Journal articles: 'Human-automated systems'

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LEVITAN, LEE, GARY GOLEMBIEWSKI, and JOHN R. BLOOMFIELD. "Human Factors Issues for Automated Highway Systems." ITS Journal - Intelligent Transportation Systems Journal 4, no. 1-2 (January 1998): 21–47. http://dx.doi.org/10.1080/10248079808903735.

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A.K. Noaman, Redwan, Mohd Alauddin Mohd Ali, Nasharuddin Zainal, and Faisal Saeed. "Human Detection Framework for Automated Surveillance Systems." International Journal of Electrical and Computer Engineering (IJECE) 6, no. 2 (April 1, 2016): 877. http://dx.doi.org/10.11591/ijece.v6i2.9578.

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Vision-based systems for surveillance applications have been used widely and gained more research attention. Detecting people in an image stream is challenging because of their intra-class variability, the diversity of the backgrounds, and the conditions under which the images were acquired. Existing human detection solutions suffer in their effectiveness and efficiency. In particular, the accuracy of the existing detectors is characterized by their high false positive and negative. In addition, existing detectors are slow for online surveillance systems which lead to large delay that is not suitable for surveillance systems for real-time monitoring. In this paper, a holistic framework is proposed for enhancing the performance of human detection in surveillance system. In general, the framework includes the following stages: environment modeling, motion object detection, and human object recognition. In environment modeling, modal algorithm has been suggested for background initialization and extraction. Then for effectively classifying the motion object, edge detecting and B-spline algorithm have been used for shadow detection and removal. Then, enhanced Lucas–Kanade optical flow has been used to get the area of interest for object segmentation. Finally, to enhance the segmentation, some morphological processes were performed. In the motion object recognition stage, segmentation for each blob is performed and processed to the human detector which is a complete learning-based system for detecting and localizing objects/humans in images using mixtures of deformable part models (PFF detector). Results show enhancement in each phase of the proposed framework. These enhancements are shown in the overall performance of human detection in surveillance system.

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A.K. Noaman, Redwan, Mohd Alauddin Mohd Ali, Nasharuddin Zainal, and Faisal Saeed. "Human Detection Framework for Automated Surveillance Systems." International Journal of Electrical and Computer Engineering (IJECE) 6, no. 2 (April 1, 2016): 877. http://dx.doi.org/10.11591/ijece.v6i2.pp877-886.

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Vision-based systems for surveillance applications have been used widely and gained more research attention. Detecting people in an image stream is challenging because of their intra-class variability, the diversity of the backgrounds, and the conditions under which the images were acquired. Existing human detection solutions suffer in their effectiveness and efficiency. In particular, the accuracy of the existing detectors is characterized by their high false positive and negative. In addition, existing detectors are slow for online surveillance systems which lead to large delay that is not suitable for surveillance systems for real-time monitoring. In this paper, a holistic framework is proposed for enhancing the performance of human detection in surveillance system. In general, the framework includes the following stages: environment modeling, motion object detection, and human object recognition. In environment modeling, modal algorithm has been suggested for background initialization and extraction. Then for effectively classifying the motion object, edge detecting and B-spline algorithm have been used for shadow detection and removal. Then, enhanced Lucas–Kanade optical flow has been used to get the area of interest for object segmentation. Finally, to enhance the segmentation, some morphological processes were performed. In the motion object recognition stage, segmentation for each blob is performed and processed to the human detector which is a complete learning-based system for detecting and localizing objects/humans in images using mixtures of deformable part models (PFF detector). Results show enhancement in each phase of the proposed framework. These enhancements are shown in the overall performance of human detection in surveillance system.

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Chick, Morey J. "Human safety risk in automated information systems." Journal of Technology Transfer 10, no. 2 (March 1986): 43–52. http://dx.doi.org/10.1007/bf02173399.

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Micheletti, G. F. "The automated factory—Human systems and creative propulsion." International Journal of Advanced Manufacturing Technology 3, no. 4 (August 1988): 1–2. http://dx.doi.org/10.1007/bf02601830.

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Gregoriades, A., and A. G. Sutcliffe. "Automated assistance for human factors analysis in complex systems." Ergonomics 49, no. 12-13 (October 10, 2006): 1265–87. http://dx.doi.org/10.1080/00140130600612721.

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Lyons, Joseph B., Kolina S. Koltai, Nhut T. Ho, Walter B. Johnson, David E. Smith, and R. Jay Shively. "Engineering Trust in Complex Automated Systems." Ergonomics in Design: The Quarterly of Human Factors Applications 24, no. 1 (January 2016): 13–17. http://dx.doi.org/10.1177/1064804615611272.

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We studied the transparency of automated tools used during emergency operations in commercial aviation. Transparency (operationalized as increasing levels of explanation associated with an automated tool recommendation) was manipulated to evaluate how transparent interfaces influence pilot trust of an emergency landing planning aid. We conducted a low-fidelity study in which commercial pilots interacted with simulated recommendations from NASA’s Emergency Landing Planner (ELP) that varied in their associated levels of transparency. Results indicated that trust in the ELP was influenced by the level of transparency within the human–machine interface of the ELP. Design recommendations for automated systems are discussed.

