Knowledge-Driven Semantic Segmentation for Waterway Scene Perception

Semantic segmentation as one of the most popular scene perception techniques has been studied for autonomous vehicles. However, deep learning-based solutions rely on the volume and quality of data and knowledge from specific scene might not be incorporated. A novel knowledge-driven semantic segmentation method is proposed for waterway scene perception. Based on the knowledge that water is irregular and dynamically changing, a Life Time of Feature (LToF) detector is designed to distinguish water region from surrounding scene. Using a Bayesian framework, the detector as the likelihood function is combined with U-Net based semantic segmentation to achieve an optimized solution. Finally, two public datasets and typical semantic segmentation networks, FlowNet, DeepLab and DVSNet are selected to evaluate the proposed method. Also, the sensitivity of these methods and ours to dataset is discussed

Modeling of Ship Collision Risk Index Based on Complex Plane and Its Realization

Ship collision risk index is the basic and important concept in the domain of ship collision avoidance. In this paper, the advantages and deficiencies of the various calculation methods of ship collision risk index are pointed out. Then the ship collision risk model based on complex plane, which can well make up for the deficiencies of the widely-used evaluation model proposed by Kearon.J and Liu ruru is proposed. On this basis, the calculation method of collision risk index under the encountering situation of multi-ships is constructed, then the three-dimensional image and spatial curve of the risk index are figured out. Finally, single chip microcomputer is used to realize the model. And attaching this single chip microcomputer to ARPA is helpful to the decision-making of the marine navigators

Extended State Observer-Based Parameter Identification of Response Model for Autonomous Vessels

Identification of parameters involved in the linear response model with high precision is a highly cost-effective, as well as a challenging task, in developing a suitable model for the verification and validation (V+V) of some key techniques for autonomous vessels in the virtual testbed, e.g., guidance, navigation, and control (GNC). In order to deal with this identification problem, a novel identification framework is proposed in this paper by introducing the extended state observer (ESO), and the well-evaluated robust weighted least square support vector regression algorithm (RW-LSSVR). A second-order linear response model is investigated in this study due to its wide use in controller designs. Considering the highly possible situation that only limited states could be measured directly, the required but immeasurable states in identifying parameters contained in the response model are approximately estimated by the ESO. Theoretical analysis of the stability is given to show and improve the applicability of the ESO. Simulation studies based on linear response models with predefined parameter values of a cargo vessel and a patrol vessel maneuvering in an open water area are carried out, respectively. Results show that the proposed approach not only estimates immeasurable states with high accuracy but also ensures good performance on the parameter identification of the response model with very close values to the nominal ones. The proven identified approach is economic because it only requires limited kinds of low-cost sensors

Review of Different Propulsion Methods for Hybrid-Electric Propulsion Ship

This paper reviews different hybrid-electric propulsion modes, i.e., series hybrid, parallel hybrid, and series-parallel hybrid. It then focuses on traditional propeller propulsion, shaftless rim propulsion, and pod propulsion. It mainly distinguishes and compares various propulsion methods, from advantages and disadvantages, power range, to technical issues, and analyzes the applicable ships and propulsion efficiencies for each type of propulsion method. Although shaftless rim propulsion and pod propulsion have various key technical challenges, their propulsion efficiencies are higher than traditional propeller propulsion. And they are promising to be used in hybrid power ships in the near future

Review of Different Propulsion Methods for Hybrid-Electric Propulsion Ship

This paper reviews different hybrid-electric propulsion modes, i.e., series hybrid, parallel hybrid, and series-parallel hybrid. It then focuses on traditional propeller propulsion, shaftless rim propulsion, and pod propulsion. It mainly distinguishes and compares various propulsion methods, from advantages and disadvantages, power range, to technical issues, and analyzes the applicable ships and propulsion efficiencies for each type of propulsion method. Although shaftless rim propulsion and pod propulsion have various key technical challenges, their propulsion efficiencies are higher than traditional propeller propulsion. And they are promising to be used in hybrid power ships in the near future

Modelling of the Marine Traffic Situation Complexity

With the growth of traffic density, traditional collision risk models cannot thoroughly describe the complex traffic any more. Therefore, in this paper, a marine traffic situation complexity model, which is based on the relationship between ships, is introduced to metric the complexity of vessel traffic. Firstly, traffic density factor and traffic conflict factors are considered to construct the traffic unit complexity model, reflecting the traffic complexity and traffic characteristics; Secondly, by extending the traffic unit complexity model into the own-ship complexity model, the influences of the positions of other ship on the complexity spatial distribution are analysed; Finally, two scenarios are imported to validate the availability of the complexity model. The verification results show that the complexity can respond to different route structures and traffic situations sensitively

Extreme Weather Impacts on Inland Waterways Transport of Yangtze River

The impact of extreme weather events on the navigation environment in the inland waterways of the Yangtze River is an interdisciplinary hotspot in subjects of maritime traffic safety and maritime meteorology, and it is also a difficult point for the implementation of decision-making and management by maritime and meteorological departments in China. The objective of this study is to review the variation trends and distribution patterns in the periods of adverse and extreme weather events that are expected to impact on inland waterways transport (IWT) on the Yangtze River. The frequency of severe weather events, together with the changes in their spatial extension and intensity, is analyzed based on the ERA-Interim datasets (1979–2017) and the GHCNDEX dataset (1979–2017), as well as the research progresses and important events (2004–2016) affecting the navigation environment. The impacts of extreme weather events on IWT accidents and phenomena of extreme weather (e.g., thunderstorms, lightning, hail, and tornadoes) that affect the navigation environment are also analyzed and discussed. The results show that: (1) the sections located in the plain climate zone is affected by extreme weather in every season, especially strong winds and heat waves; (2) the sections located in the hilly mountain climate zone is affected particularly by spring extreme phenomena, especially heat waves; (3) the sections located in the Sichuan Basin climate zone is dominated by the extreme weather phenomena in autumn, except cold waves; (4) the occurrence frequency of potential flood risk events is relatively high under rainstorm conditions and wind gusts almost affect the navigation environment of the Jiangsu and Shanghai sections in every year; (5) the heat wave indices (TXx, TR, and WSDI) tend to increase and the temperature of the coldest day of the year gradually increases; (6) the high occurrences of IWT accidents need to be emphasized by relevant departments, caused by extreme weather during the dry season; and (7) the trends and the degree of attention of extreme weather events affecting IWT are ranked as: heat wave > heavy rainfall > wind gust > cold spell > storm. Understanding the seasonal and annual frequency of occurrence of extreme weather events has reference significance for regional management of the Yangtze River