Risk identification and assessment of human-machine conflict

The process industries are fully embracing digitalization and artificial intelligence (AI). Industry 4.0 has also transformed the production structures in the process industries to increase productivity and profitability; however, this has also led to emerging risks. The rapid growth and transformation have created gaps and challenges in various aspects, for example, information technology (IT) vs. operation technology (OT), human vs. AI, and traditional statistical analysis vs. machine learning. A notable issue is the apparent differences in decision-making between humans and machines, primarily when they work together. Contradictory observations, states, goals, and actions may lead to conflict between these two decision-makers. Such conflicts have triggered numerous catastrophes in recent years. Moreover, conflicts may become even more elusive and confusing under external forces, e.g., cyberattacks. Therefore, this thesis focuses on human-machine conflict. Five research tasks are conducted to explore the risk of human-machine conflict. More specifically, the thesis presents a systematic literature review on the impact of digitalization on process safety, highlights the myths and misconceptions of data modeling on process safety analysis, and attempts to clarify associated concepts in the area of human-machine conflict. In addition, the thesis summarizes the causes of conflicts and generalizes the mathematical expressions of the causes. It illustrates the evolutional process of conflicts, proposes the measurement of conflicts, develops the risk assessment model of conflicts, and explores the condition of conflict convergence, divergence, and resolution. The thesis also iii demonstrates the proposed methodology and risk models in process systems, for example, the two-phase separator and the Continuous Stirred Tank Reactor (CSTR). It verifies the conflict between manual and automated control (e.g., proportional-integral-derivative control (PID) and model predictive control (MPC)). This thesis proves that conflict is another more profound and implicit phenomenon that raises risks more rapidly and severely. Conflicts are highly associated with faults and failures. Various factors can trigger human-machine conflict, including sensor faults, cyberattacks, human errors, and sabotage. This thesis attempts to provide the readers with a clear picture of the human-machine conflict, alerts the industry and academia about the risk of human-machine conflict, and emphasizes human-centered design

Image processing techniques for the perception of automotive environments with applications to pedestrian detection

The experience of the ARGO Project: it started in 1996 at the University of Parma, Italy, based on the previous experience within the European PROMETHEUS Project. In 1997 the ARGO prototype vehicle was set up with sensors and actuators, and the first version of the GOLD software system – able to locate one lane marking and generic obstacles on the vehicle’s path – was installed. In June 1998 the vehicle underwent a major test (the MilleMiglia in Automatico, a 2000 km tour on Italian highways) in order to test the complete equipment

Automatic Image Annotation using Image Clustering in Multi – Agent Society

The rapid growth of the internet provides tremendous resource for information in different domains (text, image, voice, and many others). This growth introduces new challenge to hit an exact match due to huge number of document returned by search engines where millions of items can be returned for certain subject. Images have been important resources for information, and billions of images are searched to fulfill user demands, which face the mentioned challenge. Automatic image annotation is a promising methodology for image retrieval. However most current annotation models are not yet sophisticated enough to produce high quality annotations. This thesis presents online intelligent indexing for image repositories based on their contents, although content based indexing and retrieving systems have been introduced, this thesis is adding an intelligent technique to re-index images upon better understanding for its composed concepts. Collaborative Agent scheme has been developed to promote objects of an image to concepts and re-index it according to domain specifications. Also this thesis presents automatic annotation system based on the interaction between intelligent agents. Agent interaction is synonym to socialization behavior dominating Agent society. The presented system is exploiting knowledge evolution revenue due to the socialization to charge up the annotation process

Enhancing user experience and safety in the context of automated driving through uncertainty communication

