Safe Distance Research Articles

Research on AEB-P Control Strategy Considering Braking Process Comfort

A control approach for the pedestrian-oriented automobile automatic emergency braking system (AEB-P) that takes driving comfort into account is suggested in an effort to further optimize the AEB-P system's control algorithm. Firstly, for the AEB-P assessment standard of C-NCAP, a braking safety distance model that takes the driver's comfort into account during braking is created. The next step was to construct a hierarchical controller using PID and MPC principles. Lastly, CarSim and Matlab/Simulink are used to build and validate the test scenarios and control methods. The simulation results demonstrate that both ride comfort and driving safety can be guaranteed by the suggested control technique.

Study on the dynamic response characteristics of lining structures in large-section tunnel blasting using JH-2 model analysis

The lining structures of tunnels are typically constructed using sprayed or cast concrete materials, and their performance and quality during tunnel excavation and blasting are crucial for the stability and safety of tunnels. Therefore, the safe distance between the lining structure and blasting source should be determined to avoid concrete damage caused by blasting vibrations. In this study, taking the subway tunnel of Danshan Station in Qingdao as an example, the JH-2 model is introduced as the constitutive model of the tunnel blasting simulation, and the JH-2 model parameters of the local surrounding rock are obtained by experiments, and finally the numerical simulation and theoretical verification are carried out to study the safety distance of shotcrete under various safety judgment standards. The results indicate that the JH-2 model can effectively simulate the propagation of stress waves under different media conditions, and the closer the strength parameters and pressure constant of the lining structure are to those of the surrounding rock, the safer the concrete–rock bonding interface. During tunnel blasting construction using the ring blasting method, the peak particle velocity (PPV) of the lining structure increases with an increase in the arch angle. Based on the numerical simulation results, we recommend that concrete lining be constructed at a distance of at least 62 m from the blasting source to avoid damage caused by vibrations. The effect of concrete tensile failure caused by longitudinal stress is much smaller than the damage to the bonding interface caused by the PPV and can be neglected.

Study on trajectory optimization of satellite rapid orbit formation flying for space object

This paper proposes a method of collaborative trajectory planning that utilizes convex optimization and IFPSO to tackle the issue of rapid formation reconstruction by multiple satellites in a low Earth circular orbit. The trajectory optimisation in this study uses convex optimisation and takes into account thrust limitations and safety distance. The time optimal solution is replaced by the path optimal solution, resulting in a suboptimal solution. The time-suboptimal trajectory solving method for formation flying using the CVX software is designed. The IFPSO is used to allocate configurations and waypoints for formation reconstruction, with the aim of balancing fuel consumption across the fleet and reducing the overall fuel consumption of the satellite. The effectiveness of the proposed approach is confirmed by numerical simulation. Despite sacrificing some computational efficiency, the method offered can solve the issues of configuration allocation and trajectory optimization.

Optimizing Solar Potential: Site Potential Selection for Floating Photovoltaics in the Sepaku Semoi Dam Reservoir

Green energy is considered an essential solution to address the world’s energy scarcity. However, there are several technologies available for producing green energy, including photovoltaics, with a specific focus on floating photovoltaics. The application of photovoltaics on water surfaces can enhance the cooling effect of solar modules, thereby achieving optimal temperatures. The implementation of floating photovoltaics should be approached with careful consideration, for instance, hydrodynamic aspects, reservoir water level fluctuations, forest shadow effects, and safety distance from Dam Facilities. Furthermore, in light of the relocation of the Indonesian National Capital City from Jakarta to Ibu Kota Nusantara (IKN), the city’s green energy options must be thoroughly studied and researched. The Sepaku Semoi Dam is located in Penajam Paser Utara, Kalimantan Timur, and is designated as a flood control and raw rater supplier for IKN. In this research, hydrodynamic simulations using MIKE 21 were conducted to determine water surface velocities. These results were then combined with reservoir depth and the location of areas unaffected by forest shadows. The outcome of this analysis revealed that 15.2% of the water surface area in the Sepaku Semoi Dam Reservoir has the potential for installing floating photovoltaics. With an energy density of floating photovoltaic around 100 MW/km2, Sepaku Semoi Dam Reservoir would produce 50.83 MW. As a result, this research has generated a Potential Location Map for Floating Photovoltaics in Sepaku Semoi Reservoir Dam Reservoir.

