Building a Formal Model of a Human-Interactive System: Insights into the Integration of Formal Methods and Human Factors Engineering

Both the human factors engineering (HFE) and formal methods communities are concerned with finding and eliminating problems with safety-critical systems. This work discusses a modeling effort that leveraged methods from both fields to use model checking with HFE practices to perform formal verification of a human-interactive system. Despite the use of a seemingly simple target system, a patient controlled analgesia pump, the initial model proved to be difficult for the model checker to verify in a reasonable amount of time. This resulted in a number of model revisions that affected the HFE architectural, representativeness, and understandability goals of the effort. If formal methods are to meet the needs of the HFE community, additional modeling tools and technological developments are necessary

Evaluating humanhuman communication protocols with miscommunication generation and model checking

Abstract. Human-human communication is critical to safe operations in domains such as air transportation where airlines develop and train pilots on communication procedures with the goal to ensure that they check that verbal air traffic clearances are correctly heard and executed. Such communication protocols should be designed to be robust to miscommunication. However, they can fail in ways unanticipated by designers. In this work, we present a method for modeling human-human communication protocols using the Enhanced Operator Function Model with Communications (EOFMC), a task analytic modeling formalism that can be interpreted by a model checker. We describe how miscommunications can be generated from instantiated EOFMC models of human-human communication protocols. Using an air transportation example, we show how model checking can be used to evaluate if a given protocol will ensure successful communication. Avenues of future research are explored

Formal Modeling and Analysis for Interactive Hybrid Systems

An effective strategy for discovering certain kinds of automation surprise and other problems in interactive systems is to build models of the participating (automated and human) agents and then explore all reachable states of the composed system looking for divergences between mental states and those of the automation. Various kinds of model checking provide ways to automate this approach when the agents can be modeled as discrete automata. But when some of the agents are continuous dynamical systems (e.g., airplanes), the composed model is a hybrid (i.e., mixed continuous and discrete) system and these are notoriously hard to analyze. We describe an approach for very abstract modeling of hybrid systems using relational approximations and their automated analysis using infinite bounded model checking supported by an SMT solver. When counterexamples are found, we describe how additional constraints can be supplied to direct counterexamples toward plausible scenarios that can be confirmed in high-fidelity simulation. The approach is illustrated though application to a known (and now corrected) human-automation interaction problem in Airbus aircraft

Using Relative Position and Temporal Judgments to Assess the Effects of Texture and Field of View on Spatial Awareness for Synthetic Vision Systems Displays

Synthetic Vision Systems (SVS) depict computer generated views of terrain surrounding an aircraft. In the assessment of textures and field of view (FOV) for SVS, no studies have directly measured the 3 levels of spatial awareness: identification of terrain, its relative spatial location, and its relative temporal location. This work introduced spatial awareness measures and used them to evaluate texture and FOV in SVS displays. Eighteen pilots made 4 judgments (relative angle, distance, height, and abeam time) regarding the location of terrain points displayed in 112 5-second, non-interactive simulations of a SVS heads down display. Texture produced significant main effects and trends for the magnitude of error in the relative distance, angle, and abeam time judgments. FOV was significant for the directional magnitude of error in the relative distance, angle, and height judgments. Pilots also provided subjective terrain awareness ratings that were compared with the judgment based measures. The study found that elevation fishnet, photo fishnet, and photo elevation fishnet textures best supported spatial awareness for both the judgments and the subjective awareness measures

A Minimax Network Flow Model for Characterizing the Impact of Slot Restrictions

This paper proposes a model for evaluating long-term measures to reduce congestion at airports in the National Airspace System (NAS). This model is constructed with the goal of assessing the global impacts of congestion management strategies, specifically slot restrictions. We develop the Minimax Node Throughput Problem (MINNTHRU), a multicommodity network flow model that provides insight into air traffic patterns when one minimizes the worst-case operation across all airports in a given network. MINNTHRU is thus formulated as a model where congestion arises from network topology. It reflects not market-driven airline objectives, but those of a regulatory authority seeking a distribution of air traffic beneficial to all airports, in response to congestion management measures. After discussing an algorithm for solving MINNTHRU for moderate-sized (30 nodes) and larger networks, we use this model to study the impacts of slot restrictions on the operation of an entire hub-spoke airport network. For both a small example network and a medium-sized network based on 30 airports in the NAS, we use MINNTHRU to demonstrate that increasing the severity of slot restrictions increases the traffic around unconstrained hub airports as well as the worst-case level of operation over all airports

Attitudes and Biases of Health Professionals Toward Individuals with Disabilities: An Evidence-Based Practice Project

This Evidence-Based Practice (EBP) project considered the following question: What are the attitudes and biases of health professionals toward individuals with disabilities and what are the implications for training

Unlocking Women's Leadership Potential: A Curricular Example for Developing Female Leaders in Academia

Women in academia face unique challenges when it comes to advancing to professorship. Using latest research about gender and academic leadership, we present a training curriculum that is sensitive to the unique demands of women in and aspiring to leadership positions in academia. The context-specific and evidence-based approach and a focus on self-directed leadership development are unique characteristics of the training. It aims to enhance women's motivation to lead, increase their knowledge about academic leadership, and empower them to seek the support they need to proactively work toward appointment to a professorship. We also delineate an evaluation framework, which addresses these targeted outcomes. The findings from a pilot program in Germany confirmed that the curriculum is effective in developing women as academic leaders. The discussion highlights the significance of a context-specific and evidence-based approach to women's leadership development in academia