Safety-critical Information Research Articles

Sailing Too Close to the Wind? How Harnessing Patient Voice Can Identify Drift towards Boundaries of Acceptable Performance.

This opinion paper investigates how healthcare organizations identify and act upon different types of risk signals. These signals may generally be acknowledged, but we also often see with hindsight that they might not be because they have become a part of normal practice. Here, we detail how risk signals from patients and families should be acknowledged as system-level safety critical information and as a way of understanding and changing safety culture in healthcare. We discuss how healthcare organizations could work more proactively with patient experience data in identifying risks and improving system safety.

Context-aware resource allocation for vehicle-to-vehicle communications in cellular-V2X networks

Cellular Vehicle-to-Everything (C-V2X) networks provide critical support for intelligently connected vehicles (ICVs) and intelligent transport systems (ITS). C-V2X utilizes vehicle-to-vehicle (V2V) communication technology to exchange safety–critical information among neighbors. V2V communication has stringent high-reliability and low-latency requirements. The existing solutions on resource allocation for V2V communications mainly rely on channel states to optimize resource utilization but fail to consider vehicle safety requirements, which cannot satisfy safety application performance. In this paper, we focus on application-driven channel resource allocation strategy for V2V communications. First, we propose an inter-packet reception model to represent the delay between two consecutive and successful reception packets at a receiver. We then design an application-specific utility function where the utility depends on the packet reception performance and vehicle safety context. Finally, we formulate the channel resource allocation problem as a non-cooperative game model. The game model can guide each node to cooperate and achieve the trade-off between fairness and efficiency in channel resource allocation. The simulation results show that our work can significantly improve the reliability of V2V communications and guarantee the vehicle safety application performance.

Assessment of Pedestrian-to-Vehicle Communication Pre-Crash Safety Warnings to Avoid Collisions

In recent years, road safety is getting more attention to reduce road pedestrian accidents caused by vehicles. The research community is trying to find new techniques related to accident avoidance in the existing vehicle driver assistance systems. These techniques involve the exchange of safety critical information between pedestrians and vehicles. This is called vehicle-to-pedestrian (V2P) communication system, which provides road safety and management to different Vulnerable-Road-Users (VRUs). Furthermore, V2P communication systems use various technologies and different methods to cooperate with the VRUs. These attributes can be considered to design constraints for V2P communication system. In this paper, the authors examine V2P safety aspects and have simulated different V2P scenarios considering real environments. Moreover, the authors analyze the V2P safety in different scenarios by considering the timely exchange of safety messages. The authors presented these results in different V2P approaches for separate VRU groups in different pre-crash situations.

Neural-Network-Based Dynamic Flight Envelop Protection Within Integrated Aircraft Control System

A sparse recurrent fuzzy neural network (SRFNN)-based dynamic flight envelope protection (FEP) method is proposed and integrated into an aircraft control system against possible failures. As a baseline of the aircraft control system, a fault-tolerant flight controller is used to compensate the uncertainties caused by failures, such as damaged wing. As an augmentation, the SRFNN-based dynamic FEP is employed to prevent damaged aircraft from breaking through the safe flight envelope bounds, which are updated adaptively with the help of the safety-critical information obtained by the SRFNN. Additionally, the performance of the fault-tolerant flight controller can be improved after the proposed dynamic FEP is integrated into the aircraft control system. The integrated aircraft control system not only can improve the performance of aircraft with some failures but also can prevent the damaged aircraft from getting out of control. Simulations are conducted to test and verify the effectiveness of the fault-tolerant flight controller and the SRFNN-based dynamic FEP. Simulation results show the efficacy of the proposed integrated aircraft control system.

Safety Embedded Differential Dynamic Programming Using Discrete Barrier States

Certified safe control is a growing challenge in robotics, especially when performance and safety objectives must be concurrently achieved. In this work, we extend the barrier state (BaS) concept, recently proposed for safe stabilization of continuous time systems, to safety embedded trajectory optimization for discrete time systems using discrete barrier states (DBaS). The constructed DBaS is embedded into the discrete model of the safety-critical system integrating safety objectives into the system's dynamics and performance objectives. Thereby, the control policy is directly supplied by safety-critical information through the barrier state. This allows us to employ the DBaS with differential dynamic programming (DDP) to plan and execute safe optimal trajectories. The proposed algorithm is leveraged on various safety-critical control and planning problems including a differential wheeled robot safe navigation in randomized and complex environments and on a quadrotor to safely perform reaching and tracking tasks. The DBaS-based DDP (DBaS-DDP) is shown to consistently outperform penalty methods commonly used to approximate constrained DDP problems as well as CBF-based safety filters.

