Journal articles on the topic 'Collision avoidance'
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Wickens, Christopher D., Adam Williams, Benjamin A. Clegg, and C. A. P. Smith. "Nautical Collision Avoidance." Human Factors: The Journal of the Human Factors and Ergonomics Society 62, no. 8 (September 18, 2019): 1304–21. http://dx.doi.org/10.1177/0018720819871409.
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Objective Experimentally investigate maneuver decision preferences in navigating ships to avoid a collision. How is safety (collision avoidance) balanced against efficiency (deviation from path and delay) and rules of the road under conditions of both trajectory certainty and uncertainty. Background Human decision error is a prominent factor in nautical collisions, but the multiple factors of geometry of collisions and role of uncertainty have been little studied in empirical human factors literature. Approach Eighty-seven Mechanical Turk participants performed in a lower fidelity ship control simulation, depicting ownship and a cargo ship hazard on collision or near-collision trajectories of various conflict geometries, while controlling heading and speed with the sluggish relative dynamics. Experiment 1 involved the hazard on a straight trajectory. In Experiment 2, the hazard could turn on unpredictable trials. Participants were rewarded for efficiency and penalized for collisions or close passes. Results Participants made few collisions, but did so more often when on a collision path. They sometimes violated the instructed rules of the road by maneuvering in front of the hazard ship’s path. They preferred speed control to heading control. Performance degraded in conditions of uncertainty. Conclusion Data reveal an understanding of maneuver decisions and conditions that affect the balance between safety and efficiency. Application The simulation and data highlight the degrading role of uncertainty and provide a foundation upon which more complex questions can be asked, asked of more trained navigators, and decision support tools examined.
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patil, Shreya. "Train Collision Avoidance System." Bonfring International Journal of Software Engineering and Soft Computing 6, Special Issue (October 31, 2016): 82–85. http://dx.doi.org/10.9756/bijsesc.8248.
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Li, Jinxin, Hongbo Wang, Wei Zhao, and Yuanyuan Xue. "Ship’s Trajectory Planning Based on Improved Multiobjective Algorithm for Collision Avoidance." Journal of Advanced Transportation 2019 (April 9, 2019): 1–12. http://dx.doi.org/10.1155/2019/4068783.
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With vigorous development of the maritime trade, many intelligent algorithms have been proposed to avoid collisions due to resulting casualties and increased costs. According to the international regulations for preventing collisions at sea (COLREGs) and the self-evolution ability of the intelligent algorithm, the collision avoidance trajectory can be more consistent with the requirements of reality and maritime personnel. In this paper, the optimization of ship collision avoidance strategies is realized by both an improved multiobjective optimization algorithm NSGA-II and the ship domain under the condition of a wide sea area without any external disturbances. By balancing the safety and economy of ship collision avoidance, the avoidance angle and the time to the action point are used as the variables encoded by the algorithm, and the fuzzy ship domain is used to calculate the collision avoidance risk to achieve collision avoidance. The simulation results show that the proposed method can optimize the ship collision avoidance strategy and provide a reasonable scheme for ship navigation.
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Liu, Xin, Shuwei Ren, Lei Zhang, Wei Shen, and Yubo Tu. "Research on Dynamic Path Planning and Tracking Control for Ship Collision Avoidance." Journal of Physics: Conference Series 2607, no. 1 (October 1, 2023): 012012. http://dx.doi.org/10.1088/1742-6596/2607/1/012012.
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Abstract Ship collisions are prevalent every year, leading to significant maritime traffic accidents. This paper presents research on dynamic path planning and tracking control for ship collision avoidance by integrating ship automatic avoidance technology to address this issue. We conducted a comprehensive study on artificial potential fields, trajectory tracking, and route trajectory tracking in response to the current state of ship collision avoidance and trajectory tracking. The study employed vector decomposition and slider control as research methods to analyze, optimize, and modify ship collision avoidance methods. Additionally, we carried out collision avoidance simulations using MATLAB to verify the stability and safety of ship trajectory tracking under various methods to advance the research on ship collision avoidance and trajectory. The proposed approach has the potential to significantly reduce ship collisions and enhance ship trajectory safety.
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Fan, Yunsheng, Xiaojie Sun, Guofeng Wang, and Dongdong Mu. "Collision Avoidance Controller for Unmanned Surface Vehicle Based on Improved Cuckoo Search Algorithm." Applied Sciences 11, no. 20 (October 19, 2021): 9741. http://dx.doi.org/10.3390/app11209741.
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For the dynamic collision avoidance problem of an unmanned surface vehicle (USV), a dynamic collision avoidance control method based on an improved cuckoo search algorithm is proposed. The collision avoidance model for a USV and obstacles is established on the basis of the principle of the velocity obstacle method. Simultaneously, the Convention on the International Regulations for Preventing Collisions at Sea (COLREGS) is incorporated in the collision avoidance process. For the improvement of the cuckoo algorithm, the adaptive variable step-size factor is designed to realize the adaptive adjustment of flight step-size, and a mutation and crossover strategy is introduced to enhance the population diversity and improve the global optimization ability. The improved cuckoo search algorithm is applied to the collision avoidance model to obtain an optimal collision avoidance strategy. According to the collision avoidance strategy, the desired evasion trajectory is obtained, and the tracking controller based on PID is used for the Lanxin USV. The experimental results show the feasibility and effectiveness of the proposed collision avoidance method, which provides a solution for the autonomous dynamic collision avoidance of USVs.
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Zheng, Mao, Kehao Zhang, Bing Han, Bowen Lin, Haiming Zhou, Shigan Ding, Tianyue Zou, and Yougui Yang. "An Improved VO Method for Collision Avoidance of Ships in Open Sea." Journal of Marine Science and Engineering 12, no. 3 (February 26, 2024): 402. http://dx.doi.org/10.3390/jmse12030402.
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In order to effectively deal with collisions in various encounter situations in open water environments, a ship collision avoidance model was established, and multiple constraints were introduced into the velocity obstacle method, a method to determine the ship domain by calculating the safe distance of approach was proposed. At the same time, the ship collision avoidance model based on the ship domain is analyzed, and the relative velocity set of the collision cone is obtained by solving the common tangent line within the ellipse. The timing of starting collision avoidance is determined by calculating the ship collision risk, and a method for ending collision avoidance is proposed. Finally, by comparing the simulation experiments of the improved algorithm with those of the traditional algorithm and the actual ship experiment results of manual ship maneuvering, it is shown that the method can effectively avoid collisions based on safe encounter distances that comply with navigation experience in different encounter situations. At the same time, it has better performance in collision avoidance behavior. It has certain feasibility and practical applicability.
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Wang, Weiqiang, Liwen Huang, Kezhong Liu, Xiaolie Wu, and Jingyao Wang. "A COLREGs-Compliant Collision Avoidance Decision Approach Based on Deep Reinforcement Learning." Journal of Marine Science and Engineering 10, no. 7 (July 9, 2022): 944. http://dx.doi.org/10.3390/jmse10070944.
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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.
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Li, Qiang. "A Research on Autonomous Collision Avoidance under the Constraint of COLREGs." Sustainability 15, no. 3 (January 30, 2023): 2446. http://dx.doi.org/10.3390/su15032446.
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In this paper, a decision-making model suitable for the collision avoidance (CA) of numerous target ships (TSs) is proposed, based on the principle of ship collision avoidance geometry and the characteristics of numerous target ships’ collision avoidance at sea. To ensure that the collision avoidance behaviors of own-ship (OS) are subject to the International Regulations for Preventing Collisions at Sea (COLREGS), this paper gives full consideration to the requirements of COLREGS within the scope of CA action and the time of collision avoidance. A ship CA simulation is established based on the Mathematical Modeling Group (MMG) model. To optimize the CA decision-making model, the influence of hydrodynamic force on steering time required to reach the new course is integrated into the collision avoidance simulation system. The simulation results show that the method can quickly and effectively determine a collision avoidance decision under the complex situation of numerous target ships and static obstacles, and it can consider the unpredictable strategies used by other vessels.
