Showing papers by "Xiumin Chu published in 2019"

An Improved A-Star Algorithm Considering Water Current, Traffic Separation and Berthing for Vessel Path Planning

Abstract: A traditional A-Star (A*) algorithm generates an optimal path by minimizing the path cost. For a vessel, factors of path length, obstacle collision risk, traffic separation rule and manoeuvrability restriction should be all taken into account for path planning. Meanwhile, the water current also plays an important role in voyaging and berthing for vessels. In consideration of these defects of the traditional A-Star algorithm when it is used for vessel path planning, an improved A-Star algorithm has been proposed. To be specific, the risk models of obstacles (bridge pier, moored or anchored ship, port, shore, etc.) considering currents, traffic separation, berthing, manoeuvrability restriction have been built firstly. Then, the normal path generation and the berthing path generation with the proposed improved A-Star algorithm have been represented, respectively. Moreover, the problem of combining the normal path and the berthing path has been also solved. To verify the effectiveness of the proposed A-Star path planning methods, four cases have been studied in simulation and real scenarios. The results of experiments show that the proposed A-Star path planning methods can deal with the problems denoted in this article well, and realize the trade-off between the path length and the navigation safety.

Inland Ship Trajectory Restoration by Recurrent Neural Network

Abstract: The quality of Automatic Identification System (AIS) data is of fundamental importance for maritime situational awareness and navigation risk assessment. To improve operational efficiency, a deep learning method based on Bi-directional Long Short-Term Memory Recurrent Neural Networks (BLSTM-RNNs) is proposed and applied in AIS trajectory data restoration. Case studies have been conducted in two distinct reaches of the Yangtze River and the capability of the proposed method has been evaluated. Comparisons have been made between the BLSTM-RNNs-based method and the linear method and classic Artificial Neural Networks. Satisfactory results have been obtained by all methods in straight waterways while the BLSTM-RNNs-based method is superior in meandering waterways. Owing to the bi-directional prediction nature of the proposed method, ship trajectory restoration is favourable for complicated geometry and multiple missing points cases. The residual error of the proposed model is computed through Euclidean distance which decreases to an order of 10 m. It is considered that the present study could provide an alternative method for improving AIS data quality, thus ensuring its completeness and reliability.

Water level forecasting using a hybrid algorithm of artificial neural networks and local Kalman filtering

Abstract: The dynamic processes in the tidal reaches of the Yangtze River lead to the complexity of short-term water level forecasting. Historical data of daily water level are obtained for the lower reaches (Anqing–Wuhu–Nanjing) of the Yangtze River. Stationary time series of water level is derived by making the first-order difference with the raw datasets. An artificial neural network–Kalman hybrid model is proposed for water level forecasting, in which the Kalman filtering is introduced for partial data reconstruction. The model is calibrated with the hydrologic daily water level data of years 2014–2016 for MaAnshan station. Comparing with the traditional artificial neural network model, daily water level predictions are improved by the hybrid algorithm. Discrepancies appear under the circumstance of sharp variations of water level observations. Moreover, the implementation strategy of Kalman filtering algorithm is explored, which indicates the superiority of local Kalman filtering.

Short-term vessel traffic flow forecasting by using an improved Kalman model

Abstract: Vessel traffic flow forecasting is of significant importance for the water transport safety, especially in the multi-bridge water areas. An improved Kalman model combining regression analysis and Kalman filtering is proposed for short-term vessel traffic flow forecasting between Wuhan Yangtze River Bridge (hereafter WYRB) and the Second Wuhan Yangtze River Bridge (hereafter SWYRB). Given the vessel traffic flow of WYRB is positively correlated with that of SWYRB, its regression coefficient is obtained as well as the regression predictions. The predictions are further used to replace the state transition equation of Kalman filtering. The prediction results of the improved Kalman model demonstrate better agreements with field observations, and hence, illustrate good capability of the proposed method in the short-term traffic flow forecasting. The discrepancy between the model predictions and field observations is generally attributed to the inherent deficiency of Kalman filtering method and the errors resulted from automatic identification system (AIS) data (e.g. missed AIS data). The proposed method can provide a support for the real-time and accurate basis for the ship traffic planning management.