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Fuest, Tanja, Alexander Feierle, Elisabeth Schmidt, and Klaus Bengler. "Effects of Marking Automated Vehicles on Human Drivers on Highways." Information 11, no. 6 (May 28, 2020): 286. http://dx.doi.org/10.3390/info11060286.

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Due to the short range of the sensor technology used in automated vehicles, we assume that the implemented driving strategies may initially differ from those of human drivers. Nevertheless, automated vehicles must be able to move safely through manual road traffic. Initially, they will behave as carefully as human learners do. In the same way that driving-school vehicles tend to be marked in Germany, markings for automated vehicles could also prove advantageous. To this end, a simulation study with 40 participants was conducted. All participants experienced three different highway scenarios, each with and without a marked automated vehicle. One scenario was based around some roadworks, the next scenario was a traffic jam, and the last scenario involved a lane change. Common to all scenarios was that the automated vehicles strictly adhered to German highway regulations, and therefore moved in road traffic somewhat differently to human drivers. After each trial, we asked participants to rate how appropriate and disturbing the automated vehicle’s driving behavior was. We also measured objective data, such as the time of a lane change and the time headway. The results show no differences for the subjective and objective data regarding the marking of an automated vehicle. Reasons for this might be that the driving behavior itself is sufficiently informative for humans to recognize an automated vehicle. In addition, participants experienced the automated vehicle’s driving behavior for the first time, and it is reasonable to assume that an adjustment of the humans’ driving behavior would take place in the event of repeated encounters.

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Ossig, Johannes, Stephanie Cramer, and Klaus Bengler. "Concept of an Ontology for Automated Vehicle Behavior in the Context of Human-Centered Research on Automated Driving Styles." Information 12, no. 1 (January 8, 2021): 21. http://dx.doi.org/10.3390/info12010021.

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In the human-centered research on automated driving, it is common practice to describe the vehicle behavior by means of terms and definitions related to non-automated driving. However, some of these definitions are not suitable for this purpose. This paper presents an ontology for automated vehicle behavior which takes into account a large number of existing definitions and previous studies. This ontology is characterized by an applicability for various levels of automated driving and a clear conceptual distinction between characteristics of vehicle occupants, the automation system, and the conventional characteristics of a vehicle. In this context, the terms ‘driveability’, ‘driving behavior’, ‘driving experience’, and especially ‘driving style’, which are commonly associated with non-automated driving, play an important role. In order to clarify the relationships between these terms, the ontology is integrated into a driver-vehicle system. Finally, the ontology developed here is used to derive recommendations for the future design of automated driving styles and in general for further human-centered research on automated driving.

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Ossig, Johannes, Stephanie Cramer, and Klaus Bengler. "Concept of an Ontology for Automated Vehicle Behavior in the Context of Human-Centered Research on Automated Driving Styles." Information 12, no. 1 (January 8, 2021): 21. http://dx.doi.org/10.3390/info12010021.

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In the human-centered research on automated driving, it is common practice to describe the vehicle behavior by means of terms and definitions related to non-automated driving. However, some of these definitions are not suitable for this purpose. This paper presents an ontology for automated vehicle behavior which takes into account a large number of existing definitions and previous studies. This ontology is characterized by an applicability for various levels of automated driving and a clear conceptual distinction between characteristics of vehicle occupants, the automation system, and the conventional characteristics of a vehicle. In this context, the terms ‘driveability’, ‘driving behavior’, ‘driving experience’, and especially ‘driving style’, which are commonly associated with non-automated driving, play an important role. In order to clarify the relationships between these terms, the ontology is integrated into a driver-vehicle system. Finally, the ontology developed here is used to derive recommendations for the future design of automated driving styles and in general for further human-centered research on automated driving.

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Lank, Christian, Max Haberstroh, and Matthias Wille. "Interaction of Human, Machine, and Environment in Automated Driving Systems." Transportation Research Record: Journal of the Transportation Research Board 2243, no. 1 (January 2011): 138–45. http://dx.doi.org/10.3141/2243-16.

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Martin, T. "Considering Human Factors in the Design of Automated Manufacturing Systems." IFAC Proceedings Volumes 25, no. 27 (September 1992): 55–61. http://dx.doi.org/10.1016/s1474-6670(17)49558-9.

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Altendorf, Eugen, Constanze Schreck, Gina Weßel, Yigiterkut Canpolat, and Frank Flemisch. "Utility assessment in automated driving for cooperative human–machine systems." Cognition, Technology & Work 21, no. 4 (August 13, 2019): 607–19. http://dx.doi.org/10.1007/s10111-019-00557-4.

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Umetalieva, Ch T., N. Y. Temirbaeva, and B. N. Nurtaev. "THEORY OF BUILDING AUTOMATED CONTROL SYSTEMS." Herald of KSUCTA, №2, Part 1, 2022, no. 2-1-2022 (April 30, 2022): 295–99. http://dx.doi.org/10.35803/1694-5298.2022.2.295-299.

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The task of collecting, processing and disseminating (exchanging) information stood at all stages of human development. For a long time, the main tools for solving it were the human brain, hearing and language. Storing information in computer memory gives a fundamentally new quality of dynamics, that is, the ability to quickly recover and use it directly in problems solved on a computer. Modern printing equipment, equipped with modern computers, allows, if necessary, to quickly present any selected information on paper. In the process of development of the administrative data management system, the need arose for an automated facility management system (ACS).

