Collision Prevention Research Articles

Opening the black box of bird-window collisions: passive video recordings in a residential backyard.

Collisions with windows on buildings are a major source of bird mortality. The current understanding of daytime collisions is limited by a lack of empirical data on how collisions occur in the real world because most data are collected by recording evidence of mortality rather than pre-collision behaviour. Based on published literature suggesting a causal relationship between bird collision risk and the appearance of reflections on glass, the fact that reflections vary in appearance depending on viewing angle, and general principles of object collision kinematics, we hypothesized that the risk and lethality of window collisions may be related to the angle and velocity of birds' flight. We deployed a home security camera system to passively record interactions between common North American bird species and residential windows in a backyard setting over spring, summer and fall seasons over 2 years. We captured 38 events including 29 collisions and nine near-misses in which birds approached the glass but avoided impact. Only two of the collisions resulted in immediate fatality, while 23 birds flew away immediately following impact. Birds approached the glass at variable flight speeds and from a wide range of angles, suggesting that the dynamic appearance of reflections on glass at different times of day may play a causal role in collision risk. Birds that approached the window at higher velocity were more likely to be immediately killed or stunned. Most collisions were not detected by the building occupants and, given that most birds flew away immediately, carcass surveys would only document a small fraction of window collisions. We discuss the implications of characterizing pre-collision behaviour for designing effective collision prevention methods.

КООРДИНАЦІЯ АНТИ-КОЛІЗІЙНИХ ДІЙ СУДЕН

The mechanisms of coordination of anti-collision measures of ships are systematized and analyzed. The main of these mechanisms is COLREG, which regulates the actions of two vessels. It is shown that non-regulated coordination used in addition to COLREG is based on the standardized qualification of ship operators and includes knowledge of good seamanship recommendations. In the analysis of mechanisms of binary coordination, the classification of situations of ships' approach is clarified, and principles of a choice of actions general for ships of the same and different navigation statuses in free and constrained waters at normal visibility are highlighted. Ways of reception of numerical values of restrictions on parameters of passing targets in different sailing conditions are offered. It is noted that in order to solve the problem of automation of collision prevention processes, radar-AIS technologies should be supplemented with video camera technologies in the visible and infrared range combined with computer vision. The role of communication in vessel actions coordination has been analyzed. Proposals for its improvement given the achievements in the field of scientific and technological progress are elaborated. It is recommended to use AIS alerts of planned evasive trajectory to decrease uncertainty in the collision prevention process. To reduce the volume of these notifications, it is proposed to replace the segments of changes in motion parameters with time-equivalent segments of rectilinear uniform motion sections. It gets rid of transmitting data characterizing the manoeuvrability of a ship and planned modes of course or/and speed change, and practically does not worsen the assessment of the safety of the measures selected to avoid a collision. The received information allows the ship to present the trajectory of the giving way vessel on the screen in graphical form, both in true and relative motion. Using this capability allows the first ship to quickly assess the safety of the second vessel's planned operations. Keywords: collision avoidance, coordination mechanisms, anti-collision plans, mapping of evasive trajectories.

Investigation of the characteristics of the manipulators collision prevention system

The paper considers the problem of detecting and preventing collisions of manipulators with each other and with segments of the robot itself in a virtual environment. The proposed solution is to use simulator, which can simulate the physical laws of the real world with defined level of approximation, as well as methods and algorithms for collision detection in the virtual environment. Methods of representation of objects in the environment, due to which it is possible to detect collisions quickly, are considered. The collision control subsystem for the movement of two manipulators, controlled by a human operator, is simulated in the Unity environment, and its reaction speed is investigated.

