Minimum Safe Distance Research Articles

Analysis of Safety Distances in Fire Explosions at Indoor Tank Storage Facilities Containing Flammable Liquids in Neighborhood Living Facilities

This study analyzed the minimum safe distance required for rescue activities in a flammable liquid fire explosion in an indoor tank storage facility within a neighborhood living facility. The safe distance was derived using guidelines, accident data, and simulations of accident cases. The considered chemicals were acetone, which was used as the refined oil, and N-dodecane, which was used as the diesel. The Busan bathhouse fire explosion in 2023 was selected as the accident case. The results indicated that the safe distance in the guidelines was 50 m, and the safe distance for accident cases considering only thermal radiation was 30 m. The simulation results showed that the radiation heat and overpressure of refined oil were in the ranges of 17~52 m and 26~129 m, respectively, whereas the radiation heat of diesel oil was in the range of 19~47 m. Hence, it is reasonable to apply a minimum safety distance of 50 m, as set by the fire brigade, upon the initial arrival of a flammable liquid leak accident. To provide relief activities for a chemical rescue team arriving in the middle of an accident, it is necessary to create and provide data that can be used to set appropriate safety distances based on the characteristics of the material and environment.

Integrated automatic parking path planning and trajectory tracking optimization method

Current automatic parking systems often separate path planning and trajectory tracking, increasing complexity and failing to meet the parking needs of autonomous cars. Consequently, this study presents an approach based on Multi-stage Nonlinear Model Predictive Control (MSNMPC) for integrated autonomous parking path planning and trajectory tracking optimization. The method represents the evolution of uncertainty parameters over time through a scenario tree, and the MSNMPC controller with a predictive horizon P defines P + 1 phases, each with specific cost and constraint functions that depend only on the vehicle state and control inputs of that phase to satisfy the constraints of all phases of the parking process. In addition, the method integrates path planning and tracking control into one optimization problem, which is solved online to achieve integrated parking control. Simulation confirms that, in comparison to MPC with RRT* hierarchical control, the integrated parking scheme of MSNMPC has less lateral error and offers superior flexibility and tracking performance. To verify the generality of the scheme, it was validated in the diagonal parking scenario and the vertical parking scenario, respectively. The results show that, compared to the control experiments, the parking elapsed time has been reduced by 10.76% and 9.02%, respectively, enhancing parking efficiency. In addition, the parking error has decreased by 30.77% and 38.46%, respectively, thus improving parking accuracy. Moreover, the minimum safe distance in the control scheme for addressing uncertainty factors is 0.7 m greater than that of the control experiments, meeting the driving requirements for driverless vehicles in parking scenarios.

Risk-Aware Lane Change and Trajectory Planning for Connected Autonomous Vehicles Based on a Potential Field Model

To enhance the safety of lane changes for connected autonomous vehicles in an intelligent transportation environment, this study draws from potential field theory to analyze variations in the risks that vehicles face under different traffic conditions. The safe minimum vehicle distance is dynamically adjusted, and a comprehensive vehicle risk potential field model is developed. This model systematically quantifies the risks encountered by connected autonomous vehicles during the driving process, providing a more accurate assessment of safety conditions. Subsequently, vehicle motion is decoupled into lateral and longitudinal components within the Frenet coordinate system, with quintic polynomials employed to generate clusters of potential trajectories. To improve computational efficiency, trajectory evaluation metrics are developed based on vehicle dynamics, incorporating factors such as acceleration, jerk, and curvature. An initial filtering process is applied to these trajectories, yielding a refined set of candidates. These candidate trajectories are further assessed using a minimum safety distance model derived from potential field theory, with optimization focusing on safety, comfort, and efficiency. The algorithm is tested in a three-lane curved simulation environment that includes both constant-speed and variable-speed lane change scenarios. Results show that the collision risk between the target vehicle and surrounding vehicles remains below the minimum safety distance threshold throughout the lane change process, ensuring a high level of safety. Furthermore, across various driving conditions, the target vehicle’s acceleration, jerk, and trajectory curvature remained well within acceptable limits, demonstrating that the proposed lane change trajectory planning algorithm successfully balances safety, comfort, and smoothness, even in complex traffic environments.