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Cheng, Zhiyou, Yaling Li, and Bing Wu. "Early Warning Method and Model of Inland Ship Collision Risk Based on Coordinated Collision-Avoidance Actions." Journal of Advanced Transportation 2020 (July 20, 2020): 1–14. http://dx.doi.org/10.1155/2020/5271794.
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To reduce the occurrence of ship collisions, immediate danger, and close-quarters situations in narrow inland waterways, a step-by-step early warning system for ship collision-avoidance actions was developed, along with an early warning method and model of collision risk based on coordinated collision-avoidance actions. This study first analyzed the importance of coordinated collision-avoidance actions in inland waterways, and the process and key components of coordinated collision-avoidance actions were studied. Then, the early warning method of inland ship collision risk based on coordinated collision-avoidance actions was introduced; the effectiveness of the early warning method was comparatively analyzed via experimental observations. A framework of early warning model of inland ship collision risk was created based on the early warning method; a collision risk early warning model for inland ships based on coordinated collision-avoidance actions was proposed according to the relationship between the distance/time to the closest point of approach (DCPA, TCPA), coordination degree of collision-avoidance actions of the two considered ships and collision risk; moreover, the early warning model of inland ship collision risk was further considered for quantitative calculation. Finally, the application of the early warning method and model was demonstrated using a case study. The results indicate that the early warning method of inland ship collision risk based on coordinated collision-avoidance actions could effectively reduce the emergence of close-quarters situations and immediate danger, and the early warning model could quantitatively show the evolution of collision risk of two ships along with the process of coordinated collision-avoidance actions.
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Liang, Zuopeng, Fusheng Li, and Shibo Zhou. "An Improved NSGA-II Algorithm for MASS Autonomous Collision Avoidance under COLREGs." Journal of Marine Science and Engineering 12, no. 7 (July 20, 2024): 1224. http://dx.doi.org/10.3390/jmse12071224.
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Autonomous collision avoidance decision making for maritime autonomous surface ships (MASS), as one of the key technologies for MASS autonomous navigation, is a research hotspot focused on by relevant scholars in the field of navigation. In order to guarantee the rationality, efficacy, and credibility of the MASS autonomous collision avoidance scheme, it is essential to design the MASS autonomous collision avoidance algorithm under the stipulations of the Convention on the International Regulations for Preventing Collisions at Sea (COLREGs). In order to enhance the autonomous collision avoidance decision-making capability of MASS in accordance with the relevant provisions of COLREGs, an improved NSGA-II autonomous collision avoidance decision-making algorithm based on the good point set method (GPS-NSGA-II) is proposed, which incorporates the collision hazard and the path cost of collision avoidance actions. The experimental results in the four simulation scenarios of head-on situation, overtaking situation, crossing situation, and multi-ship encounter situation demonstrate that the MASS autonomous collision avoidance decision making based on the GPS-NSGA-II algorithm under the constraints of COLREGs is capable of providing an effective collision avoidance scheme that meets the requirements of COLREGs in common encounter situations and multi-ship avoidance scenarios promptly, with a promising future application.
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Xu, Qingyang, Chuang Zhang, and Ning Wang. "Multiobjective Optimization Based Vessel Collision Avoidance Strategy Optimization." Mathematical Problems in Engineering 2014 (2014): 1–9. http://dx.doi.org/10.1155/2014/914689.
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The vessel collision accidents cause a great loss of lives and property. In order to reduce the human fault and greatly improve the safety of marine traffic, collision avoidance strategy optimization is proposed to achieve this. In the paper, a multiobjective optimization algorithm NSGA-II is adopted to search for the optimal collision avoidance strategy considering the safety as well as economy elements of collision avoidance. Ship domain and Arena are used to evaluate the collision risk in the simulation. Based on the optimization, an optimal rudder angle is recommended to navigator for collision avoidance. In the simulation example, a crossing encounter situation is simulated, and the NSGA-II searches for the optimal collision avoidance operation under the Convention on the International Regulations for Preventing Collisions at Sea (COLREGS). The simulation studies exhibit the validity of the method.
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Namgung, Ho. "Local Route Planning for Collision Avoidance of Maritime Autonomous Surface Ships in Compliance with COLREGs Rules." Sustainability 14, no. 1 (December 25, 2021): 198. http://dx.doi.org/10.3390/su14010198.
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A maritime autonomous surface ship (MASS) ensures safety and effectiveness during navigation using its ability to prevent collisions with a nearby target ship (TS). This avoids the loss of human life and property. Therefore, collision avoidance of MASSs has been actively researched recently. However, previous studies did not consider all factors crucial to collision avoidance in compliance with the International Regulations for Preventing Collisions at Sea (COLREGs) Rules 5, 7, 8, and 13–17. In this study, a local route-planning algorithm that takes collision-avoidance actions in compliance with COLREGs Rules using a fuzzy inference system based on near-collision (FIS-NC), ship domain (SD), and velocity obstacle (VO) is proposed. FIS-NC is used to infer the collision risk index (CRI) and determine the time point for collision avoidance. Following this, I extended the VO using the SD to secure the minimum safe distance between the MASS and the TS when they pass each other. Unlike previous methods, the proposed algorithm can be used to perform safe and efficient navigation in terms of near-collision accidents, inferred CRI, and deviation from the course angle route by taking collision-avoidance actions in compliance with COLREGs Rules 5, 7, 8, and 13–17.
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Wu, Xiaolie, Kezhong Liu, Jinfen Zhang, Zhitao Yuan, Jiongjiong Liu, and Qing Yu. "An Optimized Collision Avoidance Decision-Making System for Autonomous Ships under Human-Machine Cooperation Situations." Journal of Advanced Transportation 2021 (August 27, 2021): 1–17. http://dx.doi.org/10.1155/2021/7537825.
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Maritime Autonomous Surface Ships (MASSs) are attracting increasing attention in recent years as it brings new opportunities for water transportation. Previous studies aim to propose fully autonomous system on collision avoidance decisions and operations, either focus on supporting conflict detection or providing with collision avoidance decisions. However, the human-machine cooperation is essential in practice at the first stage of automation. An optimized collision avoidance decision-making system is proposed in this paper, which involves risk appetite (RA) as the orientation. The RA oriented collision avoidance decision-making system (RA-CADMS) is developed based on human-machine interaction during ship collision avoidance, while being consistent with the International Regulations for Preventing Collisions at Sea (COLREGS) and Ordinary Practice of Seamen (OPS). It facilitates automatic collision avoidance and safeguards the MASS remote control. Moreover, the proposed RA-CADMS are used in several encounter situations to demonstrate the preference. The results show that the RA-CADMS is capable of providing accurate collision avoidance decisions, while ensuring efficiency of MASS maneuvering under different RA.
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Wang, Bing, Yixiong He, Weixuan Hu, Junmin Mou, Liling Li, Ke Zhang, and Liwen Huang. "A Decision-Making Method for Autonomous Collision Avoidance for the Stand-On Vessel Based on Motion Process and COLREGs." Journal of Marine Science and Engineering 9, no. 6 (May 28, 2021): 584. http://dx.doi.org/10.3390/jmse9060584.