Framework for determining the safety distance of karst caves adjacent to tunnels

Karst caves pose safety issues for tunnels in karst areas. Karst caves at a certain distance from the tunnel must be treated fully to mitigate risks. A threshold of 3 m is typically adopted; caves within this threshold are fully treated, while those beyond are left untreated, regardless of the geological environment, cave features, tunnel design, operating conditions, etc. This poses risks to tunnel safety during construction and operation. This paper proposes a novel framework based on the aforementioned aspects to determine the treatment distance for caves from the perspective of uncertainty and risk. Geological conditions include the soil and rock type, weathering degree, underground water system, and pH. Karst caves primarily include the size, shape, distance, spatial distribution, density, and filling condition; the tunnel aspect refers to the tunnel diameter, construction method, design life, importance, lining, and tolerable criterion; and operation conditions refer to the vehicle speed, operation time, vehicle load, and maintenance. Herein, the parameters/indices for these aspects and methods to quantify their values are described. A decision-making process is illustrated to revive the mindset of risks in tunnel engineering. The proposed framework is effective for optimizing decision-making in karst cave treatment for tunnels in karst areas.

Effect of Emotionalizing Sounds on the Estimation and Evaluation of Displayed Safety Distances

Musicological and traffic psychology research shows that emotions can be changed by certain tone combinations or sound characteristics and that emotions, in turn, influence our driving behavior. Nevertheless, there are no studies on how a dynamic active sound design could influence driving behavior via changing the emotional state of drivers in certain driving situations. Based on a previous study, emotionalizing sounds, characterized by their capacity to evoke specific emotional responses in individuals, were created and used to investigate their effect on the perception of safety distances in an online study. To test this, participants made statements on the safety distance shown in videos of cars following scenarios combined with emotionalizing sounds. The results show a significant difference in the estimated safety distance for videos combined with sounds invoking positive emotions like light-heartedness vs. sounds invoking negative emotions like feeling threatened. The odds of the safety distance being evaluated as too small compared with appropriate were two to three times higher for some threatening sounds vs. the positive sounds. The results further suggest that threatening sounds influenced participants’ wishes to increase the depicted safety distances. The results show that emotionalizing sounds had effects on the participants, though not all were statistically significant.

Physical Distancing is Better than Social Distancing”: A Breakdown of the Shift in Society’s Psychology and Behaviour

This study focuses on social and physical distancing narratives during the outbreak of Covid-19 in India. Researchers have attempted to explore the trajectory of discursive practices that define social and physical distancing and its impact on human psychology. Further, the study looks at the communication strategies that have been mediated to create a mediatized reality focused on keeping a safe distance from one another to prevent the spread of the virus that caused self-isolation, compelled quarantine, and worry over health issues like psychological distress, Depression, and mental anxiety. Researchers have incorporated mediation, analyzing the narratives around societal and cultural practices that are integral to societal behavioral patterns. Implementing physical distancing in India happened because many communities understood social distancing along caste lines. Major highlights of the study are that despite the efforts made by the Government, media, and other institutions, discriminatory practices existed.