Guaranteed real-time cooperative collision avoidance for n-DOF manipulators

Abstract This paper presents a decentralized, cooperative, real-time avoidance control strategy for robotic manipulators. The proposed avoidance control law builds on the concepts of artificial potential field functions and provides tighter bounds on the minimum safe distance when compared to traditional potential-based controllers. Moreover, the proposed avoidance control law is given in analytical, continuous closed form, avoiding the use of optimization techniques and discrete algorithms, and is rigorously proven to guarantee collision avoidance at all times. Examples of planar and 3D manipulators with cylindrical links under the proposed avoidance control are given and compared with the traditional approach of modeling links and obstacles with multiple spheres. The results show that the proposed avoidance control law can achieve, in general, faster convergence, smaller tracking errors, and lower control torques than the traditional approach. Furthermore, we provide extensions of the avoidance control to robotic manipulators with bounded control torques.

Human-redundant robot interaction and redundancy utilization based on three-dimensional force sensor

To make full use of redundant characteristics, the inverse kinematics algorithm based on augmented Jacobian matrix with the goal of avoiding joint limit and obstacle is adopted. Then, admittance control system is established for human-robot interaction, and force control is converted into motion control of robot. Through the expansion of Jacobian matrix, the model of joint limit avoidance is established. Regarding obstacle avoidance in human-robot interaction process, the potential function gradient is calculated and augmented Jacobian matrix is formed. Thus, comprehensive control model of human-robot interaction and obstacle avoidance is established. When the external force is applied, the robot can move smoothly along the human hand. The robot's motion process is smooth and compliant. At the same time, when performing task of avoiding joint limit, the values of the joint angle are within the set range. The average angle margin of the four joints is over 60 %. So the goal of avoiding the joint limit is achieved. When adding obstacle avoidance in the interaction control, the difference value between the minimum distance and safe distance is always positive. The safety margin of the distance is over 20 %. So the robot does not contact with the obstacle. So human-robot interaction and redundancy utilization can be realized simultaneously.

Experimental implementation of skeleton tracking for collision avoidance in collaborative robotics

Collaborative robotic manipulators can stop in case of a collision, according to the ISO/TS 15066 and ISO 10218-1 standards. However, in a human-robot collaboration scenario where the robot and the human share the workspace, a better solution with concerns to production and operator safety would be to perceive in advance the presence of an obstacle and be able to avoid it, thereby completing the task without halting the robot. In this paper, an obstacle avoidance algorithm is tested using a sensor system for real-time human detection; the operator represents a potential dynamic obstacle that can interfere with the robot motion. The sensor system consists of three RGB-D cameras. A custom software framework has been developed in Python exploiting machine learning tools for human skeleton detection. The coordinates of the human body joints relative to the manipulator base are used as input to the obstacle avoidance algorithm. The use of multiple sensors makes it possible to limit the occlusion problem; in addition, the choice of non-wearable sensors goes in the direction of better operator comfort. A series of experimental tests were performed to verify the accuracy of skeleton detection and the ability of the system to avoid obstacles in real time. The human motion caption system, in particular, was validated through a comparison with a commercial system based on wearable IMU sensors widely used and validated in motion capture. There is an NRMSE of 3.23%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$3.23\\%$$\\end{document} for the RGB-D camera-based skeleton detection system, against an NRMSE of 12.23%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$12.23\\%$$\\end{document} for the IMU wearable sensor system. Test results confirm that the system is able to avoid collisions with the human body under various conditions, static or dynamic, ensuring a minimum safety distance to any part of the manipulator. In 44 tests in which the operator moves around the robot with possible collisions (at a speed typical of manufacturing operations), the minimum operator-robot distance averaged 208mm\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$208\\,\ extrm{mm}$$\\end{document}, being 200mm\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$200\\,\ extrm{mm}$$\\end{document} the limit safety distance set by algorithm.

Multi-constraint improved RS path planning method for unmanned rice direct seeding machine

Path planning is one of the key technologies that determines the efficiency and quality of field operations using autonomous agricultural machinery. To date, there has been extensive research on global coverage path planning for unmanned agricultural machinery within the working area; however, the issue of “encircling and edging” left by the machinery during headland turns is often overlooked. This study focuses on the operational conditions of unmanned agricultural machinery in the rice fields of southern China. The path planning problem is abstracted under physical constraints, such as the space at the field headland, the agricultural environment (e.g., types of field ridges), the turning characteristics of the machinery, turning radius, working width, and minimum safety distance, into mathematical constraints. This yields an optimized path planning model and sequence combination. Based on the improved Reeds–Shepp curve, an en-circling and edging path planning algorithm is designed. The planned path for the unmanned agricultural machinery from start to finish consists only of arcs and straight lines, suitable for the right-angle turning, reversing, and 180° U-turn operations required for rice field machinery, thus significantly improving the coverage of field edges and missed areas at the headland. A rice direct-seeding machine was used as a test subject for encircling and edging field trials, with tests conducted in rectangular, trapezoidal, and irregular quadrilateral rice fields. The results show that, for rectangular plots, the full-field coverage rate of rice direct-seeding operations can reach 96.44%; for trapezoidal plots, the coverage rate is 95.47%; and for irregular quadrilateral fields, the coverage rate is 95.69%. These results are promising, indicating that the encircling and edging path planning based on the improved Reeds–Shepp curve can effectively increase the full-field coverage rate of unmanned agricultural machinery, improving work quality and meeting the needs of modernized, intelligent agricultural machinery operations.