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A great number of collision accidents can be attributed to incongruous collision-avoidance actions between the give-way vessel and the stand-on vessel in a crossing or overtaking situation. If the give-way vessel does not take appropriate collision-avoidance action according to international regulations for preventing collisions at sea, the last barrier to pass safely is the appropriate and effective collision-avoidance action taken by the stand-on vessel. To find the proper autonomous collision-avoidance action of the stand-on vessel, a method is proposed that combines quantitative analysis rules of collision-avoidance with the deduction of nonlinear maneuvering motion process based on the mathematical model group, which conformity can reach 90%. This research presents a method to calculate the timing and most effective collision-avoidance actions for the stand-on vessel based on the four-stage theory of encountering vessels and the characteristics of vessel motion. The accuracy of the latest-action timing and the action amplitude for the stand-on vessel can be increased to the level of second and degree, respectively. A novel model of collision risk index is constructed by the latest time of the feasible collision-avoidance action on the precise of different course-altering amplitude. Methods to find the stand-on vessel’s proper collision-avoidance actions in the open sea are presented. The simulation indicates the proposed method for the stand-on vessel can make correct collision-avoidance decisions autonomously.
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Haider, Shahab, Ziaul Haq Abbas, Ghulam Abbas, Muhammad Waqas, Shanshan Tu, and Wei Zhao. "A Novel Cross-Layer V2V Architecture for Direction-Aware Cooperative Collision Avoidance." Electronics 9, no. 7 (July 8, 2020): 1112. http://dx.doi.org/10.3390/electronics9071112.
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The death toll due to highway crashes is increasing at an alarming rate across the globe. Vehicular Ad Hoc Networks (VANETs) have emerged as a promising solution to prevent crashes by enabling collision avoidance applications. However, a robust and stable collision avoidance application is a cross-layer problem that must address a number of key challenges across all layers of a VANET communication architecture. This paper presents and evaluates a novel VANET protocol suite, named Direction-Aware Vehicular Collision Avoidance (DVCA), which covers application, security services, network, and link layers. DVCA is a vehicle-to-vehicle communication architecture that provides enhanced collision probability computation and adaptive preventive measures for cooperative collision avoidance on bi-directional highways. Moreover, DVCA enables secure, in-time, and reliable dissemination of warning messages, which provides adequate time for vehicles to prevent collisions. Simulation and analytical results demonstrate reasonable reduction in collisions by DVCA, as compared with eminent VANET communication architectures.
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Li, Jinxin, Hongbo Wang, Zhiying Guan, and Chong Pan. "Distributed Multi-Objective Algorithm for Preventing Multi-Ship Collisions at Sea." Journal of Navigation 73, no. 5 (March 3, 2020): 971–90. http://dx.doi.org/10.1017/s0373463320000053.
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Avoidance of collisions at sea is crucial to navigational safety. In this paper, we use a distributed algorithm to communicate the entire collision avoidance trajectory information for each ship. In each communication, we suggest a new improvement function considering safety and efficiency to identify the avoidance ship in each cycle. Considering the nonlinear collision avoidance trajectory of ships, a new method for calculating the degree of danger using a velocity obstacle algorithm is proposed. Therefore, in each communication, each ship considers the avoidance behaviours of other ships in planning its avoidance trajectory. Additionally, we combine bi-criterion evolution (BCE) and the ant lion optimiser to plan the entire collision avoidance path. Three scenarios are designed to demonstrate the performance of this method. The results show that the proposed method can find a suitable collision-free solution for all ships.
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Zhou, Yu, Weijie Du, Jiao Liu, Haoqing Li, Manel Grifoll, Weijun Song, and Pengjun Zheng. "Determination of Ship Collision Avoidance Timing Using Machine Learning Method." Sustainability 16, no. 11 (May 29, 2024): 4626. http://dx.doi.org/10.3390/su16114626.
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The accurate timing for collision avoidance actions is crucial for preventing maritime collisions. Traditional methods often rely on collision risk assessments, using quantitative indicators like the Distance to the Closest Point of Approach (DCPA) and the Time to the Closest Point of Approach (TCPA). Ship Officers on Watch (OOWs) are required to execute avoidance maneuvers once these indicators reach or exceed preset safety thresholds. However, the effectiveness of these indicators is limited by uncertainties in the maritime environment and the human behaviors of OOWs. To address these limitations, this study introduces a machine learning method to learn collision avoidance behavior from empirical data of ship collision avoidance, particularly in cross-encounter situations. The research utilizes Automatic Identification System (AIS) data from the open waters around Ningbo Zhoushan Port. After data preprocessing and applying spatio-temporal constraints, this study identifies ship trajectory pairs in crossing scenarios and calculates their relative motion parameters. The Douglas–Peucker algorithm is used to identify the timing of ship collision avoidance actions and a collision avoidance decision dataset is constructed. The Random Forest algorithm was then used to analyze the factors affecting the timing of collision avoidance, and six key factors were identified: the distance, relative speed, relative bearing, DCPA, TCPA, and the ratio of the lengths of the giving-way and stand-on ships. These factors serve as inputs for the XGBoost algorithm model, which is enhanced with Particle Swarm Optimization (PSO), and thus constructing a ship collision avoidance decision model. In addition, considering the inherent errors in any model and the dynamic nature of the ship collision avoidance process, an action time window for collision avoidance is introduced, which provides a more flexible time range for ships to make timely collision avoidance responses based on actual conditions and the specific encounter environment. This model provides OOWs with accurate timing for taking collision avoidance decisions. Case studies have validated the practicality and effectiveness of this model, offering new theoretical foundations and practical guidance for maritime collision avoidance.
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Chen, C. W., P. H. Hsieh, and W. H. Lai. "APPLICATION OF DECISION TREE ON COLLISION AVOIDANCE SYSTEM DESIGN AND VERIFICATION FOR QUADCOPTER." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W6 (August 23, 2017): 71–75. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w6-71-2017.
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The purpose of the research is to build a collision avoidance system with decision tree algorithm used for quadcopters. While the ultrasonic range finder judges the distance is in collision avoidance interval, the access will be replaced from operator to the system to control the altitude of the UAV. According to the former experiences on operating quadcopters, we can obtain the appropriate pitch angle. The UAS implement the following three motions to avoid collisions. Case1: initial slow avoidance stage, Case2: slow avoidance stage and Case3: Rapid avoidance stage. Then the training data of collision avoidance test will be transmitted to the ground station via wireless transmission module to further analysis. The entire decision tree algorithm of collision avoidance system, transmission data, and ground station have been verified in some flight tests. In the flight test, the quadcopter can implement avoidance motion in real-time and move away from obstacles steadily. In the avoidance area, the authority of the collision avoidance system is higher than the operator and implements the avoidance process. The quadcopter can successfully fly away from the obstacles in 1.92 meter per second and the minimum distance between the quadcopter and the obstacle is 1.05 meters.
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Li, Yun, and Haiyu Zhang. "Collision Avoidance Decision Method for Unmanned Surface Vehicle Based on an Improved Velocity Obstacle Algorithm." Journal of Marine Science and Engineering 10, no. 8 (July 29, 2022): 1047. http://dx.doi.org/10.3390/jmse10081047.
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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.
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Xie, Weidong, Longhui Gang, Mingheng Zhang, Tong Liu, and Zhixun Lan. "Optimizing Multi-Vessel Collision Avoidance Decision Making for Autonomous Surface Vessels: A COLREGs-Compliant Deep Reinforcement Learning Approach." Journal of Marine Science and Engineering 12, no. 3 (February 22, 2024): 372. http://dx.doi.org/10.3390/jmse12030372.