Energy-Efficiency Joint Trajectory and Resource Allocation Optimization in Cognitive UAV Systems

In this article, an effective energy-efficiency optimization problem is investigated in the cognitive unmanned aerial vehicle (UAV) communication system, where the moving following UAV (FUAV) transmits collected data to the leading UAV (LUAV) by reusing the spectrum of the ground primary user. For this scenario, a novel joint UAV trajectory and resource allocation optimization algorithm is proposed. We aim to maximize the energy efficiency of the cognitive UAV communication systems under interference, shortest step size, collision prevention, and speed constraints. However, this optimization problem is difficult to be solved, as it is nonconvex and involves strong relations among many variables. To address this issue, we first decompose the original optimization problem into four subproblems: 1) spectrum sensing duration subproblem; 2) spectrum sensing threshold subproblem; 3) transmitted power subproblem; and 4) FUAV trajectory optimization subproblem. For spectrum sensing duration subproblem and spectrum sensing threshold subproblem, their optimal solutions can be efficiently solved via a golden section search method. For the transmitted power subproblem, the closed-form expression of the optimal transmitted power is deduced. For the nonconvex FUAV trajectory optimization subproblem, we consider the shortest step size design under known starting and destination positions and then obtain an approximate solution of FUAV trajectory via the successive convex optimization (SCO) technique. Finally, an alternate iterative framework with fast convergence is designed to solve the original optimization problem. The simulation results show that the proposed algorithm has 18 times improvement in energy efficiency compared with the straight flight scheme with lower energy consumption.

Autonomous mobile robot travel under deadlock and collision prevention algorithms by agent-based modelling in warehouses

ABSTRACT Recent dramatic increase in e-commerce has also increased the adoption of automation technologies in warehouses. Autonomous mobile robots (AMRs) are from those technologies widely utilized in warehouse operations. It is important to design the operation of those robotic systems in such a way that, they meet the current and future system requirements correctly. In this paper, we study flexible travel of AMRs in warehouses by developing smart deadlock and collision prevention algorithms on agent-based modelling. By that, AMR agents can interact with each other and environment, so that they can make smart decisions maximizing their goals. We compare the performance of the developed flexible travel system with non-flexible designs where there is a single AMR dedicated to a specific zone so that no deadlock or collision possibility takes place. The results show that AMRs may provide up to 39% improvement in the flexible system compared to its non-flexible design.

설문분석을 통한 어선 충돌사고 저감을 위한 기초연구

Marine accidents on fishing vessels accounted for the majority of all marine accidents. Collision accidents are the third most common, and most of them are caused due to operational carelessness. The purpose of this study is to identify the fundamental factors that cause collision accidents using questionnaire and to prepare fundamental countermeasures to protect human life and the marine environment. The survey was conducted on 216 people, focusing on the representative fishing port of the country. As a result of the study, collision accidents of fishing vessels mainly occur between fishing vessels. In addition, they acquire a small ship operating license through experience on board. It was identified that the fishing vessel seamen used the electronic navigation device to determine the risk of collision with other ships. Therefore, in this study, support for the installation of electronic navigation equipment on fishing vessels and systematic education such as collision prevention regulation and use of electronic navigation equipment support for reducing collision accidents were suggested as countermeasures. However, this study is a basic study using questionnaires to understand the fundamental factors of collision accidents. Therefore, the detailed follow-up studies such as understanding the effects of each factor are needed in the future.

Collision prevention control method for production riser system in deep sea

In the deep-sea oil and gas exploitation process, the adjacent risers under the influence of environmental load and shielding effect will produce large amplitude vibration, which may lead to collision and damage to the riser structure. However, there is a lack of study on active collision-preventing control based on vessel flexible riser array system. This paper aims to better prevent the collision between vessel-risers and increase the motion spacing. Preliminarily, we model the vessel-risers system composed of top production vessel, riser array and environment load based on Hamilton's principle and the improved shielding effect model. In the next part, considering the control spillover problem, we design the collision-preventing boundary controllers directly for distributed parameter system (DPS) without discretization or simplification. And the uniform boundedness of the control system is strictly proved by the Lyapunov direct method. Eventually, we verify the effectiveness and feasibility of the collision-preventing controllers by simulating the system in different ocean currents. At the same time, the parameters of the collision-preventing controllers are independent of those of the riser array system, which ensures the robustness of the system.

