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.

Deindustrialisation and industrial communities: the Lanarkshire coalfields c.1947-1983

This thesis examines deindustrialisation, the declining contribution of industrial activities to economic output and employment, in Lanarkshire, Scotland’s largest coalfield between the early nineteenth and mid-twentieth century. It focuses on contraction between the National Coal Board’s (NCB) vesting in 1947 and the closure of Lanarkshire’s last colliery, Cardowan, in 1983. Deindustrialisation was not the natural outcome of either market forces or geological exhaustion. Colliery closures and falling coal employment were the result of policy-makers’ decisions. The thesis consists of four thematic chapters: political economy, moral economy, class and community, and generation and gender. The analysis is based on archival sources including Scottish Office reports and correspondence relating to regional policy, and NCB records. These are supported by National Union of Mineworkers Scottish Area and STUC meeting minutes, and oral history testimonies from over 30 men and women with Lanarkshire coalfield backgrounds, as well as two focus groups. The first two chapters analyse the process of deindustrialisation, with the first offering a top-down perspective and the second a bottom-up viewpoint. In chapter one deindustrialisation is analysed through changes in political economy. Shifts in labour market structure are examined through the development of regional policy and its administration by the Scottish Office. The analysis centres upon a policy network of Scottish business elites and civil servants who shaped a vision of modernisation via industrial diversification through attracting inward investment. In chapter two the perspective shifts to community and workforce. It analyses responses to coalfield contraction through a moral economy of customary rights to colliery employment. A detailed investigation of Lanarkshire colliery closures between the 1940s and 1980s emphasises the protracted nature of deindustrialisation. Chapters three and four consider the social and cultural structures which shaped the moral economy but were heavily altered by deindustrialisation. Chapter three focuses on the dense networks that linked occupation, community, and class consciousness. Increasing coalfield centralisation and remote control of pits from NCB headquarters in London, and mounting hostility to coal closures, contributed to an accentuated sense of Scottish-ness. Chapter four illuminates gender and generational dimensions. The differing experiences of cohorts of men who faced either early retirement, redundancy or transfer to alternative sectors, or those who never attained anticipated industrial employment due to final closures, are analysed in terms of constructions of masculinity and the endurance of cultural as well as material losses. This is counterpoised to women who gained industrial work in assembly plants and the perceived gradual attainment of an improved economic and social position whilst continuing to navigate structures of patriarchy.