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Automatic collision avoidance decision making for vessels is a critical challenge in the development of autonomous ships and has become a central point of research in the maritime safety domain. Effective and systematic collision avoidance strategies significantly reduce the risk of vessel collisions, ensuring safe navigation. This study develops a multi-vessel automatic collision avoidance decision-making method based on deep reinforcement learning (DRL) and establishes a vessel behavior decision model. When designing the reward function for continuous action spaces, the criteria of the “Convention on the International Regulations for Preventing Collisions at Sea” (COLREGs) were adhered to, taking into account the vessel’s collision risk under various encounter situations, real-world navigation practices, and navigational complexities. Furthermore, to enable the algorithm to precisely differentiate between collision avoidance and the navigation resumption phase in varied vessel encounter situations, this paper incorporated “collision avoidance decision making” and “course recovery decision making” as state parameters in the state set design, from which the respective objective functions were defined. To further enhance the algorithm’s performance, techniques such as behavior cloning, residual networks, and CPU-GPU dual-core parallel processing modules were integrated. Through simulation experiments in the enhanced Imazu training environment, the practicality of the method, taking into account the effects of wind and ocean currents, was corroborated. The results demonstrate that the proposed algorithm can perform effective collision avoidance decision making in a range of vessel encounter situations, indicating its efficiency and robust generalization capabilities.
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Zhu, Hongyang, and Yi Ding. "Optimized Dynamic Collision Avoidance Algorithm for USV Path Planning." Sensors 23, no. 9 (May 8, 2023): 4567. http://dx.doi.org/10.3390/s23094567.
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Ship collision avoidance is a complex process that is influenced by numerous factors. In this study, we propose a novel method called the Optimal Collision Avoidance Point (OCAP) for unmanned surface vehicles (USVs) to determine when to take appropriate actions to avoid collisions. The approach combines a model that accounts for the two degrees of freedom in USV dynamics with a velocity obstacle method for obstacle detection and avoidance. The method calculates the change in the USV’s navigation state based on the critical condition of collision avoidance. First, the coordinates of the optimal collision avoidance point in the current ship encounter state are calculated based on the relative velocities and kinematic parameters of the USV and obstacles. Then, the increments of the vessel’s linear velocity and heading angle that can reach the optimal collision avoidance point are set as a constraint for dynamic window sampling. Finally, the algorithm evaluates the probabilities of collision hazards for trajectories that satisfy the critical condition and uses the resulting collision avoidance probability value as a criterion for course assessment. The resulting collision avoidance algorithm is optimized for USV maneuverability and is capable of handling multiple moving obstacles in real-time. Experimental results show that the OCAP algorithm has higher and more robust path-finding efficiency than the other two algorithms when the dynamic obstacle density is higher.
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Wei, Guan, and Wang Kuo. "COLREGs-Compliant Multi-Ship Collision Avoidance Based on Multi-Agent Reinforcement Learning Technique." Journal of Marine Science and Engineering 10, no. 10 (October 4, 2022): 1431. http://dx.doi.org/10.3390/jmse10101431.
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The congestion of waterways can easily lead to traffic hazards. Moreover, according to the data, the majority of sea collisions are caused by human error and the failure to comply with the Convention on the International Regulation for the preventing Collision at Sea (COLREGs). To avoid this situation, ship automatic collision avoidance has become one of the most important research issues in the field of marine engineering. In this study, an efficient method is proposed to solve multi-ship collision avoidance problems based on the multi-agent reinforcement learning (MARL) algorithm. Firstly, the COLREGs and ship maneuverability are considered for achieving multi-ship collision avoidance. Subsequently, the Optimal Reciprocal Collision Avoidance (ORCA) algorithm is utilized to detect and reduce the risk of collision. Ships can operate at the safe velocity computed by the ORCA algorithm to avoid collisions. Finally, the Nomoto three-degrees-of-freedom (3-DOF) model is used to simulate the maneuvers of ships. According to the above information and algorithms, this study designs and improves the state space, action space and reward function. For validating the effectiveness of the method, this study designs various simulation scenarios with thorough performance evaluations. The simulation results indicate that the proposed method is flexible and scalable in solving multi-ship collision avoidance, complying with COLREGs in various scenarios.
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Watanabe, Kento, Jun’ichi Kaneko, and Kenichiro Horio. "Development of Tool Collision Avoidance Method Adapted to Uncut Workpiece Shape." International Journal of Automation Technology 11, no. 2 (March 1, 2017): 235–41. http://dx.doi.org/10.20965/ijat.2017.p0235.
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This study developed an automatic planning method for tool collision avoidance, with posture adapted to the uncut shape of a workpiece to avoid collisions between the tool and workpiece in five-axis machining. This method sequentially judges the likelihood of collision between the holder and shank parts of the tool and the workpiece while machining, which is updated with tool motion. Then it automatically determines tool postures in which no collisions occur. The process of setting the search range for collision avoidance postures of the tool when collisions occur is made more efficient; it is possible to prevent rapid changes in tool posture at the time of avoidance, while reducing the time for geometric operations necessary when searching for compatible orientations.
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Lin, Jun Ting, Xiao Ming Wang, and Jian Wu Dang. "A New Collision Avoidance Strategy for Chinese Train Control System." Applied Mechanics and Materials 614 (September 2014): 179–83. http://dx.doi.org/10.4028/www.scientific.net/amm.614.179.
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There are still enormous amount of collision between trains even if comprehensive and complex technology, such as train control system, is extensively deployed in the infrastructure which should help to avoid such collisions. Experiences from aviation, maritime, and road transport systems have shown that the probability of collisions can be significantly reduced with collision avoidance systems basing on direct vehicle-to-vehicle communication on-board, which do hardly require infrastructure components. Additional Collision Avoidance System overlay Train Control System (CASOTCS) for Chinese railway, which is independent of the regular control mechanism, is provided in this paper. CASOTCS unit architecture and its key issues: position detection, direct train-to-train communication and collision surveillance resolution are also discussed. CASOTCS receives and evaluates the information broadcasted by other infinity trains, if a potential collision is detected, lead to collision alerts and avoidance resolution advisories. CASOTCS has the potential to increase safety and efficiency in the future, such as shorten the distance between trains.
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Tsou, Ming-Cheng, Sheng-Long Kao, and Chien-Min Su. "Decision Support from Genetic Algorithms for Ship Collision Avoidance Route Planning and Alerts." Journal of Navigation 63, no. 1 (December 1, 2009): 167–82. http://dx.doi.org/10.1017/s037346330999021x.
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When an officer of the watch (OOW) faces complicated marine traffic, a suitable decision support tool could be employed in support of collision avoidance decisions, to reduce the burden and greatly improve the safety of marine traffic. Decisions on routes to avoid collisions could also consider economy as well as safety. Through simulating the biological evolution model, this research adopts the genetic algorithm used in artificial intelligence to find a theoretically safety-critical recommendation for the shortest route of collision avoidance from an economic viewpoint, combining the international regulations for preventing collisions at sea (COLREGS) and the safety domain of a ship. Based on this recommendation, an optimal safe avoidance turning angle, navigation restoration time and navigational restoration angle will also be provided. A Geographic Information System (GIS) will be used as the platform for display and operation. In order to achieve advance notice of alerts and due preparation for collision avoidance, a Vessel Traffic Services (VTS) operator and the OOW can use this system as a reference to assess collision avoidance at present location.
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Tang, Jun, Miquel Angel Piera, Yunxiang Ling, and Linjun Fan. "Extended Traffic Alert Information to Improve TCAS Performance by means of Causal Models." Mathematical Problems in Engineering 2015 (2015): 1–11. http://dx.doi.org/10.1155/2015/303768.
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Near-midair collisions (NMACs) between aircraft have long been a primary safety concern and have incessantly motivated the development of ingenious onboard collision avoidance (CA) systems to reduce collision risk. The Traffic Alert and Collision Avoidance System (TCAS) acts as a proverbially accepted last-resort means to resolve encounters, while it also has been proved to potentially induce a collision in the hectic and congested traffic. This paper aims to improve the TCAS collision avoidance performance by enriching traffic alert information, which strictly fits with present TCAS technological requirements and extends the threat detection considering induced collisions and probabilistic pilot response. The proposed model is specified in coloured Petri net (CPN) formalism, to generate by simulation all the future possible downstream reachable states to enhance the follow-up decision making of pilots via synthesising relevant information related to collision states. With the complete state space, the potential collision scenarios can be identified together with those manoeuvres that may transform a conflict into a collision. The causal TCAS model is demonstrated to work effectively for complex multiaircraft scenarios and to identify the feasible manoeuvres that contribute to reduce the nonzero TCAS-induced collision risk.
