274 research outputs found

    Assessing the Impact of Multi-variate Steering-rate Vehicle Control on Driver Performance in a Simulation Framework

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    When a driver turns a steering-wheel, he or she normally expects the vehicle\u27s steering system to communicate an equivalent amount of signal to the road-wheels. This relationship is linear and occurs regardless of the steering-wheel\u27s position within its rotational travel. The linear steering paradigm in passenger vehicles has gone largely unchanged since mass production of passenger vehicles began in 1901. However, as more electronically-controlled steering systems appear in conjunction with development of autonomous steering functions in vehicles, an opportunity to advance the existing steering paradigms arises. The following framework takes a human-factors approach toward examining and evaluating alternative steering systems by using Modeling and Simulation methods to track and score human performance. Present conventional steering systems apply a linear relationship between the steering-wheel and the road wheels of a vehicle. The rotational travel of the steering-wheel is 900° and requires two-and-a-half revolutions to travel from end-stop to opposite end-stop. The experimental steering system modeled and employed in this study applies a dynamic curve response to the steering input within a shorter, 225° rotational travel. Accommodation variances, based on vehicle speed and steering-wheel rotational position and acceleration, moderate the apparent steering input to augment a more-practical, effective steering rate. This novel model follows a paradigm supporting the full range of steering-wheel actuation without necessitating hand repositioning or the removal of the driver\u27s hands from the steering-wheel during steering maneuvers. In order to study human performance disparities between novel and conventional steering models, a custom simulator was constructed and programmed to render representative models in a test scenario. Twenty-seven males and twenty-seven females, ranging from the ages of eighteen to sixty-five were tested and scored using the driving simulator that presented two successive driving test vignettes: One vignette using conventional 900° steering with linear response and the other employing the augmented 225° multivariate, non-linear steering. The results from simulator testing suggest that both males and females perform better with the novel system, supporting the hypothesis that drivers of either gender perform better with a system augmented with 225° multivariate, non-linear steering than with a conventional steering system. Further analysis of the simulated-driving scores indicates performance parity between male and female participants, supporting the hypothesis positing no significant difference in driver performance between male and female drivers using the augmented steering system. Finally, composite data from written questionnaires support the hypothesis that drivers will prefer driving the augmented system over conventional steering. These collective findings support justification for testing and refining novel steering systems using Modeling and Simulation methods. As a product of this particular study, a tested and open-sourced simulation framework now exists such that researchers and automotive designers can develop, as well as evaluate their own steering-oriented products within a valid human-factors construct. The open-source nature of this framework implies a commonality by which otherwisedisparate research and development work can be associated. Extending this framework beyond basic investigation to reach applications requiring morespecialized parameters may even impact drivers having special needs. For example, steeringsystem functional characteristics could be comparatively optimized to accommodate individuals afflicted with upper-body deficits or limited use of either or both arms. Moreover, the combined human-factors and open-source approaches distinguish the products of this research as a common and extensible platform by which purposeful automotive-industry improvements can be realized—contrasted with arbitrary improvements that might be brought about predominantly to showcase technological advancements

    Ubiquitous Integration and Temporal Synchronisation (UbilTS) framework : a solution for building complex multimodal data capture and interactive systems

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    Contemporary Data Capture and Interactive Systems (DCIS) systems are tied in with various technical complexities such as multimodal data types, diverse hardware and software components, time synchronisation issues and distributed deployment configurations. Building these systems is inherently difficult and requires addressing of these complexities before the intended and purposeful functionalities can be attained. The technical issues are often common and similar among diverse applications. This thesis presents the Ubiquitous Integration and Temporal Synchronisation (UbiITS) framework, a generic solution to address the technical complexities in building DCISs. The proposed solution is an abstract software framework that can be extended and customised to any application requirements. UbiITS includes all fundamental software components, techniques, system level layer abstractions and reference architecture as a collection to enable the systematic construction of complex DCISs. This work details four case studies to showcase the versatility and extensibility of UbiITS framework’s functionalities and demonstrate how it was employed to successfully solve a range of technical requirements. In each case UbiITS operated as the core element of each application. Additionally, these case studies are novel systems by themselves in each of their domains. Longstanding technical issues such as flexibly integrating and interoperating multimodal tools, precise time synchronisation, etc., were resolved in each application by employing UbiITS. The framework enabled establishing a functional system infrastructure in these cases, essentially opening up new lines of research in each discipline where these research approaches would not have been possible without the infrastructure provided by the framework. The thesis further presents a sample implementation of the framework on a device firmware exhibiting its capability to be directly implemented on a hardware platform. Summary metrics are also produced to establish the complexity, reusability, extendibility, implementation and maintainability characteristics of the framework.Engineering and Physical Sciences Research Council (EPSRC) grants - EP/F02553X/1, 114433 and 11394

