Collision Safety Research Articles

Non-Newtonian Fluid Based Non-Linear Impedance Control for Robotic Manipulators

The increasing presence of robots in sectors involving physically or mentally unhealthy tasks, such as high-repetition jobs, chemical synthesis, and high-temperature environments, has led to advancements in robotics for tasks requiring complex environmental interaction, such as grinding, polishing, and assembly. However, the structural rigidity of most industrial robots, which contrasts with the flexibility of human muscles, limits their effectiveness in such tasks. Impedance control, a widely studied framework for managing robot-environment dynamics, has been expanded to address these challenges but struggles with vibrations and collision dynamics. To address these issues without sacrificing flexibility, this study proposes integrating a non-Newtonian fluid-based damping element into impedance control, leveraging fluid dynamics to improve vibration damping and collision safety, enhancing robotic performance in interactive applications.

Research on the collision safety of battery packs with interlaced battery cell arrangement

Ensuring collision safety performance is imperative in battery pack layout design. Conventional battery pack configurations face challenges due to a single-load transfer path issue and disregard the inherent deformability of battery cells. To tackle these challenges and facilitate load dispersion for a wider distribution of collision energy absorption among battery cells, this study suggests a battery cell layout inspired by a biomimetic honeycomb structure. The research model utilizes a uniform battery model and directly encapsulates the batteries within the battery pack, aligning with current packaging trends and enabling interleaved arrangements. Through side pillar collision simulations, the study compared and analyzed aspects such as deformation intrusion of the battery pack, acceleration of deformation in the affected region, impact load transmission, and battery failure scenarios. The findings indicate that the interleaved arrangement offers additional load transmission paths, reducing battery pack deformation intrusion by over 3.8% and effectively optimizing the majority of vulnerable battery cells, leading to a decrease in battery cell damage by over 7.3%. This effect is particularly notable in high-energy impact areas where numerous battery cells surpass failure thresholds. Furthermore, analyses of impacts at various positions and angles demonstrate that the interleaved arrangement of battery packs significantly enhances collision safety performance, mitigating battery damage during collisions and providing valuable insights into battery pack layout design.

Design optimization for inner core of crash box for vehicle based on NPR/PU structure

Vehicle crashworthiness is a critical aspect of the passive safety domain in passenger cars, and crash boxes play a significant role in vehicle collisions. Currently, the crash boxes predominantly utilized in vehicles are primarily simple thin-walled structures, which exhibit average energy-absorbing capabilities. To enhance vehicle collision safety, this article proposes an inner core filled with negative Poisson’s ratio (NPR) structure and polyurethane (PU) material to the design of crash box. Initially, a double-arrow type NPR structure is selected as the framework, with polyurethane (PU) serving as the filling material. This combination forms the inner core of the crash box. A collision analysis is conducted on three types of crash boxes, examining the differences in their performance indicators in detail to demonstrate the superiority of the proposed design. Subsequently, variables that significantly influence the evaluation metrics were identified through extreme value difference analysis, and these variables were designated as the design parameters for the subsequent optimization process. Finally, the Neighborhood Cultivation Genetic Algorithm (NCGA) and Non-dominated Sorting Genetic Algorithm-II (NSGA-II) were employed as optimization algorithms for the optimal design, and the optimal results of the two algorithms are determined separately using Normal Boundary Intersection (NBI) method, and then compared to determine the overall optimal solution. The simulation results indicate that the NSGA-II optimized NPR/PU collision box provides substantial advantages in overall performance. After NSGA-II optimization, the NPR/PU crash box exhibits reduced overall collapse displacement and maximum peak collision force compared to other crash boxes, along with enhanced specific energy absorption capacity. These findings indicate that the designed NPR/PU crash box significantly improves the vehicle’s crashworthiness in the event of a collision. This article offers valuable theoretical insights to support the development and exploration of automotive crash boxes.

Safe Guidance Scheme for Proximity Operations Forced Motion

Autonomous spacecraft proximity operations represent a key enabler for future mission architectures such as in-orbit servicing, active debris removal, object inspection, and in-orbit assembly. This work addresses safety concepts for the relative trajectory guidance design applicable to challenging proximity operations in the close-range domain. The relative orbital element framework is used to formulate safety checks that improve the trajectory’s robustness in case of chaser’s malfunctions or loss of control. Particularly, concepts of passive abort safety and active collision safety are applied to the trajectory design to maintain the chaser outside keep-out zones. These definitions are included within a guidance algorithm that exploits sequential convex programming to efficiently solve the fixed final time safety-constrained close-range rendezvous problem. Test cases of reconfiguration between stable relative orbits and synchronization to a rotating hold point are presented, highlighting the advantages in using these new safety concepts in terms of safety, trajectory insight, and formulation efficiency.

