A conflict cluster-based method for collision avoidance decision-making in multi-ship encounter situations

It is crucial to develop a COLREGs-compliant intelligent collision avoidance system for the safety of unmanned ships during navigation. This paper proposes a collision avoidance decision approach based on the deep reinforcement learning method. A modified collision avoidance framework is developed that takes into consideration the characteristics of different encounter scenarios. Hierarchical reward functions are established to assign reward values to constrain the behavior of the agent. The collision avoidance actions of the agent under different encounter situations are evaluated on the basis of the COLREGs to ensure ship safety and compliance during navigation. The deep Q network algorithm is introduced to train the proposed collision avoidance decision framework, while various simulation experiments are performed to validate the developed collision avoidance model. Results indicate that the proposed method can effectively perform tasks that help ships avoid collisions in different encounter scenarios. The proposed approach is a novel attempt for intelligent collision avoidance decisions of unmanned ships.

In the conditions of bad weather, the small vessels maneuvering ability of collision avoidance is seriously reduced and the vulnerability to maritime accidents increases due to the influence of strong wind and wave. This paper proposes a collision avoidance decision-making and control method for small vessels using the integrated collision risk assessment based on fuzzy logic. First, the speed of wind and height of wave in the bad weather conditions are fuzzified. Then, the collision risk indices are selected for fuzzy inference to get the basic collision risk which will be integrated with the vulnerability to collision accidents and it helps to improve the accuracy of collision risk assessment. According to the current multi-ships encounter situations, the similar cases are retrieved from the case database, and the collision avoidance decision is given after fuzzy adjustments. To implement collision avoidance actions, a fuzzy algorithm for nonlinear ship heading dynamic surface control (DSC) control considering input saturation and uncertainties is designed. The problem of "computational expansion" that may occur in high-order systems is avoided by using DSC technology. Finally, simulation experiments are implemented to verify the effectiveness of the collision avoidance method.

Coordinated multi-stage and multi-objective optimization approach for ship collision avoidance decision-making

The exploration of ship collision avoidance behavior characteristics can provide a theoretical basis for ship collision risk assessment and collision avoidance decision-making, which is significant for ensuring maritime navigation safety and the development of intelligent ships. In order to scientifically and effectively analyze the characteristics of ship collision-avoidance behavior and to seek the intrinsic connections among ship collision-avoidance behavior feature parameters(CABFPS), this study proposes a method that combines the Apriori algorithm and complex network theory to mine ship collision-avoidance behavior characteristics from massive AIS spatiotemporal data. Based on obtaining ship encounter samples and CABFPS from AIS data, the Apriori algorithm is used to mine the association rules of motion parameters, and the maximum mutual information coefficient is employed to represent the correlation between parameters. Complex networks of CABFPS for different encounter situations are constructed, and network topological indicators are analyzed. Mutual information theory is applied to identify key parameters affecting ship collision- avoidance behavior under different situations. The analysis using actual AIS data indicates that during navigation, the relationships among various parameters are closely linked and prone to mutual influence. The impact of CABFPS on ship collision-avoidance actions varies under different encounter scenarios, with relative distance and DCPA having the greatest influence on ship collision-avoidance actions. This method can comprehensively and accurately mine the correlations between CABFPS and the influence mechanism of parameters on collision-avoidance actions, providing a reference for intelligent ship navigation and the formulation of collision-avoidance decisions.

In order to improve the effectiveness of intelligent collision avoidance decision of ships, a collision avoidance decision model is established with the objective of guaranteeing the safety of ship navigation and reducing the loss of voyage, taking real-time data as the input quantity and the requirements of international maritime collision avoidance rules and the common practice of seafarers as the constraints, and MOEA/D (Multi-objective Evolutionary Algorithm Based on Decomposition) algorithm is used to optimize the objective function and calculate the optimal steering angle and steering timing. The simulation results show that the decision can meet the safety and economic requirements of ship collision avoidance under different encounter situations and can provide some reference for ship collision avoidance decision.

