Trajectory prediction uncertainty modelling for Air Traffic Management

The anticipated growth of air traffic worldwide requires enhanced Air Traffic Management (ATM) technologies and procedures to increase the system capacity, efficiency, and resilience, while reducing environmental impact and maintaining operational safety. To deal with these challenges, new automation and information exchange capabilities are being developed through different modernisation initiatives toward a new global operational concept called Trajectory Based Operations (TBO), in which aircraft trajectory information becomes the cornerstone of advanced ATM applications. This transformation will lead to higher levels of system complexity requiring enhanced Decision Support Tools (DST) to aid humans in the decision making processes. These will rely on accurate predicted aircraft trajectories, provided by advanced Trajectory Predictors (TP). The trajectory prediction process is subject to stochastic effects that introduce uncertainty into the predictions. Regardless of the assumptions that define the aircraft motion model underpinning the TP, deviations between predicted and actual trajectories are unavoidable. This thesis proposes an innovative method to characterise the uncertainty associated with a trajectory prediction based on the mathematical theory of Polynomial Chaos Expansions (PCE). Assuming univariate PCEs of the trajectory prediction inputs, the method describes how to generate multivariate PCEs of the prediction outputs that quantify their associated uncertainty. Arbitrary PCE (aPCE) was chosen because it allows a higher degree of flexibility to model input uncertainty. The obtained polynomial description can be used in subsequent prediction sensitivity analyses thanks to the relationship between polynomial coefficients and Sobol indices. The Sobol indices enable ranking the input parameters according to their influence on trajectory prediction uncertainty. The applicability of the aPCE-based uncertainty quantification detailed herein is analysed through a study case. This study case represents a typical aircraft trajectory prediction problem in ATM, in which uncertain parameters regarding aircraft performance, aircraft intent description, weather forecast, and initial conditions are considered simultaneously. Numerical results are compared to those obtained from a Monte Carlo simulation, demonstrating the advantages of the proposed method. The thesis includes two examples of DSTs (Demand and Capacity Balancing tool, and Arrival Manager) to illustrate the potential benefits of exploiting the proposed uncertainty quantification method.

Staff and students co-creating curricula in UK higher education: exploring process and evidencing value

Student engagement in learning and teaching is receiving a growing level of interest from policy makers, researchers, and practitioners. This includes opportunities for staff and students to co-create curricula, yet there are few examples within current literature which describe and critique this form of staff-student collaboration (Bovill (2013a), Healey et al (2014), Cook-Sather et al (2014). The competing agendas of neoliberalism and critical, radical pedagogies influence the policy and practice of staff and students co-creating curricula and, consequently, attempt to appropriate the purpose of it in different ways. Using case-based research methodology, my study presents analysis of staff and students co-creating curricula within seven universities. This includes 17 examples of practice across 14 disciplines. Using an inductive approach, I have examined issues relating to definitions of practice, conceptualisations of curricula, perceptions of value, and the relationship between practice and institutional strategy. I draw upon an interdisciplinary body of literature to provide the conceptual foundations for my research. This has been necessary to address the complexity of practice and includes literature relating to student engagement in learning and teaching, conceptual models of curriculum in higher education, approaches to evidencing value and impact, and critical theory and radical pedagogies. The study makes specific contributions to the wider scholarly debate by highlighting the importance of dialogue and conversational scholarship as well as identifying with participants what matters as well as what works as a means to evidence the value of collaborations. It also presents evidence of a new model of co-creating curricula and additional approaches to conceptualising curricula to facilitate collaboration. Analysis of macro and micro level data shows enactment of dialogic pedagogies within contexts of technical-rational strategy formation and implementation.