Research on Safety Separation Distance in Paired Approach Based on Monte Carlo Simulation

Faced with the increasing number of flights, efficient and orderly operations have become a critical issue for busy airports. The closely spaced parallel runway paired approach technology has been proven to be an effective solution for increasing runway capacity and operational efficiency. This research focuses on determining the safety separation between paired aircraft, particularly the collision safety limit. This study refines the kinematic modeling process by constructing a three-dimensional kinematic model and advancing the starting point of paired approach, making the simulation process more aligned with reality. Subsequently, the Monte Carlo simulation method is applied, integrating the kinematic model and considering collision risks to simulate the entire paired approach process. Multiple scenarios are created, and simulation experiments are conducted to determine the safety separation between the two paired aircraft. Finally, by adjusting parameter settings and taking the example of the two closely spaced parallel runways at Chongqing Jiangbei International Airport, the correlation between various influencing factors and the safety separation is analyzed. Different scenarios are simulated 100,000 times each, and the results show that the speed difference between the two paired aircraft has the most significant impact on the safety separation, followed by the paired approach mode and runway centerline spacing. The wake turbulence category matching has a minimal effect on the safety separation. The results provide a theoretical basis for airports with closely spaced parallel runways to further reduce the separation between paired aircraft, thereby enhancing airport capacity and runway operational efficiency.

Use of neural networks for safe collision avoidance for groups of autonomous vessels

This article analyzes and compares the effectiveness of two algorithms for collision avoidance in groups of autonomous vessels: one based on geometric analysis of vessel approach and cost function minimization for calculating a safe maneuver (traditional algorithm), and an algorithm utilizing a neural network. Both algorithms assume external control of a group of vessels within a specific area using a vessel traffic management system and coordinated maneuvering of dangerously approaching vessels. Descriptions of these algorithms are provided along with their simplified block diagrams; to solve the task of safely maneuvering a group of vessels, a sequential analysis of all possible vessel pairs in the group and changes in their courses is proposed. The process of creating three test datasets is described, two of which were generated using a program and included 100 scenarios each, while the third was manually composed and included 30 scenarios for different vessel group approach variations. During the testing of the neural network algorithm, two neural networks trained to predict safe courses for vessel pairs were utilized. The neural network used in the algorithm, trained on 743671 samples, allowed the processing of test vessel approach scenarios with an accuracy comparable to the traditional algorithm. Depending on the number of dangerously approaching vessels in the area, the neural network algorithm processed test scenarios 2–14 times faster than the traditional algorithm. The paper highlights the limitations of the described algorithms and outlines planned improvements for subsequent research, including the optimization of the safe maneuver selection methodology and further training of the neural network on larger data volumes.

On the strain rate-dependent mechanical behavior of PE separator for lithium-ion batteries

The separator is a critical component for ensuring electrochemical cycling performance and preventing internal short circuits in lithium-ion batteries. For the collision safety of lithium-ion batteries, understanding the rate-dependent mechanical behavior of the separator is essential for battery impact modeling and safety prediction. This study conducts a comprehensive experimental investigation into the strain rate–dependent tensile/compressive behavior and failure mechanism of the polyethylene (PE) separator under quasi-static and dynamic conditions. The combination of deformation images recorded by cameras and post-mortem characterization using SEM was employed to clarify the rate-dependent deformation and fracture mechanism of the separator under both tensile and compressive loading. The experimental results demonstrate a significant strain rate effect on the tensile/compressive mechanical properties and damage/failure behavior of the separator. Furthermore, the effect of the strain rate on the mechanical properties, including the tensile strength, tensile fracture strain, tensile elastic modulus, compressive modulus, yield stress and yield strain of separator, was analyzed and discussed. A significant strain rate-dependent tensile damage and fracture behavior of the separator was observed, where the fracture site exhibited an obvious phase transition and skeletal lamella fracture under extremely high strain rate tensile loading. The separator underwent severe damage under dynamic compressive conditions. The results of this study provide an important basis for the establishment of rate-dependent safety criterion and short circuit prediction of lithium-ion batteries under impact loading, and shed light on understanding separator failure-induced short circuit issues in battery collision safety scenarios.