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Yang, Zhiqiang, Hao Lu, Pengpeng Wang, and Shijie Guo. "Coordinating Obstacle Avoidance of a Redundant Dual-Arm Nursing-Care Robot." Bioengineering 11, no. 6 (May 29, 2024): 550. http://dx.doi.org/10.3390/bioengineering11060550.
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Collision safety is an essential issue for dual-arm nursing-care robots. However, for coordinating operations, there is no suitable method to synchronously avoid collisions between two arms (self-collision) and collisions between an arm and the environment (environment-collision). Therefore, based on the self-motion characteristics of the dual-arm robot’s redundant arms, an improved motion controlling algorithm is proposed. This study introduces several key improvements to existing methods. Firstly, the volume of the robotic arms was modeled using a capsule-enveloping method to more accurately reflect their actual structure. Secondly, the gradient projection method was applied in the kinematic analysis to calculate the shortest distances between the left arm, right arm, and the environment, ensuring effective avoidance of the self-collision and environment-collision. Additionally, distance thresholds were introduced to evaluate collision risks, and a velocity weight was used to control the smooth coordinating arm motion. After that, experiments of coordinating obstacle avoidance showed that when the redundant dual-arm robot is holding an object, the coordinating operation was completed while avoiding self-collision and environment-collision. The collision-avoidance method could provide potential benefits for various scenarios, such as medical robots and rehabilitating robots.
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Gnanasekera, Manaram, and Jay Katupitiya. "A Time-Efficient Method to Avoid Collisions for Collision Cones: An Implementation for UAVs Navigating in Dynamic Environments." Drones 6, no. 5 (April 25, 2022): 106. http://dx.doi.org/10.3390/drones6050106.
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This paper presents a methodology that can be used to avoid collisions of aerial drones. Even though there are many collision avoidance methods available in literature, collision cone is a proven method that can be used to predict a collision beforehand. In this research, we propose an algorithm to avoid a collision in a time-efficient manner for collision cone based aerial collision avoidance approaches. Furthermore, the paper has considered all possible scenarios including heading change, speed change and combined heading and speed change, to avoid a collision. The heading-based method was mathematically proven to be the most time-efficient method out of the three. The proposed heading-based method was compared with other work presented in the literature and validated with both simulations and experiments. A Matrice 600 Pro hexacopter is used for the collision avoidance experiments.
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Gnanasekera, Manaram, and Jay Katupitiya. "A Time-Efficient Method to Avoid Collisions for Collision Cones: An Implementation for UAVs Navigating in Dynamic Environments." Drones 6, no. 5 (April 25, 2022): 106. http://dx.doi.org/10.3390/drones6050106.
Full textAbstract:
This paper presents a methodology that can be used to avoid collisions of aerial drones. Even though there are many collision avoidance methods available in literature, collision cone is a proven method that can be used to predict a collision beforehand. In this research, we propose an algorithm to avoid a collision in a time-efficient manner for collision cone based aerial collision avoidance approaches. Furthermore, the paper has considered all possible scenarios including heading change, speed change and combined heading and speed change, to avoid a collision. The heading-based method was mathematically proven to be the most time-efficient method out of the three. The proposed heading-based method was compared with other work presented in the literature and validated with both simulations and experiments. A Matrice 600 Pro hexacopter is used for the collision avoidance experiments.
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Gnanasekera, Manaram, and Jay Katupitiya. "A Time-Efficient Method to Avoid Collisions for Collision Cones: An Implementation for UAVs Navigating in Dynamic Environments." Drones 6, no. 5 (April 25, 2022): 106. http://dx.doi.org/10.3390/drones6050106.
Full textAbstract:
This paper presents a methodology that can be used to avoid collisions of aerial drones. Even though there are many collision avoidance methods available in literature, collision cone is a proven method that can be used to predict a collision beforehand. In this research, we propose an algorithm to avoid a collision in a time-efficient manner for collision cone based aerial collision avoidance approaches. Furthermore, the paper has considered all possible scenarios including heading change, speed change and combined heading and speed change, to avoid a collision. The heading-based method was mathematically proven to be the most time-efficient method out of the three. The proposed heading-based method was compared with other work presented in the literature and validated with both simulations and experiments. A Matrice 600 Pro hexacopter is used for the collision avoidance experiments.
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Hwang, Taewoong, and Ik-Hyun Youn. "Collision Risk Situation Clustering to Design Collision Avoidance Algorithms for Maritime Autonomous Surface Ships." Journal of Marine Science and Engineering 10, no. 10 (September 27, 2022): 1381. http://dx.doi.org/10.3390/jmse10101381.
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The reliability of collision avoidance systems for Maritime Autonomous Surface Ships is one of the most critical factors for their safety. In particular, since many ship collisions occur in coastal areas, it is crucial to ensure the reliability of collision avoidance algorithms in geographically limited coastal waters. However, studies on maritime autonomous surface ships collision avoidance algorithms mainly focus on the traffic factor despite the importance of the geographic factor. Therefore, this study presents a methodology for establishing a practical collision avoidance system test bed, considering the geographic environment. The proposed methodology is a data-driven approach that objectively categorizes collision risk situations by extracting these risks using Automatic Identification System (AIS) and Electronic Navigational Chart (ENC) data, followed by clustering algorithms. Consequently, the research results present a direction for establishing test beds from the perspective of geographic and traffic factors.
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Sabattini, Lorenzo, Cristian Secchi, and Cesare Fantuzzi. "Collision avoidance for multiple Lagrangian dynamical systems with gyroscopic forces." International Journal of Advanced Robotic Systems 14, no. 1 (January 1, 2017): 172988141668710. http://dx.doi.org/10.1177/1729881416687109.
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This article introduces a novel methodology for dealing with collision avoidance for groups of mobile robots. In particular, full dynamics are considered, since each robot is modeled as a Lagrangian dynamical system moving in a three-dimensional environment. Gyroscopic forces are utilized for defining the collision avoidance control strategy: This kind of forces leads to avoiding collisions, without interfering with the convergence properties of the multi-robot system’s desired control law. Collision avoidance introduces, in fact, a perturbation on the nominal behavior of the system: We define a method for choosing the direction of the gyroscopic force in an optimal manner, in such a way that perturbation is minimized. Collision avoidance and convergence properties are analytically demonstrated, and simulation results are provided for validation purpose.
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Yang, Xiao, and Qilong Han. "Improved DQN for Dynamic Obstacle Avoidance and Ship Path Planning." Algorithms 16, no. 5 (April 25, 2023): 220. http://dx.doi.org/10.3390/a16050220.
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The avoidance of collisions among ships requires addressing various factors such as perception, decision-making, and control. These factors pose many challenges for autonomous collision avoidance. Traditional collision avoidance methods have encountered significant difficulties when used in autonomous collision avoidance. They are challenged to cope with the changing environment and harsh motion constraints. In the actual navigation of ships, it is necessary to carry out decision-making and control under the constraints of ship manipulation and risk. From the implementation process perspective, it is a typical sequential anthropomorphic decision-making problem. In order to solve the sequential decision problem, this paper improves DQN by setting a priority for sample collection and adopting non-uniform sampling, and it is applied to realize the intelligent collision avoidance of ships. It also verifies the performance of the algorithm in the simulation environment.