People Talk in Stories. Responders Talk in Data: A Framework for Temporal Sensemaking in Time- and Safety-critical Work

Global crowdsourcing teams who conduct humanitarian response use temporal narratives as a sensemaking device when time is a critical element of the data story. In dynamic situations in which the flow of online information is rapid, fluid, and disordered, the process of how distributed teams construct a temporal narrative is not well understood nor well supported by information and communication technologies (ICTs). Here, we examine an intense need for temporal sensemaking: time- and safety-critical information work during the 2017 Hurricane Maria crisis response in Puerto Rico. Our analysis of semi-structured interviews reveals how members of a global digital humanitarian group, The Standby Task Force (SBTF), use a process of triage, evaluation, negotiation, and synchronization to construct collective temporal narratives in their high-tempo, distributed information work. Informed by these empirical insights, we reflect on the design implications for cloud-based, collaborative ICTs used in time- and safety-critical remote work.

Enhancing Dependability Analysis Provisioning in CBTC Wireless Communication System With Age of Information

As a crucial part of the communication-based train control (CBTC) system, the wireless communication subsystem is responsible for transmitting safety-critical information, which directly affects the safe and efficient operation of the urban rail transit. The dependability analysis method for wireless communication in CBTC is critical and necessary to ensure the stable transmission of safety-critical information. However, most of the existing researches in CBTC lack a unified evaluation index to analyze the wireless communication dependability. In this paper, the dependability of wireless communication system in CBTC is established. To be specific, timeliness, integrity, security, and safety are used to describe the dependability of CBTC wireless communication system in our definition. The age of information (AoI) is used to quantitatively analyze the dependability in the CBTC wireless communication system. To verify the effectiveness of the proposed dependability analysis method, we quantitatively introduce the dependability of wireless communication system in CBTC with different scenarios, including packet-drop, re-transmission, handoff, and cyber-attack. Simulation results show that the designed dependability analysis method with quantized AoI can efficiently describe the dependability of CBTC wireless communication system in different scenarios.

Research and Evaluation on Safety Critical Information of Road Tanker for Dangerous Liquid Goods Based on Multi-source Data

Due to the flammable and explosive characteristics of dangerous goods and the complex road transportation environment, there are many safety risks in the road transportation of dangerous goods. Road tanker for dangerous liquid goods(Hereinafter referred to as "vehicles" unless otherwise specified) is one of the typical vehicles for road transportation of dangerous goods. In order to improve the intrinsic safety level of vehicles, this paper analyzes the basic data information of liquid dangerous goods tank vehicles on several existing related system platforms. According to the cause mechanism of the accident, combined with the analysis of vehicle accidents, eight influencing factors of vehicle accidents focusing on the intrinsic safety of vehicles are proposed, and the critical information of vehicle safety is constructed.Taking these critical safety information as evaluation indexes, a vehicle safety risk evaluation model is established based on the Extension matter-element model. Finally, it is applied in practice.

A Patent Application for NEXTGEN Flood Early Warning System

This design fiction re-imagines an important informational element of the flood early warning system in order to unpack some of the questionable assumptions that society makes about disaster. In presenting an updated, ironic, vision of an alternative system, we highlight some of the ways that received ideas about the root causes of disaster, who is responsible for public safety, and the role of private sector innovation, are so embedded in the design of technologies used in crisis management that they have become taken for granted. This work demonstrates the potential for design fiction to serve as a tool in the evaluation and critique of safety-critical information systems and as a communication tool for conveying the complex findings of disaster research. It also points to new avenues of exploration for crisis informatics work on public warning systems.

Hello? Is There Anybody in There?

