The inclusion of autonomous vehicles into our society requires not only mature automated technologies but also adequate confidence in safety guarantees. Safety of the intended functionality (SOTIF) is an incipient important field that focuses on risk led by performance limitations rather than faults. There are still plenty of gaps in addressing it, especially when concerning perception ability. This article introduces a method to evaluate SOTIF-oriented perception effectiveness for forward obstacle detection of autonomous vehicles. Both inevitable existence uncertainty and state uncertainty in perception results are taken into account, and a formal SOTIF requirement specification is defined. Based on the safety distance model, we further deduce the minimum required perception area and the perception error requirements under a given driving situation to refine the SOTIF requirement specification. Then, a SOTIF-oriented unified sensing model is established by combining sensing space and ability characteristics. The system-level perception ability of an autonomous vehicle is subsequently deduced with the assumption that every available sensor is described in the form of our proposed sensing model. Evaluation can be executed according to the above methods that support determining the SOTIF requirements and the system-level perception ability, and the entire evaluation process is presented as an algorithm in this article. Finally, a practical case generated according to a well-known autonomous vehicle prototype is used to prove the effectiveness of the method. Evaluation results can serve as suggestions to improve the overall SOTIF level for perception.

uncrewed aerial vehicle (UAV)–enabled Internet of Things UAV-enabled Internet of Things (UIoT) is composed of multiple UAV swarms, which are vulnerable to external shocks in variable environments. Currently, the majority of research on UIoT resilience primarily emphasizes internal resource reconfiguration to maintain mission execution, while overlooking the importance of performance recovery with logistics support. This article proposes a novel UIoT resilience evaluation framework that comprehensively analyzes the performance and resilience by considering various shocks and external resource support strategies. First, a UIoT modeling based on a multimodular community structure is established, and the evolutionary behaviors of UIoT are investigated by considering their cooperative adaptation mechanisms under dynamically changing operational conditions. Second, with internal allocation and external logistics support, a multistate resilience mechanism is developed, overcoming the limitations of prioritizing internal reconfiguration strategies. Third, dynamic node connection mechanisms and resource allocation strategies are proposed to maximize resilience recovery efficiency. Finally, a collaborative detection case involving 20-UAVs-IoT is illustrated to verify the effective resilience evaluation and resource allocation. The proposed method improves the resilience and performance recovery of UIoT networks, providing support for resilience evaluation and resource allocation in variable environments.

In recent years, the model-based safety analysis (MBSA) has been developing continuously. The Functional Failure Identification and Propagation (FFIP) method is a graphics processing technology which supports the analysis of fault propagation paths before making costly design commitments. However, the traditional FFIP has some deficiencies. In this paper, we extend the functional failure logic (FFL) in the FFIP and introduce the concept of deviation. So, FFIP can be used to analyze the failure process of the systems and make the logical analysis of functional failure easier. Based on the extended FFL, we present a new overview of the FFIP. The FFIP is improved by using mathematical logic and Systems Modeling Language (SysML). The standard expression of FFL is realized, which is conducive to the subsequent modeling and modification. Additionally, we use the failure logic analysis in the FFIP to improve the state machine diagram (SMD) in SysML. Finally, the improved FFIP method is used to analyze the fault propagation paths of the system and Simulink is used for simulation. The fault tree is generated according to the simulation results, the minimum cut set is calculated, and the key failure parts of the system are obtained.

Integrated modular avionics architecture has become the most attractive idea to enhance system capability as well as improve efficiency. However, this architecture makes designing a system configuration scheme difficult because multiple resources are shared to support different functions that may have been irrelevant before. This article introduces a method to optimize the configuration scheme for an integrated modular avionics system while considering functional redundancy requirements. Not only the allocation scheme, which illustrates the relationships between functions and shared resources is taken into account, but also the resource scheme, which illustrates how many shared resources are enough to cover the functional requirements is considered as a part of the configuration scheme. Toward a generic integrated modular avionics system with functional redundancy requirements, we first give a configuration scheme model as well as its related schedulability and reliability constraints. Then, the optimization process of the configuration scheme is formalized as a combination of a constraint satisfaction problem and a constraint optimization problem. Specifically, it is decomposed into two steps including: 1) finding a resource scheme which has the lowest cost but still satisfies the constraints based on a forward checking algorithm; 2) finding its corresponding allocation scheme which distributes the targeted functions to different resources as evenly and low-coupled as possible based on the NSGA-II algorithm. Finally, an example is used to prove the effectiveness of the method. The optimization method can serve as a guide to design a configuration scheme for the integrated modular avionics system.

Based on power adding technology, the linear transformer driver (LTD) scheme is widely used to generate high-energy pulsed outputs and adopts a hierarchical and modular structure. Although robust design and fault analysis for basic components have been conducted recently, there is still a lack of enough reliability analysis studies of the whole system. Taking an actual LTD system as an object, this paper presents a system reliability model based on a load-sharing mechanism. A unified load-sharing rule structure is established and four typical rules corresponding to equal, linear, exponential, and local-equal relationships are discussed in detail while evaluating the impact of the load-sharing mechanism. Subsequently, simulation experiments are performed to illustrate the effects of different load-sharing rules as well as analyzing the system reliability in which we simultaneously propose a self-adaptive Monte Carlo simulation flow to achieve the sampling probability adjustment according to the random failure sequence. The simulation results can serve as a suggestion for further improvement of the system reliability. Moreover, the model framework and the simulation analysis method described here are universal and can be applied to evaluate the reliability of other LTD-based systems with tiny modifications.