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Wróbel, Krzysztof, Mateusz Gil, Yamin Huang, and Ryszard Wawruch. "The Vagueness of COLREG versus Collision Avoidance Techniques—A Discussion on the Current State and Future Challenges Concerning the Operation of Autonomous Ships." Sustainability 14, no. 24 (December 9, 2022): 16516. http://dx.doi.org/10.3390/su142416516.
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With the development of Maritime Autonomous Surface Ships (MASS), considerable research is undertaken to secure their safety. One of the critical aspects of MASS is collision avoidance, and multiple collision avoidance algorithms have been developed. However, due to various reasons, collision avoidance of autonomous merchant vessels appears to be far from resolved. With this study, we aim to discuss the current state of Collision Avoidance Methods (CAMs) and the challenges lying ahead—from a joint academic and practical point of view. To this end, the key Rules from International Regulations for Preventing Collisions at Sea (COLREG) have been reviewed with a focus on their practical application for MASS. Moreover, the consideration of the COLREG Rules in contemporary collision avoidance algorithms has been reviewed. The ultimate objective is to identify aspects of COLREG requiring additional attention concerning MASS developments in terms of collision avoidance. Our conclusions indicate that although a lot of progress has been achieved recently, the feasibility of CAMs for MASS remains questionable. Reasons for so are the ambiguous character of the regulations, especially COLREG, as well as virtually all existing CAMs being at best only partly COLREG-compliant.
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Zhang, Yi, Dapeng Zhang, and Haoyu Jiang. "A Review of Artificial Intelligence-Based Optimization Applications in Traditional Active Maritime Collision Avoidance." Sustainability 15, no. 18 (September 7, 2023): 13384. http://dx.doi.org/10.3390/su151813384.
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The probability of collisions at sea has increased in recent years. Furthermore, passive collision avoidance has some disadvantages, such as low economic efficiency, while active collision avoidance techniques have some limitations. As a result of the advancement of computer technology, active collision avoidance techniques have also been optimized by using artificial intelligence-based methods. The purpose of this paper is to further the development of the field. After reviewing some passive collision avoidance schemes, the paper discusses the potential of active obstacle avoidance techniques. A time-tracing approach is used to review the evolution of active obstacle avoidance techniques, followed by a review of the main traditional active obstacle avoidance techniques. In this paper, different artificial intelligence algorithms are reviewed and analyzed. As a result of the analysis and discussion in this paper, some limitations in this field are identified. In addition, there are some suggestions and outlooks for addressing those limitations. In a way, the paper can serve as a guide for the development of the field.
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Xu, Qingyang, and Ning Wang. "A Survey on Ship Collision Risk Evaluation." PROMET - Traffic&Transportation 26, no. 6 (December 30, 2014): 475–86. http://dx.doi.org/10.7307/ptt.v26i6.1386.
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Recently, ship collision avoidance has become essential due to the emergence of special vessels like chemical tankers and VLCCs (very large crude carriers), etc. The information needed for safe navigation is obtained by combining electrical equipment with real-time visual information. However, misjudgements and human errors are the major cause of ship collisions according to research data. The decision support system of Collision avoidance is an advantageous facility to make up for this. Collision risk evaluation is one of the most important problems in collision avoidance decision supporting system. A review is presented of different approaches to evaluate the collision risk in maritime transportation. In such a context, the basic concepts and definitions of collision risk and their evaluation are described. The review focuses on three categories of numerical models of collision risk calculation: methods based on traffic flow theory, ship domain and methods based on dCPA and tCPA.
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Lai, Ying-Chih, and Tzu-Yun Lin. "Vision-Based Mid-Air Object Detection and Avoidance Approach for Small Unmanned Aerial Vehicles s with Deep Learning and Risk Assessment." Remote Sensing 16, no. 5 (February 21, 2024): 756. http://dx.doi.org/10.3390/rs16050756.
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With the increasing demand for unmanned aerial vehicles (UAVs), the number of UAVs in the airspace and the risk of mid-air collisions caused by UAVs are increasing. Therefore, detect and avoid (DAA) technology for UAVs has become a crucial element for mid-air collision avoidance. This study presents a collision avoidance approach for UAVs equipped with a monocular camera to detect small fixed-wing intruders. The proposed system can detect any size of UAV over a long range. The development process consists of three phases: long-distance object detection, object region estimation, and collision risk assessment and collision avoidance. For long-distance object detection, an optical flow-based background subtraction method is utilized to detect an intruder far away from the host. A mask region-based convolutional neural network (Mask R-CNN) model is trained to estimate the region of the intruder in the image. Finally, the collision risk assessment adopts the area expansion rate and bearing angle of the intruder in the images to conduct mid-air collision avoidance based on visual flight rules (VFRs) and conflict areas. The proposed collision avoidance approach is verified by both simulations and experiments. The results show that the system can successfully detect different sizes of fixed-wing intruders, estimate their regions, and assess the risk of collision at least 10 s in advance before the expected collision would happen.
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Fan, Yunsheng, Zhe Sun, and Guofeng Wang. "A Novel Reinforcement Learning Collision Avoidance Algorithm for USVs Based on Maneuvering Characteristics and COLREGs." Sensors 22, no. 6 (March 8, 2022): 2099. http://dx.doi.org/10.3390/s22062099.
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Autonomous collision avoidance technology provides an intelligent method for unmanned surface vehicles’ (USVs) safe and efficient navigation. In this paper, the USV collision avoidance problem under the constraint of the international regulations for preventing collisions at sea (COLREGs) was studied. Here, a reinforcement learning collision avoidance (RLCA) algorithm is proposed that complies with USV maneuverability. Notably, the reinforcement learning agent does not require any prior knowledge about USV collision avoidance from humans to learn collision avoidance motions well. The double-DQN method was used to reduce the overestimation of the action-value function. A dueling network architecture was adopted to clearly distinguish the difference between a great state and an excellent action. Aiming at the problem of agent exploration, a method based on the characteristics of USV collision avoidance, the category-based exploration method, can improve the exploration ability of the USV. Because a large number of turning behaviors in the early steps may affect the training, a method to discard some of the transitions was designed, which can improve the effectiveness of the algorithm. A finite Markov decision process (MDP) that conforms to the USVs’ maneuverability and COLREGs was used for the agent training. The RLCA algorithm was tested in a marine simulation environment in many different USV encounters, which showed a higher average reward. The RLCA algorithm bridged the divide between USV navigation status information and collision avoidance behavior, resulting in successfully planning a safe and economical path to the terminal.
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Wang, Pangwei, WenXiang Wu, Xiaohui Deng, Lin Xiao, Li Wang, and Min Li. "Novel Cooperative Collision Avoidance Model for Connected Vehicles." Transportation Research Record: Journal of the Transportation Research Board 2645, no. 1 (January 2017): 144–56. http://dx.doi.org/10.3141/2645-16.
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Connected vehicle technology exchanges real-time vehicle and traffic information through vehicle-to-vehicle and vehicle-to-infrastructure communication. The technology has the potential to improve traffic safety applications such as collision avoidance. In this paper, a novel cooperative collision avoidance (CCA) model that could improve the effectiveness of the collision avoidance system of connected vehicles was developed. Unlike traditional collision avoidance models, which relied mainly on emergency braking, the proposed CCA approach avoided collision through a combination of following vehicle deceleration and leading vehicle acceleration. Through spacing policy theory and nonlinear optimization, the model calculated the desired deceleration rate for the following vehicle and the acceleration rate for the leading vehicle, respectively, at each time interval. The CCA approach was then tested on a scaled platform with hardware-in-the-loop simulation embedded with MATLAB/Simulink and a car simulator package, CarSim. Results show that the proposed model can effectively avoid rear-end collisions in a three-vehicle platoon.
