Collision Risk Research Articles

Developing a Ship Collision Risk Assessment Model with Internal and External Factors: Focused on South Korea Maritime Environment

Maritime collisions pose significant risks, prompting the need for robust risk assessment models to enhance safety measures. This study endeavors to develop a comprehensive ship collision risk model reflecting the intricate marine traffic environment in South Korea. Through a survey of experienced maritime personnel and a random forest model analysis, an evaluation model integrating internal and external factors was devised. Internal factors were determined through conjoint analysis, emphasizing encounter relationships, separation distance, and vessel speed. External risk factors were established using a random forest model based on historical collision data. The model’s efficacy was then applied to and validated in the vicinity of Busan Port, a region with complex marine traffic. The resulting risk map highlighted high‐risk areas, offering valuable insights for risk management and policy formulation. This model provides a foundational framework for maritime safety policy decisions, representing a significant contribution to collision risk assessment methodologies.

Assessing ship collision risks in maritime transport based on seafarers’ experience

Assessing ship collision risks considering human factors presents persistent challenges due to the multivariate uncertainties faced by seafarers. Therefore, this study proposes a fuzzy-logic-based method to model ship collision risks in an area considering human factors. This method utilizes a hierarchical fuzzy system consisting of two fuzzy systems, fuzzy system 1 and fuzzy system 2, which are used to calculate the temporary risks and human factors, respectively. Aggregating the risks from both subsystems produces the overall collision risk index. This approach streamlines on-board risk appraisal, thereby reducing the navigator workload. While the current study delineates the risk modeling methodology, succeeding works validate the framework through simulated experiments. With adequate verification, this hierarchical fuzzy approach can assist next-generation risk-regulated navigation practices and enrich maritime agencies' traffic risk management.

Assessing ship collision risks in maritime transport based on seafarers’ experience

Assessing ship collision risks considering human factors presents persistent challenges due to the multivariate uncertainties faced by seafarers. Therefore, this study proposes a fuzzy-logic-based method to model ship collision risks in an area considering human factors. This method utilizes a hierarchical fuzzy system consisting of two fuzzy systems, fuzzy system 1 and fuzzy system 2, which are used to calculate the temporary risks and human factors, respectively. Aggregating the risks from both subsystems produces the overall collision risk index. This approach streamlines on-board risk appraisal, thereby reducing the navigator workload. While the current study delineates the risk modeling methodology, succeeding works validate the framework through simulated experiments. With adequate verification, this hierarchical fuzzy approach can assist next-generation risk-regulated navigation practices and enrich maritime agencies' traffic risk management.

Collective Neural Dynamics for Sparse Motion Planning of Redundant Manipulators Without Hessian Matrix Inversion.

Redundant manipulators have been widely used in various industries whose applications not only improve production efficiency and reduce manual labor but also promote innovation in robotics and artificial intelligence. Kinematic control plays a fundamental and crucial role in robot control. Over the past few decades, numerous motion control schemes have been proposed and applied to trajectory tracking tasks. However, most of these schemes do not consider the introduction of sparsity into the motion control of redundant manipulators, resulting in excessive joint movements, which not only consume extra energy but also increase the risk of unexpected collisions in complex environments. To solve this problem, we transform the issue of increasing the sparsity into a nonconvex optimization problem. Furthermore, a collective neural dynamics for sparse motion planning (CNDSMP) scheme for motion planning of redundant manipulators is proposed. By incorporating sparsity into the control scheme, the excessive joint movements are minimized, leading to improved efficiency and reduced collision risks. Through simulations, comparisons, and physical experiments, the effectiveness and superiority of the proposed scheme are demonstrated.

Catching Flying Ball with Drone Using Monte Carlo Model Predictive Control method

In some sporting events, including baseball, the ball few into the spectator area, resulting in serious injuries. Having witnessed such situations, we felt that the safety of the spectator environment needed to be improved. The aim is, therefore, to prevent such accidents by utilizing drones to catch flying balls. Monte Carlo Model Predictive Control (MCMPC) is a Monte Carlo-based control method. MCMPC is sample-based and does not require a gradient in the cost function, allowing discontinuous events such as collisions with obstacles to be incorporated into the predictive model. This study aims to utilize MCMPC to reduce the risk of drone collision after successful flying ball capture.