Ship autonomous collision avoidance decision from the perspective of navigation practice

Navigation safety is an eternal theme for ships, and it is an inherent strategic requirement for both transportation powers and maritime powers. With the development of intelligent ships, how to make intelligent decision-making results consistent with maritime practice is the key to navigation safety. This paper constructs a complex water area collision avoidance decision-making model that conforms to maritime practice, providing autonomous collision avoidance decision-making schemes for manned or unmanned ships. Firstly, based on the nonlinear velocity obstacle method, dynamic constraints such as ship maneuverability, target ship motion uncertainty, Convention on the International Regulations for Preventing Collisions at Sea (COLREGs), and good seamanship are fully considered, and a safe collision avoidance action plan is solved in the velocity domain; Then, by introducing an overshoot coefficient to improve the line of sight method, a feasible collision avoidance decision plan is derived by searching for a resumption navigation plan based on the safe avoidance action plan; Finally, collision avoidance decision plan is optimized to achieve autonomous collision avoidance decision-making for ships. To verify the effectiveness of the proposed model, a series of case studies, which focus on different encounter situations are designed and executed, the results indicate that the outcome of the model consistently aligns with real-world scenarios, which is in line with maritime practice.

Novel Multi‐configuration Elastic Actuator with Controllable Energy Flow and Power Modulation for Dynamic Energy Robot Systems

Designing actuators that can modulate power, achieve high energy efficiency, and ensure safe collision remains a challenge, especially for dynamic energy robot systems (DERS) with high‐performance requirements. Herein, a novel multi‐configuration elastic actuator (MCEA) is proposed based on a controllable planetary differential mechanism (PDM) with one power port from three springs. These springs, positioned between the inner gear ring and the fixed housing shell, are regulated by a single servo motor through a ratchet–pawl mechanism. This setup enables the springs to absorb energy during collisions, reducing impact and subsequently releasing this energy to boost power output. The inner gear ring functions as a controllable one‐way rotating element, acting either as an input or output for power. The MCEA's ability to manage power modulation and energy flow is demonstrated through experiments that highlight its potential for safe collision management, energy recycling, and power modulation. Experiment results indicate that the maximum output power of the MCEA in the proposed hybrid elastic actuation (HEA) mode is 8.05 times higher than that in the traditional actuation (TA) mode. A single‐legged robot with a four‐link mechanism is also built to validate the considerable performance in the application of legged robots, showing considerable adaptability and prospects for DERS.

Optimizing Vehicle Collision Safety: A Two-Mass Model with Dual Springs and Dampers for Accurate Crash Dynamics Prediction

Optimizing Vehicle Collision Safety: A Two-Mass Model with Dual Springs and Dampers for Accurate Crash Dynamics Prediction

Hybrid A-Star Path Planning Method Based on Hierarchical Clustering and Trichotomy

Aiming to improve on the poor smoothness and longer paths generated by the traditional Hybrid A-star algorithm in unstructured environments with multiple obstacles, especially in confined areas for autonomous vehicles, a Hybrid A-star path planning method based on hierarchical clustering and trichotomy is proposed. This method first utilizes the Prewitt compass gradient operator (Prewitt operator) to identify obstacle boundaries and discretize boundaries. Then, it employs a single linkage hierarchical clustering algorithm to cluster obstacles based on boundaries. Subsequently, the clustered points are enveloped using a convex hull algorithm, considering collision safety for vehicle expansion. This fundamentally addresses the ineffective expansion issue of the traditional Hybrid A-star algorithm in U-shaped obstacle clusters. Finally, the expansion strategy of Hybrid A-star algorithm nodes is improved based on the trichotomy method. Simulation results demonstrate that the improved algorithm can search for a shorter and smoother path without significantly increasing the computational time.

A large-area less-wires stretchable robot electronic skin

Nowadays more and more intelligent robots are being used in scenarios that closely interact with humans, such as collaboration, healthcare, services, etc. This requires robots to have the ability to interact with human safely. Electronic skin is one of the important means for robots to achieve this goal. However, the robot electronic skin still faces serious challenges in large-area applications. We proposed a novel large-area less-wires stretchable textile-based robot electronic skin that can detect the contact position and force in real-time. Benefit by the smartly design of the double-faced effect functional conductive textile, the robot electronic skin has a simple four-layer structure and five external wires. In addition, the stretchability of the robot electronics skin enables it to cover the complex surface of various robots in large area. Finally, the potential applications of the robot electronic skin used for human–machine safe collision avoidance are demonstrated. This study shows that the robot electronic skin has great potential in the fields of robot interaction control.