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Heikoop, Daniël D., Marjan Hagenzieker, Giulio Mecacci, Simeon Calvert, Filippo Santoni De Sio, and Bart van Arem. "Human behaviour with automated driving systems: a quantitative framework for meaningful human control." Theoretical Issues in Ergonomics Science 20, no. 6 (March 18, 2019): 711–30. http://dx.doi.org/10.1080/1463922x.2019.1574931.

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Alicandri, Elizabeth, and M. Joseph Moyer. "Human Factors and the Automated Highway System." Proceedings of the Human Factors Society Annual Meeting 36, no. 15 (October 1992): 1064–67. http://dx.doi.org/10.1518/107118192786749793.

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The Intelligent Vehicle-Highway System (IVHS) is an important and broad ranging Department of Transportation program to reduce congestion and increase safety on the nation's highway system. The Automated Highway System (AHS) represents the full realization of one IVHS subsystem, Automated Vehicle Control Systems. Efforts are underway to define and resolve critical human factors questions related to the AHS. As part of the process, human factors issues will be identified through development of hypothetical AHS scenarios. This requires a generic AHS scenario be presented, and affiliated human factors issues identified.

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Garnick, Christopher J., Jason M. Bindewald, and Christina F. Rusnock. "Designing an Automated Agent to Encourage Human Reliance." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 61, no. 1 (September 2017): 1730–34. http://dx.doi.org/10.1177/1541931213601980.

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Human reliance on automated agents can be critically important, as exemplified by a pilot relying on an automated ground collision avoidance system. While it is important that the automated agent perform a task well, thus promoting reliance on the automation, it is difficult to test human reliance on automated agents in safety-critical systems. This paper presents an automated agent designed to enable testing of human reliance on automation in the Space Navigator environment. The automated agent performs collision detection and avoidance tasks in the environment, aiding the human participant in real-time. We present a collision detection and avoidance model, comparing three potential methods for collision avoidance. Analysis shows that the new agent’s performance when teamed with another simulated agent improves upon previous individual human and human-agent team performances in the same environment, thus making it logical for humans to rely upon it. A human-subjects study confirms that the resulting automated agent/environment pairing enables human reliance studies in a low-states automation environment.

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Adiga N, Achal, Avaneesh B. Ballal, Dileep P, Harishgowda M, Roopa T S, and Gangadhar Angadi. "Smart Automated Guided Vehicle for Flexible Manufacturing Systems." ECS Transactions 107, no. 1 (April 24, 2022): 13205–20. http://dx.doi.org/10.1149/10701.13205ecst.

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In the Flexible Manufacturing System, automation and the ability to restructure the manufacturing facility is important. The development of a discretely working Smart Automated Guided Vehicle is the need of the hour. Hence the objective is to develop a compact unit load Smart Automated Guided Vehicle to increase efficiency and productivity & to overcome the problems of conventional material handling systems and improve the efficacy of manufacturing. Smart Automated Guided Vehicle is provided with navigation, weight sensing, obstacle detection systems with other auxiliary systems instrumental in zonal setup for the Smart Automated Guided Vehicle as well as adaptable for frequent changes. This model of Smart Automated Guided Vehicle is helpful for a small operational manufacturing unit for multipurpose applications at very low cost and high customizability. The objective is to provide a safe environment to the Smart Automated Guided Vehicle & its surroundings also, to reduce human dependency.

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Lee, Christopher, and James Hogan. "Automated crater detection with human level performance." Computers & Geosciences 147 (February 2021): 104645. http://dx.doi.org/10.1016/j.cageo.2020.104645.

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Orosz, Gábor. "Connected automated vehicle design among human-driven vehicles." IFAC-PapersOnLine 51, no. 34 (2019): 403–6. http://dx.doi.org/10.1016/j.ifacol.2019.01.005.

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Winter, Mary H., and Alan W. Manning. "Critical Variables in System Success: Top Managements' Commitment is Key." Water Science and Technology 28, no. 11-12 (December 1, 1993): 15–19. http://dx.doi.org/10.2166/wst.1993.0641.

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Billions of dollars and vast amounts of human energy go into implementing advanced technology every year. Yet the success rate of automated systems is estimated as low as 25%. Even today's sophisticated technology cannot prevent expensive failure or non-use of automated systems. This suggests that a change in approach is needed to successfully plan and implement automated systems, which raises the following questions. Are human factors or technical issues more significant to control systems success? What are the most important non-technical contributors? Is it possible to assure the success of a control systems project? To answer these questions a survey was carried out of people who have experience working with computer systems at utilities.

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Morozov, A. O., V. P. Klimenko, G. G. Grabovsky, M. G. Ievlev, and S. Ye Moiseienko. "Concepts of human-machine automation in APCS of heavy-plate mills rolling." Mathematical machines and systems 1 (2022): 81–96. http://dx.doi.org/10.34121/1028-9763-2022-1-81-96.

