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dc.contributor.advisorSchäfer, Andreas
dc.contributor.authorEvans, Antony
dc.date.accessioned2010-11-22T14:33:39Z
dc.date.available2010-11-22T14:33:39Z
dc.date.issued2010-10-12
dc.identifier.otherPhD.33533
dc.identifier.urihttp://www.dspace.cam.ac.uk/handle/1810/226855
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/226855
dc.description.abstractThis dissertation describes a model that predicts airline flight network, frequency and fleet changes in response to policy measures that aim to reduce the environmental impact of aviation. Such airline operational responses to policy measures are not considered by existing integrated aviation-environment modelling tools. By not modelling these effects the capability of the air transport system to adjust under changing conditions is neglected, resulting in the forecasting of potentially misleading system and local responses to constraints. The model developed follows the overriding principle of airline strategic decision making, i.e., airline profit maximisation within a competitive environment. It consists of several components describing different aspects of the air transport system, including passenger demand forecasting, flight delay modelling, estimation of airline costs and airfares, and network optimisation. These components are integrated into a framework that allows the relationships between fares, passenger demand, infrastructure capacity constraints, flight delays, flight frequencies, and the flight network to be simulated. Airline competition is modeled by simulating a strategic game between airlines competing for market share, each of which maximizes its own profit. The model is validated by reproducing historical passenger flows and flight frequencies for a network of 22 airports serving 14 of the largest cities in the United States, using 2005 population, per capita income and airport capacities as inputs. The estimated passenger flows and flight frequencies compare well to observed data for the same network (the R2 value comparing flight segment frequencies is 0.62). After validation, the model is applied to simulate traffic growth and carbon dioxide and nitrogen oxide emissions within the same network from 2005 to 2030 under a series of scenarios. These scenarios investigate airline responses to (i) airport capacity constraints, (ii) regional increases in costs in the form of landing fees, and (iii) major reductions in aircraft fuel burn, as would be achieved through the introduction of radically new technology such as a blended wing body aircraft or advanced open rotor engines. The simulation results indicate that, while airport capacity constraints may have significant system-wide effects, they are the result of local airport effects which are much greater. In particular, airport capacity constraints can have a significant impact on flight delays, passenger demand, aircraft operations, and emissions, especially at congested hub airports. If capacity is available at other airports, capacity constraints may also induce changes in the flight network, including changes in the distribution of connecting traffic between hubs and the distribution of true origin-ultimate destination traffic between airports in multi-airport systems. Airport capacity constraints are less likely to induce any significant increase in the size of aircraft operated, however, because of frequency competition effects, which maintain high flight frequencies despite reductions in demand in response to increased flight delays. The simulation results also indicate that, if sufficiently large, regional increases in landing fees may induce significant reductions in aircraft operations by increasing average aircraft size and inducing a shift in connecting traffic away from the region. The simulation results also indicate that the introduction of radically new technology that reduces aircraft fuel burn may have only limited impact on reducing system CO2 emissions, and only in the case where the new technology can be taken up by the majority of the fleet. The reason for this is that the reduced operating costs of the new technology may result in an increase in frequency competition and thus aircraft operations. In conclusion, the modelling of airline operational responses to environmental constraints is important when studying both the system and local effects of environmental policy measures, because it captures the capability of the air transport system to adjust under changing conditions.en_GB
dc.description.sponsorshipThis work was supported by the Engineering and Physical Sciences Research Council and the Natural Environment Research Council [grant number EP/D060001/1].en_GB
dc.language.isoenen_GB
dc.rightsAll Rights Reserveden
dc.rights.urihttps://www.rioxx.net/licenses/all-rights-reserved/en
dc.subjectSimulationen_GB
dc.subjectNetwork optimisatonen_GB
dc.subjectGame theoryen_GB
dc.subjectEnvironmental impacten_GB
dc.subjectAirline operationsen_GB
dc.subjectAviationen_GB
dc.titleSimulating airline operational responses to environmental constraintsen_GB
dc.typeThesisen_GB
dc.type.qualificationlevelDoctoral
dc.type.qualificationnameDoctor of Philosophy (PhD)
dc.publisher.institutionUniversity of Cambridgeen_GB
dc.publisher.departmentDepartment of Architectureen_GB
dc.publisher.departmentInstitute for Aviation and the Environmenten_GB
dc.identifier.doi10.17863/CAM.16317


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