Browse Topic: Safety testing and procedures
Rigorous validation of SAE Levels 3 and 4 autonomous systems increasingly relies on simulation. However, the simulation-reality gap remains a challenge for human-in-the-loop assessments. This study empirically quantifies the behavioral fidelity of the Car-Learning-to-Act (CARLA) simulator by recreating specific real-world traffic scenarios using the high-precision exiD drone dataset. Twenty-five participants performed a series of maneuvers, including lane changes and time-critical cut-ins. Their performance was analyzed using Dynamic Time Warping (DTW), driver profiling, and Time-to-Collision (TTC) metrics. The findings reveal a clear distinction between relative and absolute behavioral validity. In strategic decision-making tasks, the simulation demonstrated remarkably high temporal fidelity. DTW analysis explained 94% of the trajectory variance. Participants initiated lane changes with an average lag of -9 frames (0.36 s) compared to naturalistic references. These results indicate
Noise phenomena in automobiles caused by the stick-slip effect are increasingly among the most frequent reasons for customer complaints and therefore represent a critical vehicle quality attribute. To proactively address such issues, stick-slip testing of contacting material pairs is commonly applied during development. However, the predictive capability of current stick-slip test methods remains limited, particularly when highly flexible materials and realistic, stochastic excitation conditions are involved. The flexibility of sealing systems often allows the actual relative motion at the contact interface to be accommodated through adhesion and elastic deformation, thereby delaying or even preventing sliding. To date, this effect has not been represented by any characteristic parameter in conventional stick-slip testing. Instead, existing evaluations focus exclusively on the analysis of occurring stick-slip oscillations. For the initiation of stick-slip phenomena, however, not only
The intent of this standard is to establish a framework to assure that all evaporators conforming to its requirements demonstrate an acceptable health and safety environment for vehicle occupants as determined from the completed risk assessment. R-744 and low pressure (i.e., non-transcritical refrigerants with a critical temperature between 85 and 120 °C) mobile air conditioning (MAC) refrigerant evaporators shall meet the testing and labeling requirements of this standard. SAE J639 contains a list of all refrigerants considered acceptable for use in mobile thermal systems for which this standard applies when the refrigerant is used in a direct expansion architecture. SAE J639 also requires an assessment to be performed to minimize reasonable risks in MAC systems. The evaporator (as designed and manufactured) shall be part of that risk assessment, and it is the responsibility of the vehicle manufacturer to ensure all relevant aspects of the evaporator are included. It is the
1Systems level and integration testing are an integral part of the design and development of Automated Vehicles (AVs). Measurement science plays a pivotal role in testing to ensure the safe and efficient operation of AVs. This science establishes a common understanding of the units of measurement, crucial in linking human activities. This article describes the significance of measurement in studying interactions between key system technologies in AVs, including AI for perception, sensing, communications, and cybersecurity. To address the complexities of these interactions, a novel, adaptable, and interactive framework called the System Technology Interaction Model (STIM) is introduced. STIM considers both designed and emergent interactions between these system technologies, allowing AV developers to explore tailored experiments with the flexibility of filtering for focused testing. The framework currently models system interactions statically, not in real-time, to define potential
This SAE Aerospace Recommended Practice (ARP) establishes the overall component and system function guidelines and minimum performance levels for a TPMS. These guidelines include, but are not limited to: Design recommendations for system components, which: Monitor tire inflation Are located in/on the tire/wheel assembly, landing gear axle, and/or aircraft avionics compartment Recommended performance and safety guidelines for a TPMS.