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Song, Lifei, Houjing Chen, Wenhao Xiong, Zaopeng Dong, Puxiu Mao, Zuquan Xiang, and Kai Hu. "Method of Emergency Collision Avoidance for Unmanned Surface Vehicle (USV) Based on Motion Ability Database." Polish Maritime Research 26, no. 2 (June 1, 2019): 55–67. http://dx.doi.org/10.2478/pomr-2019-0025.
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Abstract The unmanned surface vehicles (USV) are required to perform a dynamic obstacle avoidance during fulfilling a task. This is essential for USV safety in case of an emergency and such action has been proved to be difficult. However, little research has been done in this area. This study proposes an emergency collision avoidance algorithm for unmanned surface vehicles (USVs) based on a motion ability database. The algorithm is aimed to address the inconsistency of the existing algorithm. It is proposed to avoid collision in emergency situations by sharp turning and treating the collision avoidance process as a part of the turning movement of USV. In addition, the rolling safety and effect of speed reduction during the collision avoidance process are considered. First, a USV motion ability database is established by numerical simulation. The database includes maximum rolling angle, velocity vector, position scalar, and steering time data during the turning process. In emergency collision avoidance planning, the expected steering angle is obtained based on the International Regulations for Preventing Collisions at Sea (COLREGs), and the solution space, with initial velocity and rudder angle taken as independent variables, is determined by combining the steering time and rolling angle data. On the basis of this solution space, the objective function is solved by the particle swarm optimization (PSO) algorithm, and the optimal initial velocity and rudder angle are obtained. The position data corresponding to this solution is the emergency collision avoidance trajectory. Then, the collision avoidance parameters were calculated based on the afore mentioned model of motion. With the use of MATLAB and Unity software, a semi-physical simulation platform was established to perform the avoidance simulation experiment under emergency situation. Results show the validity of the algorithm. Hence results of this research can be useful for performing intelligent collision avoidance operations of USV and other autonomous ships
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Li, Haibin, Xin Wang, Tianhao Wu, and Shengke Ni. "A COLREGs-Compliant Ship Collision Avoidance Decision-Making Support Scheme Based on Improved APF and NMPC." Journal of Marine Science and Engineering 11, no. 7 (July 13, 2023): 1408. http://dx.doi.org/10.3390/jmse11071408.
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In this paper, combined with the improved artificial potential field (IAPF) method and the nonlinear model predictive control (NMPC) algorithm, a collision avoidance decision-making support scheme considering ship maneuverability and the International Regulations for Preventing Collisions at Sea (COLREGs) is proposed. First, to comply with the requirements of COLREGs, an improved repulsive potential field is presented for different encounter scenarios when the ship detects the risk of collision, and the coordinated ship domain is applied to provide safety criteria for collision avoidance. Then, by transforming the MMG model to a discrete-time nonlinear system, the NMPC is utilized to predict the future state of the ship according to the current state, and the IAPF method is incorporated to calculate the potential field in each future state as the objective function. Following this approach, the action taken to avoid collision is more effective, the ship motion in avoiding collision is more accurate, and the collision avoidance decision making is more reasonable. Finally, two simulation examples of multi-ship encounter scenarios are applied to illustrate the merits and effectiveness of the proposed collision avoidance decision-making support scheme.
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Barakat, L. A., and I. Y. Kvyatkovskaya. "Autonomous collision avoidance system for unmanned vessels: algorithms and software." Applied Mathematics and Control Sciences, no. 4 (December 15, 2023): 83–93. http://dx.doi.org/10.15593/2499-9873/2023.4.05.
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Ship collision is one of the most substantial concerns in the global maritime transportation industry. Hence, navigation safety is considerably cited topic in maritime literature. Recently, Unmanned Navigation (UN) technology is gradually becoming more widely used across in the field of marine robotics. The paper investigates the problem of navigation safety in the movement control of Unmanned Vessels (UVs). The object of the study is the process of avoiding collisions of UVs. The subject of the research is the algorithms of the autonomous decision-making system and software for preventing vessel collisions during UN. The intent of this article is to improve the safety of UN by developing new Decision-Making algorithms for autonomous collision prevention of UVs in real time, taking into account the International Rules for the Prevention of Collisions at Sea, 1972 (COLREGs-72) and the recommendations of the Federal agency for sea and inland water transport of the Russian Federation (Rosmorrechflot).In this article, the fundamental concept and the key functions set of the Autonomous Collision Avoidance System (ACAS) are carried out for UVs which are marine transport vehicles capable of sensing its environment and operating without human involvement. Along this line of research, this work focuses on the development of a software algorithm for determining the most dangerous obstacle located within a radius of 12 miles (recommendations of Rosmorrechflot) around an UV based on the principle of vessels collision avoidance geometry, collision risk assessment and the characteristics of obstacles. Moreover, the proposed algorithms can prevent the collision and address the issues of real-time collision avoidance for UVs. The simulation results also demonstrate the promising application of the proposed algorithms in studying the UN safety. Nonetheless, this study provides a way forward to conduct a new information decision-making system design for UVs collision avoidance. This is currently under development, and will be proposed later.
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Hwang, Taewoong, and Ik-Hyun Youn. "Navigation Situation Clustering Model of Human-Operated Ships for Maritime Autonomous Surface Ship Collision Avoidance Tests." Journal of Marine Science and Engineering 9, no. 12 (December 20, 2021): 1458. http://dx.doi.org/10.3390/jmse9121458.
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The collision avoidance system is one of the core systems of MASS (Maritime Autonomous Surface Ships). The collision avoidance system was validated using scenario-based experiments. However, the scenarios for the validation were designed based on COLREG (International Regulations for Preventing Collisions at Sea) or are arbitrary. Therefore, the purpose of this study is to identify and systematize objective navigation situation scenarios for the validation of autonomous ship collision avoidance algorithms. A data-driven approach was applied to collect 12-month Automatic Identification System data in the west sea of Korea, to extract the ship’s trajectory, and to hierarchically cluster the data according to navigation situations. Consequently, we obtained the hierarchy of navigation situations and the frequency of each navigation situation for ships that sailed the west coast of Korea during one year. The results are expected to be applied to develop a collision avoidance test environment for MASS.
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Brunn, Paul. "Robot collision avoidance." Industrial Robot: An International Journal 23, no. 1 (February 1996): 27–33. http://dx.doi.org/10.1108/01439919610108828.
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Sun, Zhe, Yunsheng Fan, and Guofeng Wang. "An Intelligent Algorithm for USVs Collision Avoidance Based on Deep Reinforcement Learning Approach with Navigation Characteristics." Journal of Marine Science and Engineering 11, no. 4 (April 11, 2023): 812. http://dx.doi.org/10.3390/jmse11040812.
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Many achievements toward unmanned surface vehicles have been made using artificial intelligence theory to assist the decisions of the navigator. In particular, there has been rapid development in autonomous collision avoidance techniques that employ the intelligent algorithm of deep reinforcement learning. A novel USV collision avoidance algorithm based on deep reinforcement learning theory for real-time maneuvering is proposed. Many improvements toward the autonomous learning framework are carried out to improve the performance of USV collision avoidance, including prioritized experience replay, noisy network, double learning, and dueling architecture, which can significantly enhance the training effect. Additionally, considering the characteristics of the USV collision avoidance problem, two effective methods to enhance training efficiency are proposed. For better training, considering the international regulations for preventing collisions at sea and USV maneuverability, a complete and reliable USV collision avoidance training system is established, demonstrating an efficient learning process in complex encounter situations. A reward signal system in line with the USV characteristics is designed. Based on the Unity maritime virtual simulation platform, an abundant simulation environment for training and testing is designed. Through detailed analysis, verification, and comparison, the improved algorithm outperforms the pre-improved algorithm in terms of stability, average reward, rules learning, and collision avoidance effect, reducing 26.60% more accumulated course deviation and saving 1.13% more time.