Reactive Collision Avoidance Control for Nonholonomic Vehicles and Obstacles of Arbitrary Shape

Abstract Potential field-based collision avoidance algorithms for mobile robots frequently assume vehicles and obstacles to have circular or spherical shapes. This assumption not only simplifies the analysis but also limits the mobility of agents in confined spaces, particularly for vehicles with elongated or irregular shapes. To increase mobility, this letter presents a decentralized collision avoidance framework for nonholonomic systems of unicycle type that considers the non-circular shape and relative orientation of vehicles and obstacles. The framework builds on the concepts of potential field and avoidance functions. However, it proposes using a non-constant minimum safe distance radius that changes based on the shape, relative position, and relative orientation of agents. The control framework is proven to guarantee collision avoidance at all times and is shown, via simulation, to increase the ability of agents to navigate through narrow spaces safely.

The Impact of Pit Latrines on the Pollution of Groundwater in the District of Rwamagana, Rwanda

The composition and condition of a water body change over time and across different locations due to internal and external factors. In many rural and peri- urban communities in Rwamagana, the lack of treated water has increased reliance on groundwater for various household and community needs. Groundwater sources are essential for meeting the water demand in these regions. An investigation was carried out in the Rwamagana district of the eastern province of Rwanda to evaluate the influence of pit latrines on groundwater quality. The research examined the water quality of four boreholes with hand pumps and 18 improved springs located near pit latrines. The evaluation specifically looked at total coliforms (TC), electrical conductivity (EC), turbidity, and pH. The proximity of the pit latrines to the boreholes or springs was considered in order to determine the presence of fecal coliforms in the groundwater, with the goal of establishing a minimum safe distance between the pit latrines and water sources. The physicochemical indicators of the water samples met the drinking water quality criteria set by the World Health Organization (WHO). However, the levels of biological contaminants exceeded the WHO's drinking water quality standards. The highest coliform counts detected in the study were 99cfu/100ml of water. The research findings suggest a clear relationship between fecal microbes from pit latrines and their impact on groundwater quality, with the contamination effect extending up to 322.4m for improved springs and 266.2m for boreholes with hand pumps.

Safety and Environmental Sustainability of Strategic Gasoil Tanks, Affected by Fire and Explosion Incidents in the Oil Facilities of Southern Ahvaz

Background: Incidents involving fire and explosions in storage tanks containing petroleum derivatives pose significant safety and environmental risks. The Ahvaz oil field, ranking as the third-largest globally, features numerous storage tanks for petroleum derivatives, raising the likelihood of accidents and necessitating a comprehensive investigation. Methods: This study aimed to assess the repercussions of gasoline release from two strategically positioned tanks within an oil center in Ahvaz city in the year 1400. The evaluation encompassed two gasoline tanks, one with a capacity of 650 L and the other with 2.3 million L. Numerical calculation methods and the ALOHA model were employed for consequence modeling. The modeling incorporated data on climatic conditions, topographic parameters, geographical characteristics, and tank specifications. The chemical exposure index (CEI) was utilized to prioritize potential health hazards for individuals in the vicinity of the tanks. Results: The findings indicated that, based on the Emergency Response Planning Guidelines (ERPG) criteria, the minimum safe distance for a fire is 28.5 yards for the 650-liter tank and 76.5 yards for the 2.3 million-L tank. Additionally, the toxic cloud radius resulting from diesel release was 61.2 and 136 yards for the respective tanks, putting 19 employees at risk in this area. Thus, the consequences of diesel release from tanks represent plausible and noteworthy incidents that could lead to significant accidents and damages. Conclusion: Assessing the repercussions of diesel release serves as an effective management tool in emergencies involving tanks, facilitating safe and appropriate placement measures.