Occupant safety and injuries in coach frontal collision: a literature review

Occupant safety and injuries in coach frontal collision: a literature review

Research on Vehicle AEB Control Strategy Based on Safety Time–Safety Distance Fusion Algorithm

With the increasing consumer focus on automotive safety, Autonomous Emergency Braking (AEB) systems, recognized as effective active safety technologies for collision avoidance and the mitigation of collision-related injuries, are gaining wider application in the automotive industry. To address the issues of the insufficient working reliability of AEB systems and their unsatisfactory level of accordance with the psychological expectations of drivers, this study proposes an optimized second-order Time to Collision (TTC) safety time algorithm based on the motion state of the preceding vehicle. Additionally, the study introduces a safety distance algorithm derived from an analysis of the braking process of the main vehicle. The safety time algorithm focusing on comfort and the safety distance algorithm focusing on safety are effectively integrated in the time domain and the space domain to obtain the safety time–safety distance fusion algorithm. A MATLAB/Simulink–Carsim joint simulation platform has been established to validate the AEB control strategy in terms of safety, comfort, and system responsiveness. The simulation results show that the proposed safety time–safety distance fusion algorithm consistently achieves complete collision avoidance, indicating a higher safety level for the AEB system. Furthermore, the application of active hierarchical braking minimizes the distance error, at under 0.37 m, which meets psychological expectations of drivers and improves the comfort of the AEB system.

Fracture behaviors of the 1500 MPa-grade anti-oxidation hot-stamped steel: Measurement, numerical simulation and experimental validation

Ultra-high strength hot-stamped steel has been increasingly and widely used for the improvement of the collision safety and lightweight level. The 1500 MPa-grade anti-oxidation hot-stamped steel (AHS-1500), as a newly developed hot-stamped steel, is promising in the automotive industry due to its advantages of anti-oxidation, high strength, high hardenability, and no coating. It is necessary to figure out its fracture failure behaviors and further predict the fracture risk for promoting the large-scale application. In this paper, the fracture behaviors of the AHS-1500 steel plate are investigated by experiments and simulation. The fracture tests are conducted under static and dynamic loads by considering various stress states, namely uniaxial tension, notched static tension, shear, punching, center-hole static tension, and VDA bending. The fracture failure behaviors are obtained. Moreover, an Swift+Hockett-Sherby combined hardening model is adopted to extrapolate the post-necking flow stress to obtain the stress-strain relation at large strains. A fracture failure model is further established based on the GISSMO fracture failure criterion to accurately describe the failure behaviors under various stress states. The nonlinear fracture failure strain and the necking instability strain are determined with the consideration of the influence of element size and strain rate. Finally, the three-point bending experiment of a cap beam part is conducted and simulated to verify the effectiveness of the proposed model. The simulated results match the experimental ones very well, with the absolute relative errors of only 1.4 % and 4.6 % for the peak force and peak displacement, respectively. This research is favourable for contributing to high-precision numerical analysis for the design of automotive structural components and providing technical support for large-scale promotion of the AHS-1500 steel.

Coordinating Obstacle Avoidance of a Redundant Dual-Arm Nursing-Care Robot.

Collision safety is an essential issue for dual-arm nursing-care robots. However, for coordinating operations, there is no suitable method to synchronously avoid collisions between two arms (self-collision) and collisions between an arm and the environment (environment-collision). Therefore, based on the self-motion characteristics of the dual-arm robot's redundant arms, an improved motion controlling algorithm is proposed. This study introduces several key improvements to existing methods. Firstly, the volume of the robotic arms was modeled using a capsule-enveloping method to more accurately reflect their actual structure. Secondly, the gradient projection method was applied in the kinematic analysis to calculate the shortest distances between the left arm, right arm, and the environment, ensuring effective avoidance of the self-collision and environment-collision. Additionally, distance thresholds were introduced to evaluate collision risks, and a velocity weight was used to control the smooth coordinating arm motion. After that, experiments of coordinating obstacle avoidance showed that when the redundant dual-arm robot is holding an object, the coordinating operation was completed while avoiding self-collision and environment-collision. The collision-avoidance method could provide potential benefits for various scenarios, such as medical robots and rehabilitating robots.

Advanced Lightweight Structural Materials for Automobiles: Properties, Manipulation, and Perspective

The key drivers for automotive manufacturers to develop vehicles with decreased weight are the growing requirements for improved fuel efficiency. This endeavor not only tackles the issues related to fuel efficiency but also aligns with the objectives of enhanced recyclability and overall performance of the vehicle, encompassing factors like driving efficiency, braking characteristics, and collision safety. Herein, a successful strategy entails investigating and utilizing lightweight materials with superior performance as substitutes for conventional automotive materials such as cast iron and steel. This article provides a thorough analysis of the lightweight materials that are currently being researched and available for use in the production of next-generation cars. These materials include composites, light alloys, high-strength steel, and other innovative materials. The review covers all aspects of the life cycle of automotive materials, examining their mechanical and physical characteristics, production processes, characterization strategies, and their uses. Both the merits and limitations of these materials are analyzed, leading to a nuanced understanding of suitable scenarios for their application. In anticipation of future challenges, the study suggests that advancements in versatile materials or enhancements in manufacturing and treatment techniques hold promise for overcoming potential obstacles, ultimately facilitating the creation of more capable, safer, durable, and environmentally friendly vehicles.