Collision prevention of ship towing operation under environmental disturbance

Towing operations are highly reliant on the experience of the towing operators. Safety concerns arise when towing operations are subjected to environmental disturbances and dynamic traffic conditions. However, a systematic framework and approaches to enhance the safety and automation of towing operations remain lacking. This work proposes a framework of collision prevention of ship towing operations under environmental disturbance in near port waters. The focus is to prevent internal collisions between tug and assisted ship and provide early warning of possible collisions with other surrounding ships. A cooperative multi-agent control strategy is employed to specify the direction and magnitude of the towing force of the two tugs in real-time. Therefore, in the presence of environmental disturbance, the assisted ship can sail along the planned trajectory, and the acceptable safe geometric distance between each ship pair in the towing system is guaranteed. Further, a COLREGs-compliant collision alert system is designed to promptly remind the towing operators of a collision hazard with nearby ships, and different alert levels indicate different action obligations of towing operators. This proposed framework and developed methods are applied to a tandem towing system consisting of two tugs and one assisted ship to test its feasibility.

RAD51AP1 regulates ALT-HDR through chromatin-directed homeostasis of TERRA

Alternative lengthening of telomeres (ALT) is a homology-directed repair (HDR) mechanism of telomere elongation that controls proliferation in subsets of aggressive cancer. Recent studies have revealed that telomere repeat-containing RNA (TERRA) promotes ALT-associated HDR (ALT-HDR). Here, we report that RAD51AP1, a crucial ALT factor, interacts with TERRA and utilizes it to generate D- and R-loop HR intermediates. We also show that RAD51AP1 binds to and might stabilize TERRA-containing R-loops as RAD51AP1 depletion reduces R-loop formation at telomere DNA breaks. Proteomic analyses uncover a role for RAD51AP1-mediated TERRA R-loop homeostasis in a mechanism of chromatin-directed suppression of TERRA and prevention of transcription-replication collisions (TRCs) during ALT-HDR. Intriguingly, we find that both TERRA binding and this non-canonical function of RAD51AP1 require its intrinsic SUMO-SIM regulatory axis. These findings provide insights into the multi-contextual functions of RAD51AP1 within the ALT mechanism and regulation of TERRA.

Predicting future distributions and dispersal pathways for precautionary management of human-raccoon dog conflicts in metropolitan landscapes

Human-wildlife conflicts in cities are becoming increasingly common worldwide and are a challenge to urban biodiversity management and landscape planning. In comparison to compensatory management, which often focuses on addressing emergency conflicts, precautionary management allows decision-makers to better allocate limited resources on prioritized areas and initiate long-term actions in advance. However, precautionary approaches have rarely been developed or applied in biodiversity conservation. Since 2020, human-raccoon dog conflicts in Shanghai, one of the largest cities in the world, have tripled in reported number due to the rapid spread of the species in the city from 70 residential districts in 2020 to 249 residential districts in 2022. Here, we use ensemble and circuit modeling to predict suitable raccoon dog habitat and identify their potential dispersal pathways to aid the development of precautionary management strategies. We find that raccoon dog distribution is positively associated with several anthropogenic factors, including residential buildings and nighttime light, which could be signs that the species’ foraging behavior has adapted to the urban environment. We find that raccoon dogs only occupy 10.1% of its suitable habitat, and thus there is a high potential for the expansion of the raccoon dog population and more frequent human-raccoon dog conflicts in the near future. We predict 60 potential dispersal pathways across Shanghai, seven of which cross densely human populated areas and are likely to trigger excessive conflicts. Based on our findings, we propose priority areas where precautionary management strategies, such as constraining stray animal feeding and wildlife-vehicle collision prevention, would potentially alleviate human-raccoon dog conflicts. We present the first study on the precautionary approach of human-wildlife conflict in China’s major cities, and provide a practical example of how comprehensive modeling approaches can be used as the foundation of precautionary management in urban landscapes.