Quantifying risks of lane-changing behavior in highways with vehicle trajectory data under different driving environments

Improper lane-changing behavior may have a great impact on the safety of the surrounding vehicles, and accurate risk assessment of lane-changing behavior can detect improper lane-changing behavior. Many existing risk assessment methods are based on the traditional minimum safe distance model as the theoretical foundation, not taking into account the effects of different weather and road conditions. Moreover, the initially calculated safe lane-changing distance through the model is generally the limit safety distance, which deviates to some extent from the initial distance maintained when the vehicle begins to change lanes during the actual driving process. The ratio of these two distances can reflect the degree of risk between the changing vehicle and its neighboring vehicles during lane-changing. For this reason, a lane-changing safety coefficient is defined and lane-changing risk assessment model based on the hyperbolic tangent function is constructed by combining the change characteristics of this coefficient. An environmental adjustment factor was introduced into the model to consider the influence of different driving weather and road conditions on the lane-changing risk assessment. Then, based on survey data from the survey questionnaire, the weights of the influencing factors were determined by using the hierarchical analysis method, and the environmental adjustment factor in the model was calibrated by using the fuzzy comprehensive assessment method. Finally, to verify the effectiveness of the model, the lane-changing trajectories of 373 vehicles were extracted from the HighD dataset. The risk assessment value of lane-changing was calculated by using the constructed model and was classified into high-risk, medium-risk and low-risk by using the K-means++ clustering algorithm. Various evaluation results were compared with the evaluation results from the expert evaluation method and the classical risk evaluation indexes, and the evaluation results are basically the same, which verifies the effectiveness of the lane-changing risk model established.

Exploring the intra-platoon planning problem for heterogeneous train traffic under virtual coupling in the railway network via simulation

Study on the platoon planning of virtual coupling (VC) is indispensable for both passenger and freight railway operation in terms of capacity, scheduling, and timetabling. As an advanced technology in train operation and control systems, VC can significantly improve the performance of rail operations, with regards to capacity, flexibility and robustness. In this study, we mainly focus on the former one, i.e., to maximize the capacity gains, by employing the relative braking distance based spacing policy for heterogenous train traffic. To our knowledge, this article is the first to address the VC intra-platoon planning problem for a railway network. The main function/purpose of this study is to decide a leader train and allocate an order to the heterogeneous follower trains for the virtually coupled platoon in the off-line mode. The objective is transformed to minimize and compare the sum of minimum safe distance for platoons on the common shared route sections in the railway network from various perspectives, so as to seek the desirable orders of potential train consists within the platoons from the perspective of the whole railway network. Our contributions are mainly threefold. First, the conditions for train platooning under virtual coupling are synthesized. Second, the solution flow charts and algorithms for simulation are proposed, including general framework for simulation, classification of prioritizing the shared common route section, and flow charts and algorithms for decision of coupling order to train platoons. Finally, the proposed methodology was tested and discussed on the designed computational experiment (i.e., numerical simulations of a typical case study with two sets of test examples) via NetLogo platform. The numerical simulation results series revealed some key findings and validated the effectiveness of the proposed methodology. Results of this study can provide guidance to decision makers in timetabling and potential capacity bottleneck identification under VC. We believe that it is worth investigating and further advancing this research direction in the future.

Remote Safety Distance Control for Motor Vehicles

We define a method for monitoring and controlling the Safety Distance between motor vehicles. Failure to respect the safety distance between cars on roads and especially on motorways (where speeds have high values) is among the main causes of accidents. This fact generates serious inconveniences such as roadblocks, with enormous delays for car drivers reaching their destinations, as well as possible deaths and injuries. At the current state of the art, in this regard, steps have only been taken to define auxiliary systems on vehicles that signal when this distance has been reached, advising the driver to reduce speed to restore the minimum safety distance. But such systems are, in practice, negatively considered by motorists and do not lead to positive results. The Method and System defined in this work instead involve the use of a Remote System for controlling the Safety Distance, of the same type as those applied for speed control on roads and motorways. These systems are hated by car drivers, precisely because of their effectiveness and deterrence. In this work, first of all, the state of the art regarding Safety Distance control systems, which up to now have only been present on cars, is analyzed. The different methods of calculating the Safety Distance between vehicles are subsequently described. The method defined in this work is then presented, based on the remote detection of the Safety Distance on roads, especially at high speed, describing it with some figures. Here, we highlight the innovation of the system presented in this work, where, for the first time, a System for Remote controlling the Safety Distance is considered.