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Modern automated control systems can not do without the special means of organizing commu-nication with humans. The main peculiarity of human-machine interaction is the combination of formalized information processes and structures with non-formalized (as a rule, creative) in-formation processing. The latter helps not only find ways to solve complex problems that can not be found in formal models (algorithms) but also organize the process of problem solving as a holistic system. Human-machine interaction can not be fully algorithmic (in the formal sense), but it is possible to develop technology for mutual activities of humans and technical systems for problem solving. The role of people in technical control systems is constantly changing. Previously, a human was the link that was mostly responsible for process manage-ment. With the development of automated systems that was supported by the ever-increasing use of computers, people are increasingly taking over the functions of the control unit, at the same time keeping the role of an observer of the process. However, in recent years the role of humans in control systems has changed. In modern technical systems, they again play a leading role, which fully reveals their abilities and uses its boundary capabilities to optimally distribute the functions between human and machine, human and process. Human-machine interaction is a form of mutual use of reserves of humans and automated systems that is ultimately focused on humans. The article considers the stages of human-machine automation systems development, the composition and distribution of functions in human-machine systems, the possibility of their implementation, emergencies in automated technological facilities, and some examples of human-machine control in ACS TP thick-sheet rolling mills.

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Manikonda, Lydia, Tathagata Chakraborti, Sushovan De, Kartik Talamadupula, and Subbarao Kambhampati. "AI-MIX: Using Automated Planning to Steer Human Workers Towards Better Crowdsourced Plans." Proceedings of the AAAI Conference on Artificial Intelligence 28, no. 2 (July 27, 2014): 3004–9. http://dx.doi.org/10.1609/aaai.v28i2.19020.

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One subclass of human computation applications are those directed at tasks that involve planning (e.g. tour planning) and scheduling (e.g. conference scheduling). Interestingly, work on these systems shows that even primitive forms of automated oversight on the human contributors helps in significantly improving the effectiveness of the humans/crowd. In this paper, we argue that the automated oversight used in these systems can be viewed as a primitive automated planner, and that there are several opportunities for more sophisticated automated planning in effectively steering the crowd. Straightforward adaptation of current planning technology is however hampered by the mismatch between the capabilities of human workers and automated planners. We identify and partially address two important challenges that need to be overcome before such adaptation of planning technology can occur: (i) interpreting inputs of the human workers (and the requester) and (ii) steering or critiquing plans produced by the human workers, armed only with incomplete domain and preference models. To these ends, we describe the implementation of AI-MIX, a tour plan generation system that uses automated checks and alerts to improve the quality of plans created by human workers; and present a preliminary evaluation of the effectiveness of steering provided by automated planning.

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Parasuraman, Raja, Mustapha Mouloua, and Robert Molloy. "Effects of Adaptive Task Allocation on Monitoring of Automated Systems." Human Factors: The Journal of the Human Factors and Ergonomics Society 38, no. 4 (December 1996): 665–79. http://dx.doi.org/10.1518/001872096778827279.

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The effects of adaptive task allocation on monitoring for automation failure during multi task flight simulation were examined. Participants monitored an automated engine status task while simultaneously performing tracking and fuel management tasks over three 3D-min sessions. Two methods of adaptive task allocation, both involving temporary return of the automated engine status task to the human operator (“human control”), were examined as a possible countermeasure to monitoring inefficiency. For the model-based adaptive group, the engine status task was allocated to all participants in the middle of the second session for 10 min, following which it was again returned to automation control. The same occurred for the performance-based adaptive group, but only if an individual participant's monitoring performance up to that point did not meet a specified criterion. For the nonadaptive control groups, the engine status task remained automated throughout the experiment. All groups had low probabilities of detection of automation failures for the first 40 min spent with automation. However, following the lO-min intervening period of human control, both adaptive groups detected significantly more automation failures during the subsequent blocks under automation control. The results show that adaptive task allocation can enhance monitoring of automated systems. Both model-based and performance-based allocation improved monitoring of automation. Implications for the design of automated systems are discussed.

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Simavoryan, Simon Zhorzhevich, Arsen Rafikovich Simonyan, Georgii Aleksandrovich Popov, and Elena Ivanovna Ulitina. "Analysis of possible adaptation of the general pattern of immune system within the systems for preventing intrusions." Вопросы безопасности, no. 4 (April 2020): 36–46. http://dx.doi.org/10.25136/2409-7543.2020.4.33736.

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The subject of this research is the analysis of possible implementation of the mechanisms of functionality of human immune system applicable to information security systems in automated data processing systems. The objects of this research are the human immune system, information security systems, and automated data processing systems. The research is conducted on the basis of achievements of systemic-conceptual approach towards information protection in automated data processing systems, developed within the framework of the project sponsored by the Russian Foundation for Basic Research No. 19-01-00383 on creation of intelligent information protection systems based on the neural network intrusion detection systems and  the mechanisms of artificial immune systems. The article reviews similarity and difference between human immune system and information security systems. Special attention is given to identification of peculiarities of functionality of the mechanisms on detection of harmful intrusions into these systems respectively. Methodological research on the topic are carried out using the achievements in the area of creation of neural network intrusion detection system, built on the basis of artificial immune mechanisms that function similar to human immune system. The main result consists in the conclusion that adaptive information security systems containing the means and mechanisms of protection and built by analogy with the human immune system, may provide successful and effective protection of information in automated data processing systems. The specificity and importance of this conclusion is substantiated by the fact that it can be implemented despite the absence of full analogy between human immune system and information security system; moreover, multiple mechanism of protection implemented in human immune system are absent in the information security system, or the other way around.