타워크레인 전문신호수의 효율적 운영체계에 대한 연구

Recently, in the case of domestic construction sites, the ratio of construction equipment to construction manpower is increasing due to high-rise and large-scale buildings. As a result, the death toll from construction machinery and equipment accidents accounts for more than 20% of all deaths in the construction industry. Accordingly, from 2017, as a measure to strengthen safety management for tower cranes, the installation and dismantling team registration system was introduced and the right to stop work was strengthened, the professional qualification system was introduced (tower crane installation and dismantling workers), the collision prevention system became mandatory, and the installation, dismantling, and climbing work were recorded. the age limit of old cranes (restriction of use in principle for more than 20 years), and mandatory non-destructive inspection are added and managed, but most of them are limited to the management and technical fields of equipment aspects of tower cranes and have been strengthened. It seems that there are very few things. As with the results of the analysis of disaster cases of tower cranes in the past, the role of a dedicated signal operator is important when lifting weights, but anyone can play a role as a dedicated signal operator signal operator if they only receive 8 hours of special safety training, so it is urgent to supplement this. In this study, based on the review of previous research results and the analysis of disaster cases that occurred in the past 10 years (2010~2019) of tower cranes by the Korea Occupational Safety and Health Agency, we reviewed the signal management system in advanced countries such as the United States and the United Kingdom. An interview was conducted with a tower crane official (manager of a professional construction company, tower crane operator) and a signal officer, and direct and indirect problems were identified. Based on this, an improvement plan was derived by conducting a survey, and the AHP (Analytic Hierarchy Process) analysis method was used to derive the priority of the improvement plans. As a result of the study, the management system for dedicated signalman should be nationally reorganized and built and managed by improving the dedicated signalman system laws and systems. The result was that As in the results of this study, it is expected that tower crane accidents will not occur any more by implementing the improvement of laws and systems for tower crane dedicated signalmen.

Intelligent Collision Avoidance Method for Ships Based on COLRGEs and Improved Velocity Obstacle Algorithm

Collision prevention is critical for navigational safety at sea, which has developed rapidly in the past decade and attracted a lot of attention. In this article, an improved velocity obstacle (IVO) algorithm for intelligent collision avoidance of ocean-going ships is proposed in various operating conditions, taking into count both a ship’s manoeuvrability and Convention on the International Regulations for Preventing Collisions at Sea (COLREGs). An integrated model combines a three-degree-of-freedom manoeuvring model with ship propeller characteristics to provide a precise prediction of ships in various manoeuvring circumstances. In the given case, what is different to present studies, this improved algorithm allows for decision-making in two ways: altering course and changing speed. The proposed technique is demonstrated in a variety of scenarios through simulation. The findings reveal that collision-avoidance decision-making can intelligently avoid collisions with the target ships (TSs) in multi-ship situations.

Vision-Based Obstacle Detection and Collision Prevention in Self-Driving Cars

With increasing computational power and a vast amount of data to work with, deep learning has risen to prominence since the 2010s. Numerous applications are being researched and developed using deep learning. One of the applications is computer vision in self-driving cars. Convolutional Neural Networks (CNNs) are being widely used because of their high performance compared to other alternative techniques in several perception and control tasks. The Convolutional Neural Networks (CNNs) allows the automobile to learn from different types of roads, scenarios allowing the car to forecast its route on any particular road with minimum inaccuracy. This paper proposes a working model of the autonomous car, which has a Raspberry Pi 4 Model B as the control unit and processing unit. This working model gets real-time images from the Raspberry Pi camera and these images are used by the CNN model, which predicts the direction the car must turn. The raspberry pi sends the control signals to the L298n motor driver. The trained CNN model achieved an accuracy of 96.39% with the test dataset and 84.77% with the validation dataset.

The Smart Intersection: A Solution to Early-Stage Vehicle-to-Everything Deployment

Connected vehicles and connected infrastructure technology are being deployed globally. Although the connectivity technology has a demonstrated capability of aiding collision prevention, the safety benefits are not maximized because of the limited coverage during the early deployment phase. Honda’s “smart intersection” research has led the company to a pilot deployment utilizing a state-of-the-art artificial intelligence solution in infrastructure sensing technology. This sensing technology employs a vision processing system to detect and differentiate nonconnected road users, including automobiles, emergency vehicles, motorcycles, and pedestrians. The detected object types are packaged into standardized wireless vehicle-to-vehicle (V2V) safety messages. These messages are transmitted from the roadside infrastructure to nearby connected vehicles. This article first discusses a few challenges associated with infrastructure sensing and collective perception and introduces techniques that ensure the infrastructure-generated V2V data transmissions are delivered in a real-time manner and with high message accuracy. We then examine the solutions through actual implementation accuracy assessments.