The age of algorithms is here, and it is really changing people's lives. More and more ethical problems related to algorithms have attracted people's attention, but the related ethical research is still far behind the research of algorithms. As more intelligent algorithms emerge in an endless stream, there will also be a lot of algorithmic ethical issues. On the other hand, with the continuous improvement of the development level of the automobile industry, people have a stronger demand for the safety and stability of modern transportation, and more and more autonomous driving technology has been promoted and applied in the market. At present, most of the studies on the longitudinal collision avoidance system of vehicles use collision warning or emergency braking to avoid collision. However, when the vehicle is in a special situation such as high speed and slippery road, emergency steering is more effective. In order to further improve the vehicle safety and ethical algorithm design points, this article revolves around vehicle lateral active collision avoidance control method research, the collision avoidance decision-making, and path planning and collision avoidance transverse vehicle longitudinal motion control is analyzed, and based on automated driving simulation experiment, the tests carried out to verify the designed control strategy. The experimental results show that the proposed method not only has a good effect of preventing automatic driving collision but also can meet the requirements of algorithm ethics. This research can effectively guide the research of algorithmic ethics in the field of autonomous driving and effectively reduce the occurrence of traffic accidents.

Determining and visualizing safe motion parameters of a ship navigating in severe weather conditions

Automatic collision avoidance is a key technology in the research of unmanned surface vessel(USV). By establishing the collision avoidance decision coordinate system of USV, this paper estimates the motion parameters of obstacles relative to USV under two different conditions. Based on azimuth measurement information and based on azimuth and distance measurement information at the same time, analyzes the influence of speed and heading change on DCPA and TCPA, then, according to several typical sea encounters, the calculation methods of different collision avoidance decisions are given.

Changes of drivers’ visual performances when approaching a signalized intersection under different collision avoidance warning conditions

ABSTRACTThis paper proposes a new safety system named emergency steering assist (ESA), which consists of the autonomous steering subsystem and differential braking subsystem. The control system is developed to mediate the conflict objectives of vehicle stabilisation and rear-end collision avoidance in highway driving. Instead of predefining a collision-free trajectory in the entire process of collision avoidance, the process of collision avoidance is divided into two stages. In stage 1, where the vehicle is guided to enter the adjacent lane with a constant centripetal acceleration to avoid collision, the steering manoeuvre is determined by the feedforward controller based on the steering dynamics. In stage 2, where the vehicle is guided along the centreline of the adjacent lane, the steering manoeuvre is determined by the controller based on the theory of model predictive control. In addition, the differential braking subsystem is designed with a comprehensive treatment to the requirements of collision avoidance and vehicle stabilisation. Finally, the simulation results demonstrate that the proposed ESA system can effectively achieve better balance between an emergency collision avoidance manoeuvre and vehicle stabilisation at high speeds in different conditions. The hardware-in-the-loop experiment developed by the authors is used to validate the real-time performance and effectiveness of the proposed control scheme.

According to The International Regulations for Preventing Collisions at Sea, 1972, ships can only determine their collision avoidance responsibilities in accordance with the rules of “Conduct of Vessels in Sight of One Another” if the dynamic and category of the target ship is identified to be using lights and/or shapes during encounters at sea. Then, appropriate actions can be taken, and the effectiveness of the collision avoidance actions can be checked during the subsequent maneuvering process. In order to analyze and solve the problems related to lights and shapes and to adapt to the development of ship size, speed, and intelligence, this paper firstly reviews the development history and revision process of lights and shapes. Furthermore, it explains the collision avoidance responsibility of ships in sight of one another, analyzes the role of lights and shapes in the collision avoidance process, and summarizes the lights and shapes displayed by different categories of ships. Next, through qualitative and quantitative analysis, the relationship between the visibility distance of lights and shapes and the timing of ship avoidance actions is examined. Finally, the paper points out current problems related to lights and shapes, including: (1) non-uniform visibility distance of lights, (2) insufficient visibility distance of lights, and (3) small size of shapes, and proposes solutions to these problems from theoretical and practical perspectives, including: (1) unifying the visibility distance of masthead light, sidelights, and sternlight to 6 nautical miles, (2) unifying the visibility distance of the sternlight to 3 nautical miles, and (3) unifying the diameter size of shapes and the vertical distance between shapes to 1.8 m.

