Collision Avoidance Routing Research Articles

Ship Route Planning for Collision Avoidance Based on the Improved Isochrone Method

If ship navigators could access precise collision risk data and guidance for avoidance, safer navigation would be feasible. This study introduces a method for devising avoidance routes based on quantitative collision risk assessment. In particular, we propose an improved isochrone method, a cell-free approach akin to real ship navigation routes. The method uses a novel heuristic function to ensure effective collision avoidance, even in scenarios where conventional heuristic algorithms fail. Through verification cases, we demonstrate that the proposed method successfully avoided collisions, even in situations with unexpected lined-up ships, reducing maximum collision risk by up to 94.0%. Applications of the proposed method with actual AIS (Automatic Identification System) data yield simulation results with successful collision avoidance route planning. Comparing the proposed method to avoidance routes using other existing methods and to the actual ship’s route, the proposed method was able to plan a route with a 37.5% improvement in maximum collision risk and a 13.6% improvement in average collision risk.

Marine Collision Avoidance Route Planning Model for MASS Based on Domain-Based Predicted Area of Danger

When the own ship encounters target ships in a close-quarter situation, an officer on watch needs to safely and timely alter the course of the vessel to avoid a collision. If ECDIS can automatically collect the navigation parameters and plot areas of collision as quasi-static obstruction areas, it will be much easier for seafarers to implement effective route planning. Hence, this study focuses on developing the MCARP model as a theoretical concept based on the DPAD model and LCD model. By operating the MCARP using ArcGIS, DPADs and several effective collision avoidance routes can be generated and imported into ECDIS based on AIS information at large scales and ample time. The graphic overlay of DPADs and effective routes on ECDIS can serve as a collision avoidance strategy reference for the personnel controlling maritime autonomous surface ships. Finally, different ships encountering situations were input into a Transas navigational simulator. The simulation results showed that own ship could avoid collisions with multiple target ships at distances larger than the preset collision avoidance distances, which also indicated that MCARP is practically feasible.

Automatic Collision Avoidance Route Planning Method in Complex Navigation Environments

Efficient collision avoidance (CA) route planning is one of the important technologies for ensuring the safety of autonomous ships. Many CA route planning studies have been developed for the open sea, but few studies have been conducted for ships in complex navigation environments. A complex navigation environment refers to water encompassing various factors, such as multiple obstacles, varying water depths, ships collision risk, and other maritime challenges. These factors collectively contribute to the complexity of the environment. CA planning in this type of environment is a special type of route planning. To address CA in complex navigation environments, firstly, the route binary tree algorithm is utilized for conducting global route planning in order to determine the optimal path. Secondly, this paper proposes a dynamic generation of local collision avoidance trajectories along the optimal path, seamlessly integrating global route optimization and local collision avoidance. Finally, a comparative analysis is conducted using classical techniques to verify the effectiveness of the proposed method. Numerical simulation results reveal that when a ship is taken as the object of CA in the open sea, the route generated using the proposed method exhibits a remarkable level of unity with the one generated by the benchmark method of improved Artificial Potential Field (APF), particularly in terms of collision avoidance strategy selection, collision avoidance trends, and the actual trajectory. The former’s computational efficiency is improved by at least 30%. When dealing with CA at sea, with complex navigation obstacles, the proposed method considers static complex navigation obstacles, dynamic ships, and their unpredictable strategies to timeously generate a safe path which considers some key rules from the COLREGS (International Regulations for Preventing Collisions at Sea) (IMO, 1972).

Polygonal Type Fuzzy Ship Domain-Based Decision Support System for Collision Avoidance Route Planning

Polygonal Type Fuzzy Ship Domain-Based Decision Support System for Collision Avoidance Route Planning

Methods for constructing collision avoidance route for multiple unmanned aerial vehicles using OLSR-based link hierarchization

Methods for constructing collision avoidance route for multiple unmanned aerial vehicles using OLSR-based link hierarchization

Ship collision avoidance route planning using CRI-based A∗ algorithm

This study presents a novel ship route planning algorithm that takes into account both operational economy and safety by integrating the A∗ algorithm with a collision avoidance algorithm that evaluates the Collision Risk Index (CRI) between the own ship and the target ship. The CRI-based A∗ algorithm defines a penalty zone, allowing the own ship to explore safe routes based on the International Regulations for Preventing Collisions at Sea 1972 (COLREGs) and performs an adaptive and effective node search on an extended local map grid according to various encounter situations. The proposed algorithm is validated through simulations of head-on, fine-broad crossing, converging crossing, and overtaking encounters, indicating an economical and safe optimum route compared to conventional ship domain-based route planning.

An intelligent communication system for collision avoidance on roads: A smart city application

Intelligent communication systems have become the predominant paradigm in vehicular ad hoc networks. Current research in this area is limited to the dissemination of emergency information to vehicles after an accident. However, such emergency situations necessitate prompt dissemination of information to the relevant parties prior to the collision save lives. This paper proposes an intelligent collision avoidance routing technique for VANETs (CARVNET) to address this formidable obstacle. The proposed intelligent communication system aims to avoid collisions on roads by disseminating emergency warning messages instantly to the concerned entities as soon as it detects a driver’s abnormal health condition. Simulation studies are conducted in NETSIM to validate the proposed technique. The experimental results demonstrate that the proposed system outperforms existing communication systems by improving throughput by up to 50%, packet transmission by 20%, packet delivery ratio by 10%, and delay to a negligible degree.