A novel adaptive fuzzy reinforcement learning controller for a platoon of off-axle hitching tractor-trailers with a prescribed performance and path curvature compensation

This paper addresses an artificial intelligence-based platoon control (AIPC) problem of autonomous off-axle hitching tractor-trailer wheeled mobile robots (TTWMRs) in a planar motion. Towards this end, a novel saturated nonlinear interval type-2 neuro-fuzzy reinforcement learning controller is proposed to construct a convoy-like motion of TTWMRs. To overcome the cutting-corner phenomenon in the platoon motion, the curvature of the reference trajectory is estimated and the cutting-corner behaviour is prevented. In order to deal with the situation where the velocity and acceleration signals are not measurable or corrupted by the measurement noise, a high-gain observer (HGO) is employed. The prescribed performance control (PPC) is also engaged in the control design procedure to guarantee inter-vehicular communication preservation, collision prevention between each consecutive pair in the platoon, singularity cancellation, and some prespecified desired characteristics of the convoy formation tracking errors such as maximum undershoot/overshoot, convergence rate, and final tracking precision. The Lyapunov-based stability analysis reveals semi-global uniform ultimate boundedness (SGUUB) convergence of tracking errors for the entire platoon system. With the suggested control framework, simulations and comparisons are conducted in which the control performance is considerably improved compared with the existing literature.

Spatiotemporal Patterns of Cyclist Collisions in Germany: Variations in Frequency, Severity of Injury, and Type of Collision in 2019

Cycling has gained increasing interest in Germany in recent years due to its manifold environmental, societal, and economic benefits. However, the number of cyclist collisions resulting in injury or death remains high and little is known about regional variations in frequency, severity of injury, and type of collision. This study investigates spatial and temporal patterns and characteristics of cyclist collisions across Germany in 2019. Using a detailed cyclist collision dataset for most German federal states, we identified statistically significant regional differences in frequency, severity of injury, and type of collision. To facilitate this and future cyclist collision surveillance studies in Germany, we developed and published a custom R package to download and combine the collision data with geographical data. Our analysis reveals that densely populated regions exhibit higher collision rates and a higher share of collisions involving turns, but lower severity of injuries and a lower share of collisions whilst driving in a straight line, a higher collision frequency during the work week compared to weekends, and a higher collision frequency peak during morning rush hour. We also observed a markedly high share of fatal bicycle-truck collisions in densely populated regions. In contrast, rural regions show lower collision rates, but a higher share of severe collisions, a higher share of collisions whilst driving in a straight line, as well as higher collision frequencies during weekends and summer months. Our findings underscore the complex and multifaceted geographical variations in collisions involving cyclists. The results of this study suggest that a one-size-fits-all approach to collision prevention infrastructure and policy may be insufficient for addressing variations in risk, and that future efforts to improve cyclist safety should be tailored to the local geographical context.

Economic benefits of preventing bird collisions in South Korea: findings from a choice experiment survey.

Bird deaths due to collisions with artificial structures, such as glass windows of buildings and transparent noise barriers, are continuing to occur in South Korea. The government is trying to prevent bird collisions by increasing the attachment of specially designed tapes to help birds avoid windows. This article estimates the economic benefits arising from the prevention of collisions by applying a choice experiment (CE). For this purpose, a CE survey of 1000 South Korean interviewees was conducted. The four attributes to be attached with the tapes for the CE application were a transparent soundproof wall window on an expressway, a transparent soundproof wall window on a general road, a glass window in a public building, and a glass window in a private building. The unit was the percentage of each structure with the tapes attached to the window. The marginal values of a one-unit (1%p) increase in each attribute were computed to be KRW 534 (USD 0.46), KRW 233 (USD 0.20), KRW 1,318 (USD 1.13), and KRW 12,930 (USD 11.05), respectively. This quantitative information will be an important reference for implementing the prevention policy. For example, based on the collision prevention of 1000 birds per structure, the priority for attaching tapes can be placed in the order of expressways, public buildings, private buildings, and general roads.