GUI Based 6-DOF Robotic Arm for Radioactive Element Handling

Abstract: Dealing with radioactive elements while research can be dangerous as it can have acute or passive effects on humans. In present scenario research is conducted on radioactive elements by humans after Wearing personal protective equipment such as coat, gloves, safety glasses and close-toed shoes. This equipment provide protection to some extend but still prolonged exposure to radio-active element or some accident can lead to great loss in human life. We can use 3 joint moving robotic arm controlled by GUI to handle radioactive elements while research. This will stop the human exposure to the harmful waves and also reduce chances of accident. The robotic arm has three joints controlled by Four servo-motors. These three joints allows the robotic arm to move to any point in the 3d plane and pick and place objects. The movement of the robotic arm and each of its joints can be controlled from any device with Wi-Fi & Bluetooth capability. An intuitive GUI is displayed in the browser of controlling device. The remote controlled properties and the control of movement is powered by ESP32 module. ESP32 is a system on chip processor which can be programmed as per requirement and has various I/O ports which allows for different motors and sensor connectivity. The ESP32 module is programmed from computer using Arduino IDE. C program is written & then uploaded on ESP-32. We’ve also added the functionality of recording action and then playing it once or multiple times by programming function of recording and playing action. The proposed system will reduce the requirement of humans while dealing with radioactive elements. The proposed system can perform various action on radioactive elements controlled from safe distance.

Maintenance and transformation method for a multi-AUV dense formation

Accurate formation maintenance and safe formation transformations are significant challenges for multiple autonomous underwater vehicle (multi-AUV) dense formations. To address these problems, an innovative control method for a multi-AUV dense formation is proposed. First, a model predictive controller (MPC) that considers AUV input constraints and external disturbances is designed such that a multi-AUV dense formation can accurately maintain a desired formation while tracking a reference trajectory. After that, at the kinematics level, an optimal path for a safe and efficient multi-AUV dense formation transformation is generated based on the Hungarian method. Furthermore, considering an underactuated and nonlinear AUV dynamics model at the dynamics level, a potential function based on collision avoidance is established. It is added to the MPC objective function to further guarantee the potential of the formation transformation. Finally, a multi-AUV dense formation maintenance simulation shows that the proposed method can guarantee higher trajectory tracking accuracy than other algorithms. A multi-AUV dense formation transformation simulation shows that the proposed method avoids the occurrence of cross paths and a safe distance between AUVs is always maintained. The above results demonstrate that multi-AUV dense formations can achieve accurate maintenance and safe transformations, and the proposed method is feasible and effective.

Study of the Constituent Elements of the Pickpocketing Crime

Pickpocketing is a relatively common type of crime in Chinese judicial practice. The two basic characteristics of pickpocketing are that the crime should take place in a public place and the object of pickpocketing should be the property carried by others. Although the judicial interpretation has established the characteristics of pickpocketing, the debate on it has not subsided, specifically with the dispute on the definition of “public places” and “carrying”. Public places are categorized into completely open public places and relatively open public places. So the nature of public places in specific cases should be analyzed. The scope of the property being carried not just includes the property on the body of an individual, but also includes the property being placed within a safe distance from the individual in the surrounding area.

Research on airport apron planning strategy in emergency situations

In events of local war or highly infectious epidemics, airports face the problem of how to park numerous non-missioned aircraft on aprons. In this study, the apron planning problem in emergency situations (APPES) was considered to replan existing parking stands and taxiways, thus determining the numbers and locations of different aircraft types. A mixed-integer programming formulation for the APPES was developed to maximise the total revenue for the apron, where the aircraft was planned to be parked based on factors such as the safety distance and aircraft taxiing method. A two-stage approach based on the discrete particle swarm optimisation algorithm and bottom-left algorithm was designed to solve the APPES. Random instances of different sizes were generated, and the experimental results demonstrated the effectiveness of the proposed approach. The two-stage approach could find optimal solutions to the APPES for 19 of the 20 small instances and could well approximate optimal solutions for the medium and large instances within a reasonable timeframe. Parking priority factor and aircraft taxiing methods sensitivity analyses were also designed to develop a strategy that can adhere to the preferences of decision makers or increase the total revenue.