Collision Avoidance Route Planning for Autonomous Medical Devices Using Multiple Depth Cameras

Radiography is one of the most widely used imaging techniques in the world. Since its inception, it has continued to evolve, leading to the development of intelligent and automated radiography systems that are able to perceive parts of their environment and respond accordingly. However, such systems do not provide a complete view of the examination space and are therefore unable to detect multiple objects and fully ensure the safety of patients, staff and equipment during the execution of the movement. In this paper, we present a system architecture based on ROS (Robot Operating System) to solve these challenges and integrate an autonomous X-ray device. The architecture retrieves point clouds from range sensors placed at specific locations in the examination room. By integrating different subsystems, the architecture merges the data from the different sensors to map the space. It also implements downsampling and clustering methods to identify objects and later distinguish obstacles. A subsystem generates bounding boxes based on the detected obstacles and feeds them to a motion planning framework (MoveIt!) to enable collision avoidance during motion execution. At the same time, a subsystem implements a deep neural network model (PointNet) to classify the detected obstacles. Finally, the developed system architecture provided promising results after being deployed in a Gazebo simulated examination space and on a use case test platform.

A prediction model of vessel trajectory based on generative adversarial network

AbstractTrajectory prediction is an important support for analysing the vessel motion behaviour, judging the vessel traffic risk and collision avoidance route planning of intelligent ships. To improve the accuracy of trajectory prediction in complex situations, a Generative Adversarial Network with Attention Module and Interaction Module (GAN-AI) is proposed to predict the trajectories of multiple vessels. Firstly, GAN-AI can infer all vessels’ future trajectories simultaneously when in the same local area. Secondly, GAN-AI is based on adversarial architecture and trained by competition for better convergence. Thirdly, an interactive module is designed to extract the group motion features of the multiple vessels, to achieve better performance at the ship encounter situations. GAN-AI has been tested on the historical trajectory data of Zhoushan port in China; the experimental results show that the GAN-AI model improves the prediction accuracy by 20%, 24% and 72% compared with sequence to sequence (seq2seq), plain GAN, and the Kalman model. It is of great significance to improve the safety management level of the vessel traffic service system and judge the degree of ship traffic risk.

Performance analysis of collision avoidance routing protocol for inter-vehicular communication

In recent days vehicular ad-hoc networks find its extensive applications by broadcast transmissions. Vehicle to vehicle communication provide better results by avoiding the major problems in the road such as the collision of vehicles, better route selection during congestion, fuel consumption etc. In this paper we present a collision avoidance based protocol. The collision of transmitting data can be avoided using medium access control (MAC) protocol. We have assessed and analyzed the performance of the proposed routing protocol Vehicular Ad-hoc on-demand Distance Vector (VAODV), which is a modification of Ad-hoc On-demand Distance Vector (AODV) routing protocol. We have analysed the performance of the proposed VAODV protocol through simulation results and latter extended for OSPF ensuring high reliability.

Multi-target collision avoidance route planning under an ECDIS framework

The universality of the automatic identification system (AIS) as well as the electronic chart display and information system (ECDIS) installations will provide revolutionary solution schemes for the e-navigation era of informatization, intellectualization, and integration. Based on this concept, this study adopted ECDIS as an information platform for navigational decision support and used the real-time navigation information received by the AIS to construct predicted areas of danger (PAD) for target ships. The advantages of direct viewing via the PAD in the collision avoidance give PAD a new application. Subsequently, spatial data from an electronic navigation chart (ENC) was employed as a basis for generating geographical obstacles. Through the integration of a geographic information system (GIS) module, specially designed evolutionary computation, and collision prevention regulations (COLREGS) knowledge as well as by comprehensively considering overall navigation situations, this system conducted obstacle avoidance processing and selection of a route. The system could generate a route that could simultaneously achieve multi-ship encounter collision avoidance and geographical obstacle avoidance. This is expected to provide mariners with greater convenience when working at sea, reducing their workload. This system can also be used as a reference for collision avoidance decision making.

An Improved Differential Evolution Algorithm for Maritime Collision Avoidance Route Planning

High accuracy navigation and surveillance systems are pivotal to ensure efficient ship route planning and marine safety. Based on existing ship navigation and maritime collision prevention rules, an improved approach for collision avoidance route planning using a differential evolution algorithm was developed. Simulation results show that the algorithm is capable of significantly enhancing the optimized route over current methods. It has the potential to be used as a tool to generate optimal vessel routing in the presence of conflicts.

Decision Support from Genetic Algorithms for Ship Collision Avoidance Route Planning and Alerts

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.

Collision Avoidance Schemes for Orthogonal Pipe Routing

This paper describes collision detecting and avoidance schemes to automatically lay out piping routes. The overlapping between the boundary boxes of equipment and pipelines is the basis for determining two types of collision: vertex-interference and edge-interference. Three collision-avoidance routing schemes have been developed using the modified adjacency and distance matrices and the line-surface intersection method. This collision avoidance scheme is for orthogonal pipe routing and forms the basis for extension to other routing principles.