Elaboration of Distance Standards Against the Electromagnetic Effects of High-Voltage B Overhead Lines in the Republic of Benin

The high-voltage overhead lines used to transport electrical energy from production plants to distribution stations constitute a very important link in the chain of providing electrical energy to communities. However, they constitute potential sources of emission of electromagnetic waves whose impacts are harmful to human health (thermal electrical stimulation of tissues and in particular those of the brain causing different forms of cancer) if the safety distance between these lines and users is not respected. In recent years, Benin has experienced, in urban areas crossed by transport lines and particularly among populations living in the vicinity of these lines, an explosion in the rate of people suffering from cancer. This study is carried out not only to check whether the minimum distance according to the voltage levels of these lines is respected in order to ensure the safety of people living in their vicinity but also to develop a standard of minimum distances to be respected. By the numerical simulation method based on Maxwell's equations established in a supposedly empty medium, the Bio-Savart law and the Lorentz transformation, the model of wave intensity as a function of distances, is determined. The results obtained respectively give minimum safety distances of 15 meters, 20 meters and 36 meters for the 63 kV, 161 kV and 330 kV high voltage lines Category B. These distances are, by far, respected by the populations. Furthermore, the results clearly show that electric fields are more decisive in defining the minimum distances obtained.

Research analysis on the airflow-particle migration and dust disaster impact scope by the moving mining truck in the open-pit mine

For the purpose of evaluating the dust disaster impact scenario in the open-pit mine, a full-scale physical model of the 730E Komatsu heavy mining truck has been constructed and simulated in the ANSYS Fluent software with the refined wheel tire cannelure structure. The results show that the wind velocity poses a stationary-fluctuation-recovery sector along the longitudinal. A clockwise ellipse separation vortex shapes at the chamber hopper and two symmetrical trailing vortexes arise behind the mining truck. The dust exhibits a saddle shape distribution in the lateral section and shows a gradual sedimentation in the longitudinal, while the percentage of ultrafine dust increases from 26.5% to 46.3%. The minimum safety distance 45 m is feasible to avoid the dust disaster impact from mining truck. The dust disaster impact area presents a linear decrease along the longitudinal direction. It displays an initial increase and later decrease as the vertical height rises. The dust disaster impact scope delineation derived from the moving mining truck has a vital scientific practical significance for ensuring the personnel health security and defining the dust precise prevention priority, which contributes to improving the occupational health level in the open-pit mine.

Obstacle avoidance decision and trajectory tracking control of intelligent vehicle considering surrounding vehicles

To enhance the obstacle avoidance performance and trajectory tracking control stability of vehicles in emergency scenarios, and to solve the problem that the existing decision-making methods based on the minimum safe distance model cannot effectively make decisions in some scenarios, a novel lane-changing obstacle avoidance decision-making and control method is proposed. Initially, when emergency braking cannot avoid obstacles safely, the lane-changing trajectory is planned by quintic polynomial, and the minimum distance and collision detection (MDCD) algorithm is then employed to ascertain whether the lane-changing trajectory meets the safety conditions. Subsequently, a Linear Time-Varying Model Predictive Control (LTV MPC) trajectory tracking controller is designed based on the 7-DOF vehicle dynamics model. Finally, the effectiveness of the proposed method is verified through two representative scenarios. The simulation results indicate that the MDCD algorithm can ensure the safety and effectiveness of obstacle avoidance decisions in all emergency obstacle avoidance scenarios, and when tracking the emergency lane-changing trajectory in different typical scenarios, compared with the LTV MPC controller based on the single-track vehicle dynamics model (STVDM), the maximum tracking error can be reduced by 50.7% and 60.1%, respectively, while ensuring near-equivalent real-time performance operation.

Impact of On-Site Sanitation and Siting of Boreholes on Ground Water Quality in Choma Urban: A Case of New Kalundu and Humba Residential Areas.

