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Humans always wanted to go faster and higher than their own legs could carry them. This led them to invent numerous types of vehicles to move fast over land, water and air. As training how to handle such vehicles and testing new developments can be dangerous and costly, vehicle motion simulators were invented. Motion-based simulators in particular, combine visual and physical motion cues to provide occupants with a feeling of being in the real vehicle. While visual cues are generally not limited in amplitude, physical cues certainly are, due to the limited simulator motion space. A motion cueing algorithm (MCA) is used to map the vehicle motions onto the simulator motion space. This mapping inherently creates mismatches between the visual and physical motion cues. Due to imperfections in the human perceptual system, not all visual/physical cueing mismatches are perceived. However, if a mismatch is perceived, it can impair the simulation realism and even cause simulator sickness. For MCA design, a good understanding of when mismatches are perceived, and ways to prevent these from occurring, are therefore essential. In this thesis a data-driven approach, using continuous subjective measures of the time-varying Perceived Motion Incongruence (PMI), is adopted. PMI in this case refers to the effect that perceived mismatches between visual and physical motion cues have on the resulting simulator realism. The main goal of this thesis was to develop an MCA-independent off-line prediction method for time-varying PMI during vehicle motion simulation, with the aim of improving motion cueing quality. To this end, a complete roadmap, describing how to measure and model PMI and how to apply such models to predict and minimize PMI in motion simulations is presented. Results from several human-in-the-loop experiments are used to demonstrate the potential of this novel approach.
Simulation continues to be a growth area in transportation human factors. From empirical studies in the laboratory to the latest training techniques in the field, simulators offer myriad benefits for the experimenter and the practitioner. This book draws together current trends in research and training simulators for the road, rail, air and sea sectors to inform the reader how to maximize both validity and cost-effectiveness in each case. Simulators for Transportation Human Factors provides a valuable resource for both researchers and practitioners in transportation human factors on the use of simulators, giving readers concrete examples and case studies of how simulators have been developed and used in empirical research as well as training applications. It offers useful and usable information on the functional requirements of simulators without the need for any background knowledge on the technical aspects, focusing on the state of the art of research and applications in transport simulators rather than the state of the art of simulation technology. The book covers simulators in operational terms instead of task simulation/modelling and provides a useful balance between a bottom-up, academic approach and a top-down, practical perspective.
As the general notion of cognition has recently broadened to include its embodied nature, researchers' accounts of perception have increasingly come to include the body's special status as a window on the world and to accommodate the specific perceptual requirements for identifying, interpreting, and interacting with other bodies. This volume presents a comprehensive overview of the rapid progress that has been made in understanding the human body and its relationship to perception. It will help to unify the relevant research from several independent areas of cognitive psychology and cognitive neuroscience and facilitate the development of an integrated framework for the study of human-body perception.
This interpretation of perception and action allows Alain Berthoz to focus on psychological phenomena: proprioception and kinaesthesis; the mechanisms that maintain balance and co-ordination actions; and basic perceptual and memory processes involved in navigation.
This book covers the problem of fidelity in the design of virtual environments with specific reference to the design of vehicle simulators. The default design goal has been on the physical replication of a given real-world environment and, in the case of vehicles, the specific appearance and function of vehicle components. This book discusses that perceptual, rather than physical, fidelity of a virtual environment, should be the design goal and the principal purpose is to produce human behavior. This book provides the rationale and design guidance to maximize perceptual fidelity in the development of virtual environments, and therefore maximize the costeffectiveness as well.
Effective use of driving simulators requires considerable technical and methodological skill along with considerable background knowledge. Acquiring the requisite knowledge and skills can be extraordinarily time consuming, yet there has been no single convenient and comprehensive source of information on the driving simulation research being conduc
There is a growing consensus in the human factors/ergonomics community that human factors research has had little impact on significant applied problems. Some have suggested that the problem lies in the fact that much HF/E research has been based on the wrong type of psychology, an information processing view of psychology that is reductionistic and context-free. Ecological psychology offers a viable alternative, presenting a richer view of human behavior that is holistic and contextualized. The papers presented in these two volumes show the conceptual impact that ecological psychology can have on HF/E, as well as presenting a number of specific examples illustrating the ecological approach to human-machine systems. It is the first collection of papers that explicitly draws a connection between these two fields. While work in this area is only just beginning, the evidence available suggests that taking an ecological approach to human factors/ergonomics helps bridge the existing gap between basic research and applied problems.
For ‘Recent Progress in Brain and Cognitive Engineering’ Brain and Cognitive Engineering is a converging study field to derive a better understanding of cognitive information processing in the human brain, to develop “human-like” and neuromorphic artificial intelligent systems and to help predict and analyze brain-related diseases. The key concept of Brain and Cognitive Engineering is to understand the Brain, to interface the Brain, and to engineer the Brain. It could help us to understand the structure and the key principles of high-order information processing on how the brain works, to develop interface technologies between a brain and external devices and to develop artificial systems that can ultimately mimic human brain functions. The convergence of behavioral, neuroscience and engineering research could lead us to advance health informatics and personal learning, to enhance virtual reality and healthcare systems, and to “reverse engineer” some brain functions and build cognitive robots. In this book, four different recent research directions are presented: Non-invasive Brain-Computer Interfaces, Cognitive- and Neural-rehabilitation Engineering, Big Data Neurocomputing, Early Diagnosis and Prediction of Neural Diseases. We cover numerous topics ranging from smart vehicles and online EEG analysis, neuroimaging for Brain-Computer Interfaces, memory implantation and rehabilitation, big data computing in cultural aspects and cybernetics to brain disorder detection. Hopefully this will provide a valuable reference for researchers in medicine, biomedical engineering, in industry and academia for their further investigations and be inspiring to those who seek the foundations to improve techniques and understanding of the Brain and Cognitive Engineering research field.