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Wen, Richard, and Songnian Li. "Spatial Decision Support Systems with Automated Machine Learning: A Review." ISPRS International Journal of Geo-Information 12, no. 1 (December 30, 2022): 12. http://dx.doi.org/10.3390/ijgi12010012.

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Many spatial decision support systems suffer from user adoption issues in practice due to lack of trust, technical expertise, and resources. Automated machine learning has recently allowed non-experts to explore and apply machine-learning models in the industry without requiring abundant expert knowledge and resources. This paper reviews recent literature from 136 papers, and proposes a general framework for integrating spatial decision support systems with automated machine learning as an opportunity to lower major user adoption barriers. Challenges of data quality, model interpretability, and practical usefulness are discussed as general considerations for system implementation. Research opportunities related to spatially explicit models in AutoML, and resource-aware, collaborative/connected, and human-centered systems are also discussed to address these challenges. This paper argues that integrating automated machine learning into spatial decision support systems can not only potentially encourage user adoption, but also mutually benefit research in both fields—bridging human-related and technical advancements for fostering future developments in spatial decision support systems and automated machine learning.

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Sarter, Nadine B., and David D. Woods. "Mode Error in Supervisory Control of Automated Systems." Proceedings of the Human Factors Society Annual Meeting 36, no. 1 (October 1992): 26–29. http://dx.doi.org/10.1177/154193129203600108.

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Mode errors are one kind of breakdown in human-computer interaction. The concept was developed originally in the context of relatively simple reactive computerized devices such as word processors. When a device possesses multiple modes, where something is done one way in one mode and another way in another mode, there is increased potential for erroneous actions. In this paper we extend and expand the concept of mode error to supervisory control of automated resources in event-driven situations such as pilot interaction with cockpit automation. In this type of situation, the state of the automated system can change in response to either operator input, situation factors or system factors. This creates complexities in tracking system mode changes over time, surprises created by “uncommanded” mode changes, and the possibility of errors of omission as well as commission in managing multiple system modes. Progress in our understanding of mode error in the context of highly automated systems is important in our ability to develop effective countermeasures for mode-related problems in human-computer cooperation.

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Janota, Aleš, Rastislav Pirník, Juraj Ždánsky, and Peter Nagy. "Human Factor Analysis of the Railway Traffic Operators." Machines 10, no. 9 (September 19, 2022): 820. http://dx.doi.org/10.3390/machines10090820.

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The human factor is an essential aspect of the operability and safety of many technical systems. This paper focuses on the analysis of human errors in the railway domain. The subject of human reliability analysis is the behavior of operators of station-signaling systems responsible for rail traffic management. We use a technique for human-error rate prediction as the 1st generation human reliability analysis to deal with task analyses, error identification and representation, and the quantification of human error probabilities. The paper contributes to the comparison of three technologically different railway traffic control systems, having different degrees of automation—from the manually operated (electro-mechanical), through semi-automated (relay-based) to almost fully automated (computer-based) station-signaling systems. We observe the frequency of individual operations performed in time intervals and calculate human error probability and human success probability values for each operation. Thus, we can analyze human reliability and compare the workload of operators working with control systems of different degrees of automation.

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Hudgings, Carole. "Human Factors Considerations in the Design of Automated Systems for Nursing." Proceedings of the Human Factors Society Annual Meeting 32, no. 6 (October 1988): 440–44. http://dx.doi.org/10.1177/154193128803200606.

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This paper describes human factors relevant to the design of automated systems for clinical nursing information management, and several studies investigating human factors aspects of new clinical nursing information systems. Functions of systems to assist clinical nurses with information management are described. The importance of human factors in designing these computer systems is discussed by describing three categories of human factors: physical and demographic characteristics of nurses, characteristics of the hospital physical environment, and characteristics of the nursing care environment. Several human factors studies conducted by a multi-hospital corporation and two vendors to understand the nature and impact of human factors on systems design are discussed. Various data collection methodologies are described that investigate two different approaches to the design of hardware solutions for a clinical nursing information system.

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Ng, Irene C. L. "Value and systems perspectives in combining human and automated services: commentary on “seven challenges to combining human and automated service”." Canadian Journal of Administrative Sciences / Revue Canadienne des Sciences de l'Administration 27, no. 1 (March 2010): 81–84. http://dx.doi.org/10.1002/cjas.141.

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Simavoryan, Simon Zhorzhevich, Arsen Rafikovich Simonyan, Georgii Aleksandrovich Popov, and Elena Ivanovna Ulitina. "Functionality of the system of information security in automated data processing systems in the conditions of external intrusions by analogy with the human immune system." Программные системы и вычислительные методы, no. 3 (March 2021): 11–24. http://dx.doi.org/10.7256/2454-0714.2021.3.36226.