    Aesthetic choices: Defining the range of aesthetic views in interactive digital media including games and 3D virtual environments (3D VEs)

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    Defining aesthetic choices for interactive digital media such as games is a challenging task. Objective and subjective factors such as colour, symmetry, order and complexity, and statistical features among others play an important role for defining the aesthetic properties of interactive digital artifacts. Computational approaches developed in this regard also consider objective factors such as statistical image features for the assessment of aesthetic qualities. However, aesthetics for interactive digital media, such as games, requires more nuanced consideration than simple objective and subjective factors, for choosing a range of aesthetic features. From the study it was found that the there is no one single optimum position or viewpoint with a corresponding relationship to the aesthetic considerations that influence interactive digital media. Instead, the incorporation of aesthetic features demonstrates the need to consider each component within interactive digital media as part of a range of possible features, and therefore within a range of possible camera positions. A framework, named as PCAWF, emphasized that combination of features and factors demonstrated the need to define a range of aesthetic viewpoints. This is important for improved user experience. From the framework it has been found that factors including the storyline, user state, gameplay, and application type are critical to defining the reasons associated with making aesthetic choices. The selection of a range of aesthetic features and characteristics is influenced by four main factors and sub-factors associated with the main factors. This study informs the future of interactive digital media interaction by providing clarity and reasoning behind the aesthetic decision-making inclusions that are integrated into automatically generated vision by providing a framework for choosing a range of aesthetic viewpoints in a 3D virtual environment of a game. The study identifies critical juxtapositions between photographic and cinema-based media aesthetics by incorporating qualitative rationales from experts within the interactive digital media field. This research will change the way Artificial Intelligence (AI) generated interactive digital media in the way that it chooses visual outputs in terms of camera positions, field-view, orientation, contextual considerations, and user experiences. It will impact across all automated systems to ensure that human-values, rich variations, and extensive complexity are integrated in the AI-dominated development and design of future interactive digital media production

    Investigation and development of a tangible technology framework for highly complex and abstract concepts

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    The ubiquitous integration of computer-supported learning tools within the educational domain has led educators to continuously seek effective technological platforms for teaching and learning. Overcoming the inherent limitations of traditional educational approaches, interactive and tangible computing platforms have consequently garnered increased interest in the pursuit of embedding active learning pedagogies within curricula. However, whilst Tangible User Interface (TUI) systems have been successfully developed to edutain children in various research contexts, TUI architectures have seen limited deployment towards more advanced educational pursuits. Thus, in contrast to current domain research, this study investigates the effectiveness and suitability of adopting TUI systems for enhancing the learning experience of abstract and complex computational science and technology-based concepts within higher educational institutions (HEI)s. Based on the proposal of a contextually apt TUI architecture, the research describes the design and development of eight distinct TUI frameworks embodying innovate interactive paradigms through tabletop peripherals, graphical design factors, and active tangible manipulatives. These computationally coupled design elements are evaluated through summative and formative experimental methodologies for their ability to aid in the effective teaching and learning of diverse threshold concepts experienced in computational science. In addition, through the design and adoption of a technology acceptance model for educational technology (TAM4Edu), the suitability of TUI frameworks in HEI education is empirically evaluated across a myriad of determinants for modelling students’ behavioural intention. In light of the statistically significant results obtained in both academic knowledge gain (μ = 25.8%) and student satisfaction (μ = 12.7%), the study outlines the affordances provided through TUI design for various constituents of active learning theories and modalities. Thus, based on an empirical and pedagogical analyses, a set of design guidelines is defined within this research to direct the effective development of TUI design elements for teaching and learning abstract threshold concepts in HEI adaptations