Gelsari and Lentini marshes (Sicily, Italy), a wetland of extremely high biodiversity. Consequences on avifauna from the crossing of an overhead high-voltage power line

In the Gelsari and Lentini marshes (Sicily, Italy), which constitute a vast and historically well-known wetland on the central eastern coast of Sicily, the crossing of an overhead high-voltage power line surprisingly had been planned and approved. This choice was made despite the high landscape value that these marshes possess, the environmental protection constraints they enjoy, the interest they hold for the biodiversity conservation in Sicily, and their extraordinary ability to attract avifauna. At present, the work, which began in August 2021, has resulted in the placement of all supports. An estimate of the risk of mortality of avifauna that the presence of the power line will produce has been made, limiting the survey to species of high conservation interest, which are among those present in the marshes. It turned out that the risks of collision of avifauna and especially of species considered of high conservation interest, due largely to the characteristics of the power line and especially its route, are extremely high; the damage that is likely to occur does not, therefore, seem to have been properly assessed, neither at the design nor at the approval stages of the project. Given that the impact of the power line does not appear to be mitigable, neither with regard to the landscape nor with regard to avifauna, considering, in the latter case, especially the high mortality risks to which species of high conservation interest would be subjected, it is believed that the only solution to avoid such damage is to make a modification to the route of the power line in the section affecting the marshes.

Preventing aircraft from wildlife strikes using trajectory planning based on the enhanced artificial potential field approach

Wildlife strikes refer to collisions between animals and aircraft during flight or taxiing. While such collisions can occur at any phase of a flight, the majority occur during takeoff and landing, particularly at lower altitudes. Given that most reported collisions involve birds, our focus was primarily on bird strikes, in line with statistical data. In the aviation industry, aircraft safety takes precedence, and attention must also be paid to optimizing route distances to minimize operational costs, posing a multi-objective optimization challenge. However, wildlife strikes can occur suddenly, even when aircraft strictly adhere to their trajectories. The aircraft may then need to deviate from their planned paths to avoid these collisions, necessitating the adoption of alternative routes. In this article, we proposed a method that combines artificial potential energy (APE) and morphological smoothing to not only reduce the risk of collisions but also maintain the aircraft's trajectory as closely as possible. The concept of APE was applied to flight trajectory planning (TP), where the aircraft's surroundings were conceptualized as an abstract artificial gravitational field. This field exerts a "gravitational force" towards the destination, while bird obstacles exert a "repulsive force" on the aircraft. Through simulation studies, our proposed method helps smooth the trajectory and enhance its security.

Keel bone fractures affect laying hens' mobility, but no evidence for reciprocal effects.

Keel bone fractures (KBF) are prevalent in commercial laying hens and are considered one of the greatest welfare concerns in the egg-production industry. While clear associations exist between KBF and animal mobility, suggesting that KBF impair mobility, the effect of mobility on KBF remains unclear. We combined data from three studies that assessed keel bone fracture severity through radiographs and monitored hens' transitions between different zones of a multi-tier aviary system (the three tiers, a littered floor, and a winter garden) the week prior to radiograph. For each hen, we extracted two daily movement behaviours: the vertical distance travelled and the mean number of zones crossed within one transition; and two daily space-use behaviours: the time spent in the top tier and the unevenness of time spent across zones. We used hierarchical Bayesian continuous time dynamic modelling to estimate how a change in a behaviour predicted a later change in keel bone fracture severity, and vice versa. Increased fracture severity did not predict later changes in space-use behaviours, but it did predict changes in movement behaviours. Specifically, increased fracture severity led to decreased vertical travelled distance and a tendency to cross more zones within one transition, suggesting impaired mobility in hens with increased fracture severity. In contrast, we found no evidence that movement or space-use behaviours predict later change in fracture severity, challenging previous literature suggesting that vertical locomotion through jumping and flying may exacerbate keel bone fractures in complex three-dimensional systems due to increased risk of collisions. However, similar efforts accounting for the location of fractures on the keel could unveil the potential influence of movement and space-use behaviours in the formation and change (healing or worsening) of KBF and increase our ability to mitigate their effects.

Evaluating Drivers’ Response to Road Hazard: A Simulation Study

The presence of unexpected conditions on the road increases the risk of collisions for drivers. To effectively manage these risks, drivers must first accurately perceive hazards and then respond appropriately. The behavior of drivers and their responses to potential road hazards are investigated in this study. It is possible that one motorist may opt to gradually reduce the velocity of their vehicle, while another individual in the same situation might opt for forceful braking at the moment of initial awareness. This indicates the divergence reactions of drivers to identical hazards. This study introduces the hazards response scale (HRS) as a metric to assess the differences in hazard response among participants and its effect on safe driving by undertaking a driving simulation study. The results reveal that a lower HRS index correlates with a higher level of driving safety. By evaluating the relationship between demographic variables and HRS, it was found that increasing age and driving experience are associated with lower HRS scores, thus enhancing driving safety. Notably, women exhibit lower HRS values than men, suggesting that they tend to drive more safely.