As social media has become more present in people's day-to-day lives, many turn to these platforms in natural disasters to keep abreast of the ever-evolving crisis situation. Facing the increasing amount of crisis-related information available on the social media platforms, users tend to focus on and reach out to authoritative sources---individuals or organizations that provide authoritative and credible crisis-related information due to their official status or position. As they provide high-quality information, response from the authoritative sources can be especially valuable to social media users directly affected in natural disasters. In this study, we aim to extend the reach of credible information during crisis, and direct the attention of authoritative users to the affected users who need their help. Specifically, we investigate what factors differentiate the tweets by regular users that receive responses from authoritative accounts from those that do not. We find that regular users' popularity and official accounts' level of busyness do not seem to affect the likelihood of tweets receiving a response. We thus explore the linguistic features of the tweets' content. Topic modeling and sentiment analysis results suggest that these linguistic aspects of the tweets may affect the response rate from authoritative sources. Our findings suggest crisis-related policy implications, as well as design implications for social media platforms where such exchanges take place, which can potentially increase the reach of credible information in a crisis and help those affected obtain the safety-critical information they need.

Multimodal Displays to Reduce Distraction In Locomotive Engineers

Multi-modal displays that allow the locomotive engineer to delay safety-critical dispatches in high workload scenarios offer the promise of reducing the cognitive distraction that occurs when the locomotive engineer must listen to a dispatcher’s communication. In an effort to determine whether locomotive engineers could delay safety-critical information from the dispatcher in high workload scenarios, we developed and evaluated such a multi-modal display system. It was hypothesized that locomotive engineers, when provided with the ability to postpone the delivery of information from the dispatcher, would perform better than locomotive engineers who were not provided that capability. Contrary to the above hypothesis, an analysis of the eye tracking measures indicated that the engineers performed more poorly in the multi-modal display system condition, indicating that the system as designed did not allow the engineer to safely delay dispatch messages. We conclude that aspects of the new system that seemed to increase distraction should be redesigned to modify how and when the engineer uses the system to access information and allow for a safe delay of safety-critical information.

Capacity and Delay Scaling for Broadcast Transmission in Highly Mobile Wireless Networks

Futuristic communication network formed by autonomously operated, unmanned aerial vehicles, has piqued researchers interests in highly mobile wireless networks. Exchanging safety critical information, with low latency and high throughput, in such systems is of paramount importance. We study the broadcast capacity and minimum delay scaling laws for such highly mobile wireless networks, in which each node has to disseminate packets to all other nodes in the network. In particular, we consider a cell partitioned network under an IID mobility model, in which each node chooses a new position at random, every time slot. We derive scaling laws for broadcast capacity and minimum delay as a function of the network size. We propose a simple first-come-first-serve flooding scheme, which nearly achieve both capacity and minimum delay scaling. Thus, in contrast to what has been speculated in the literature, we show that there is nearly no tradeoff between capacity and delay. Our results also show that high mobility does not improve broadcast capacity. Our analysis makes use of the theory of Markov Evolving Graphs (MEGs), and develops two new bounds on flooding time in MEGs by relaxing the previously required expander property assumption. Simulation results verify our analysis, and throw up interesting open problems.

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Who is allowed to read and write?

A Review and Development Methodology of a LightWeight Security Model for IoT-based Smart Devices

Internet of Things (IoT) turns into another time of the Internet, which contains connected smart objects over the Internet. IoT has numerous applications, for example, smart city, smart home, smart grid and healthcare. In common, the IoT system comprises of heterogeneous devices that deliver then trade endless sums of safety-critical information, also as privacy-sensitive information. Nevertheless, connected devices can give your business a genuine lift, yet anything that is connected to the Internet can be vulnerable to cyberattacks. Most present IoT arrangements rely upon centralized architecture by associating with cloud servers through the Internet. The public cloud is described as computing services publicized by third-party suppliers over the Internet, making them accessible to anybody who needs to use or buy them. This solution gives magnificent flexible calculation and information the executives capacities, as IoT systems are developing increasingly mind-boggling; nonetheless, despite everything, it faces different of security issues. One of the weaknesses is that your information moving in IoT devices by means of public cloud could be in danger, despite the fact that the hacker was not explicitly focusing on you and with the public cloud you have insignificant authority over how rapidly you can grow the cloud. In this case, a secured protocol in IoT is vital to ensure optimum security to the information being traded between connected devices. To overcome the limitation, in this paper, we conduct a comprehensive review on existing security protocols and propose a development methodology of a blockchain-based lightweight security model that provides end to end security. By utilizing lightweight, an authenticated client can get to the information of IoT sensors remotely. The presentation investigation shows that lightweight offers better security, less overheads, and low communication.