    Practical, appropriate, empirically-validated guidelines for designing educational games

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    There has recently been a great deal of interest in the potential of computer games to function as innovative educational tools. However, there is very little evidence of games fulfilling that potential. Indeed, the process of merging the disparate goals of education and games design appears problematic, and there are currently no practical guidelines for how to do so in a coherent manner. In this paper, we describe the successful, empirically validated teaching methods developed by behavioural psychologists and point out how they are uniquely suited to take advantage of the benefits that games offer to education. We conclude by proposing some practical steps for designing educational games, based on the techniques of Applied Behaviour Analysis. It is intended that this paper can both focus educational games designers on the features of games that are genuinely useful for education, and also introduce a successful form of teaching that this audience may not yet be familiar with

    Computers for learning : an empirical modelling perspective

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    In this thesis, we explore the extent to which computers can provide support for domain learning. Computer support for domain learning is prominent in two main areas: in education, through model building and the use of educational software; and in the workplace, where models such as spreadsheets and prototypes are constructed. We shall argue that computerbased learning has only realised a fraction of its full potential due to the limited scope for combining domain learning with conventional computer programming. In this thesis, we identify some of the limitations in the current support that computers offer for learning, and propose Empirical Modelling (EM) as a way of overcoming them. We shall argue that, if computers are to be successfully used for learning, they must support the widest possible range of learning activities. We introduce an Experiential Framework for Learning (EFL) within which to characterise learning activities that range from the private to the public, from the empirical to the theoretical, and from the concrete to the abstract. The term ‘experiential’ reflects a view of knowledge as rooted in personal experience. We discuss the merits of computer-based modelling methods with reference to a broad constructionist perspective on learning that encompasses bricolage and situated learning. We conclude that traditional programming practice is not well-suited to supporting bricolage and situated learning since the principles of program development inhibit the essential cognitive model building activity that informs domain learning. In contrast, the EM approach to model construction directly targets the semantic relation between the computer model and its domain referent and exploits principles that are closely related to the modeller’s emerging understanding or construal. In this way, EM serves as a uniform modelling approach to support and integrate learning activities across the entire spectrum of the EFL. This quality makes EM a particularly suitable approach for computer-based model construction to support domain learning. In the concluding chapters of the thesis, we demonstrate the qualities of EM for educational technology with reference to practical case studies. These include: a range of EM models that have advantages over conventional educational software due to their particularly open-ended and adaptable nature and that serve to illustrate a variety of ways in which learning activities across the EFL can be supported and scaffolded

    Interactive Imitation Learning in Robotics: A Survey

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    Interactive Imitation Learning (IIL) is a branch of Imitation Learning (IL) where human feedback is provided intermittently during robot execution allowing an online improvement of the robot's behavior. In recent years, IIL has increasingly started to carve out its own space as a promising data-driven alternative for solving complex robotic tasks. The advantages of IIL are its data-efficient, as the human feedback guides the robot directly towards an improved behavior, and its robustness, as the distribution mismatch between the teacher and learner trajectories is minimized by providing feedback directly over the learner's trajectories. Nevertheless, despite the opportunities that IIL presents, its terminology, structure, and applicability are not clear nor unified in the literature, slowing down its development and, therefore, the research of innovative formulations and discoveries. In this article, we attempt to facilitate research in IIL and lower entry barriers for new practitioners by providing a survey of the field that unifies and structures it. In addition, we aim to raise awareness of its potential, what has been accomplished and what are still open research questions. We organize the most relevant works in IIL in terms of human-robot interaction (i.e., types of feedback), interfaces (i.e., means of providing feedback), learning (i.e., models learned from feedback and function approximators), user experience (i.e., human perception about the learning process), applications, and benchmarks. Furthermore, we analyze similarities and differences between IIL and RL, providing a discussion on how the concepts offline, online, off-policy and on-policy learning should be transferred to IIL from the RL literature. We particularly focus on robotic applications in the real world and discuss their implications, limitations, and promising future areas of research
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