Uncertainty-Aware Decision Making for Safe Navigation of Autonomous Ships

During ship encounters, uncertainty surrounding other vessels’ intentions and future trajectories can complicate situation assessment. When encountering an erratic vessel, navigators will take precautionary actions to avoid any risk of collision. This paper introduces a new decision-making algorithm tailored to address uncertainty in vessel encounters at sea. The proposed method achieves this by defining the risk of a future scenario as the combination of two factors: the probability of collision and the magnitude of the uncertainty. As this method does not assume deterministic future trajectories for either of the vessels, it can therefore be applied to any pair of vessels, and it allows the use for anticipation of future behaviours of other vessels in a scene. The method is verified through a simulation study.

Applications and Challenges of Computer Vision in Autonomous Driving

Abstract The rapid evolution of autonomous driving technology has spurred deeper exploration into its multifaceted domains. This paper focuses on enhancing the intelligence and safety of autonomous driving systems through the application of computer vision. Specifically, the integration of EIoU loss and Varifocal Loss functions within the YOLOv5 algorithm facilitates the training of higher-quality samples at reduced costs. This enhanced YOLOv5 algorithm is adept at detecting traffic entities and incorporates the Matrix NMS algorithm to further refine the loss function adjustments. Moreover, this study employs the proximal policy optimization algorithm to construct a vehicular behavioral decision model for autonomous driving. This model utilizes cubic polynomial equations to depict lane-changing trajectories and introduces a safety distance rule to mitigate collision risks during autonomous maneuvers. Comparative analyses reveal that the modified YOLOv5 algorithm surpasses its predecessors—YOLOv3 and YOLOv4—in terms of detection accuracy and processing speed. Notably, the improved YOLOv5 algorithm exhibits lower network loss values than its original version, achieving faster and more stable convergence. In practical applications, the algorithm successfully identified and labeled 20,025 intelligent vehicular targets, with initial testing accuracy reaching 96.12%. This accuracy improved to 96.36% following the application of EIoU adaptive tuning to reduce risk-free class loss, and further fine-tuning elevated the accuracy to 96.54%. The integration of computer vision into autonomous driving technology thus holds significant promise for advancing the field.

Assessment of the risk of a dangerous event of a human collision with a remote-controlled robot

This study assesses the risk of a collision between a human and the “Robot Arm” during remote control, using a 6DoIt Mobile Robot Arm with six degrees of freedom. The bow-tie approach, combined with EN ISO 12100 standards, was employed to evaluate the risk of such a dangerous event, considering physical, organizational, psychosocial, and informational factors. The proposed risk assessment method is based on the bow-tie model, emphasizing the importance of determining the possibility of avoiding hazards as per EN ISO 12100. A three-level protective system – physical, psychological, and informational – is suggested to mitigate the risk, interconnected to enhance safety by reducing the severity of potential consequences. The approach has been refined to better determine the severity of outcomes, focusing on the ability to avoid danger. Additionally, recommendations for enhancing robotics safety management were developed, aiming to improve the effectiveness of measures to reduce collision risks during the operation of the “Robot Arm”.

Airspace Saturation and Midair Collision Risk: A Case Study at a Class D Airport

Airspace Saturation and Midair Collision Risk: A Case Study at a Class D Airport

Collision Risk Assessment for Intelligent Vehicles Considering Multi-Dimensional Uncertainties

Collision Risk Assessment for Intelligent Vehicles Considering Multi-Dimensional Uncertainties

Wire marking reduces bird collisions with a transmission powerline in western Belgium

Summary Collisions with powerlines affect birds worldwide, including countries such as Belgium where a nationwide model indicated high avian collision risk in the IJzerbroeken region (seasonally flooded riverside wetlands). Large numbers of waterbirds winter in this area, which is crossed by a 70-kV transmission line. To manage avian collision risk, the transmission system operator, Elia, installed AB Hammarprodukter’s FireFly™ FF line markers incorporating reflective, glow-in-the-dark, high contrast, and moving elements intended to increase the visibility of the transmission line to flying birds. We evaluated the effectiveness of FireFly line markers by comparing the numbers of avian carcasses found during 11 surveys annually in 2001 and 2018 (22 total surveys) before line markers were installed compared with 11 surveys conducted in 2021 after line marking. Before line marking, we found 30 avian carcasses attributable to collision in 2001 and 113 in 2018. After, we found six carcasses attributable to collision in 2021. In 2021, FireFly line markers correlated with a reduction in collision rate, depending on the pre-treatment year and species group, of at least 85% and up to 100%. The line was composed of two configurations, with half of the spans (two-thirds of the monitored line length) supported by tall pylons with shield wires, and half of the spans supported by shorter pylons without shield wires. After line marking, six collisions (100% in 2021) occurred on spans supported by tall pylons, and none (0%) occurred on spans supported by short pylons. Thus, in 2021, FireFly line markers correlated with an observed mortality reduction of at least 73% and up to 100%, depending on the configuration being considered. These findings suggest FireFly line markers substantially reduced wintering bird collisions in our study area.