To ensure navigation safety, unmanned surface vehicles (USVs) need to have autonomous collision avoidance capability. A large number of studies on ship collision avoidance are available, and most of these papers assume that the target ships keep straight or follows the International Regulations for Preventing Collisions at Sea (COLREGS). However, in the actual navigation process, the target ship may temporarily turn. Based on the above reasons, this paper proposes a multi-ship collision avoidance decision method for USVs based on the improved velocity obstacle algorithm. In the basic dynamic ship domain model, a collision risk model is constructed to improve the accuracy of the risk assessment between the USV and target ships. The velocity obstacle algorithm is combined with the dynamic ship domain, and the collision avoidance timing and method are judged according to the collision risk. The simulation results show that the decision method can handle the situation that the target ship temporarily turns and has an emergency collision avoidance capability. Compared with the traditional VO algorithm, the collision avoidance time of the method is shorter, and the number of course changes is less.

At present, the multi-targets autonomous vehicles identify are mainly various road users such as vehicles and pedestrians in cities. However, in recent years, there are increasing vehicle-animal accidents in pastoral areas of China, and there is a lack of corresponding practical intelligent safety warning measurements. In order to realise the identification and collision avoidance of typical animals, this study obtains the basic characteristics of collisions and the animals’ behavioural characteristics from the pastoral accidents investigation. Firstly, an attempt to focus on the use of the algorithm of the binocular infra-red equipment is made, with the main targets of identification being domestic animals at night or under low brightness conditions. Secondly, the algorithm technology roadmap from the identification and the risk assessment to collision avoidance decision-making is designed. Further, based on the technical route, a feasible solution and overall technical program is presented, which outlines the five aspects of the proposed engineering-ready scheme’s architecture. The methodology used involves transfer learning and the PSMNet network model. The paper concludes that the system can predict the animal’s movement and make proper decisions by utilising binocular infra-red equipment, integrating its algorithms and the support of its behavioural risk assessment. The research results will contribute to the animal collision avoidance technology and the traffic safety in pastoral areas in the future.

Although the navigation safety has been greatly improved nowadays, automation of ship driving are not achieved completely as the automation of collision avoidance has not achieved perfectly. This paper mainly research on ship domain modeling and application for ship collision avoidance. The novel achievements are that it proposed a 3-d model of ship domain and improved the danger judgments of collision to determine the more suitable timing and magnitude of action. This paper divided process of ship collision avoidance into three stages: ship domain build stage, danger judgment stage and action stage. Based on theories of each process of ship collision avoidance codified in 2-d coordinate system, this paper made simulations for crossing situation to express collision avoidance process.

The evaluation of collision avoidance strategies for special-purpose unmanned ground vehicles (UGVs) operating in dynamic environments with human presence is presented in this study. The autonomous wheeled vehicle equipped with an armament module for combat and reconnaissance tasks is described considering mission specifications and off-road usage scenarios. The main operational parameters are outlined, and the obstacle detection features integrated into the PERUN vehicle are introduced. The control system architecture is presented, along with installed sensors and their perception capabilities of surrounding object detection. Safety considerations in operational conditions where human presence force appropriate collision avoidance actions are discussed. Real field tests conducted in diverse weather and environmental conditions, such as industrial area and unstructured terrains, are shown to demonstrate the system's performance. Carried out tests show that the collision avoidance system enables obstacle detection and proving the effectiveness of steering strategies for the platform's navigation. The safe operation of unmanned systems in environments with human presence is crucial for the successful deployment and scalability of UGV technologies.