This study presents a data-driven approach for strengthening aviation safety by integrating human factors assessment with modern predictive modeling techniques. The work focuses on understanding how human performance, operational conditions, and system-level interactions collectively influence safety risk, and how these interactions can be quantified to support improved design and decision-making. Unlike previous studies that address human factors or predictive modeling in isolation, this research offers a unified framework that links causal human factors indicators with statistical modeling, feature extraction, and machine learning based risk estimation. The novelty of this work lies in the structured pipeline that transforms raw categorical and narrative human factors information into measurable predictors that can be analyzed using structural modeling and machine learning. The methodology includes data preparation, dimensionality reduction, latent pattern discovery, dependence
The aerospace industry is undergoing a significant digital transformation in the way system requirements are defined, communicated, and managed. Major OEMs are moving towards fully model-based development processes, with plans to deliver requirements exclusively in the form of models. It is no longer sufficient to manage requirements using traditional document-based approaches; instead, organizations must adopt tools and processes that enable the consumption, interpretation, and implementation of model-based requirements. However, MBSE itself does not ensure that the requirements defined within the model are complete or consistent. Without rigorous validation techniques, even well-structured models can carry forward poorly defined or conflicting requirements — leading to errors that propagate throughout the development lifecycle. This work proposes an approach that integrates formal methods into MBSE workflows by enabling completeness and consistency checks of SysML-based requirements
Aircraft verification and certification entail a variety of testing tasks and require coordination among numerous stakeholders across different disciplines to ensure alignment on requirements. Historically, certification strategies have relied on both physical testing and high-fidelity simulation. The integration of these complementary approaches is essential to address their respective blind spots and to support credible certification evidence. A key challenge lies in the rigorous correlation of simulation models with physical test data. Flutter verification, for instance, is a critical component in defining the aircraft’s flight envelope and plays a foundational role in certifying safe operational boundaries. In this work, the process of freedom from flutter verification is demonstrated. This work introduces a novel approach to combining simulation and test data with the aim to accelerate and streamline the verification process leading to more efficient and cost-effective aircraft
Air Traffic Management (ATM) must be familiar with the exact Aircraft Take-off Weights (ATOWs) of airplanes to make the most use of runways, maintain safety margins high, and keep utilization and resources in balance. This paper aims to present a dependable ATOW forecasting methodology that can assist the air transport industry in enhancing operational decision-making. This research used datasets acquired from the EUROCONTROL Performance Review Commission (PRC) 2024 Aircraft Take-Off Weight Estimation dataset featuring 527,000 flights over Europe containing aircraft details, air trips and flight conditions. Technique comprises structured data input, inspection of missing data, timestamp aggregation to identify demand cycles over time, and domain-specific feature engineering using distance_per_minute, block_minutes, taxiout_ratio, and a strong wake turbulence metric The two supervised learning models used were Linear Regression (LR) for understanding and XGBoost for performance
Since 2019, sex equity in traffic crashes has been a highly debated topic in vehicle safety, especially following the 2019 study by Forman et al. (1) claiming that female occupants face a 73 percent greater risk of serious injury in frontal crashes compared to male occupants. This was soon followed by a Consumer Reports Article by Keith Barry (2), which attempted to identify underlying factors contributing to the higher risk. These have been embraced by several parties since 2019. Firstly, it was alleged that vehicle design practice over the last four decades considered safety for the male population only and ignored that of the female as evidenced by the exclusive use of the mid-sized male Anthropomorphic Test Devices (ATDs) in Regulatory and Safety Ratings tests and not with an average sized female ATD. The absence of such an ATD for testing of vehicles “set the course for four decades’ worth of car safety design, with deadly consequences” (2). Secondly, although there is a
With new energy vehicles developing rapidly, battery safety, as an important part of the impact on the range of new energy vehicles and vehicle safety, has become the focus of attention. The battery pack protection plate is a core component to protect the battery, its performance needs not only impact resistance, but also lightweight, honeycomb sandwich structure with its excellent energy absorption characteristics and weight reduction performance by the battery pack protection plate performance research. At present, the core-to-face sheet interaction in conventional sandwich structures subjected to impact loads has not been fully elucidated, and the quantitative characterization of damage is insufficient, so this paper aims to optimize the lightweight impact-resistant structure by exploring the synergistic energy dissipation mechanism between the high-strength core material and the steel plate. The study combines theory and simulation, adopting ideal rigid-plastic film theory to
This SAE Aerospace Information Report (AIR) supplements ARP4754B/ED-79B by identifying the crucial elements to be considered when constructing the development assurance plans described in Section 3 (Development Assurance Planning) of ARP4754B/ED-79B for integrated systems. Section 4.6.4 of ARP4754B/ED-79B expands the aircraft/system integration and verification activities by emphasizing testing during integration to investigate for unintended behaviors. However, guidelines are needed for planning that are specifically aimed at the aircraft level and at integrating across system functions and boundaries. Until such guidelines are more comprehensively provided, this AIR presents a collection of lessons learned from past certification programs involving integrated systems, and as such it may be considered in conjunction with Sections 3 and 4 of ARP4754B/ED-79B. ARP4761A/ED-135 elaborates the safety activities by adding processes and methods such as the Aircraft or System Functional Hazard
Letter from the Guest Editor
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