed method, the ship collision frequency can be estimated, besides, the risk area can also be determined. The results obtained from the method could provide a reference on furthering enhance the navigational safety for the Maritime and Port Authority.

Effective use of port waterways is conducive to enhancing port competitiveness. To minimize the waiting time of ships, improve traffic efficiency, and enhance the applicability of the model to the presence of uncertain factors, a fuzzy scheduling optimization method for ships suitable for one-way waterways is proposed based on fuzzy theory. Considering the ambiguity of the speed of ships entering and exiting the port or the time it takes to cross the channel, the previous research on vessel scheduling on one-way waterways has been extended by introducing a triangular fuzzy number and a method for determining the feasible navigable time window of a ship subject to the tide height constraint was proposed. In this study, the genetic algorithm is used to construct the mathematical model for solving fuzzy vessel scheduling problems based on time optimization, and the minimum delay strategy is used to determine the service sequence. Then, the parameters setting are discussed in detail to find the optimal settings. Finally, an experimental comparative analysis of the randomly generated cases was conducted based on the simulated data. The results show that the designed fuzzy vessel scheduling algorithm reduces the dependence on the port environment, is versatile, and can effectively improve the efficiency of ship schedules and traffic safety compared to other methods. Moreover, it can avoid the problem of the illegal solution occurring in the manual scheduling method.

To improve the efficiency of in-wharf vessels and out-wharf vessels in seaports, taking into account the characteristics of vessel speeds that are not fixed, a vessel scheduling method with whole voyage constraints is proposed. Based on multi-time constraints, the concept of a minimum safety time interval (MSTI) is clarified to make the mathematical formula more compact and easier to understand. Combining the time window concept, a calculation method for the navigable time window constrained by tidal height and drafts for vessels is proposed. In addition, the nonlinear global constraint problem is converted into a linear problem discretely. With the minimum average waiting time as the goal, the genetic algorithm (GA) is designed to optimize the reformulated vessel scheduling problem (VSP). The scheduling methods under different priorities, such as the first-in-first-out principle, the largest-draft-vessel-first-service principle, and the random service principle are compared and analyzed experimentally with the simulation data. The results indicate that the reformulated and simplified VSP model has a smaller relative error compared with the general priority scheduling rules and is versatile, can effectively improve the efficiency of vessel optimization scheduling, and can ensure traffic safety.

In order to solve the problem of collision avoidance decision-making by using the ship domain that only can be applied to certain waters, and if's connected parameters cannot match the evaluation parameters of collision risk (CR), the optimal collision risk model based on Fuzzy Quaternion Ship Domains (FQSD) was been proposed. In order to solve the problem when making decision to avoid collision by using the shortest distance that does not consider cross track error (XTE) and time deviation (TDEV), and it also cannot let the overall voyage(OV) to be the shortest throughout the voyage, the objective function combines with XTE, TDEV and OV was been proposed. Considering with the ship domain, The International Regulations for Preventing Collisions at Sea 1972 (COLREGS) (IMO 1972) and the watch officer's subjective consciousness, the optimal collision avoidance path was been obtained by using the particle swarm optimization (PSO) algorithm. The simulation results show that the above optimal method can quickly obtain the optimal collision avoidance path and improve the safety and energy efficiency of transportation.