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This article is dedicated to construction of the system of information security in automated data processing systems that function by analogy with the human immune system. The subject of this research is the development of the procedure for countering external intrusions of viruses, spam, and other destructive software programs in automated data processing systems. The object of this research is the systems of ensuring information security in automated data processing systems and human immune system. Methodological research on elaboration of the procedure for identification of intrusion is conducted via methods of artificial intelligence, systemic analysis, theory of neural and immune systems in the sphere of ensuring information security based on the achievements of systemic analysis and a systemic-conceptual approach towards information security in automated data processing systems. The main result lies in the developed general procedure for the functionality of the system of ensuring information security in countering external intrusions in the form of block-diagram and its description. The procedure is based on the idea of similarity in functionality of the mechanisms and procedures for protection against external intrusions in both, human immune system and automated data processing system, as well as drawing parallel between them. The main peculiarity of the developed procedure lies in its applicability to the accepted classification of the initial external environment of intrusion onto physical, information, field, and infrastructure environments. Such approach guarantees the novelty of the development from the perspective of constant updating of human immune system countering mechanisms to the external intrusions and its application for each environment in applicable to automated data processing systems.

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Korbelak, Kristopher, Jeffrey Dressel, David Band, and Jennifer Blanchard. "Teaming with Technology at the TSA: Practical Methods for Enhancing Human Performance with Automation in Operational Environments." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 62, no. 1 (September 2018): 639–40. http://dx.doi.org/10.1177/1541931218621146.

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Automated systems are not only commonplace but often are a necessity to complete highly specialized tasks across many operational environments. The Transportation Security Administration (TSA) aims to enhance human performance and increase safety through the acquisition and implementation of various types of automated systems. The Human Performance Branch (HPB) at TSA supports this aim through research on human factors that influence interactions with automation. Knowledge gained from HPB efforts informs TSA of the automated systems that will best suit worker needs, how to integrate these systems into the general workflow, and the relevant human factors that will support proper system use and, ultimately, enhance human performance. This discussion panel reviews a theoretical framework the TSA can use to guide assessment of multiple drivers of human performance in a consistent and standardized fashion as well as several TSA projects investigating three categories of human factors known to influence performance with automation – human (i.e., individual differences, cognitive constraints), context (e.g., organizational influence, environment), and system characteristics (e.g., type of automation) – and how those factors can be accounted for in the operational environment.

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Manikonda, Lydia, Tathagata Chakraborti, Kartik Talamadupula, and Subbarao Kambhampati. "Herding the Crowd: Using Automated Planning for Better Crowdsourced Planning." Human Computation 4, no. 1 (April 18, 2017): 25–46. http://dx.doi.org/10.15346/hc.v4i1.52.

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One subclass of human computation applications are those directed at tasks that involve planning (e.g. tour planning) and scheduling (e.g. conference scheduling). Interestingly, work on these systems shows that even primitive forms of automated oversight on the human contributors helps in significantly improving the effectiveness of the humans/crowd. In this paper, we argue that the automated oversight used in these systems can be viewed as a primitive automated planner, and that there are several opportunities for more sophisticated automated planning in effectively steering crowdsourced planning. Straightforward adaptation of current planning technology is however hampered by the mismatch between the capabilities of human workers and automated planners. We identify and partially address two important challenges that need to be overcome before such adaptation of planning technology can occur: (i) interpreting inputs of the human workers (and the requester) and (ii) steering or critiquing plans produced by the human workers, armed only with incomplete domain and preference models. To these ends, we describe the implementation of AI-MIX, a tour plan generation system that uses automated checks and alerts to improve the quality of plans created by human workers.

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Piccini, M. "Human Factors in the Design of Supervisory Control Systems and Human-Machine Interfaces for Highly Automated Complex Systems." Cognition, Technology & Work 4, no. 4 (November 1, 2002): 256–71. http://dx.doi.org/10.1007/s101110200024.

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Wang, Zhen, Klaus Zechner, and Yu Sun. "Monitoring the performance of human and automated scores for spoken responses." Language Testing 35, no. 1 (December 19, 2016): 101–20. http://dx.doi.org/10.1177/0265532216679451.

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As automated scoring systems for spoken responses are increasingly used in language assessments, testing organizations need to analyze their performance, as compared to human raters, across several dimensions, for example, on individual items or based on subgroups of test takers. In addition, there is a need in testing organizations to establish rigorous procedures for monitoring the performance of both human and automated scoring processes during operational administrations. This paper provides an overview of the automated speech scoring system SpeechRaterSM and how to use charts and evaluation statistics to monitor and evaluate automated scores and human rater scores of spoken constructed responses.

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Biondi, Francesco N., and Balasingam Balakumar. "Human factors of automated driving systems: a compendium of lessons learned." International Journal of Human Factors and Ergonomics 1, no. 1 (2021): 1. http://dx.doi.org/10.1504/ijhfe.2021.10036735.

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Biondi, Francesco N., and Balasingam Balakumar. "Human factors of automated driving systems: a compendium of lessons learned." International Journal of Human Factors and Ergonomics 8, no. 2 (2021): 183. http://dx.doi.org/10.1504/ijhfe.2021.116066.

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Cummings, M. L., and Sylvain Bruni. "Human-automated planner collaboration in complex resource allocation decision support systems." Intelligent Decision Technologies 4, no. 2 (February 11, 2010): 101–14. http://dx.doi.org/10.3233/idt-2010-0072.

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MacMillan, Jean. "Integrating Human and Machine Vision: Lessons from Automated Target Recognition Systems." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 38, no. 19 (October 1994): 1310–11. http://dx.doi.org/10.1177/154193129403801913.