Using Hill Climb Assembler Encoding neural networks to control follower vehicles in an underwater swarm

The paper presents the application of neural networks evolving under the Hill Climb Assembler Encoding (HCAE) algorithm to control follower autonomous underwater vehicles that are members of a swarm consisting of one leader vehicle and a group of followers. The leader is responsible for global navigation and guiding the swarm, while low-cost followers unable to cover longer distances on their own follow the leader. To locate the leader, the followers only use information about the distance to it. Directional information is unavailable to the followers. Moreover, information about the distance is transmitted to followers with a frequency depending on the number of followers: the more followers, the lower the frequency. In addition to tracking the leader, the followers must also be able to avoid collisions with other followers and the leader. To this end, they are equipped with short-range sensors looking around each follower. The simulations presented in the paper were carried out for different swarm sizes, different sensor ranges, different collision distances, and variable leader speed, and showed high effectiveness of the proposed neural solution. The most common strategy for the followers when following a leader was to circle it at a certain safe distance depending on the sensor range.

Глобальное планирование маршрута мобильного робота на основе графовых методов

The problem of global route planning for a mobile robot between two given points in a known area with static obstacles is considered. To solve the problem of constructing a route in an area with a large number of obstacles of complex shape, an integrated approach based on graph theory methods is proposed. It includes the Voronoi diagram, visibility graph and the Dijkstra's algorithm. At the first stage, the study area is represented as a polygonal object, the space outside the object is considered as obstacles. Next, to get a safe distance from obstacles, an internal buffer of the polygonal object is built using the Minkowski difference. Then the vertices of the polygon are compacted, and the Voronoi polygons are constructed from the resulting vertices. The median axis of the polygon is calculated from the Voronoi polygons. Then the Dijkstra's algorithm is applied to calculate the shortest path. The resulting path is used to construct a visibility graph, and the Dijkstra's algorithm is reapplied to the resulting graph. The proposed approach allows to build a route that is optimal in terms of length and distance to obstacles. It significantly reduces the computational complexity of constructing a visibility graph. The approach was implemented in the freely distributed QGIS geographic information system for planning the route of a mobile robot in an aquatic environment. The results of the experiment showed that the Voronoi diagram reduced the number of vertices required to construct the visibility graph by 8.3 times, while the visibility graph improved the path obtained from the Voronoi diagram by 8%. The proposed approach can be used for global planning of routes for mobile robots in various environments.

An improved dynamic window approach algorithm for dynamic obstacle avoidance in mobile robot formation

Dynamic Window Approach (DWA) algorithm is a commonly used choice in dynamic obstacle avoidance. However, the traditional DWA algorithm evaluation function is poorly adapted to dynamic obstacle avoidance and has defects in efficiency and safety. In this paper, we consider the speed and heading of the mobile robot formation and the speed and heading of the obstacles and design the speed-varying obstacle avoidance and safety distance evaluation coefficients. The objective is to design an improved DWA algorithm to improve the obstacle avoidance ability of mobile robot formations when encountering dynamic obstacle interference. First, the obstacle environment in which the mobile robot formation is located is analyzed to determine the obstacles that threaten the formation and those that are not. Second, the obstacle velocity space is evaluated and analyzed using the velocity change evaluation coefficient so that the robot formation’s obstacle avoidance behavior after the combination of angular and linear travel velocities has high robustness in the face of dynamic obstacle interference. Finally, the evaluation coefficient of safe obstacle avoidance distance is designed to accurately judge the positional relationship between the robot formation and dynamic obstacles at the moment of obstacle avoidance, which maximizes the safety of the robot formation traveling. The experimental results show that the improved algorithm shortens the obstacle avoidance time by 37.3% and saves 16.8% of the distance traveled than the traditional algorithm. It also achieves good results in terms of robustness and safety.