Deep Deterministic Policy Gradient (DDPG)-Based Resource Allocation Scheme for NOMA Vehicular Communications

This paper investigates the resource allocation problem in vehicular communications based on multi-agent Deep Deterministic Policy Gradient (DDPG), in which each Vehicle-to-Vehicle (V2V) communication acts as agent and adopts Non-Orthogonal Multiple Access (NOMA) technology to share the frequency spectrum that pre-allocated to Vehicle-to-Infrastructure (V2I) communications. Different with conventional D2D communications, the fast varying channel condition due to the high mobility in vehicular environment causes the difficulty of collecting instantaneous Channel State Information (CSI) at base station. Meanwhile, one tremendous challenge faced by vehicular communications is how to maximize the sum-rate of V2I communications simultaneously guaranteeing the latency and reliability requirements for the transmission of safety-critical information in V2V communications. In response, we formulate the resource allocation problem as a decentralized Discrete-time and Finite-state Markov Decision Process (DFMDP), in which allocation decisions are made by multiple agents that do not have complete and global network information. Due to the complexity of the problem, we propose a DDPG algorithm which is capable of handling continuous high dimensional action spaces to find the optimal allocation strategy. Numerical results verify that each agent can effectively learn from the environment by means of the proposed DDPG algorithm to maximize the sum-rate of V2I communications while satisfying the stringent latency and reliability constraints of V2V communications.

MARC: A Novel Framework for Detecting MITM Attacks in eHealthcare BLE Systems.

Real-time and ubiquitous patient monitoring demands the use of wireless data acquisition through resource constrained medical sensors, mostly configured with No-input No-output (NiNo) capabilities. Bluetooth is one of the most popular and widely adopted means of communicating this sensed information to a mobile terminal. However, over simplified implementations of Bluetooth low energy (BLE) protocol in eHealth sector is susceptible to several wireless attacks, in particular the Man-in-the-Middle (MITM) attack. The issue arises due to a lack of mutual authentication and integrity protection between the communicating devices, which may lead to compromise of confidentiality, availability and even the integrity of this safety-critical information. This research paper presents a novel framework named MARC to detect, analyze, and mitigate Bluetooth security flaws while focusing upon MITM attack against NiNo devices. For this purpose, a comprehensive solution has been proposed, which can detect MITM signatures based upon four novel anomaly detection metrics: analyzing Malicious scan requests, Advertisement intervals, RSSI levels, and Cloned node addresses. The proposed solution has been evaluated through practical implementation and demonstration of different attack scenarios, which show promising results concerning accurate and efficient detection of MITM attacks.

Resource Allocation for High-Reliability Low-Latency Vehicular Communications With Packet Retransmission

In vehicular communications, safety-critical information exchange has stringent reliability and latency requirements. However, lack of accurate instantaneous channel state information due to high mobility poses a great challenge to meet these requirements and the situation gets more complicated when packet retransmission is considered. Based on only large-scale fading channel information, we perform spectrum and power allocation to maximize the sum ergodic capacity of vehicular-to-infrastructure (V2I) links, while guaranteeing reliability and latency requirements of vehicular-to-vehicular (V2V) links. First, for each possible V2I–V2V spectrum reusing pair, we analyze the queueing system for the V2V link and derive the packet loss probability and average packet sojourn time under fixed power allocation. Then, an optimal power allocation is derived for each possible pair. Afterwards, we optimize the spectrum reusing pattern by addressing a polynomial time solvable bipartite matching problem. Simulation results confirm the accuracy of the proposed queueing analysis. Moreover, the proposed resource allocation strategy can improve the ergodic capacity of the V2I links under the precondition of guaranteeing the V2V links’ requirements on reliability and latency.