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Noparatayaporn, Prapaporn, Rungpetch Sakulbumrungsil, Tanita Thaweethamcharoen, and Wunwisa Sangseenil. "Comparison on Human Resource Requirement between Manual and Automated Dispensing Systems." Value in Health Regional Issues 12 (May 2017): 107–11. http://dx.doi.org/10.1016/j.vhri.2017.03.007.

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Cernetic, Janko. "Special section on automated systems based on human skills and knowledge." Control Engineering Practice 10, no. 5 (May 2002): 559. http://dx.doi.org/10.1016/s0967-0661(02)00014-x.

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Jiang, Xiaochun, Anand K. Gramopadhye, Brian J. Melloy, and Laurence W. Grimes. "Evaluation of best system performance: Human, automated, and hybrid inspection systems." Human Factors and Ergonomics in Manufacturing 13, no. 2 (2003): 137–52. http://dx.doi.org/10.1002/hfm.10031.

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Vreuls, Donald, and Richard W. Obermayer. "Human-System Performance Measurement in Training Simulators." Human Factors: The Journal of the Human Factors and Ergonomics Society 27, no. 3 (June 1985): 241–50. http://dx.doi.org/10.1177/001872088502700302.

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Automated human-system performance measurement subsystems are being specified as a requirement in modern training simulators. Although hardware and software technology can support this requirement, there are many unanswered questions about the design of real-time automated measurement systems. Fundamental performance measurement problems and research issues are discussed.

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Liu, Yuan-Cheng, Nikol Figalová, and Klaus Bengler. "Transparency Assessment on Level 2 Automated Vehicle HMIs." Information 13, no. 10 (October 10, 2022): 489. http://dx.doi.org/10.3390/info13100489.

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The responsibility and role of human drivers during automated driving might change dynamically. In such cases, human-machine interface (HMI) transparency becomes crucial to facilitate driving safety, as the states of the automated vehicle have to be communicated correctly and efficiently. However, there is no standardized transparency assessment method to evaluate the understanding of human drivers toward the HMI. In this study, we defined functional transparency (FT) and, based on this definition, proposed a transparency assessment method as a preliminary step toward the objective measurement for HMI understanding. The proposed method was verified in an online survey where HMIs of different vehicle manufacturers were adopted and their transparencies assessed. Even though no significant result was found among HMI designs, FT was found to be significantly higher for participants more experienced with SAE Level 2 automated vehicles, suggesting that more experienced users understand the HMIs better. Further identification tests revealed that more icons in BMW’s and VW’s HMI designs were correctly used to evaluate the state of longitudinal and lateral control. This study provides a novel method for assessing transparency and minimizing confusion during automated driving, which could greatly assist the HMI design process in the future.

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Eramian, Mark, Christopher Power, Stephen Rau, and Pulkit Khandelwal. "Benchmarking Human Performance in Semi-Automated Image Segmentation." Interacting with Computers 32, no. 3 (May 2020): 233–45. http://dx.doi.org/10.1093/iwcomp/iwaa017.

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Abstract Semi-automated segmentation algorithms hold promise for improving extraction and identification of objects in images such as tumors in medical images of human tissue, counting plants or flowers for crop yield prediction or other tasks where object numbers and appearance vary from image to image. By blending markup from human annotators to algorithmic classifiers, the accuracy and reproducability of image segmentation can be raised to very high levels. At least, that is the promise of this approach, but the reality is less than clear. In this paper, we review the state-of-the-art in semi-automated image segmentation performance assessment and demonstrate it to be lacking the level of experimental rigour needed to ensure that claims about algorithm accuracy and reproducability can be considered valid. We follow this review with two experiments that vary the type of markup that annotators make on images, either points or strokes, in tightly controlled experimental conditions in order to investigate the effect that this one particular source of variation has on the accuracy of these types of systems. In both experiments, we found that accuracy substantially increases when participants use a stroke-based interaction. In light of these results, the validity of claims about algorithm performance are brought into sharp focus, and we reflect on the need for a far more control on variables for benchmarking the impact of annotators and their context on these types of systems.

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Bisantz, Ann M., and Amy R. Pritchett. "Measuring the Fit between Human Judgments and Automated Alerting Algorithms: A Study of Collision Detection." Human Factors: The Journal of the Human Factors and Ergonomics Society 45, no. 2 (June 2003): 266–80. http://dx.doi.org/10.1518/hfes.45.2.266.27243.

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Methodologies for assessing human judgment in complex domains are important for the design of both displays that inform judgment and automated systems that suggest judgments. This paper uses the n-system lens model to evaluate the impact of displays on human judgment and to explicitly assess the similarity between human judgments and a set of potential judgment algorithms for use in automated systems. First, the need for and concepts underlying judgment analysis are outlined. Then the n-system lens model and its parameters are formally described. This model is then used to examine a previously conducted study of aircraft collision detection that had been analyzed using standard analysis of variance methods. Our analysis found the same main effects as did the earlier analysis. However, n-system lens model analysis was able to provide greater insight into the information relied upon for judgments and the impact of displays on judgment. Additionally, the analysis was able to identify attributes of human judgments that were---and were not---similar to judgments produced by automated systems. Potential applications of this research include automated aid design and operator training.