Operators of highly automated driving systems may exhibit behaviour characteristic of overtrust issues due to an insufficient awareness of automation fallibility. Consequently, situation awareness in critical situations is reduced and safe driving performance following emergency takeovers is impeded. Previous research has indicated that conveying system uncertainties may alleviate these issues. However, existing approaches require drivers to attend the uncertainty information with focal attention, likely resulting in missed changes when engaged in non-driving-related tasks. This research project expands on existing work regarding uncertainty communication in the context of automated driving. Specifically, it aims to investigate the implications of conveying uncertainties under consideration of non-driving-related tasks and, based on the outcomes, develop and evaluate an uncertainty display that enhances both user experience and driving safety. In a first step, the impact of visually conveying uncertainties was investigated under consideration of workload, trust, monitoring behaviour, non-driving-related tasks, takeover performance, and situation awareness. For this, an anthropomorphic visual uncertainty display located in the instrument cluster was developed. While the hypothesised benefits for trust calibration and situation awareness were confirmed, the results indicate that visually conveying uncertainties leads to an increased perceived effort due to a higher frequency of monitoring glances. Building on these findings, peripheral awareness displays were explored as a means for conveying uncertainties without the need for focused attention to reduce monitoring glances. As a prerequisite for developing such a display, a systematic literature review was conducted to identify evaluation methods and criteria, which were then coerced into a comprehensive framework. Grounded in this framework, a peripheral awareness display for uncertainty communication was developed and subsequently compared with the initially proposed visual anthropomorphic uncertainty display in a driving simulator study. Eye tracking and subjective workload data indicate that the peripheral awareness display reduces the monitoring effort relative to the visual display, while driving performance and trust data highlight that the benefits of uncertainty communication are maintained. Further, this research project addresses the implications of increasing the functional detail of uncertainty information. Results of a driving simulator study indicate that particularly workload should be considered when increasing the functional detail of uncertainty information. Expanding upon this approach, an augmented reality display concept was developed and a set of visual variables was explored in a forced choice sorting task to assess their ordinal characteristics. Particularly changes in colour hue and animation-based variables received high preference ratings and were ordered consistently from low to high uncertainty. This research project has contributed a series of novel insights and ideas to the field of human factors in automated driving. It confirmed that conveying uncertainties improves trust calibration and situation awareness, but highlighted that using a visual display lessens the positive effects. Addressing this shortcoming, a peripheral awareness display was designed applying a dedicated evaluation framework. Compared with the previously employed visual display, it decreased monitoring glances and, consequentially, perceived effort. Further, an augmented reality-based uncertainty display concept was developed to minimise the workload increments associated with increases in the functional detail of uncertainty information.</div

Sense and Respond

Over the past century, the manufacturing industry has undergone a number of paradigm shifts: from the Ford assembly line (1900s) and its focus on efficiency to the Toyota production system (1960s) and its focus on effectiveness and JIDOKA; from flexible manufacturing (1980s) to reconfigurable manufacturing (1990s) (both following the trend of mass customization); and from agent-based manufacturing (2000s) to cloud manufacturing (2010s) (both deploying the value stream complexity into the material and information flow, respectively). The next natural evolutionary step is to provide value by creating industrial cyber-physical assets with human-like intelligence. This will only be possible by further integrating strategic smart sensor technology into the manufacturing cyber-physical value creating processes in which industrial equipment is monitored and controlled for analyzing compression, temperature, moisture, vibrations, and performance. For instance, in the new wave of the ‘Industrial Internet of Things’ (IIoT), smart sensors will enable the development of new applications by interconnecting software, machines, and humans throughout the manufacturing process, thus enabling suppliers and manufacturers to rapidly respond to changing standards. This reprint of “Sense and Respond” aims to cover recent developments in the field of industrial applications, especially smart sensor technologies that increase the productivity, quality, reliability, and safety of industrial cyber-physical value-creating processes

STABLE ADAPTIVE STRATEGY of HOMO SAPIENS and EVOLUTIONARY RISK of HIGH TECH. Transdisciplinary essay

The co-evolutionary concept of Three-modal stable evolutionary strategy of Homo sapiens is developed. The concept based on the principle of evolutionary complementarity of anthropogenesis: value of evolutionary risk and evolutionary path of human evolution are defined by descriptive (evolutionary efficiency) and creative-teleological (evolutionary correctly) parameters simultaneously, that cannot be instrumental reduced to others ones. Resulting volume of both parameters define the trends of biological, social, cultural and techno-rationalistic human evolution by two gear mechanism ˗ gene-cultural co-evolution and techno- humanitarian balance. The resultant each of them can estimated by the ratio of socio-psychological predispositions of humanization/dehumanization in mentality. Explanatory model and methodology of evaluation of creatively teleological evolutionary risk component of NBIC technological complex is proposed. Integral part of the model is evolutionary semantics (time-varying semantic code, the compliance of the biological, socio-cultural and techno-rationalist adaptive modules of human stable evolutionary strategy)