Resource Allocation for Low-Latency Vehicular Communications: An Effective Capacity Perspective

Vehicular communications face a tremendous challenge in guaranteeing low latency for safety-critical information exchange due to fast varying channels caused by high mobility. Focusing on the tail behavior of random latency experienced by packets, latency violation probability (LVP) deserves particular attention. Based on only large-scale channel information, this paper performs spectrum and power allocation to maximize the sum ergodic capacity of vehicle-to-infrastructure (V2I) links while guaranteeing the LVP for vehicle-to-vehicle (V2V) links. Using the effective capacity theory, we explicitly express the latency constraint with introduced latency exponents. Then, the resource allocation problem is decomposed into a pure power allocation subproblem and a pure spectrum allocation subproblem, both of which can be solved with global optimum in polynomial time. Simulation results show that the effective capacity model can accurately characterize the LVP. In addition, the effectiveness of the proposed algorithm is demonstrated from the perspectives of the capacity of the V2I links and the latency of the V2V links.

LANGUAGE BARRIERS COMPLEXITY AND THEIR IMPLICATIONS WITH FATAL CONSEQUENCES IN AVIATION

This paper deals with language barriers and their direct interference in aviation accidents with fatality. The paper first gives the definition of language barriers in general, elaborating the reasons why they emerge, their intricacy and attainable solutions for minimizing them. Language cannot be isolated from culture and cultural competencies apply in principle to mutual understanding and minimize impedance and any misunderstanding. Language barriers cause many problems and nature of any communication is subject to misinterpretation and misunderstanding. The criticism given to this topic indicates that language barriers can sometimes cause misunderstandings that lead to conflict, frustration, offense and hurt feelings. Besides that, if people do not share the same language, misunderstanding might arise from language barrier complexity and people sometimes face serious consequences. Lack of communication and higher level of misunderstanding as a result of language barriers might lead to fatal consequences. Language barriers may appear even in monolingual areas as the result of complex terminology for specific scientific areas - phraseology. Miscommunication is viewed as one of the most frequent forms of error, whether made by one person or more, the repercussions can be catastrophic. Planes are the safest means of transportation, however, when a plane accident happens, fatal consequences are inevitable. Miscommunication between pilots and air traffic controllers produced by language barriers is considered as the major reason for many aviation accidents. The globalization of aviation is leading to a multicultural, multinational mix of crews. When different cultures and nationalities are obliged to work together, various miscommunications can arise. With differing ethnic and national backgrounds, pilots’ communicative styles also differ. Language barriers between pilots and air traffic controllers lead to deaths, experts say. English for the purpose of aviation was adopted as the international language of pilots and air traffic controllers in 2011, language barriers still cause many problems, impede any progress or halt it. Lack of effective communication between the members of the flight crew restricts the flow of safety-critical information, information which could prevent the occurrence of an aviation accident or incident. The paper also clarifies judgment and demeanor of several experts who have done some research covering the topic of aviation accidents and their possible solutions for minimizing language barriers that, despite modern technology, still play a significant role in fatality.

Software-Defined Heterogeneous Vehicular Networking: The Architectural Design and Open Challenges

The promising advancements in the telecommunications and automotive sectors over the years have empowered drivers with highly innovative communication and sensing capabilities, in turn paving the way for the next-generation connected and autonomous vehicles. Today, vehicles communicate wirelessly with other vehicles and vulnerable pedestrians in their immediate vicinity to share timely safety-critical information primarily for collision mitigation. Furthermore, vehicles connect with the traffic management entities via their supporting network infrastructure to become more aware of any potential hazards on the roads and for guidance pertinent to their current and anticipated speeds and travelling course to ensure more efficient traffic flows. Therefore, a secure and low-latency communication is highly indispensable in order to meet the stringent performance requirements of such safety-critical vehicular applications. However, the heterogeneity of diverse radio access technologies and inflexibility in their deployment results in network fragmentation and inefficient resource utilization, and these, therefore, act as bottlenecks in realizing the aims for a highly efficient vehicular networking architecture. In order to overcome such sorts of bottlenecks, this article brings forth the current state-of-the-art in the context of intelligent transportation systems (ITS) and subsequently proposes a software-defined heterogeneous vehicular networking (SDHVNet) architecture for ensuring a highly agile networking infrastructure to ensure rapid network innovation on-demand. Finally, a number of potential architectural challenges and their probable solutions are discussed.