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Kaiser, Stefan A. "Legal Challenges of Automated and Autonomous Systems." Volume 60 · 2017 60, no. 1 (January 1, 2018): 173–201. http://dx.doi.org/10.3790/gyil.60.1.173.

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With an increasing influence of computers and software, automation is affecting many areas of daily life. Autonomous systems have become a central notion, but many systems have reached only a lower level of automation and not yet full autonomy. Information technology and software have a strong impact and their industries are introducing their own business cultures. Even though autonomy will enable systems to act independently from direct human input and control in complex scenarios, the factors of responsibility, control, and attribution are of crucial importance for a legal framework. Legal responsibility has to serve as a safeguard of fundamental rights. Responsibility can be attributed by a special legal regime, and mandatory human override and fallback modes can assure human intervention and control. It is proposed to establish a precautionary regulatory regime for automated and autonomous systems to include general principles on responsibility, transparency, training, human override and fallback modes, design parameters for algorithms and artificial intelligence, and cyber security. States need to take a positivist approach, maintain their regulatory prerogative, and, in support of their exercise of legislative and executive functions, establish an expertise independent of industry in automation, autonomy, algorithms, and artificial intelligence.

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Wolter, Stefan, Giancarlo Caccia Dominioni, Sebastian Hergeth, Fabio Tango, Stuart Whitehouse, and Frederik Naujoks. "Human–Vehicle Integration in the Code of Practice for Automated Driving." Information 11, no. 6 (May 27, 2020): 284. http://dx.doi.org/10.3390/info11060284.

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The advancement of SAE Level 3 automated driving systems requires best practices to guide the development process. In the past, the Code of Practice for the Design and Evaluation of ADAS served this role for SAE Level 1 and 2 systems. The challenges of Level 3 automation make it necessary to create a new Code of Practice for automated driving (CoP-AD) as part of the public-funded European project L3Pilot. It provides the developer with a comprehensive guideline on how to design and test automated driving functions, with a focus on highway driving and parking. A variety of areas such as Functional Safety, Cybersecurity, Ethics, and finally the Human–Vehicle Integration are part of it. This paper focuses on the latter, the Human Factors aspects addressed in the CoP-AD. The process of gathering the topics for this category is outlined in the body of the paper. Thorough literature reviews and workshops were part of it. A summary is given on the draft content of the CoP-AD Human–Vehicle Integration topics. This includes general Human Factors related guidelines as well as Mode Awareness, Trust, and Misuse. Driver Monitoring is highlighted as well, together with the topic of Controllability and the execution of Customer Clinics. Furthermore, the Training and Variability of Users is included. Finally, the application of the CoP-AD in the development process for Human-Vehicle Integration is illustrated.

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Elish, Madeleine Clare. "Moral Crumple Zones: Cautionary Tales in Human-Robot Interaction." Engaging Science, Technology, and Society 5 (March 23, 2019): 40. http://dx.doi.org/10.17351/ests2019.260.

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As debates about the policy and ethical implications of AI systems grow, it will be increasingly important to accurately locate who is responsible when agency is distributed in a system and control over an action is mediated through time and space. Analyzing several high-profile accidents involving complex and automated socio-technical systems and the media coverage that surrounded them, I introduce the concept of a moral crumple zone to describe how responsibility for an action may be misattributed to a human actor who had limited control over the behavior of an automated or autonomous system. Just as the crumple zone in a car is designed to absorb the force of impact in a crash, the human in a highly complex and automated system may become simply a component—accidentally or intentionally—that bears the brunt of the moral and legal responsibilities when the overall system malfunctions. While the crumple zone in a car is meant to protect the human driver, the moral crumple zone protects the integrity of the technological system, at the expense of the nearest human operator. The concept is both a challenge to and an opportunity for the design and regulation of human-robot systems. At stake in articulating moral crumple zones is not only the misattribution of responsibility but also the ways in which new forms of consumer and worker harm may develop in new complex, automated, or purported autonomous technologies.

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Kaß, Christina, Stefanie Schoch, Frederik Naujoks, Sebastian Hergeth, Andreas Keinath, and Alexandra Neukum. "Standardized Test Procedure for External Human–Machine Interfaces of Automated Vehicles." Information 11, no. 3 (March 24, 2020): 173. http://dx.doi.org/10.3390/info11030173.

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Research on external human–machine interfaces (eHMIs) has recently become a major area of interest in the field of human factors research on automated driving. The broad variety of methodological approaches renders the current state of research inconclusive and comparisons between interface designs impossible. To date, there are no standardized test procedures to evaluate and compare different design variants of eHMIs with each other and with interactions without eHMIs. This article presents a standardized test procedure that enables the effective usability evaluation of eHMI design solutions. First, the test procedure provides a methodological approach to deduce relevant use cases for the evaluation of an eHMI. In addition, we define specific usability requirements that must be fulfilled by an eHMI to be effective, efficient, and satisfying. To prove whether an eHMI meets the defined requirements, we have developed a test protocol for the empirical evaluation of an eHMI with a participant study. The article elucidates underlying considerations and details of the test protocol that serves as framework to measure the behavior and subjective evaluations of non-automated road users when interacting with automated vehicles in an experimental setting. The standardized test procedure provides a useful framework for researchers and practitioners.

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Journal articles on the topic 'Human-automated systems'

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