Evaluation of force pain thresholds to ensure collision safety in worker-robot collaborative operations.

With the growing demand for robots in the industrial field, robot-related technologies with various functions have been introduced. One notable development is the implementation of robots that operate in collaboration with human workers to share tasks, without the need of any physical barriers such as safety fences. The realization of such collaborative operations in practice necessitates the assurance of safety if humans and robots collide. Thus, it is important to establish criteria for such collision scenarios to ensure robot safety and prevent injuries. Collision safety must be ensured in both pinching (quasi-static contact) and impact (transient contact) situations. To this end, we measured the force pain thresholds associated with impacts and evaluated the biomechanical limitations. This measurements were obtained through clinical trials involving physical collisions between human subjects and a device designed for generating impacts, and the force pain thresholds associated with transient collisions between humans and robots were analyzed. Specifically, the force pain threshold was measured at two different locations on the bodies of 37 adults aged 19-32 years, using two impactors with different shapes. The force pain threshold was compared with the results of other relevant studies. The results can help identify biomechanical limitations in a precise and reliable manner to ensure the safety of robots in collaborative applications.

A Hierarchical Trajectory Planning Algorithm for Automated Guided Vehicles in Construction Sites

Herein, to address the challenges faced by Automatic Guided Vehicles (AGVs) in construction site environments, including heavy vehicle loads, extensive road search areas, and randomly distributed obstacles, this paper presents a hierarchical trajectory planning algorithm that combines coarse planning and precise planning. In the first-level coarse planning, lateral and longitudinal sampling is performed based on road environment constraints. A multi-criteria cost function is designed, taking into account factors such as deviation from the road centerline, shortest path cost, and obstacle collision safety cost. An efficient dynamic programming algorithm is used to obtain the optimal path. Considering nonholonomic constraints of vehicles, eliminating inflection points using improved B-Spline path fitting, and a quadratic programming algorithm is proposed to enhance path smoothness, completing the coarse planning algorithm. In the second-level precise planning, the coarse planning path is used as a reference line, and small-range sampling is conducted based on AGV motion constraints, including lateral displacement and longitudinal velocity. Lateral and longitudinal polynomials are constructed. To address the impact of randomly appearing obstacles on vehicle stability and safety, an evaluation function is designed, considering factors such as jerk and acceleration. The optimal trajectory is determined through collision detection, ensuring both safe obstacle avoidance and AGV smoothness. Experimental results demonstrate the effectiveness of this method in solving the path planning challenges faced by AGVs in construction site environments characterized by heavy vehicle loads, extensive road search areas, and randomly distributed obstacles.

Protecting occupant in autonomous vehicle accident with rotating seat and belt airbag

In autonomous vehicle, since that occupants no long need to operate the vehicle, they will have time to relax and entertain or communicate with other people. In order to improve the collision safety of the occupants who move freely and have different seat orientation angles in autonomous vehicle, a protection strategy based on the cooperative control of the rotating seat and belt airbag to avoid occupant injuries is proposed: in the pre-crash phase, the occupant on a rotated seat is repositioned into a close-to-standard frontal facing position, while the belt airbag deploys; in the crash phase, the fully deployed belt airbag cushions and absorbs occupant impact with the support of the occupant’s legs to reduce injury. Firstly, the current prediction time for unavoidable collisions in self-driving cars is about 350 ms, therefore, the airbag can be inflated by enlarging the inflation duration to reduce its impact during deployment. Due to the fixed installation position of the dashboard airbag, which cannot accompany the deficiency of seat movement, a new type of belt airbag is designed; Then, the simulation models of ±45° and ±90° seat orientation were established to study the injury mechanism and kinematic response of occupants with different seat orientations in frontal crashes; Finally, the simulation models of active rotating seat with belt airbag were established to study the kinematic response and injury risk of occupants with rotating seat and belt airbag protection strategy. The belt airbag with a capacity of 65 L developed in this paper could effectively protect occupants in a frontal collision at an inflation time of 200 ms and a total inflation mass of 31.4 g; The occupant safety strategy based on rotating seat and belt airbag can effectively reduce the risk of collision injury of occupants with different seat orientations in autonomous vehicle.