Intelligent collision avoidance system and method for ships based on maneuverability modeling

Abstract: The invention provides a ship intelligent collision avoidance system based on manoeuvrability modeling, comprising a state sensing subsystem, wherein the state parameters of the ship and the positioninformation of an obstacle are obtained; the maneuverability modeling module processes the ship's own state parameters, constructs the sample pairs, carries on the ship maneuverability on-line modeling, and predicts the ship's possible arrival position at the next time under all feasible maneuverability. The intelligent collision avoidance module combines the position information of the obstacle,Binary navigable area information and collision avoidance rules are used to carry out dynamic path planning. In path planning, the maneuverability modeling module predicts the possible arrival position of the ship at the next time as a constraint, outputs a reasonable planning path point sequence, and decouples it into a heading tracking sequence and a speed tracking sequence. Track the planned real-time heading and speed respectively. The invention realizes the intelligent collision avoidance decision of the ship on the basis of the on-line prediction of the ship maneuverability, and realizesthe safe and autonomous navigation of the ship.

Classification of Ship Trajectories by Using Naive Bayesian algorithm

Abstract: In order to automatically classify the ship’s historical trajectory and predict the class of a ship’s trajectory, a ship’s track classification algorithm based on naive Bayesian method is proposed. Using the Automatic Identification System (AIS) data of the Yangtze River in Wuhan section, the AIS data is first preprocessed to extract valid trajectory data. Then the trajectory data is analyzed and the characteristics of average speed, average heading, maximum heading, minimum heading, heading variance and maximum turning rate are extracted. The Naive Bayes classifier is trained and verified. The results show that the accuracy of classification is as high as about 98.59%. It takes only 0.165s to extract features from 709 ship trajectories. The Naive Bayesian classification method can effectively classify inland ship trajectories.

Marine diesel engine speed control based on adaptive state-compensate extended state observer-backstepping method:

Abstract: The marine diesel engine propulsion system is a nonlinear system with time delay. In order to realize the accurate and real-time control of the marine diesel engine speed, a new method based on sta...

Carrier-borne aircrafts aviation operation automated scheduling using multiplicative weights apprenticeship learning:

Abstract: Efficiency and safety are vital for aviation operations in order to improve the combat capacity of aircraft carrier. In this article, the theory of apprenticeship learning, as a kind of artificial ...

Characteristics of vessel traffic flow during waterway regulations: A case study in the Yangtze River

Abstract: The inland water transport plays a significant role in the comprehensive transport system of China. Theories and models concerning vessel traffic flow simulation and characteristics have been developed rapidly in recent several decades. In this paper, the influence of deep water channel regulation construction of Yangtze River (China) on vessel traffic flow has been identified. Probabilistic distributions of vessel size, vessel speed and traffic volume are investigated. In view of the complex navigational environment, Monte Carlo simulation has been adopted for vessel traffic flow investigation. The results indicate a favorable agreement between model predictions and field observations. Moreover, the LCG algorithm used in the MCS could be further improved to accomplish better simulation. The present study provides a useful basis for research on inland ship behavior and navigational risk assessment.

A hardware-in-the-loop simulation system and a method for automatic scheduling of a carrier-based aircraft

Abstract: The invention provides a hardware-in-the-loop simulation system for automatic dispatching of a carrier aircraft, which comprises an aircraft carrier deck model. Multi-agent system of carrier aircraft,which is used to simulate the recovery process of carrier aircraft; the controller on the agent controls the rotational speed and direction of the driving wheel according to the rotational speed of the driving wheel collected by the rotational speed sensor and the indication received by the communication unit, and uploads the rotational speed and the direction of the driving wheel through the communication unit. The agent is also provided with a positioning mark; image acquisition system for Real-time Image Acquisition of Aircraft Carrier Deck Model; the recognition and positioning monitoringsystem is used for obtaining the real-time state of the agent by recognizing the position of the agent and the positioning mark on the agent according to the real-time image of the aircraft carrier deck model. The automatic scheduling system of carrier-based aircraft is used to receive and process the real-time states of multi-agent in real-time. According to the preset scheduling model and optimization algorithm, the paths of each agent are determined and distributed to the corresponding agent. The invention provides an evaluation and verification environment for the research of the scheduling optimization of the carrier-based aircraft and the improvement of the out-going rate.

Research on Navigation Risk Identification of Three Gorges Ship Lock Based on Improved Analytic Hierarchy Process

Abstract: As one of the world famous navigation architectures, Three Gorges ship lock plays a significant role in the inland water transport system of China. Combining analytic hierarchy process and discrete fuzzy set, the factors that may affect the navigation safety of the Three Gorges Ship Lock are analyzed step by step from the perspectives of human, ship, environment, and management by using expert survey data. The results show that the total contribution rate of safety management to the navigation risk of the Three Gorges Ship Lock is up to 16%, and the human factor is a crucial factor affecting the navigation risk. The utility of risk control schemes can be evaluated through risk assessment. Suggestions are further made for maritime administration and accident prevention in the Three Gorges Ship Lock waters.