Assessment of ship collision risk based on the recorded accident cases: Structural damage and environmental recovery

Assessment of ship collision risk based on the recorded accident cases: Structural damage and environmental recovery

Overview and Key Technology of the Membrane Drag Sail for Low Earth Orbit Satellite Deorbit

With the escalating frequency of space activities, particularly the launch of constellation satellites, the amount of space debris experienced gradually increases, posing threats to the safety and sustainability of the space environment. To counteract the growth of debris, active deorbit devices are imperative for spacecrafts. In low Earth orbit (LEO), the drag sail device has emerged as a highly effective solution due to its ability to increase the spacecraft’s windward area, facilitating rapid deorbit by leveraging atmospheric drag as the primary perturbation. In this study, recent developments of membrane drag sail deorbit technology for LEO satellites are summarized, as well as the current problems such as attitude instability, dangerous space environment, and folding and unfolding issues. Moreover, crucial technologies such as modeling and simulation of deorbit efficiency, attitude stabilization, collision risk analysis and protection design, sail surface atomic oxygen protection design, and folding and unfolding of the drag sail are discussed. Finally, the development trends and technology applications of membrane drag sail deorbit for LEO satellites are presented.

Tying up loose ends together: Cetaceans, maritime traffic and spatial management tools in the Strait of Gibraltar

Abstract The transboundary area of the Strait of Gibraltar is home to seven protected cetacean species that are threatened by high intensity of maritime traffic. More comprehensive knowledge of cetaceans and maritime traffic is required, together with analyses of legislations, strategies and policies. This study quantitatively investigates cetacean distribution and maritime traffic intensity and, for the species of community interest bottlenose dolphin, habitat suitability. Results are qualitatively discussed considering the overlap of cetacean hot spots with different maritime activities and the consistency of spatial conservation management measures in force. The Fixed Line Transect Mediterranean Monitoring Network protocols were followed for 59 visual surveys using ferries as observation platforms for monitoring cetaceans and maritime traffic. Surveys were carried out along the transects between Algeciras and Ceuta and between Algeciras and Tanger‐Med, in 2018 and 2019. 264 cetacean sightings, including seven different species and four near‐miss collision events (involving pilot, sperm and fin whales), were reported. Monitoring cetaceans from ferries in the Strait provided insights into cetacean distribution and maritime traffic, enabling the identification of cetacean hot spots, suitable habitats and maritime traffic high‐risk zones. A transboundary management effort is required, together with an adaptive approach for protecting highly mobile species such as cetaceans. Proposals include a long‐term cetacean monitoring program carried out by dedicated observers on board ferries as a cost‐effective methodology and mandatory training for crew members, to increase cetacean knowledge and reduce collision risk. The designation of an international temporal or, in some zones, permanent speed reduction area (i.e., Cetacean Critical Navigation Zone, with a maximum speed of 13 knots) and of a micro‐sanctuary with a seasonal no‐take zone in the Bay between Algeciras and Gibraltar, together with international surveillance, are recommended measures for the enhancement of conservation efforts in the Strait.

Good Seamanship Score Quantification in Complex and Congested Waterways

This paper presents a novel method to quantify seafarers’ good seamanship during navigation scenarios with multi-vessel encounters, in open and confined waters, and to compute COLREG's-compliant path deviations for avoiding collision and grounding. Accurate quantification of good seamanship necessitates comprehensive information about the vessels state and the surrounding environment, obtainable through the AIS system and electronic nautical charts. Our work advances the current state-of-the-art by: (1) incorporating a normalized grounding risk for navigating confined waters, (2) factoring in speed changes for a probabilistic assessment of collision risk, and (3) considering the minimum possible scenario risk based on vessel kinodynamic constraints. The proposed method is evaluated using historical AIS data and sea charts of Danish waters. The evaluation results demonstrate improved fairness scoring by acknowledging that navigators may lack risk-free options.

Point Cloud-Based Spatial Environment Development for Near Real-Time Erection Simulation in Shipyards

<i>Interference and collisions often occur in the loading process at shipyards. Existing simulation methods focus primarily on resource processes and schedules, and there is a lack of real-time reflection in the complex and highly variable loading process. This study aims to develop a spatial environment incorporating real-time product data, such as hulls, and confirms its effectiveness by simulating various construction scenarios. As a method, a near real-time spatial environment based on broadband laser scanning was established, with the situation of loading heavy cargo assumed when converting an existing ship into an LNG dual-fuel propulsion ship. A case study simulation of near-real-time cargo loading processes was then conducted using Unity 3D to confirm the interference and collision risks within the spatial environment. The results indicated that interference occurred in structures previously not identified in the design data, and a collision occurred during the loading object erection phase. The simulation confirmed that the identification of interference and collision risks during the erection phase highlights the need for a relocation or removal process of potential hazards before erection takes place. An improved erection simulation that integrates near real-time data could effectively prevent interference and collision risks.</i>