An Improved Aquila Optimizer with Local Escaping Operator and Its Application in UAV Path Planning

Background: With the development of intelligent technology, Unmanned aerial vehicles (UAVs) are widely used in military and civilian fields. Path planning is the most important part of UAV navigation system. Its purpose is to find a smooth and feasible path from the start to the end. Objective: In order to obtain a better flight path, this paper presents an improved Aquila optimizer combing the opposition-based learning and the local escaping operator, named LEOAO, to deal with the UAV path planning problem in three-dimensional environments. Methods: UAV path planning is modelled as a constrained optimization problem in which the cost function consists of one objective: path length and four constraints: safe distance, flight height, turning angle and climbing/diving angle. In this paper, the LEOAO is introduced to find the optimal path by minimizing the cost function, and B-Spline is invited to represent a smooth path. The local escaping operator is used to enhance the search ability of the algorithm. Results: To test the performance of LEOAO, two scenarios are applied based on basic terrain function. Experiments show that the proposed LEOAO outperforms other algorithms such as the grey wolf optimizer, whale optimization algorithm, including the original Aquila optimizer. Conclusion: The proposed algorithm combines the opposition-based learning and local escaping operator. The opposition-based learning algorithm has the ability to accelerate convergence. And the introduction of LEO effectively balances the exploration and exploitation abilities of the algorithm and improves the quality of the population. Finally, the improved Aquila optimizer obtains a better path.

An aerial framework for Multi-View grape bunch detection and route Optimization using ACO

Typically, commercial orchards and vineyards consist of large fields that encounter similar development phases at once. Thus, it becomes necessary to efficiently fly over all fields to detect fruit and identify their status in a very limited timeframe. For this purpose, Unmanned Aerial Vehicles (UAVs) path planning plays a pivotal role in agriculture as it enables optimal coverage of agricultural fields, leading to enhanced data acquisition and improved precision agriculture practices, for instance, disease assessment and pesticide application. In addition, deep learning techniques offer precise image analysis. On the one hand, object detection has been applied to agricultural fields to carry out a wide range of operations, such as detecting apples and predicting yield in vineyards, with higher detection accuracy when the fruits are fully visible. On the other hand, when crops present leaf-occlusion, the algorithms face difficulties and are unable to adapt to the specific characteristics of the field. Therefore, this study seeks to address this issue by developing a novel framework to enhance UAV path planning for data collection in vineyards, considering the current biophysical environment. To this end, the proposed framework requires two flights: i) a first flight (survey) to acquire insights on the crop structure and environment, and ii) a second flight using the Ant Colony Optimization Max-Min Ant System (ACO-MMAS) algorithm to enhance image acquisition by considering multiple angles to overcome partial leaf-occlusion. Further, the optimisation algorithm can potentially boost the acquisition of datasets for fruit detection by considering single and multiple UAVs flying synchronously while ensuring a safe distance between platforms and efficient coverage. The method was tested in two vineyards with different environmental characteristics, increasing levels of difficulty and acquired during two different growing seasons. It improved the length of the computed paths by up to 24%, compared to a base algorithm that considers only the closest point without any optimisation, improving the decision-making processes and resource allocation in crop management.

Studying Probability of Domino Effect in Chemical Storage Tanks Using Hazard Index

The accidents caused by the domino effect in industries are highly harmful. This study aims to analyze the occurrence probability of the domino effect with respect to possible explosion and fire scenarios in chemical tanks. Using the results obtained by previous studies, reviewing past accidents, and according to the equipment damage models, threshold values were used for extraction process equipment and inherent safety distances as a criterion to prevent domino accidents. According to primary scenarios and experimental equations, the escalation vector was determined for different tanks. According to the assumption that fire radius is equivalent to inherent safety distance, the fireball radius for tank 1 was calculated 535.7 m. According to the results, the DCP index of tank 3 can be considered the most critical unit. This research studies the probability of the domino effect and means to prevent them according to criteria and hazard index parameters.