Transferable Collision Detection Learning for Collaborative Manipulator Using Versatile Modularized Neural Network

As human-robot collaboration increases and robots are applied to everyday life, interest in safety issues is increasing. To be safely used in real life, in addition to collision prevention algorithms, robots need to quickly detect unexpected collisions and take appropriate actions. Recently, deep learning-based collision detection algorithms have been proposed to overcome the limitations of model-based collision detection methods, but there are also limitations on deep learning methods, especially in data collection. The collected data are often insufficient because collecting collision data is laborious and intrinsically imbalanced, meaning that the collision data are much smaller than the free-motion data. Moreover, since collecting collision data is risky and might cause potential damage to the robot, applying the deep learning method to a new target robot on mass production is highly restricted. Therefore, in this article, an inductive bias is imposed on network structure and input variable to be sample-efficiently trained, which is suitable for insufficient imbalanced data. The proposed modularized neural network removes the connection between other joints at the front part of the network, reducing the search space of the learnable parameter. Moreover, the input variable is selected to take both dynamics features and error-related features into account. Consequently, the proposed method is versatile, showing successful generalization performance to random motion, random collision location, and various loads at the end-effector. Furthermore, to circumvent the limitations of applying deep learning methods to mass production, transfer learning is proposed, which does not require any collision data from the target robot. The proposed data-mixture method and collision ratio adjustment method for fine-tuning are validated with two source robots and one target robot. The transferred network is effective to be applied on mass production without losing performance compared to a specific-robot-trained network(a network trained with specific robot data and applied to the same robot).

어구부표의 표시 방법 개선에 대한 입법론적 고찰 - 어구 손상사고 사례를 중심으로 -

Accidents between small ships and small fishing vessels sailing in the coastal waters of Korea and facilities installed for fishing on the coast occur frequently every year. These accidents are mainly caused by aquaculture farms, fishing nets, and gill nets installed in coastal waters. Common causes of ship accidents include the negligence of the officers of the crew on a sailing vessel, non-compliance with course maintenance, confirmation of ship position, and general navigation. It can be in various ways, such as non-compliance with the principles and regulations on the prevention of collisions at sea. In particular, to examine the cause of the accident related to the fishing net damage accident, it was analyzed through the decision of the Maritime Safety Tribunal, and as a result, the cause of the accident was neglect of the boundary, not securing an appropriate distance from the installed fishing gear, and insufficient establishment of the voyage plan. In order to reduce accidents caused by these human factors, it takes a long time and a lot of money, such as constant safety education for seafarers or changes to systems such as ship safety management system. In this paper, measures to reduce the occurrence of accidents by removing other risk factors other than human factors by intuitively discovering fishing gear a little faster are presented in 「Fisheries Act」, 「Rules on the Management of Fishing Licenses, etc.」, 「Aquaculture and fishing grounds」 We will try to find a way to reduce the damage to fishing nets by identifying and improving problems in the “Installation Standards for Marking Facilities” and “Aquaculture Industry Development Act”.

An Intelligent delay efficient data aggregation scheduling for distributed sensor networks

Data aggregation is the most prominent task in many wireless sensor network (WSN) applications, that enables all data from the network to be collected at the sink node. The most critical issue in data aggregation is data aggregation scheduling. This problem becomes even cumbersome when considered to obtain minimum latency and collision in the networks where fixed amount of data can be aggregated. Many researches have been conducted to resolve the issue of data delivery with low latency and collision. Though, some methods nearly achieved this objective but at the cost of increased complexity. Also, many works assume the system to be centralized having knowledge of every related device in the network. Practically, WSNs are likely to be distributed where each device’s information is dissociated from the other. In this context, a data aggregation scheduling algorithm is proposed to aggregate the data from a tree-based distributed sensor network. An effective aggregation tree construction based on Dijkstra’s algorithm is adopted which avoids the chance of re-transmission of data. Furthermore, a new collision prevention scheduling (CPS) algorithm is designed which ensures the data aggregation through non-collision schedules using minimum time slots. The proposed method shows 54.74% less aggregation latency compared to its competitor data aggregation scheduling approach. The outcome of extensive simulations confirms the efficiency and good performance of the proposed algorithm over previous works.