Groundwater is a climate–resilient source of freshwater for most sub–Sahara African countries and plays a vital role in sustaining improved access to safe water in pursuit of United Nations Sustainable Development Goal 6 – water and sanitation for all by 2030. However, the potential for on-site sanitation to cause major contamination to groundwater has been known for many years, prompting authorities to advise minimum safe distances between boreholes (water sources) and soakaway. This study evaluated the effects of on-site sanitation and borehole placement on the quality of groundwater in residential areas. The study employed an embedded mixed methodology with a descriptive cross-sectional approach. 138 household heads were involved in the study and 15 water samples were collected for microbiological analysis. Data from households was collected using structured questionnaires while upholding all ethical issues. The study found that 85% of households used on-site sanitation systems as their primary means of waste treatment and disposal, while the remaining 15% used other methods like pit latrines. Due to the utility company’s unstable and unreliable supply of water, residents turned to alternative sources of drinking water, such as drilling boreholes and hand-dug wells within and around compounds, using soakaway systems for waste disposal close to the drinking water source. The chi-square tests revealed that the position of the soakaway, as well as the distance between the water sources and the soakaway, have an influence on water quality. The study concluded that establishment of water sources near any pollution source (soakaway) has a negative impact on the quality of groundwater resources. We recommended that local authorities should not permit construction at any plot less than 30 x 30 meters in its dimensions to have both borehole and on-site sanitation system but rather one of the two.

The Impact of LiDAR Configuration on Goal-Based Navigation within a Deep Reinforcement Learning Framework.

Over the years, deep reinforcement learning (DRL) has shown great potential in mapless autonomous robot navigation and path planning. These DRL methods rely on robots equipped with different light detection and range (LiDAR) sensors with a wide field of view (FOV) configuration to perceive their environment. These types of LiDAR sensors are expensive and are not suitable for small-scale applications. In this paper, we address the performance effect of the LiDAR sensor configuration in DRL models. Our focus is on avoiding static obstacles ahead. We propose a novel approach that determines an initial FOV by calculating an angle of view using the sensor's width and the minimum safe distance required between the robot and the obstacle. The beams returned within the FOV, the robot's velocities, the robot's orientation to the goal point, and the distance to the goal point are used as the input state to generate new velocity values as the output action of the DRL. The cost function of collision avoidance and path planning is defined as the reward of the DRL model. To verify the performance of the proposed method, we adjusted the proposed FOV by ±10° giving a narrower and wider FOV. These new FOVs are trained to obtain collision avoidance and path planning DRL models to validate the proposed method. Our experimental setup shows that the LiDAR configuration with the computed angle of view as its FOV performs best with a success rate of 98% and a lower time complexity of 0.25 m/s. Additionally, using a Husky Robot, we demonstrate the model's good performance and applicability in the real world.

Forward Collision Warning Strategy Based on Millimeter-Wave Radar and Visual Fusion

Forward collision warning (FCW) is a critical technology to improve road safety and reduce traffic accidents. However, the existing multi-sensor fusion methods for FCW suffer from a high false alarm rate and missed alarm rate in complex weather and road environments. For these issues, this paper proposes a decision-level fusion collision warning strategy. The vision algorithm and radar tracking algorithm are improved in order to reduce the false alarm rate and omission rate of forward collision warning. Firstly, this paper proposes an information entropy-based memory index for an adaptive Kalman filter for radar target tracking that can adaptively adjust the noise model in a variety of complex environments. Then, for visual detection, the YOLOv5s model is enhanced in conjunction with the SKBAM (Selective Kernel and Bottleneck Attention Mechanism) designed in this paper to improve the accuracy of vehicle target detection. Finally, a decision-level fusion warning fusion strategy for millimeter-wave radar and vision fusion is proposed. The strategy effectively fuses the detection results of radar and vision and employs a minimum safe distance model to determine the potential danger ahead. Experiments are conducted under various weather and road conditions, and the experimental results show that the proposed algorithm reduces the false alarm rate by 11.619% and the missed alarm rate by 15.672% compared with the traditional algorithm.

Data-driven modeling of downwind toxic gas dispersion in lithium-ion battery failures using computational fluid dynamics

Understanding the toxicity hazard associated with lithium-ion battery systems (electric vehicles, e-mobility devices, energy storage systems, etc.) is critical due to their increasing prevalence in densely populated areas. In this work, a meta-analysis of literature data on the main toxic gas species emitted by lithium-ion batteries was conducted. The aggregated data were used as inputs to computational fluid dynamics simulations to characterize the universe of potential toxic gas concentration profiles. These simulations were run for various ambient conditions and battery characteristics. Results are reported in terms of estimated minimum safety distances based on immediately dangerous to life or health (IDLH) values, which could help inform decisions regarding effective firefighting and evacuation recommendations. A sensitivity analysis was also run to identify the key factors that influence safety distances as well as the combination of factors that led to the largest and shortest safety distances. Additionally, using toxicity data from the literature, the downwind toxicity of an internal combustion engine vehicle fire was compared to that of an electric vehicle fire. A relatively simple simulation setup was used for all simulations to make the results as general as possible.