REAL TIME WIRELESS FIRE FIGHTING ROBOT

The Real-time Wireless Firefighting Robot is an innovative autonomous robotic system designed for effective fire response in hazardous environments. This robot integrates advanced technologies such as wireless communication, sensors, and real-time data processing to enhance firefighting capabilities. Equipped with a high-resolution camera, the robot can navigate through smoke-filled areas and transmit live video feeds to the control center. The wireless communication system enables seamless remote operation, allowing firefighters to assess the situation and make informed decisions. The robot's robust design and fire-resistant materials ensure its durability in high-temperature environments. Overall, the Live Wireless Firefighting Robot presents a cutting-edge solution for improving firefighting efficiency and reducing risks to human responders. This robot is equipped with advanced sensors for real-time fire detection and localization. Its wireless connectivity enables remote control and monitoring, allowing firefighters to operate it from a safe distance. The robot's mobility and agility enable it to navigate challenging environments, reaching areas that may be hazardous for humans. With a built-in water or foam spraying system, the robot can effectively suppress fires. Additionally, it incorporates live video streaming to provide a comprehensive view of the situation. The use of wireless technology not only facilitates seamless communication but also ensures quick response times, making this robot a valuable asset in firefighting scenarios, minimizing risks to human lives. Key Words: Fire Fighting Robot, Mobility, Live video feeds.

Distributed Localization for UAV–UGV Cooperative Systems Using Information Consensus Filter

In the evolving landscape of autonomous systems, the integration of unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) has emerged as a promising solution for improving the localization accuracy and operational efficiency for diverse applications. This study introduces an Information Consensus Filter (ICF)-based decentralized control system for UAVs, incorporating the Control Barrier Function–Control Lyapunov Function (CBF–CLF) strategy aimed at enhancing operational safety and efficiency. At the core of our approach lies an ICF-based decentralized control algorithm that allows UAVs to autonomously adjust their flight controls in real time based on inter-UAV communication. This facilitates cohesive movement operation, significantly improving the system resilience and adaptability. Meanwhile, the UAV is equipped with a visual recognition system designed for tracking and locating the UGV. According to the experiments proposed in the paper, the precision of this visual recognition system correlates significantly with the operational distance. The proposed CBF–CLF strategy dynamically adjusts the control inputs to maintain safe distances between the UAV and UGV, thereby enhancing the accuracy of the visual system. The effectiveness and robustness of the proposed system are demonstrated through extensive simulations and experiments, highlighting its potential for widespread application in UAV operational domains.

Knowledge and Practices of Nurses Regarding Aseptic Techniques for Infection Prevention in Operating Room at Tertiary Care Hospital

Background: Surgical site infections (SSIs) remain a significant concern in operating rooms, largely influenced by the adherence to aseptic techniques by healthcare professionals. Despite the critical role of operating room nurses in preventing these infections, gaps in knowledge and practice persist, affecting the overall quality of patient care in tertiary healthcare settings. Objective: This study aimed to assess the knowledge and practices of operating room nurses regarding aseptic techniques for infection prevention in tertiary care hospitals. Methods: A descriptive cross-sectional study was conducted at a tertiary care hospital in Lahore, involving 130 operating room nurses with over a year of service. The study employed purposive sampling to administer a validated questionnaire assessing demographic data, knowledge, and practices related to aseptic techniques. Data were collected from January to March 2023 and analyzed using SPSS version 25, employing descriptive and inferential statistics to explore the relationship between demographic factors and knowledge/practices of aseptic techniques. Results: The study found that 60% of nurses were aware that a gown is considered sterile in specified areas, and 54.6% understood the contamination risks of dropped sterile packages. Approximately 62.3% recognized the importance of maintaining a safe distance during procedures. Despite these knowledge indicators, 94% of nurses routinely practiced sterile techniques, and 91% adhered to proper handwashing protocols. However, the overall level of knowledge concerning aseptic techniques was low, with significant gaps that could potentially impact patient safety. Conclusion: The study highlights a discrepancy between the knowledge and practices of operating room nurses regarding aseptic techniques, indicating a critical need for enhanced training and continuous education to bridge these gaps and improve infection control measures in surgical settings.