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Zhang, Ke, Liwen Huang, Xiao Liu, Jiahao Chen, Xingya Zhao, Weiguo Huang, and Yixiong He. "A Novel Decision Support Methodology for Autonomous Collision Avoidance Based on Deduction of Manoeuvring Process." Journal of Marine Science and Engineering 10, no. 6 (June 1, 2022): 765. http://dx.doi.org/10.3390/jmse10060765.
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In the last few years, autonomous ships have attracted increasing attention in the maritime industry. Autonomous ships with an autonomous collision avoidance capability are the development trend for future ships. In this study, a ship manoeuvring process deduction-based dynamic adaptive autonomous collision avoidance decision support method for autonomous ships is presented. Firstly, the dynamic motion parameters of the own ship relative to the target ship are calculated by using the dynamic mathematical model. Then the fuzzy set theory is adopted to construct collision risk models, which combine the spatial collision risk index (SCRI) and time collision risk index (TCRI) in different encountered situations. After that, the ship movement model and fuzzy adaptive PID method are used to derive the ships’ manoeuvre motion process. On this basis, the feasible avoidance range and the optimal steering angle for ship collision avoidance are calculated by deducting the manoeuvring process and the modified velocity obstacle (VO) method. Moreover, to address the issue of resuming sailing after the ship collision avoidance is completed, the Line of Sight (LOS) guidance system is adopted to resume normal navigation for the own ship in this study. Finally, the dynamic adaptive autonomous collision avoidance model is developed by combining the ship movement model, the fuzzy adaptive PID control model, the modified VO method and the resume-sailing model. The results of the simulation show that the proposed methodology can effectively avoid collisions between the own ship and the moving TSs for situations involving two or multiple ships, and the own ship can resume its original route after collision avoidance is completed. Additionally, it is also proved that this method can be applied to complex situations with various encountered ships, and it exhibits excellent adaptability and effectiveness when encountering multiple objects and complex situations.
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Shan, Lin, Huan-Bang Li, Ryu Miura, Takashi Matsuda, and Takeshi Matsumura. "A Novel Collision Avoidance Strategy with D2D Communications for UAV Systems." Drones 7, no. 5 (April 22, 2023): 283. http://dx.doi.org/10.3390/drones7050283.
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In recent years, safety operation issues related to the autonomous flight of unmanned aerial vehicles (UAVs) have become popular research and development topics worldwide. Among all UAV applications, multiple UAV-related applications are emerging due to the integration of UAVs into 6G networks, which is an important topic for next-generation wireless communication systems. For multiple UAV applications, flight safety among UAVs is the most significant issue. Therefore, collision avoidance for UAVs has become an emerging topic in UAV-related research. In the past, although many UAV collision avoidance methods have been proposed, there is still a probability of other problems, such as no possible avoidance route and unmanaged UAVs that are without centralized control, which both result in an unpredictable risk of collisions. In this study, we investigate the current existing methods and propose novel collision avoidance methods based on the elastic collision principle. To verify the performance of the proposed methods, we also conduct simulations in this paper to demonstrate their effectiveness. From the simulation results, it can be seen that the proposed methods can effectively perform collision avoidance for multiple UAVs. Specifically, using the proposed methods, all UAVs can reach their destination points within reasonable time resources without any collision, validating the effectiveness of the proposed methods.
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Yu, Jiagen, Zhengjiang Liu, and Xianku Zhang. "DCA-Based Collision Avoidance Path Planning for Marine Vehicles in Presence of the Multi-Ship Encounter Situation." Journal of Marine Science and Engineering 10, no. 4 (April 12, 2022): 529. http://dx.doi.org/10.3390/jmse10040529.
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The problem of ship collision avoidance path planning is one of the key problems in the ship motion control field. Aiming at the high computational time problem of path planning in multi-ship encounter situations and the impact of the target ship’s action changes on path planning, this paper proposes a dynamic path-planning method based on dynamic cluster analysis (DCA), which is used to dynamically cluster target ships with similar attributes into a group ship, reducing the number of calculated targets and improving the efficiency of path planning. Taking into full consideration the action requirements of the International Regulations for Preventing Collisions at Sea (COLREGs), the course alteration action matrix (CAAM) for collision avoidance is established to limit the space of candidate solutions. On the basis of the rapid optimization capability of the deterministic optimization algorithm (DOA), a dynamic monitoring mechanism is introduced to establish a multi-ship encounter intelligent collision avoidance decision-making model that meets the needs of real-time collision avoidance. The simulation results showed that the method can obtain a dynamic collision avoidance path that is safe and feasible.
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Zhou, Lingyu, Huayong Li, Jun Wei, Xingxu Pu, Akim D. Mahunon, and Liqiang Jiang. "Design and Simulation Analysis of a New Type of Assembled UHPC Collision Avoidance." Applied Sciences 10, no. 13 (June 30, 2020): 4555. http://dx.doi.org/10.3390/app10134555.
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Ship-bridge collisions are one of the most common types of accidents, and bridge anti-ship collision devices are of great importance for bridge protection. First, a new type of assembled ultra-high performance concrete (UHPC) collision avoidance is proposed in this paper. The main components of the device are double-deck, two-way, densely reinforced ultra-high performance concrete floating boxes that are connected by high-strength bolts to form the whole structure and are equipped with steel supporting elements to form a collision energy dissipation device. The device is self-floating in water, is strongly energy absorbing due to plastic deformation, has a high degree of toughness, is corrosion resistant, and so on. This device also benefits from modular manufacturing, efficient installation, and easy replacement of damaged parts. Then, in this paper, the main parameters of the new collision avoidance, such as the material of the internal supporting elements, the wall thickness of the floating box, and the reinforcement ratio of the floating box, are optimized. Finally, a performance analysis and evaluation of the UHPC collision avoidance for the Honghe Bridge in Zhuhai City are carried out by using LS-DYNA program. The numerical results show that the new collision avoidance has significant advantages in reducing the ship–bridge collision force, prolonging the ship–bridge collision time, and protecting the ship. The results show that the assembled UHPC collision avoidance system is very effective for protecting ships and bridges in the event of a ship–bridge collision.
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Song, Lifei, Zhuo Chen, Zaopeng Dong, Zuquan Xiang, Yunsheng Mao, Yiran Su, and Kai Hu. "Collision avoidance planning for unmanned surface vehicle based on eccentric expansion." International Journal of Advanced Robotic Systems 16, no. 3 (May 1, 2019): 172988141985194. http://dx.doi.org/10.1177/1729881419851945.
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The International Regulations for Preventing Collisions at Sea (COLREGS) specify certain navigation rules for ships at risk for collision. Theoretically, the safety of unmanned surface vehicles and traffic boats would be guaranteed when they comply with the COLREGS. However, if traffic boats do not comply with the demands of the convention, thereby increasing the danger level, then adhering to the COLREGS may be dangerous for the unmanned surface vehicle. In this article, a dynamic obstacle avoidance algorithm for unmanned surface vehicles based on eccentric expansion was developed. This algorithm is used to solve the possible failure of collision avoidance when the unmanned surface vehicle invariably obeys the COLREGS during the avoidance process. An obstacle avoidance model based on the velocity obstacle method was established. Thereafter, an eccentric expansion operation on traffic boats was proposed to ensure a reasonable balance between safety and the rules of COLREGS. The expansion parameters were set according to the rules of COLREGS and the risk level of collision. Then, the collision avoidance parameters were calculated based on the aforementioned motion model. With the use of MATLAB and Unity software, a semi-physical simulation platform was established to perform the avoidance simulation experiment under different situations. Results show the validity, reliability and intellectuality of the algorithm. This research can be used for intelligent collision avoidance of unmanned surface vehicle and other automatic driving ships.